A white paper was published by Verint Consulting in the UK and was based on international research by Ventana Research. Although they didn't mention the sample size and the countries they surveyed in their summary (which was all the information I received), their results are very interesting. Some of the key findings from the research are:
1. 81 percent of the organizations surveyed agree that the customer experience impacts loyalty and advocacy.
2. 73 percent agree that the customer experience impacts satisfaction and the amount they spend.
3. Less than 33 percent of the companies use analytics to understand what is happening in their customer interactions
4. More than 50 percent rely on subjective, irregular and delayed feedback from agents and customers.
5. More than 33 percent of the companies lack documented processes to govern telephone calls. This percentage rises to 65 and 66 percent for web and IVR-based self-service, respectively.
6. 28 percent of the companies have documented processes for handling a single interaction across multiple channels.
7. 61 percent are making a correlation between customer experience and customer loyalty, 56 percent with levels of complaints, 43 percent with customer lifetime value and 39 percent with customer advocacy.
8. 20 percent of the companies have already deployed analytics and/or business intelligence tools.
9. 42 percent of the companies noted they will begin using analytics next year.
The bottom line that jumps out of this research is that most companies know that the customer experience is important. Unfortunately, the companies either don't know how to manage the customer experience or haven't given it the priority. I think the real issue is that most of these companies don't realize that there are analytics that will provide them with some guidance for management.
Tuesday, December 30, 2008
Friday, December 19, 2008
The Case Against Customer Service
It is not often that I see an example of a business being successful when the underlying business strategy is to not adopt customer service. Michael O'Leary, CEO of Ryanair is a skeptic about the value of customer service and when given the opportunity to turn around Ryanair Airline as he took over the helm, he looked at the business model for Southwest Airlines, an airline he believed was successful, and then bench marked Ryanair against Southwest. Once he saw how Southwest had succeeded, he adopted their model except that he chose NOT to include customer service. His view which he backed by research suggested that the primary factor and almost sole driver for customer choice of an airline in the European coach and economy segment is low, low fares.
Since he has instituted this philosophy Ryanair has posted record growth and a reasonable profit over a sustained period of time. When he was interviewed by the Wall Street Journal in 2004, it is reported that his comment was that in head-to-head competition, low prices will always beat out "value services."
The bottom line for Ryanair is their business model that seems to be working is "low price versus competition is the driver to business success and profitability; not satisfying customer service for building customer loyalty." While this might not be the formula for success for other businesses or even other airline market segments, Mr. O'Leary has found the primary, and possibly the only driver for success in his market segment. This is a lesson for those of us who believe that we must always have a strong customer service component to achieve business success.
Since he has instituted this philosophy Ryanair has posted record growth and a reasonable profit over a sustained period of time. When he was interviewed by the Wall Street Journal in 2004, it is reported that his comment was that in head-to-head competition, low prices will always beat out "value services."
The bottom line for Ryanair is their business model that seems to be working is "low price versus competition is the driver to business success and profitability; not satisfying customer service for building customer loyalty." While this might not be the formula for success for other businesses or even other airline market segments, Mr. O'Leary has found the primary, and possibly the only driver for success in his market segment. This is a lesson for those of us who believe that we must always have a strong customer service component to achieve business success.
Car Loyalty
JD Power just released a survey conducted between November 2007 and May 2008 on 147,238 new car buyers. The purpose was to measure the percentage of new car buyers who repurchased the same brand when they bought their new car.
The survey results show the following:
1. The industry average is 48 percent of customers repurchased the same brand as the car they are replacing.
2. Honda had the highest repurchased percentage 64.7 percent followed by Toyota at 63.2 percent, with Lexus third with 60.4 percent and Mercedes Benz fourth at 58.6 percent.
3. The three lowest were Jaguar at the bottom with 26.2 percent, Pontiac next with 27.2 percent and third from the bottom is Mitsubishi at 28.1 percent.
Apparently the Korean auto manufacturers are not happy with the repurchase percentage of their brands since both Hyundai at 46.7 percent and Kia at 32.5 percent are below the industry average. They apparently believe that because they are building a high quality automobile their repurchase percentage should be higher. Some experts have suggested the reason for the Korean automobiles having such low repurchase scores is not their cars but the purchase process and after sales service.
These same experts note that Honda's feat of coming in first was not so much a result of product quality as customer satisfaction with the after sales service.
The bottom line is after sales service (repair and parts sales) is both the highest margin component of the dealership, it is also one of the most important aspects of retaining customers.
The survey results show the following:
1. The industry average is 48 percent of customers repurchased the same brand as the car they are replacing.
2. Honda had the highest repurchased percentage 64.7 percent followed by Toyota at 63.2 percent, with Lexus third with 60.4 percent and Mercedes Benz fourth at 58.6 percent.
3. The three lowest were Jaguar at the bottom with 26.2 percent, Pontiac next with 27.2 percent and third from the bottom is Mitsubishi at 28.1 percent.
Apparently the Korean auto manufacturers are not happy with the repurchase percentage of their brands since both Hyundai at 46.7 percent and Kia at 32.5 percent are below the industry average. They apparently believe that because they are building a high quality automobile their repurchase percentage should be higher. Some experts have suggested the reason for the Korean automobiles having such low repurchase scores is not their cars but the purchase process and after sales service.
These same experts note that Honda's feat of coming in first was not so much a result of product quality as customer satisfaction with the after sales service.
The bottom line is after sales service (repair and parts sales) is both the highest margin component of the dealership, it is also one of the most important aspects of retaining customers.
Saturday, December 13, 2008
A Dissssenting Opinion
I saw a blog by Perceptions dated December 6th where the author takes to task the ACSI (American Customer Satisfaction Index). The author provides two charts. The first chart shows the ACSI scores for four financial services companies (Wachovia, Bank of America, JP Morgan and Wells Fargo) over the last 4 years (2003 through 2007). The second chart shows the stock performance of these same companies for the first ten months of 2008. A simple viewing of the two charts shows that customer satisfaction is very stable for each of the four financial institutions and the stock performance shows dramatic decline in 2008.
I believe the author is making the point that customer satisfaction can't predict the future performance of companies. I suggest the author read the book "the Black Swan" by Nassim Taleb to see if he can understand that there may be some other variables in play. He may also want to review the very many papers that show strong correlations between customer satisfaction and financial performance. I don't think thee is anyone who truly believes that customer satisfaction is the only driver of future performance of a company. To think that customer satisfaction is the sole driver of a company's financial performance is a clue to the depth of the author's knowledge. Naivete' doesn't wear well on the web.
I believe the author is making the point that customer satisfaction can't predict the future performance of companies. I suggest the author read the book "the Black Swan" by Nassim Taleb to see if he can understand that there may be some other variables in play. He may also want to review the very many papers that show strong correlations between customer satisfaction and financial performance. I don't think thee is anyone who truly believes that customer satisfaction is the only driver of future performance of a company. To think that customer satisfaction is the sole driver of a company's financial performance is a clue to the depth of the author's knowledge. Naivete' doesn't wear well on the web.
Service Counts More than Price
It appears that Accenture has surveyed more than 4,100 consumers in various countries (countries other than the US are not identified). The survey was conducted over the summer of 2008 when the signs of the current financial crisis were emerging. Their key finding during this market turmoil is that consumers found service, more than price, to be a clear differentiator.
According to their survey results 67% of the respondents reported that they switched companies because of poor customer service. In the US the percentage is even higher
(73%). The percentage of customers who switched because of lower prices was 47%. Accenture has been performing this same survey for four years and the survey results show the increasing impact of service. The first survey reported 48% of the respondents said they were switching because of customer service. In four years the percentage has increased 19% (about 5% per year).
There were four other interesting findings; namely,
1. US consumers are the least likely to believe that technology has significantly increased customer service in the past five years.
2. When choosing a new provider, US customers weighed price and customer service equally.
3. The most important aspect of customer service identified by consumers was employees who are knowledgeable and well informed.
4. Consumers estimated they BROUGHT $4,000 WORTH OF BUSINESS to their new provider.
The bottom line is that survey after survey seems to be repeating the same message, customer service is a vital strategic weapon for companies. Unfortunately most companies haven't figured out how to use the weapon.
According to their survey results 67% of the respondents reported that they switched companies because of poor customer service. In the US the percentage is even higher
(73%). The percentage of customers who switched because of lower prices was 47%. Accenture has been performing this same survey for four years and the survey results show the increasing impact of service. The first survey reported 48% of the respondents said they were switching because of customer service. In four years the percentage has increased 19% (about 5% per year).
There were four other interesting findings; namely,
1. US consumers are the least likely to believe that technology has significantly increased customer service in the past five years.
2. When choosing a new provider, US customers weighed price and customer service equally.
3. The most important aspect of customer service identified by consumers was employees who are knowledgeable and well informed.
4. Consumers estimated they BROUGHT $4,000 WORTH OF BUSINESS to their new provider.
The bottom line is that survey after survey seems to be repeating the same message, customer service is a vital strategic weapon for companies. Unfortunately most companies haven't figured out how to use the weapon.
Thursday, December 11, 2008
CMOs Don't Seem to Get It
I just finished reading the executive summary of the Routes to Revenue. It is a report that presents the findings of a survey of 650 senior marketers in 2008 published by the Infoprint Solutions Company. The first item that jumps out of the report is that 76 percent of the senior marketers believe they are not realizing the full revenue potential of their current customers. Only about 46.5 percent believe they have know their retention rates, customer profitability and customer lifetime value.
The report goes on to list various obstacles for not attaining greater customer penetration. The report lists the following obstacles:
1. Lack of real time data and analytics.
2. Information being selectively gathered and often inaccurate and incomplete.
3. Data being siloed and restricted across the organization.
The new roads to acquiring new business were listed as:
1. Launch new products aimed at specific market segments.
2. Establish new partnerships and revenue-sharing agreements.
3. Stepping up demand generation and customer acquisition programs
4. Expand geographical presence and intensifying international focus.
5. Ramping up eCommerce and customer-direct communications
6. Restructuring or expanding channels of distribution.
The answers to the question of what the companies are doing to improve revenue and reduce costs, the responses were:
1. 40 percent said they were reducing headcount and overhead
2. 38.7 percent said they were automating complex and costly processes.
3. 31.2 percent said they were outsourcing more services and functions
4. 27.8 percent said they were reformulating products or minimizing packaging to contain costs.
When asked what they were doing to increase efficiency and effectiveness, the responses were:
1. 64 percent were evaluating all areas of marketing to increase yield and accountability.
2. 47.3 percent said they were bringing more discipline and rigor to marketing budgeting and spending.
3. 47.3 percent said they were leveraging existing resources within the organization to enhance customer communications.
4. 40.9 percent said they were exploring new customized communications technologies.
5. 38.7 percent said they were moving more marketing investments to internet and mobile channels.
6. 33.3 percent said they were improving behavioral targeting of advertising and online marketing campaigns.
7. 31.5 percent said they were driving adoption and use of CRM and sales automation applications.
The survey listed the ways companies are trying to better engage core audiences. The Routes to Revenue were:
1. 60 percent said they would introduce better segmentation, profiling and targeting strategies.
2. 48.7 percent said they would add or improve their data base marketing systems.
3. 30.3 percent said they would acquire new customer and market analytics capability.
4. 29.8 percent said they would personalize multi-channel communication and customer touch points.
5. 26.4 percent said they would individualize print, email and text messaging, call center or web interactions.
6. 25.8 percent said they would build online customer communities and interactive channels.
7. 25.2 percent said they would capture more customer information via the web and at point-of-sale.
The bottom line is that CMOs (chief marketing officers) don't seem to understand the impact of customer service on loyalty, retention and customer attraction. There are a number of blogs in my archives that provide supporting evidence of the value of customer service in keeping business and attracting new business. See if you can find the few insights they noted that would increase share of pocket through customer service or attraction of new customers through customer loyalty. They may find the answers to higher retention rates, customer profitability and customer lifetime value if they can think outside the box of marketing. It would appear that they can only see the customers through the eyes of marketing - seems a bit myopic. For more data check my next blog.
The report goes on to list various obstacles for not attaining greater customer penetration. The report lists the following obstacles:
1. Lack of real time data and analytics.
2. Information being selectively gathered and often inaccurate and incomplete.
3. Data being siloed and restricted across the organization.
The new roads to acquiring new business were listed as:
1. Launch new products aimed at specific market segments.
2. Establish new partnerships and revenue-sharing agreements.
3. Stepping up demand generation and customer acquisition programs
4. Expand geographical presence and intensifying international focus.
5. Ramping up eCommerce and customer-direct communications
6. Restructuring or expanding channels of distribution.
The answers to the question of what the companies are doing to improve revenue and reduce costs, the responses were:
1. 40 percent said they were reducing headcount and overhead
2. 38.7 percent said they were automating complex and costly processes.
3. 31.2 percent said they were outsourcing more services and functions
4. 27.8 percent said they were reformulating products or minimizing packaging to contain costs.
When asked what they were doing to increase efficiency and effectiveness, the responses were:
1. 64 percent were evaluating all areas of marketing to increase yield and accountability.
2. 47.3 percent said they were bringing more discipline and rigor to marketing budgeting and spending.
3. 47.3 percent said they were leveraging existing resources within the organization to enhance customer communications.
4. 40.9 percent said they were exploring new customized communications technologies.
5. 38.7 percent said they were moving more marketing investments to internet and mobile channels.
6. 33.3 percent said they were improving behavioral targeting of advertising and online marketing campaigns.
7. 31.5 percent said they were driving adoption and use of CRM and sales automation applications.
The survey listed the ways companies are trying to better engage core audiences. The Routes to Revenue were:
1. 60 percent said they would introduce better segmentation, profiling and targeting strategies.
2. 48.7 percent said they would add or improve their data base marketing systems.
3. 30.3 percent said they would acquire new customer and market analytics capability.
4. 29.8 percent said they would personalize multi-channel communication and customer touch points.
5. 26.4 percent said they would individualize print, email and text messaging, call center or web interactions.
6. 25.8 percent said they would build online customer communities and interactive channels.
7. 25.2 percent said they would capture more customer information via the web and at point-of-sale.
The bottom line is that CMOs (chief marketing officers) don't seem to understand the impact of customer service on loyalty, retention and customer attraction. There are a number of blogs in my archives that provide supporting evidence of the value of customer service in keeping business and attracting new business. See if you can find the few insights they noted that would increase share of pocket through customer service or attraction of new customers through customer loyalty. They may find the answers to higher retention rates, customer profitability and customer lifetime value if they can think outside the box of marketing. It would appear that they can only see the customers through the eyes of marketing - seems a bit myopic. For more data check my next blog.
Tuesday, December 9, 2008
The Drivers for e-Loyalty
Last week I wrote a blog about e-Loyalty. I would like to add some additional information to the e-Loyalty model by describing what, I believe, are some of the key drivers. It is always easy to say the drivers for e-Loyalty are the same as the drivers for face-to-face loyalty. That might be easy to say but it certainly is not correct.
When we are dealing face-to-face with customers the three components of loyalty are the product, the process and the people that represent the company. I believe the same components are there for e-Loyalty but with some additional considerations.
1. The PRODUCT has to have the same or better value proposition as the product that can be handled. When customers use the internet the company can offer a large set of choices without carrying the inventory, can provide warranties and well-known brands. The first component is still the competitive product.
2. The SERVICE PROCESS has the same name as the face-to-face service except the website and the technology replace the service process. Instead of a person there to answer questions, the web must provide fast page loads, an easy to navigate browser, language options, effective search functions, and a quick shopping checkout process.
3. The CUSTOMER SERVICE may or may not include contact with a real person. Some web sites do have a contact button that will immediately transfer to a real person. In this case, the customer service process has the same characteristics as a call center. Without the direct connect to customer service, customer service becomes the typical customer service function which handles customer inquiries, warranty administration, and problems that are not answered by the web site FAQs.
The main reason I am discussing these e-Loyalty components is the additional consideration of the website characteristics and the technology that are not necessary with face-to-face business but become critical on the web. The web site becomes a process that provides fast response to customer inquiries (usually through the net) and is easy to contact, provides an easy payment method (such as Pay-Pal), and provides delivery options from very fast at extra cost to snail mail at the lowest cost.
A secondary reason for discussing web loyalty is the aspect of trust and security for the web site. Trust and security are rarely a concern when dealing face-to-face with customers. On the web there is the concern for privacy and trust. Reputation becomes significant (who wants to spend money on an unknown; yes, I know there are many who do, but they generally do it irresponsibly). There is also the requirement for authentication in both directions. We know there are many hoaxes and scams on the web and that should alert every customer to be wary of an unknown site.
The bottom line is the web is a great selling tool and can be used effectively to build customer loyalty; however, it must be designed to incorporate the additional features of customer service along with web trust and security that are not necessary in the world of face-to-face business.
When we are dealing face-to-face with customers the three components of loyalty are the product, the process and the people that represent the company. I believe the same components are there for e-Loyalty but with some additional considerations.
1. The PRODUCT has to have the same or better value proposition as the product that can be handled. When customers use the internet the company can offer a large set of choices without carrying the inventory, can provide warranties and well-known brands. The first component is still the competitive product.
2. The SERVICE PROCESS has the same name as the face-to-face service except the website and the technology replace the service process. Instead of a person there to answer questions, the web must provide fast page loads, an easy to navigate browser, language options, effective search functions, and a quick shopping checkout process.
3. The CUSTOMER SERVICE may or may not include contact with a real person. Some web sites do have a contact button that will immediately transfer to a real person. In this case, the customer service process has the same characteristics as a call center. Without the direct connect to customer service, customer service becomes the typical customer service function which handles customer inquiries, warranty administration, and problems that are not answered by the web site FAQs.
The main reason I am discussing these e-Loyalty components is the additional consideration of the website characteristics and the technology that are not necessary with face-to-face business but become critical on the web. The web site becomes a process that provides fast response to customer inquiries (usually through the net) and is easy to contact, provides an easy payment method (such as Pay-Pal), and provides delivery options from very fast at extra cost to snail mail at the lowest cost.
A secondary reason for discussing web loyalty is the aspect of trust and security for the web site. Trust and security are rarely a concern when dealing face-to-face with customers. On the web there is the concern for privacy and trust. Reputation becomes significant (who wants to spend money on an unknown; yes, I know there are many who do, but they generally do it irresponsibly). There is also the requirement for authentication in both directions. We know there are many hoaxes and scams on the web and that should alert every customer to be wary of an unknown site.
The bottom line is the web is a great selling tool and can be used effectively to build customer loyalty; however, it must be designed to incorporate the additional features of customer service along with web trust and security that are not necessary in the world of face-to-face business.
Monday, December 8, 2008
What About the Customer Asset?
I like the work of the Aberdeen Group. They do good research and I like reading their reports. I just received their report titled "Asset Performance Management" dated November, 2008. They start by making the point that in turbulent times, many companies are looking for ways to get more from their existing investments. They say this is especially true for asset intensive industries. Their approach is to suggest that these companies adopt a holistic strategy to manage the complete asset base. The Aberdeen Group includes plant equipment, facilities, automation, instrumentation, data, information technology and employees in their definition of asset.
So far so good. Are there companies that do not work at maximizing the use of their assets? But that is not the point here. If you look at the words in the Box describing the mission of the Customer Institute at the top of this blog the key is managing the CUSTOMER ASSET. This is where, I believe, most companies and certainly most consultants really miss the point about customers. In some previous blogs I noted some different ways to identify the asset value of customers. My perspective is that the customer asset is the MOST IMPORTANT asset and was omitted in their report.
Companies spend a fortune measuring and maintaining the assets that the accountants say are important, and they are important. But I rarely see a company that is truly managing their customer asset. I ask companies how healthy is your customer asset? Most companies have no idea. Is it more healthy than last year? If not, why not, and what are you doing about it? I get a lot of blank stares.
Two of my objectives in writing this blog, other than to be a file cabinet for my ideas and data, is to inspire those who are working in the area of customers to start building models to better understand the customers and then to start looking at the customer as an asset. Until businesses can understand the asset value of a customer, the customer, while considered important, will not have the board room attention that, in my opinion, it deserves.
So far so good. Are there companies that do not work at maximizing the use of their assets? But that is not the point here. If you look at the words in the Box describing the mission of the Customer Institute at the top of this blog the key is managing the CUSTOMER ASSET. This is where, I believe, most companies and certainly most consultants really miss the point about customers. In some previous blogs I noted some different ways to identify the asset value of customers. My perspective is that the customer asset is the MOST IMPORTANT asset and was omitted in their report.
Companies spend a fortune measuring and maintaining the assets that the accountants say are important, and they are important. But I rarely see a company that is truly managing their customer asset. I ask companies how healthy is your customer asset? Most companies have no idea. Is it more healthy than last year? If not, why not, and what are you doing about it? I get a lot of blank stares.
Two of my objectives in writing this blog, other than to be a file cabinet for my ideas and data, is to inspire those who are working in the area of customers to start building models to better understand the customers and then to start looking at the customer as an asset. Until businesses can understand the asset value of a customer, the customer, while considered important, will not have the board room attention that, in my opinion, it deserves.
Friday, December 5, 2008
Cyber Satisfaction
Foresee Results, a survey company, is conducting some customer satisfaction studies on cyber shoppers during this holiday season. They have just released the results of the Cyber Monday shopping. They surveyed more than 270,000 visitors at more than 80 online retailers between Friday, November 28th and Cyber Monday, December 1st. They used the ACSI methodology because of the ACSI's scientifically proven predictive abilities. ACSI has shown in previous studies (see their web site or call them directly for specific references) that satisfaction is the best measure of future success.
There are two points that, in my opinion are worth discussing; namely the satisfaction comparison between this year and last year and the impact of e-retail website satisfaction scores on purchases.
1. The Cyber Monday customer satisfaction score is down about 1% from 2007. (Score was 76.6 in 2007 and 75.9 in 2008 on a 100 point scale). Apparently the satisfaction scores were lower on every website element that was measured. Considering all the problems with the economy, it would appear that little was translated into the satisfaction of using the web for cyber shopping. There are many possible speculations to explain this minimal impact. Of course, it would be worthwhile to know how this compares to the customer satisfaction of shoppers at the malls on Black friday. I leave that to the speculators.
2. The more important point comes from the data analysis performed by Foresee Results. They noticed that e-retail websites with superior satisfaction scores (greater than 80) had customers that were significantly more likely to purchase online and offline than visitors to sites with subpar customer satisfaction (scores less than 70).
The bottom line is that this evidence appears to demonstrate that customer satisfaction is not limited to face-to-face communication. This study demonstrates once again the three legged stool of customer satisfaction ( satisfaction has three compontents; naamely, product, process and people). In this case, the customer contact with the e-retailer is limited to the web site process and product (people are not involved). The web e-retailers who understand this and built a website whose process exceeds the customer expectations and allows easy access to its products is rewarded by increased sales.
Perhaps this is obvious, but given this result, it once again demonstrates that satisfaction is a significant key to increased sales.
There are two points that, in my opinion are worth discussing; namely the satisfaction comparison between this year and last year and the impact of e-retail website satisfaction scores on purchases.
1. The Cyber Monday customer satisfaction score is down about 1% from 2007. (Score was 76.6 in 2007 and 75.9 in 2008 on a 100 point scale). Apparently the satisfaction scores were lower on every website element that was measured. Considering all the problems with the economy, it would appear that little was translated into the satisfaction of using the web for cyber shopping. There are many possible speculations to explain this minimal impact. Of course, it would be worthwhile to know how this compares to the customer satisfaction of shoppers at the malls on Black friday. I leave that to the speculators.
2. The more important point comes from the data analysis performed by Foresee Results. They noticed that e-retail websites with superior satisfaction scores (greater than 80) had customers that were significantly more likely to purchase online and offline than visitors to sites with subpar customer satisfaction (scores less than 70).
The bottom line is that this evidence appears to demonstrate that customer satisfaction is not limited to face-to-face communication. This study demonstrates once again the three legged stool of customer satisfaction ( satisfaction has three compontents; naamely, product, process and people). In this case, the customer contact with the e-retailer is limited to the web site process and product (people are not involved). The web e-retailers who understand this and built a website whose process exceeds the customer expectations and allows easy access to its products is rewarded by increased sales.
Perhaps this is obvious, but given this result, it once again demonstrates that satisfaction is a significant key to increased sales.
Wednesday, December 3, 2008
Customer Loyalty Mathematics
Dr. Mark Klein is a physicist who is using his mathematical skills to help companies tune their marketing programs. He has developed some mathematical models which, according to Dr. Klein, will improve the effectiveness of marketing campaigns. The reason I have chosen to mention this is that it is rare to find someone who is specifically mentioning the use of mathematics to understand customer loyalty. What appears most often in the market is different companies and consultants saying they do customer loyalty surveys better than others. In most cases the difference between the various groups (companies or consultants) is negligible.
The good news is that Dr. Klein mentions some mathematical techniques that he uses. The bad news is he doesn't say enough for someone like me to understand those techniques and be able to validate them.
He has a "Field Guide to Mathematical Marketing" available from his web site (55 pages). The book, which can be downloaded from his website at no cost, does an excellent job of making the case for using mathematics to better understand your customers. For that reason alone, the book is worth the time to read, especially if you think that mathematics has no place in analyzing customer loyalty.
Unfortunately, there are no mathematics in the document. The document does contain vary good descriptions of the statistical applications that appear to be one of the key tools he uses (factor analysis, factorial designs and fractional factorial designs). I am surprised he doesn't mention some of the other experimental statistical designs such as Latin Squares and Graeco-Latin Squares as long as he is using experimental designs. In any case, as I learned in school, it is always a good idea to know what is inside a black box (for those not used to the term, a black box is something that performs but you don't know how or why) before you buy it and thus until I know more about his application of the various methodologies noted, I am limited in the amount of support I can give. One of my concerns is what assumptions are required.
Some interesting observations made by Dr. Klein:
1. He believes that customer loyalty to be a more predictive measure of customer purchasing than customer satisfaction.
2. He also believes that customer satisfaction is a backwards-looking measure whereas customer loyalty, as noted above is more predictive of the future behavior of your customers.
3. He believes that most people in marketing (and probably in customer service/support) avoid using mathematics even though it would be beneficial.
4. He is a strong proponent of selling to existing customers and believes that the more information that you have about you're customer, the better job you can do in developing marketing programs to encourage them to buy.
Finally, I reviewed the software program on his site that allows a demonstration. Here is where I am a little concerned about the "black box." I am reminded of the phrase from my programming days that said "garbage in, garbage out" was corrected to say "garbage in, gospel out." The demonstration is excellent without being too complex for the non-mathematical observer, but it is not clear what is happening and why. Of course, that may be the idea, to sell the concept without giving away the company secrets.
The bottom line is that I am not recommending Dr. Klein's mathematical modeling because I do not have sufficient information to evaluate how he is using the techniques. I am, however, pointing out that there are a few people with enough education, such as Dr. Klein, to use the power of mathematics to help companies improve their understanding of their customers and customer loyalty.
The good news is that Dr. Klein mentions some mathematical techniques that he uses. The bad news is he doesn't say enough for someone like me to understand those techniques and be able to validate them.
He has a "Field Guide to Mathematical Marketing" available from his web site (55 pages). The book, which can be downloaded from his website at no cost, does an excellent job of making the case for using mathematics to better understand your customers. For that reason alone, the book is worth the time to read, especially if you think that mathematics has no place in analyzing customer loyalty.
Unfortunately, there are no mathematics in the document. The document does contain vary good descriptions of the statistical applications that appear to be one of the key tools he uses (factor analysis, factorial designs and fractional factorial designs). I am surprised he doesn't mention some of the other experimental statistical designs such as Latin Squares and Graeco-Latin Squares as long as he is using experimental designs. In any case, as I learned in school, it is always a good idea to know what is inside a black box (for those not used to the term, a black box is something that performs but you don't know how or why) before you buy it and thus until I know more about his application of the various methodologies noted, I am limited in the amount of support I can give. One of my concerns is what assumptions are required.
Some interesting observations made by Dr. Klein:
1. He believes that customer loyalty to be a more predictive measure of customer purchasing than customer satisfaction.
2. He also believes that customer satisfaction is a backwards-looking measure whereas customer loyalty, as noted above is more predictive of the future behavior of your customers.
3. He believes that most people in marketing (and probably in customer service/support) avoid using mathematics even though it would be beneficial.
4. He is a strong proponent of selling to existing customers and believes that the more information that you have about you're customer, the better job you can do in developing marketing programs to encourage them to buy.
Finally, I reviewed the software program on his site that allows a demonstration. Here is where I am a little concerned about the "black box." I am reminded of the phrase from my programming days that said "garbage in, garbage out" was corrected to say "garbage in, gospel out." The demonstration is excellent without being too complex for the non-mathematical observer, but it is not clear what is happening and why. Of course, that may be the idea, to sell the concept without giving away the company secrets.
The bottom line is that I am not recommending Dr. Klein's mathematical modeling because I do not have sufficient information to evaluate how he is using the techniques. I am, however, pointing out that there are a few people with enough education, such as Dr. Klein, to use the power of mathematics to help companies improve their understanding of their customers and customer loyalty.
Tuesday, December 2, 2008
Service Quality - What is it?
There is some interesting work being done by Phil Klaus (terminal degree and title unknown) at the Cranfield School of Management in England. He is working on a scale that represents not only the attributes of the customer experience (the reasons why customers choose (or not) to purchase and then weighting them. He defines the customer experience as the sum of the attributes leading to customer purchasing and repurchasing behavior. His research is focused on the financial services industry.
Mr. Klaus believes the whole story of customer purchasing behavior is multi-faceted and complicated. He states that research shows that customer decision cannot be reduced anymore into a simple "functionality versus price" formula. He asserts that purchasing behavior is driven more by the emotional and subconscious elements and less by the functional attributes of products and services.
From this assertion he believes that offering high-quality goods and services alone is not sufficient. He is suggesting that organizations must compete on a more complex level by creating a satisfactory customer experience through all stages of the buying process, managing the customer's expectations and assessments, before, during and after the buying process. The customer experience is a broad, holistic concept that managers find difficult to measure and manage.
At this point I would like to interject that I agree with much of what he is stating. My wife, a psychotherapist, has pointed out to me that most decisions are rationalizations of the underlying emotions. the four basic emotions are happy, sad, mad and afraid. It makes sense that people generally do not make a purchase when they are sad or mad. People more often make a purchase when they are either happy or afraid.
For example, people buy a tv when they are happy. I never see shoppers who are mad or sad looking at tvs. (I must admit there are some personality disorders that buy under other conditions - some are called shopaholics and some are a step beyond where the urge to shop is psychotic). Customers may also make purchases because of some fear. People will purchase excessive amounts of food if they think there will be a food shortage.
Of course, the problem presented by Mr. Klaus is what personality factors that contribute to happy or afraid does one examine. Since each consumer purchase decision is based on an individual, any survey developed must be able to accommodate all personality profiles for the market and how they react when happy or afraid. When the purchase experience is in the B2B market, the emotional and subconscious elements are dramatically less and more emphasis is placed on the functional attributes of products and services. The research that Mr. Klaus is doing appears to be limited to the consumer market.
Since the development of a scale that measures the customer experience becomes an overwhelming task, I believe Mr. Klaus is taking his measures from the customer corridor. By that I mean the questions that he proposes will pertain to the different ways a customer can experience the company by walking through the corridors (people and processes) of the company.
From this research Mr. Klaus has developed a scale that provides measures and weighting of each of the attributes of the customer experience. The bottom line is that his results may end up being no different that many scales that we see today. However, he has a great concept and only tying his research hypothesis to the real world with real data will tell the story.
The last bottom line is that the industry needs a consistent quality measure of the customer experience. There are many quality measures in use and proposed in the marketplace but none have risen to the top and become the standard.
Mr. Klaus believes the whole story of customer purchasing behavior is multi-faceted and complicated. He states that research shows that customer decision cannot be reduced anymore into a simple "functionality versus price" formula. He asserts that purchasing behavior is driven more by the emotional and subconscious elements and less by the functional attributes of products and services.
From this assertion he believes that offering high-quality goods and services alone is not sufficient. He is suggesting that organizations must compete on a more complex level by creating a satisfactory customer experience through all stages of the buying process, managing the customer's expectations and assessments, before, during and after the buying process. The customer experience is a broad, holistic concept that managers find difficult to measure and manage.
At this point I would like to interject that I agree with much of what he is stating. My wife, a psychotherapist, has pointed out to me that most decisions are rationalizations of the underlying emotions. the four basic emotions are happy, sad, mad and afraid. It makes sense that people generally do not make a purchase when they are sad or mad. People more often make a purchase when they are either happy or afraid.
For example, people buy a tv when they are happy. I never see shoppers who are mad or sad looking at tvs. (I must admit there are some personality disorders that buy under other conditions - some are called shopaholics and some are a step beyond where the urge to shop is psychotic). Customers may also make purchases because of some fear. People will purchase excessive amounts of food if they think there will be a food shortage.
Of course, the problem presented by Mr. Klaus is what personality factors that contribute to happy or afraid does one examine. Since each consumer purchase decision is based on an individual, any survey developed must be able to accommodate all personality profiles for the market and how they react when happy or afraid. When the purchase experience is in the B2B market, the emotional and subconscious elements are dramatically less and more emphasis is placed on the functional attributes of products and services. The research that Mr. Klaus is doing appears to be limited to the consumer market.
Since the development of a scale that measures the customer experience becomes an overwhelming task, I believe Mr. Klaus is taking his measures from the customer corridor. By that I mean the questions that he proposes will pertain to the different ways a customer can experience the company by walking through the corridors (people and processes) of the company.
From this research Mr. Klaus has developed a scale that provides measures and weighting of each of the attributes of the customer experience. The bottom line is that his results may end up being no different that many scales that we see today. However, he has a great concept and only tying his research hypothesis to the real world with real data will tell the story.
The last bottom line is that the industry needs a consistent quality measure of the customer experience. There are many quality measures in use and proposed in the marketplace but none have risen to the top and become the standard.
Saturday, November 29, 2008
Customer Perspective from the Brits
A DHL Express survey of 1200 British adults give some interesting insights into the value of customer service and some of the dissatisfiers. Some of the results of the survey include:
1. 35% of the Brits think that products and services have the most impact on their purchasing decisions. However, 27% think that customer service has the most impact.
2. Women are more concerned than men about customer service 29% for women and 24% for men.
3. The top dissatisfier for customer service among the Brits is waiting times (83%). The second was language barriers (80%). The third was lack of knowledge (74%).
4. The average Brit prefers face-to-face communication (39%). A close second is computer-based communication (35%). Face-to-face communication is more popular with men than women (43% for men versus 36% for women).
5. Age makes a difference. Consumers between the ages of 16 and 24 were more tolerant of poor customer service. Only 44% would seek an alternative provider. Consumers over the age of 55 would seek an alternative provider 64% of the time after receiving poor customer service.
6. 86% of the Brits say that poor customer service affects their decision to make future purchases from a company and 95% say that poor customer service affects their perception of the business as a whole. These percentages are dramatically different that the statistic in item #1 above and appear to be in congruent with the previous statistic. Since respondents are often not congruent in their thinking, this may not be a survey problem.
Since I would expect DHL Express to perform a valid survey, I am concluding that the results are truly indicative of the Brits perspective of customer service. The bottom line is that these findings give another perspective of the impact of customer service on loyalty to a business. Having spoken to several Brits at a conference in London in October, these results track their anecdotal remarks.
1. 35% of the Brits think that products and services have the most impact on their purchasing decisions. However, 27% think that customer service has the most impact.
2. Women are more concerned than men about customer service 29% for women and 24% for men.
3. The top dissatisfier for customer service among the Brits is waiting times (83%). The second was language barriers (80%). The third was lack of knowledge (74%).
4. The average Brit prefers face-to-face communication (39%). A close second is computer-based communication (35%). Face-to-face communication is more popular with men than women (43% for men versus 36% for women).
5. Age makes a difference. Consumers between the ages of 16 and 24 were more tolerant of poor customer service. Only 44% would seek an alternative provider. Consumers over the age of 55 would seek an alternative provider 64% of the time after receiving poor customer service.
6. 86% of the Brits say that poor customer service affects their decision to make future purchases from a company and 95% say that poor customer service affects their perception of the business as a whole. These percentages are dramatically different that the statistic in item #1 above and appear to be in congruent with the previous statistic. Since respondents are often not congruent in their thinking, this may not be a survey problem.
Since I would expect DHL Express to perform a valid survey, I am concluding that the results are truly indicative of the Brits perspective of customer service. The bottom line is that these findings give another perspective of the impact of customer service on loyalty to a business. Having spoken to several Brits at a conference in London in October, these results track their anecdotal remarks.
Friday, November 28, 2008
The Real Impact of Customer Complaints
John Goodman, past president of TARP and currently president of e-satisfy has given some factual data behind some of the statistics that are bandied around in the customer service business. I was glad to see his statistics and understand where they came from. While this data is relatively old, it contains data that I see in the blogs on a regular basis. (This might suggest that many people are satisfied with using old data and just using the phrase "research has shown." The information shown below was published by John Goodman in Competitive advantage, June, 1999.
1. 50% of consumers will complain to a front line person and in the B2B environment the number is 75%.
2. Only 1 to 5% will escalate the complaint to a local manager or corporate HQ. For large ticket items 50% go to the front line and 5 to 10% escalate to local management or corporate HQ. Interestingly, if the company has an 800 number the percentages double. The most important statistic is that only 1 out of 100 to 500 complaints will ever be seen by a senior executive.
3. If the complaint results in out-of-pocket loss the complaint rate is 50 to 75%. Otherwise, the complaint rate for mistreatment, quality and incompetence evoke only a 5 to 30% complaint rates.
4. Tom Peters used to suggest that for every bad experience 10 people will be told and for every good experience only 2 people will be told. From this he noted that bad news travels faster than good news. John Goodman's data suggests that the ratio is really 2 to 1. The original study for Coca-Cola in 1981 showed that a median of 5persons heard about a good experience and 10 heard about a bad experience. A later study for Coca-Cola found that resolution of a problem on the first contact improved loyalty 10% higher than resolution via multiple contacts. A similar study for a domestic auto manufacturer found the numbers to be 8 and 16 respectively.
5. The general rule of thumb I have heard for many years is that it costs five times as much to acquire a new customer as it does to retain an existing customer. Once again, John Goodman gives us the history. They studied new auto customers and found that there was a cost of $375 in advertising for each auto sold. Since the company had a 50% base of loyal customers, the actual advertising cost to acquire a new customer was actually $750 per auto sold. The goodwill expense to retain a customer was $150. Hence the ratio of cost to acquire a new customer versus the cost to retain a customer was 5 to 1.
6. One of the final statistics is one that seems to vary from person to person. According to a study first published in 1988, customers who complain and are satisfied are 8% more loyal than if they had no problem at all. From my studies, I have found similar statistics.
7. I have heard the statistic that 68% of all people who defect leave because of a poor employee attitude. The statistic that John Goodman offers, that is based on a study by TARP suggests that 20% are caused by employee actions, 40% by corporate products and processes and 40% are caused by customer mistakes or incorrect expectations.
The bottom line is that some of the more often quoted customer complaint statistics seem to be constant and do not change with time. At least now we know where some of these "rule of thumb" statistics were derived. The statistics noted above were derived from studies while John Goodman was president of TARP.
1. 50% of consumers will complain to a front line person and in the B2B environment the number is 75%.
2. Only 1 to 5% will escalate the complaint to a local manager or corporate HQ. For large ticket items 50% go to the front line and 5 to 10% escalate to local management or corporate HQ. Interestingly, if the company has an 800 number the percentages double. The most important statistic is that only 1 out of 100 to 500 complaints will ever be seen by a senior executive.
3. If the complaint results in out-of-pocket loss the complaint rate is 50 to 75%. Otherwise, the complaint rate for mistreatment, quality and incompetence evoke only a 5 to 30% complaint rates.
4. Tom Peters used to suggest that for every bad experience 10 people will be told and for every good experience only 2 people will be told. From this he noted that bad news travels faster than good news. John Goodman's data suggests that the ratio is really 2 to 1. The original study for Coca-Cola in 1981 showed that a median of 5persons heard about a good experience and 10 heard about a bad experience. A later study for Coca-Cola found that resolution of a problem on the first contact improved loyalty 10% higher than resolution via multiple contacts. A similar study for a domestic auto manufacturer found the numbers to be 8 and 16 respectively.
5. The general rule of thumb I have heard for many years is that it costs five times as much to acquire a new customer as it does to retain an existing customer. Once again, John Goodman gives us the history. They studied new auto customers and found that there was a cost of $375 in advertising for each auto sold. Since the company had a 50% base of loyal customers, the actual advertising cost to acquire a new customer was actually $750 per auto sold. The goodwill expense to retain a customer was $150. Hence the ratio of cost to acquire a new customer versus the cost to retain a customer was 5 to 1.
6. One of the final statistics is one that seems to vary from person to person. According to a study first published in 1988, customers who complain and are satisfied are 8% more loyal than if they had no problem at all. From my studies, I have found similar statistics.
7. I have heard the statistic that 68% of all people who defect leave because of a poor employee attitude. The statistic that John Goodman offers, that is based on a study by TARP suggests that 20% are caused by employee actions, 40% by corporate products and processes and 40% are caused by customer mistakes or incorrect expectations.
The bottom line is that some of the more often quoted customer complaint statistics seem to be constant and do not change with time. At least now we know where some of these "rule of thumb" statistics were derived. The statistics noted above were derived from studies while John Goodman was president of TARP.
Wednesday, November 26, 2008
Loyalty Accounting
I am not an accountant, but I read an article that raised a red flag at me. The article was addressing what are the accounting principles that can be applied to loyalty programs. I found the article in "Customer World" and it references an article by Rajiv Goyal in the DNA Money magazine in India.
I have chosen to address this topic for the following reasons:
1. I have seen very little written about this topic
2. Understanding the way accountants deal with loyalty programs may be a real issue in measuring their performance (success or failure).
3. I would like to be able to factor in the accounting impact into the loyalty math models.
4. It is about time that accountants start thinking about customers and become a part of the customer-centric company
The problem as I understand it concerns how the value of loyalty points can be accounted for before they are redeemed. When a company (such as an airline, credit card company, or even a clothing store) offers customers loyalty points, there is no easy way of knowing when the points will be redeemed. At the time when the points are awarded, the company takes on a liability for the value of those points. However, the time at which the points will be redeemed is not known so that there is no way of allocating the funds to a specific accounting period. Thus, the accountant can become frustrated because there is no way that the books can be reconciled without doing something with those "ugly" loyalty points.
As the number of loyalty points increases, the value of the accumulated loyalty points increases (as the airlines are seeing) and the financial impact can become staggering.
Of course, all this time the company, and especially the marketing department that created the loyalty points program, is basking in the increased business that has accrued from the program. The sales and marketing people are looking forward to a big bonus check for the great job they have done in recapturing some old customers and increasing the sales from existing customers. And well they should - they did just what management wanted them to do.
There are two points to consider; namely,
1. not all the points will be redeemed, and
2. the value given for each point was computed before the program was initiated so that the profit margin on the products will still be sufficient to meet company profit goals even if all points are redeemed.
The issues that still remain for the accountant are:
1. Since the loyalty points act like a discount on sales, there is no way to predict how much of a discount to use since not all points will be redeemed.
2. There is no way to determine what provision should be made for the liabilities.
3. There is also no way to determine the time period in which the discounts will occur.
4. There are no specific guidelines in the accounting standards in India (and probably anywhere else) on how to handle these discounts.
In general, the accountants do not see customers in the same way that sales and marketing see them. The article points out the need for customer-centric by accountants. I agree.
The bottom line is we need to get all areas of the firm to be customer-centric and that includes accounting if we are to be able to truly focus on the customer.
I have chosen to address this topic for the following reasons:
1. I have seen very little written about this topic
2. Understanding the way accountants deal with loyalty programs may be a real issue in measuring their performance (success or failure).
3. I would like to be able to factor in the accounting impact into the loyalty math models.
4. It is about time that accountants start thinking about customers and become a part of the customer-centric company
The problem as I understand it concerns how the value of loyalty points can be accounted for before they are redeemed. When a company (such as an airline, credit card company, or even a clothing store) offers customers loyalty points, there is no easy way of knowing when the points will be redeemed. At the time when the points are awarded, the company takes on a liability for the value of those points. However, the time at which the points will be redeemed is not known so that there is no way of allocating the funds to a specific accounting period. Thus, the accountant can become frustrated because there is no way that the books can be reconciled without doing something with those "ugly" loyalty points.
As the number of loyalty points increases, the value of the accumulated loyalty points increases (as the airlines are seeing) and the financial impact can become staggering.
Of course, all this time the company, and especially the marketing department that created the loyalty points program, is basking in the increased business that has accrued from the program. The sales and marketing people are looking forward to a big bonus check for the great job they have done in recapturing some old customers and increasing the sales from existing customers. And well they should - they did just what management wanted them to do.
There are two points to consider; namely,
1. not all the points will be redeemed, and
2. the value given for each point was computed before the program was initiated so that the profit margin on the products will still be sufficient to meet company profit goals even if all points are redeemed.
The issues that still remain for the accountant are:
1. Since the loyalty points act like a discount on sales, there is no way to predict how much of a discount to use since not all points will be redeemed.
2. There is no way to determine what provision should be made for the liabilities.
3. There is also no way to determine the time period in which the discounts will occur.
4. There are no specific guidelines in the accounting standards in India (and probably anywhere else) on how to handle these discounts.
In general, the accountants do not see customers in the same way that sales and marketing see them. The article points out the need for customer-centric by accountants. I agree.
The bottom line is we need to get all areas of the firm to be customer-centric and that includes accounting if we are to be able to truly focus on the customer.
Saturday, November 22, 2008
The Problem with Assumptions
I just finished reading an article by Michael Lieberman in the November Issue of Quirk's Marketing Research Review. The article is titled Measuring and maximizing the ROI of a loyalty program. Needless to say, it caught my attention.
First let me say that Mr. Lieberman has presented an excellent case for showing how an ROI can be computed for a given loyalty program. He uses a technique referred to as Monte Carlo Simulation. This technique uses a series of random trials (events) to see how a system that is not deterministic will respond by going through the process a large number of times. By using some statistical distributions to represent the different ways elements of the system (customers) could act, the output provides a picture of those many trials. This technique has been used for a long time and has been well tested and accepted.
There are two very important aspects to performing a Monte Carlo simulation. The first is to understand the assumptions used and second is to compare the simulation results to actual results. Unfortunately, the magazine did not give Mr. Leiberman the space to fully demonstrate the power of Monte Carlo simulation and answer these two aspects.
The first aspect which was inadequately discussed was a clear and complete discussion of the assumptions in his model. The second aspect was to compare the simulation results to the real world that he was simulating. There was no there, there. The results of his simulation were not compared to actual data.
Some of the assumptions that should have been explained in the article might include:
1. the relationship between the dollar value of the purchases and the incentives given. Is the relationship linear, non-linear or ???
2. the variation of margins for different product mixes. Was this considered a constant?
3. the percentage of loyalty points that will be redeemed (if the data is categorized then the assumptions should be noted by group unless it is further assumed that the groups are all the same).
4. the belief that a customer's spending behavior will change because their spending has changed.
The second aspect is that results must ALWAYS be compared with the real world. Yes, computers can produce a lot of output that seems to represent the real world, but until it is tested and verified in the real world, it is just computer output. The fact is that the computer output may be 100 percent accurate or 10 percent accurate, but you will never know it unless it is checked against the actual system in place.
For example, when I worked at Xerox, we were investigating the idea of going to team service. One of the variables we needed to understand was the statistical distribution of the time to complete a service call. The assumption was that the service completion time was statistically distributed according to the negative exponential distribution. Before we ran our simulation model we built an analytical queuing model to get an idea what the optimum team size should be. We could not easily include meetings, lunches and parts chasing into our model so the only way to get an accurate assessment of the optimum team size was to build the simulation model to account for the vagaries that were not easily modeled analytically. As it turned out the service completion time distribution was not a simple negative distribution, it was a significantly different variant of the negative exponential distribution and one that made a difference in our results. While it did not change the optimum team size, it did impact the value of the team.
The point here is that you must carefully describe the model and ALL its assumptions so that you are not misled by the computer results. A friend of mine once said that GIGO does not stand for "Garbage - In Garbage Out." Rather it stands for "Garbage In - Gospel Out."
The bottom line is that Monte Carlo Simulations provide an excellent tool for pre-testing business policies. I believe that Michael Lieberman did do the work and managed the assumptions. Unfortunately, his article doesn't reflect that. Sometimes an editorial pen can kill you.
First let me say that Mr. Lieberman has presented an excellent case for showing how an ROI can be computed for a given loyalty program. He uses a technique referred to as Monte Carlo Simulation. This technique uses a series of random trials (events) to see how a system that is not deterministic will respond by going through the process a large number of times. By using some statistical distributions to represent the different ways elements of the system (customers) could act, the output provides a picture of those many trials. This technique has been used for a long time and has been well tested and accepted.
There are two very important aspects to performing a Monte Carlo simulation. The first is to understand the assumptions used and second is to compare the simulation results to actual results. Unfortunately, the magazine did not give Mr. Leiberman the space to fully demonstrate the power of Monte Carlo simulation and answer these two aspects.
The first aspect which was inadequately discussed was a clear and complete discussion of the assumptions in his model. The second aspect was to compare the simulation results to the real world that he was simulating. There was no there, there. The results of his simulation were not compared to actual data.
Some of the assumptions that should have been explained in the article might include:
1. the relationship between the dollar value of the purchases and the incentives given. Is the relationship linear, non-linear or ???
2. the variation of margins for different product mixes. Was this considered a constant?
3. the percentage of loyalty points that will be redeemed (if the data is categorized then the assumptions should be noted by group unless it is further assumed that the groups are all the same).
4. the belief that a customer's spending behavior will change because their spending has changed.
The second aspect is that results must ALWAYS be compared with the real world. Yes, computers can produce a lot of output that seems to represent the real world, but until it is tested and verified in the real world, it is just computer output. The fact is that the computer output may be 100 percent accurate or 10 percent accurate, but you will never know it unless it is checked against the actual system in place.
For example, when I worked at Xerox, we were investigating the idea of going to team service. One of the variables we needed to understand was the statistical distribution of the time to complete a service call. The assumption was that the service completion time was statistically distributed according to the negative exponential distribution. Before we ran our simulation model we built an analytical queuing model to get an idea what the optimum team size should be. We could not easily include meetings, lunches and parts chasing into our model so the only way to get an accurate assessment of the optimum team size was to build the simulation model to account for the vagaries that were not easily modeled analytically. As it turned out the service completion time distribution was not a simple negative distribution, it was a significantly different variant of the negative exponential distribution and one that made a difference in our results. While it did not change the optimum team size, it did impact the value of the team.
The point here is that you must carefully describe the model and ALL its assumptions so that you are not misled by the computer results. A friend of mine once said that GIGO does not stand for "Garbage - In Garbage Out." Rather it stands for "Garbage In - Gospel Out."
The bottom line is that Monte Carlo Simulations provide an excellent tool for pre-testing business policies. I believe that Michael Lieberman did do the work and managed the assumptions. Unfortunately, his article doesn't reflect that. Sometimes an editorial pen can kill you.
Wednesday, November 19, 2008
One Positive Aspect of Using a Survey
Professors Paul Dholakia and Vicki Morwitz completed a research study that tested the impact of a customer survey impact on loyalty. Their research study has been published in the Harvard Business Review. The objective of their study was to determine whether or not the process of performing a survey causes significant changes in the future behavior of those receiving the survey.
They worked with a financial institution and selected customers with high levels of satisfaction and created two groups. The first group participated in a customer survey of customer satisfaction. The second group (control group) did not participate in any research. The behaviors and profitability of each group was tracked for one year following the survey.
The observed differences included:
1. Survey participants were THREE times as likely to open new accounts with the firm.
2. Survey participants were LESS THAN HALF as likely to defect.
3. Survey participants had a profitability profile that was significantly better than the non participation group.
4. Survey participants continued to open hew accounts at a faster rate and to defect at a slower rate than the nonparticipants even after a year.
Professors Dholakia and Morwitz believe the effects of survey participation will last anywhere from THREE to EIGHT years.
The most important aspect of this research is that surveys themselves have a positive effect on customers. The effects may, in fact, cause sustained changes in customer behavior. The evidence appears to demonstrate that the differences are quantifiable with a measurable impact on the financial performance of the firm.
One important research question is why this is happening. There are many hypotheses that might explain the customer behavior. Let us hope that the work of Professors Dholakia and Morwitz will continue their research that appears to have such a significant impact on survey work.
One caveat to this research is that it was performed on only one company in only one industry. It will be interesting to see if these results can be replicated in other companies in other industries.
They worked with a financial institution and selected customers with high levels of satisfaction and created two groups. The first group participated in a customer survey of customer satisfaction. The second group (control group) did not participate in any research. The behaviors and profitability of each group was tracked for one year following the survey.
The observed differences included:
1. Survey participants were THREE times as likely to open new accounts with the firm.
2. Survey participants were LESS THAN HALF as likely to defect.
3. Survey participants had a profitability profile that was significantly better than the non participation group.
4. Survey participants continued to open hew accounts at a faster rate and to defect at a slower rate than the nonparticipants even after a year.
Professors Dholakia and Morwitz believe the effects of survey participation will last anywhere from THREE to EIGHT years.
The most important aspect of this research is that surveys themselves have a positive effect on customers. The effects may, in fact, cause sustained changes in customer behavior. The evidence appears to demonstrate that the differences are quantifiable with a measurable impact on the financial performance of the firm.
One important research question is why this is happening. There are many hypotheses that might explain the customer behavior. Let us hope that the work of Professors Dholakia and Morwitz will continue their research that appears to have such a significant impact on survey work.
One caveat to this research is that it was performed on only one company in only one industry. It will be interesting to see if these results can be replicated in other companies in other industries.
The Government and Good Customer Service
I think I have found a real oximoron. The surprising news is that public satisfaction with government web sites is increasing. Holy Cow!!!
According to the ACSI, one of the most reputable survey services in the US notes that the aggregate score of 73.9 out of 100 points increased from 72.9 in the previous quarter. This latest score is among the highest since the index was launched in 2003 and nearly matching the high of 74 points that occurred in 2006.
According to Larry Freed, President and CEO of Foresee Research, which published the report 27 percent of the government sites surveyed scored 80 or above on the index. If some can achieve scores of 80 or more, that means that there are still some government web sites that are not serving the public very well.
Some of the other AMAZING and positive facts noted in the report are:
1. GSA's main web site is up 9 points from last year and 22 points from when it was first measured.
2. National Center for Drug Abuse made significant gains.
3. national Resource Conservation Service also made significant gains.
While the private sector still out-performs the government, the government appears to be working to improve their site satisfaction.
Let's hope the government continues to improve its web sites. We the people deserve web sites that work and are easy to use. It's about time the government figured this out!
According to the ACSI, one of the most reputable survey services in the US notes that the aggregate score of 73.9 out of 100 points increased from 72.9 in the previous quarter. This latest score is among the highest since the index was launched in 2003 and nearly matching the high of 74 points that occurred in 2006.
According to Larry Freed, President and CEO of Foresee Research, which published the report 27 percent of the government sites surveyed scored 80 or above on the index. If some can achieve scores of 80 or more, that means that there are still some government web sites that are not serving the public very well.
Some of the other AMAZING and positive facts noted in the report are:
1. GSA's main web site is up 9 points from last year and 22 points from when it was first measured.
2. National Center for Drug Abuse made significant gains.
3. national Resource Conservation Service also made significant gains.
While the private sector still out-performs the government, the government appears to be working to improve their site satisfaction.
Let's hope the government continues to improve its web sites. We the people deserve web sites that work and are easy to use. It's about time the government figured this out!
Monday, November 17, 2008
Loyalty Metrics That Make Sense
There are probably as many loyalty metrics as there are consultants. At one extreme some say you only need one while the other extreme says you need a PhD in statistics to understand all the interactions that a customer has with your organization. My personal leanings are toward the middle but nearer the low end.
I was recently reading the work of Jeanne Bliss, the author of "Chief Customer Officer" and thought she had a pretty good idea of the kind of metrics that makes sense and yet is reasonably comprehensible. She devotes a chapter to these metrics in her book and refers to the metrics as Guerrilla Metrics. I think she calls them Guerrilla Metrics because it will take Guerrilla tactics to get them implemented in your organization. I think she may be over-stating the problem, but she appears to be speaking from experience.
Guerrilla metrics consist of five measures (reasonable and comprehensive in my mind). The following descriptions of the metrics reasonably describe them in simple language.
1. Measure the number of new customers in a specific reporting period (weekly, monthly or quarterly). The idea is not to just count them but also categorize them at the same time. By that I mean classify them according to the types of products and services they are buying and then assess them in terms of value (lifetime or some other measure that differentiates the high value customer from the low value customer).
2. Measure the number of customers you lose in the same reporting period. This is one of the most overlooked aspects of customer loyalty. Many companies have no idea when they lose a customer. Unless you know why you are losing customers, you may continue to lose them. Remember the sage quote "if you don't know your history you are bound to repeat it."
3. Repeat customers or customers who renew on-going contracts. Just as it is important to know why customers leave, it is also important to know why they come back.
4. Measure the revenue and profitability of each of the categories of customers identified previously. There are two reasons for this measure; namely, (i) to rank order each group in terms of profitability and (ii) to see if there is migration from one group to another - preferably from a lower profit and revenue group to a higher one - but just as important to note when migration starts to move from higher revenue and profit groups to lower ones.
5. Measure the number of referrals from existing customers. This is similar to the NPS measure except it requires that you track the rate of referrals overall but more specially by customer group. If your company is not getting referrals that may be a sign of a customer disconnect somewhere along the customer corridor.
These five measures are all great measures in my opinion. However, they are also very difficult measures to accurately assess. The bottom line is that we know that there is a strong relationship between customer-centric organizations and ROI. Hence, we can conclude that it probably takes a comprehensive customer metric system requiring multiple measures to examine all aspects of customers (coming ,going, staying and referring new customers). For example, using NPS one would only be measuring the fifth component of the five Guerrilla measures.
With these measures one could easily start building a business model that would show the net customer perspective each reporting period (new + existing + newly referred customers - lost customers). This could be done by each business segment to show both quantity of customers and value. I would be interested to know if there are any companies that use this type of customer metric system. Drop me a comment if you know of one or, better yet, if you are one.
I was recently reading the work of Jeanne Bliss, the author of "Chief Customer Officer" and thought she had a pretty good idea of the kind of metrics that makes sense and yet is reasonably comprehensible. She devotes a chapter to these metrics in her book and refers to the metrics as Guerrilla Metrics. I think she calls them Guerrilla Metrics because it will take Guerrilla tactics to get them implemented in your organization. I think she may be over-stating the problem, but she appears to be speaking from experience.
Guerrilla metrics consist of five measures (reasonable and comprehensive in my mind). The following descriptions of the metrics reasonably describe them in simple language.
1. Measure the number of new customers in a specific reporting period (weekly, monthly or quarterly). The idea is not to just count them but also categorize them at the same time. By that I mean classify them according to the types of products and services they are buying and then assess them in terms of value (lifetime or some other measure that differentiates the high value customer from the low value customer).
2. Measure the number of customers you lose in the same reporting period. This is one of the most overlooked aspects of customer loyalty. Many companies have no idea when they lose a customer. Unless you know why you are losing customers, you may continue to lose them. Remember the sage quote "if you don't know your history you are bound to repeat it."
3. Repeat customers or customers who renew on-going contracts. Just as it is important to know why customers leave, it is also important to know why they come back.
4. Measure the revenue and profitability of each of the categories of customers identified previously. There are two reasons for this measure; namely, (i) to rank order each group in terms of profitability and (ii) to see if there is migration from one group to another - preferably from a lower profit and revenue group to a higher one - but just as important to note when migration starts to move from higher revenue and profit groups to lower ones.
5. Measure the number of referrals from existing customers. This is similar to the NPS measure except it requires that you track the rate of referrals overall but more specially by customer group. If your company is not getting referrals that may be a sign of a customer disconnect somewhere along the customer corridor.
These five measures are all great measures in my opinion. However, they are also very difficult measures to accurately assess. The bottom line is that we know that there is a strong relationship between customer-centric organizations and ROI. Hence, we can conclude that it probably takes a comprehensive customer metric system requiring multiple measures to examine all aspects of customers (coming ,going, staying and referring new customers). For example, using NPS one would only be measuring the fifth component of the five Guerrilla measures.
With these measures one could easily start building a business model that would show the net customer perspective each reporting period (new + existing + newly referred customers - lost customers). This could be done by each business segment to show both quantity of customers and value. I would be interested to know if there are any companies that use this type of customer metric system. Drop me a comment if you know of one or, better yet, if you are one.
Friday, November 14, 2008
Impact of Dissatisfiers
I have written extensively about the very significant difference between satisfiers and dissatisfiers. I have made the point that customers will tolerate a temporary decline in performance of a company process or product that is a satisfier (such as the temperature of a hamburger at McDonalds that is not really warm), and continue to do business with the company. However, when a customer experiences a decline in a dissatisfier, the impact can be immediate loss of that customer (such as a finding a dirty restroom at the McDonalds).
This difference has been validated by a survey of 500 Australian adults by StollzNow Research. On the positive side they found that 28 percent of consumers will remain loyal to companies that provide them with the best service. But consider the impact of the dissatisfiers.
1. 79 percent of consumers have stopped doing business with an organization because of a bad experience (you can bet it had to do with a dissatisfier).
2. 71 percent of consumers tell others about their negative experience with the aim of preventing other consumers from doing business with the company at fault.
The primary reason I am using this wonderful example of the impact of dissatisfiers is to point out that most surveys do not have the ability to sort out the satisfiers from the dissatisfiers. Companies can recover from a decline in performance of a product or service which is known to be a satisfier but will begin to lose customers immediately when a product or service that is a dissatisfier declines.
The bottom line is that companies must be aware of what the dissatisfiers are. They must be ever vigilant to manage the dissatisfiers because of the immediacy of the impact on their business.
This difference has been validated by a survey of 500 Australian adults by StollzNow Research. On the positive side they found that 28 percent of consumers will remain loyal to companies that provide them with the best service. But consider the impact of the dissatisfiers.
1. 79 percent of consumers have stopped doing business with an organization because of a bad experience (you can bet it had to do with a dissatisfier).
2. 71 percent of consumers tell others about their negative experience with the aim of preventing other consumers from doing business with the company at fault.
The primary reason I am using this wonderful example of the impact of dissatisfiers is to point out that most surveys do not have the ability to sort out the satisfiers from the dissatisfiers. Companies can recover from a decline in performance of a product or service which is known to be a satisfier but will begin to lose customers immediately when a product or service that is a dissatisfier declines.
The bottom line is that companies must be aware of what the dissatisfiers are. They must be ever vigilant to manage the dissatisfiers because of the immediacy of the impact on their business.
Thursday, November 13, 2008
Satisfiers and Loyalty for Rental Cars
JD Power just published the 2008 Rental Car Satisfaction Study. The study was based on more than 13,400 evaluations from business and leisure travelers who rented a vehicle at an airport location between September 2007 and October 2008.
The study showed the top three rental car companies were Enterprise, Hertz and Alamo in that order. The scoring was based on 6 general factors:
1. costs and fees
2. pick-up process
3. rental car
4. return process
5. reservation process
6. shuttle van/bus.
Note that these are general variables and should/must have some additional detail measures behind them to make them actionable. The report indicates there are some additional factors that have a particularly strong impact on satisfaction; namely,
1. adequate prep of the vehicle
2. ensure customers receive the vehicle model they reserve
3. minimizing wait times for vehicle pick up and drop off.
Recall that in previous my previous blogs I have identified the three components of loyalty as product, process and people. Other than the cost/fees component the other five factors contain a combination of process and people. In order to translate the factors into actionable items each of those five factors must be broken into its component parts that relate to the service process and the people in the service process. For example, the satisfaction of having a short wait time for pick up can be dramatically reduce by a driver who has dirty clothes and a bad attitude. Of course the other side of the coin is that satisfaction resulting from a long wait can be dramatically improved with a very courteous driver with a can-do attitude. The point is that all three components of loyalty must be included in order to maximize the impact on customer loyalty.
Another point to be made from examining these factors is that there is no discussion of which factors are satisfies and which are dissatisfiers. The difference is critical. Recall that satisfiers have room to move with little impact on overall satisfaction whereas dissatisfiers can cause customers to leave immediately with a simultaneous major negative impact on overall satisfaction.
Some further statistics from the study suggests the impact of an imbalance of the three loyalty components. When the data is parsed into groups the following statistics are observed:
1. When customers say they experience a problem, overall satisfaction declines more than 10% compared to customers that had no problems.
2. If the problem is not resolved, overall satisfaction drops approximately an additional 5%.
The final set of statistics relate to the typical loyalty questions; (i) likely to use the car company again, and (ii) likely to recommend. Below are the statistics that relate these two measures to the measure of overall satisfaction:
1. For customers who are highly committed, 86 percent said they will definitely use the care company again and 88 percent said they would definitely recommend the company to others.
2. For customers with only a medium commitment, 21 percent said they would definitely use the car company again and 20 percent would definitely recommend the car company to others.
The bottom line is that there is an obvious impact of satisfaction on loyalty when you examine this data. One interesting point is that customers with a high level of commitment are about 4 times more likely to return and recommend. The economic impact of this statistic would warrant careful consideration by all rental car companies to focus on satisfaction. There is one additional point to be made from the data. Namely, there apparently are about 20% of the customers with only a medium commitment who act like apostles. Maybe some of these customers with only medium commitment are part-time apostles.
The study showed the top three rental car companies were Enterprise, Hertz and Alamo in that order. The scoring was based on 6 general factors:
1. costs and fees
2. pick-up process
3. rental car
4. return process
5. reservation process
6. shuttle van/bus.
Note that these are general variables and should/must have some additional detail measures behind them to make them actionable. The report indicates there are some additional factors that have a particularly strong impact on satisfaction; namely,
1. adequate prep of the vehicle
2. ensure customers receive the vehicle model they reserve
3. minimizing wait times for vehicle pick up and drop off.
Recall that in previous my previous blogs I have identified the three components of loyalty as product, process and people. Other than the cost/fees component the other five factors contain a combination of process and people. In order to translate the factors into actionable items each of those five factors must be broken into its component parts that relate to the service process and the people in the service process. For example, the satisfaction of having a short wait time for pick up can be dramatically reduce by a driver who has dirty clothes and a bad attitude. Of course the other side of the coin is that satisfaction resulting from a long wait can be dramatically improved with a very courteous driver with a can-do attitude. The point is that all three components of loyalty must be included in order to maximize the impact on customer loyalty.
Another point to be made from examining these factors is that there is no discussion of which factors are satisfies and which are dissatisfiers. The difference is critical. Recall that satisfiers have room to move with little impact on overall satisfaction whereas dissatisfiers can cause customers to leave immediately with a simultaneous major negative impact on overall satisfaction.
Some further statistics from the study suggests the impact of an imbalance of the three loyalty components. When the data is parsed into groups the following statistics are observed:
1. When customers say they experience a problem, overall satisfaction declines more than 10% compared to customers that had no problems.
2. If the problem is not resolved, overall satisfaction drops approximately an additional 5%.
The final set of statistics relate to the typical loyalty questions; (i) likely to use the car company again, and (ii) likely to recommend. Below are the statistics that relate these two measures to the measure of overall satisfaction:
1. For customers who are highly committed, 86 percent said they will definitely use the care company again and 88 percent said they would definitely recommend the company to others.
2. For customers with only a medium commitment, 21 percent said they would definitely use the car company again and 20 percent would definitely recommend the car company to others.
The bottom line is that there is an obvious impact of satisfaction on loyalty when you examine this data. One interesting point is that customers with a high level of commitment are about 4 times more likely to return and recommend. The economic impact of this statistic would warrant careful consideration by all rental car companies to focus on satisfaction. There is one additional point to be made from the data. Namely, there apparently are about 20% of the customers with only a medium commitment who act like apostles. Maybe some of these customers with only medium commitment are part-time apostles.
Monday, November 10, 2008
Cultural Impact on Customer Loyalty
As I have noted in previous blogs, I have a large and growing data base of customer satisfaction data from information technology services. One of the areas I have studied is help desks (often referred to as technical support). I have been finding that there is a definite cultural component to high technology service. This may also be true for other areas but I can only speak to the service support for high technology equipment.
The largest difference I found in a recent study of help desks was between the United States and the Benelux countries. The sample sizes were large and met the criteria of a probability sample. For the United States the sample was 90,437 and for the Benelux countries the sample was 6600. Clearly, the sample sizes are sufficient to draw valid statistical conclusions. The really good news was the sample had wonderful characteristics; namely,
1. All data taken by the same survey organization.
2. All equipment had relatively the same complexity.
3. There were at least 10 companies in the data and all have very similar SLAs (Service Level Agreements).
4. All scales were the same (1 to 5 with 5 being highest and 1 being lowest).
To give an indication of the difference between customer satisfaction for help desk the United States and the Benelux countries, the 61.4 percent of the customers in the United States sample scored help desk satisfaction 5 whereas 28 percent of the Benelux countries sample scored help desk satisfaction 5.
The question is why would United States customers score a 5 for help desk service more then twice as often as the Benelux customers. Remember, the survey was taken for high technology companies that provide world-wide service at about the same service level.
This becomes even more interesting when I compared the percent of customers who scored 1 for help desk satisfaction. The United States had 3.3 percent and Benelux had 3.0 percent of their customers who decided that help desk satisfaction was very unsatisfactory.
The percent difference for scores of 5 are DRAMATICALLY HIGHER for the United States than Benelux but the difference for scores of 1 are not nearly as dramatic.
The difference is definitely at the high end of the scale. I am sure there are some excellent sociologists that cold give a plausible explanation. My first hypothesis about why this difference exists is that the attitude of the personnel on the help desk is different. I have not yet tested this but here is my reasoning:
1. It is easier to get rid of an under-performing technician in the United States than in the Benelux countries; therefore, the US tech has a greater downside for not performing well than the Benelux tech.
2. The customers in the Benelux countries may have a higher standard for service than the US customers.
3. Workload levels may be different between the United States and Benelux countries.
4. The training levels may be different and more comprehensive in the United States than Benelux countries.
5. The fact that the help desks in the Benelux countries has to deal with multiple languages could have an effect.
The bottom line is that customer satisfaction and the implied customer loyalty appears to have a very strong component. The next step is to isolate each of the contributing factors and assess which ones can be controlled and which ones are going to be there no matter what.
The largest difference I found in a recent study of help desks was between the United States and the Benelux countries. The sample sizes were large and met the criteria of a probability sample. For the United States the sample was 90,437 and for the Benelux countries the sample was 6600. Clearly, the sample sizes are sufficient to draw valid statistical conclusions. The really good news was the sample had wonderful characteristics; namely,
1. All data taken by the same survey organization.
2. All equipment had relatively the same complexity.
3. There were at least 10 companies in the data and all have very similar SLAs (Service Level Agreements).
4. All scales were the same (1 to 5 with 5 being highest and 1 being lowest).
To give an indication of the difference between customer satisfaction for help desk the United States and the Benelux countries, the 61.4 percent of the customers in the United States sample scored help desk satisfaction 5 whereas 28 percent of the Benelux countries sample scored help desk satisfaction 5.
The question is why would United States customers score a 5 for help desk service more then twice as often as the Benelux customers. Remember, the survey was taken for high technology companies that provide world-wide service at about the same service level.
This becomes even more interesting when I compared the percent of customers who scored 1 for help desk satisfaction. The United States had 3.3 percent and Benelux had 3.0 percent of their customers who decided that help desk satisfaction was very unsatisfactory.
The percent difference for scores of 5 are DRAMATICALLY HIGHER for the United States than Benelux but the difference for scores of 1 are not nearly as dramatic.
The difference is definitely at the high end of the scale. I am sure there are some excellent sociologists that cold give a plausible explanation. My first hypothesis about why this difference exists is that the attitude of the personnel on the help desk is different. I have not yet tested this but here is my reasoning:
1. It is easier to get rid of an under-performing technician in the United States than in the Benelux countries; therefore, the US tech has a greater downside for not performing well than the Benelux tech.
2. The customers in the Benelux countries may have a higher standard for service than the US customers.
3. Workload levels may be different between the United States and Benelux countries.
4. The training levels may be different and more comprehensive in the United States than Benelux countries.
5. The fact that the help desks in the Benelux countries has to deal with multiple languages could have an effect.
The bottom line is that customer satisfaction and the implied customer loyalty appears to have a very strong component. The next step is to isolate each of the contributing factors and assess which ones can be controlled and which ones are going to be there no matter what.
Wednesday, November 5, 2008
Proactive versus Reactive Customer Management
There was an interesting survey performed by Shape the Future, a market research company in the UK. While there was no information on the sample size of their survey, the results are interesting. The major statistic is that 70.3 percent of the companies are measuring customer satisfaction, which implies that 29.7 percent are not. They note that most of the companies that say they are measuring customer satisfaction are employing simple and informal tactics, such as relying on unsolicited customer feedback. The exact breakdown of the 29.7 percent not measuring customer satisfaction offer the following reasons:
1. Believe that customer will tell them if there is a problem.
2. Never thought about measuring customer satisfaction.
3. Are too busy to measure customer satisfaction
4. Plan to measure customer satisfaction in the future.
The first thing that comes to mind is that there is no understanding of the difference between a "good" customer and a "nice" customer. They must believe that all their customers are good customers. If I haven't noted this difference before, a good customer is one who will tell you when something is not done satisfactorily. A nice customer doesn't want to take the time to tell you or is not willing to confront you with the problem. The nice customer just goes away without saying anything. Of course we all want good customers but, unfortunately, not all customers are good customers.
One of the comments by Shape the Future, which is in agreement with my comment above, is that the results are saying too many businesses assume that people will give them useful feedback. Nope! There are too many "nice" customers in the market. They do point out that unhappy customers often leave without telling them why.
The point I want to make in this blog is that companies seem to think they know their customers when, in fact, most of them are out-of-touch. The study several years ago by Bain & Company surveyed 362 companies in the US and found that only 8% of their customers described their experience as "superior," yet 80% of the companies surveyed believe the experience they have been providing is indeed "superior." Many firms have CRM (Customer Relationship Management) programs but only know the customers after there is a record of a customer interaction. Thus, these CRM programs are lagging programs since they only look at the touch points after an interaction.
The bottom line is that customer experience with the company should be viewed from a leading perspective. Rather than waiting for an interaction, companies should be looking at the customer's experiences to determine where the gaps are between what the customer perceives and what the customer experiences. This approach will lead to a better understanding of how to increase loyalty and share of pocket by proactively filling the product and service gaps.
1. Believe that customer will tell them if there is a problem.
2. Never thought about measuring customer satisfaction.
3. Are too busy to measure customer satisfaction
4. Plan to measure customer satisfaction in the future.
The first thing that comes to mind is that there is no understanding of the difference between a "good" customer and a "nice" customer. They must believe that all their customers are good customers. If I haven't noted this difference before, a good customer is one who will tell you when something is not done satisfactorily. A nice customer doesn't want to take the time to tell you or is not willing to confront you with the problem. The nice customer just goes away without saying anything. Of course we all want good customers but, unfortunately, not all customers are good customers.
One of the comments by Shape the Future, which is in agreement with my comment above, is that the results are saying too many businesses assume that people will give them useful feedback. Nope! There are too many "nice" customers in the market. They do point out that unhappy customers often leave without telling them why.
The point I want to make in this blog is that companies seem to think they know their customers when, in fact, most of them are out-of-touch. The study several years ago by Bain & Company surveyed 362 companies in the US and found that only 8% of their customers described their experience as "superior," yet 80% of the companies surveyed believe the experience they have been providing is indeed "superior." Many firms have CRM (Customer Relationship Management) programs but only know the customers after there is a record of a customer interaction. Thus, these CRM programs are lagging programs since they only look at the touch points after an interaction.
The bottom line is that customer experience with the company should be viewed from a leading perspective. Rather than waiting for an interaction, companies should be looking at the customer's experiences to determine where the gaps are between what the customer perceives and what the customer experiences. This approach will lead to a better understanding of how to increase loyalty and share of pocket by proactively filling the product and service gaps.
Monday, November 3, 2008
The Black Swan for Loyalty
I have included the book by Nassim Taleb (The Black Swan) on my book list. The Wall Street Journal today (November 3rd) had an article about Black Swans and Nassim Talib in particular (Section C - Money and Investing, page C1). It turns out the Nassim Taleb is a professor of mathematical finance at NYU and has a hedge fund that is based on black swans. If you haven't already read this book, I highly recommend it. The subtitle of the book is "the impact of the highly improbable." To save a little time, a black swan event "has three principle characteristics; namely, it is unpredictable, it carries massive impact; and after the fact we concoct an explanation that makes it appear less random, and more predictable that it was." Nassim Taleb believes that black swans underlie almost everything about our world, from the rise of religions to events in our personal lives. It is this concept of the highly improbable that led him to describe them as "black swans" since black swans were once thought to be an impossible animal until they found one.
I don't want to summarize the book, my intention is to point out that black swans also occur in business and with customers. In fact, the whole intention of this blog is to make the case that a black swan event with a customer is one that seals customer loyalty and create the kind of "apostle" that is mentioned in other articles about loyalty.
A black swan event is one step beyond a "WOW" event. I described a black swan event on this blog August 11, 2007. Another example of a black swan event for me that created customer loyalty was with a customer who ran a food processing plant in Mississippi. The plant ran two shifts each day from 8am until midnight. It was important the the food was properly cooked to prevent salmonella or some other bacteria from getting into the food. I was head of service for Taylor Instrument company and received a call from the plant manger who suggested I resign from Taylor because I was overcharging the customers. He had a bill with 8 hours of overtime plas 1 hour of regular time. He pointed out that the sign-in sheets for his plant could only verify the 1 hour of regular time.
He wanted me to know that he intended to call the president of Taylor and recommend that he fire me. I suggested that he wait for 24 hours and that I would get back to him with an explanation for the charges. To make a long story short, our local technician had traveled all night to the next closest technician to get a critical part that was needed for the repair just so that the food processing plant would not be shutdown the next day while awaiting the replacement part.
When I explained the reason for the charge I had an instant apostle. He was amazed that someone who did not work for him would spend the entire night traveling 400 miles round trip to make sure his plant was operational when the 8am shift came in the next day.
The bottom line is that a highly improbable event (such as a technician driving all night just to make sure that a plant was not shutdown) creates an apostle. No company can expect to have black swans occur on a regular basis - that would negate the black swan inference. However, companies must be prepared to deliver a black swan event when the opportunity occurs (and they do occur). The question I would ask any company that has a desire to build customer loyalty is "are you prepared to respond to a black swan event." Then I would ask "will you know a black swan event if you see it."
I don't want to summarize the book, my intention is to point out that black swans also occur in business and with customers. In fact, the whole intention of this blog is to make the case that a black swan event with a customer is one that seals customer loyalty and create the kind of "apostle" that is mentioned in other articles about loyalty.
A black swan event is one step beyond a "WOW" event. I described a black swan event on this blog August 11, 2007. Another example of a black swan event for me that created customer loyalty was with a customer who ran a food processing plant in Mississippi. The plant ran two shifts each day from 8am until midnight. It was important the the food was properly cooked to prevent salmonella or some other bacteria from getting into the food. I was head of service for Taylor Instrument company and received a call from the plant manger who suggested I resign from Taylor because I was overcharging the customers. He had a bill with 8 hours of overtime plas 1 hour of regular time. He pointed out that the sign-in sheets for his plant could only verify the 1 hour of regular time.
He wanted me to know that he intended to call the president of Taylor and recommend that he fire me. I suggested that he wait for 24 hours and that I would get back to him with an explanation for the charges. To make a long story short, our local technician had traveled all night to the next closest technician to get a critical part that was needed for the repair just so that the food processing plant would not be shutdown the next day while awaiting the replacement part.
When I explained the reason for the charge I had an instant apostle. He was amazed that someone who did not work for him would spend the entire night traveling 400 miles round trip to make sure his plant was operational when the 8am shift came in the next day.
The bottom line is that a highly improbable event (such as a technician driving all night just to make sure that a plant was not shutdown) creates an apostle. No company can expect to have black swans occur on a regular basis - that would negate the black swan inference. However, companies must be prepared to deliver a black swan event when the opportunity occurs (and they do occur). The question I would ask any company that has a desire to build customer loyalty is "are you prepared to respond to a black swan event." Then I would ask "will you know a black swan event if you see it."
Friday, October 31, 2008
Three Metrics for Retail Loyalty
Aberdeen Research conducted a survey of 231 retail enterprises between May and June 2008 to determine the state of loyalty technology in retail. The survey results indicated that 58% of best-in-class companies in retail found that lifetime customer value had great impact on loyalty. They defined lifetime customer value as the present value of future cash flows through long-term customer relationships. They also found that 93% of retailers execute loyalty programs as a standard offering for their web store or catalog customers.
A significant point made in the report is that lifetime customer value in retail is being overshadowed by loyalty programs which are more tactical in nature than the more strategic lifetime customer value strategy. The survey found the following three factors were the most significant for justifying spending on loyalty:
1. Repeat visits were used by 61% of the retailers,
2. Incremental sales were used by 58% of the retailers, and
3. Overall satisfaction were used by 57% of the retailers.
The retail business is somewhat unique in that it is dominated by the need to be current. Since many retailers generate much of their revenue in only a few seasons, missing one (or even worse more than one) can quickly put a retailer out of business.
For this reason alone, the three criteria noted above seem particularly relevant for the fast pace of retail.
The bottom line is that these three factors really represent complementary measures of loyalty. Some people would add share-of-pocket as another possible measure. If there is a recession (and it seems very likely, if it hasn't already begun), the retailers who manage their business with an eye toward building and maintaining customer loyalty will be better positioned to survive than those who ignore the value of a loyal customer.
A significant point made in the report is that lifetime customer value in retail is being overshadowed by loyalty programs which are more tactical in nature than the more strategic lifetime customer value strategy. The survey found the following three factors were the most significant for justifying spending on loyalty:
1. Repeat visits were used by 61% of the retailers,
2. Incremental sales were used by 58% of the retailers, and
3. Overall satisfaction were used by 57% of the retailers.
The retail business is somewhat unique in that it is dominated by the need to be current. Since many retailers generate much of their revenue in only a few seasons, missing one (or even worse more than one) can quickly put a retailer out of business.
For this reason alone, the three criteria noted above seem particularly relevant for the fast pace of retail.
The bottom line is that these three factors really represent complementary measures of loyalty. Some people would add share-of-pocket as another possible measure. If there is a recession (and it seems very likely, if it hasn't already begun), the retailers who manage their business with an eye toward building and maintaining customer loyalty will be better positioned to survive than those who ignore the value of a loyal customer.
Thursday, October 30, 2008
Metric Confusion
The Gartner Group recently held its CRM Summit in Washington, D.C. where the opening theme was managing the customer experience. Ed Thompson, Vice President made the point that focus on CRM has shifted to better managing the customer experience. He provided two interesting statistics; namely,
1. 80% of executives think customer satisfaction is more important than it was three years ago.
2. 95% of business leaders see customer satisfaction as the next competitive battleground.
3. Most companies have an average of seven metrics.
4. Most companies have their own derivative of the net promoter score.
He pointed out that everything else a company does is easy to copy - such as price, product and delivery.
The big question at the Summit "How do you measure it?"
Ed Thompson pointed out that there is no one measurement of the customer experience. Customer loyalty provides an incomplete picture. There are two types of loyalty; namely rational and emotional loyalty. While rational loyalty seems to be the more common measure of loyalty, emotional loyalty is the kind of loyalty that really needs to be measured. Emotional loyalty, according to Thompson, convinces customers to "get tattoos of your brand". "The problem is that emotions change quickly and demand different sorts of questions in surveys which need to be conducted very frequently".
Again Thompson made the point that NPS, while a popular metric, is good for causal analytics but not for B2B companies. He noted that NPS captures some emotional loyalty and some benchmark information "but most important it is simple and appeals to the board of your company."
I think the key point that I got out of Ed Thompson's remarks is that organizations have many measurements of the customer experience of which customer satisfaction and customer loyalty are just two. The metrics include:
1. The brand is measured by marketing communications and includes product and service design.
2. Quality is measured by process improvement and process engineering.
3. Customer satisfaction is measured in sales, service or market research.
4. Customer loyalty is measured by customer churn, retention, referrals or loyalty management.
Most people would agree that companies have a lot of information about their customers but do not take the time and effort to integrate that information into a composite picture. The customer measurements noted above demonstrate this point particularly well.
This ties in well with an article in the Harvard Business Review issue of February, 2007 by Meyer and Schwager titled "Understanding Customer Experience" that makes the argument that measuring customer experience is the preferable measure to any CRM measurement. I will review this article in a later blog.
The bottom line is that too many companies do not take the time or utilize their internal resources to integrate the multiple dimensions of the customer experiences that have been documented and lie within their internal data bases.
1. 80% of executives think customer satisfaction is more important than it was three years ago.
2. 95% of business leaders see customer satisfaction as the next competitive battleground.
3. Most companies have an average of seven metrics.
4. Most companies have their own derivative of the net promoter score.
He pointed out that everything else a company does is easy to copy - such as price, product and delivery.
The big question at the Summit "How do you measure it?"
Ed Thompson pointed out that there is no one measurement of the customer experience. Customer loyalty provides an incomplete picture. There are two types of loyalty; namely rational and emotional loyalty. While rational loyalty seems to be the more common measure of loyalty, emotional loyalty is the kind of loyalty that really needs to be measured. Emotional loyalty, according to Thompson, convinces customers to "get tattoos of your brand". "The problem is that emotions change quickly and demand different sorts of questions in surveys which need to be conducted very frequently".
Again Thompson made the point that NPS, while a popular metric, is good for causal analytics but not for B2B companies. He noted that NPS captures some emotional loyalty and some benchmark information "but most important it is simple and appeals to the board of your company."
I think the key point that I got out of Ed Thompson's remarks is that organizations have many measurements of the customer experience of which customer satisfaction and customer loyalty are just two. The metrics include:
1. The brand is measured by marketing communications and includes product and service design.
2. Quality is measured by process improvement and process engineering.
3. Customer satisfaction is measured in sales, service or market research.
4. Customer loyalty is measured by customer churn, retention, referrals or loyalty management.
Most people would agree that companies have a lot of information about their customers but do not take the time and effort to integrate that information into a composite picture. The customer measurements noted above demonstrate this point particularly well.
This ties in well with an article in the Harvard Business Review issue of February, 2007 by Meyer and Schwager titled "Understanding Customer Experience" that makes the argument that measuring customer experience is the preferable measure to any CRM measurement. I will review this article in a later blog.
The bottom line is that too many companies do not take the time or utilize their internal resources to integrate the multiple dimensions of the customer experiences that have been documented and lie within their internal data bases.
Saturday, October 25, 2008
Promoter versus Apostle
NPS continues to gather momentum. The categorization of the Promoters and Detractors as a way of viewing customers has a strong appeal. There is a competing categorization of customers that has more appeal to me. The term Apostle is a much stronger word to describe a loyal customer than Promoter. The term Apostle came out of the article "Value Profit Chain: Treat Employees like Customers and Customers like Employees" by Sasser and Jones.
The purpose of this blog is to look at these two competing scales for customers. One of the problems I see occurring is that companies will try to compare statistics when the scales for each statistic are not identical. While there are other scales being used, these two seem to dominate the literature today.
The NPS categorization has little granularity and puts customers into three very large buckets. It would appear that all detractors fall into the Detractor bucket and all Promoters fall into the Promoter bucket. There may be further refinement for these terms, however, I am not aware of any at this time.
On the other hand, the Apostle model has five categories. I believe the following definitions are reasonable representations:
1. Antagonist - those customers with low satisfaction scores who spread negative word of mouth about the product and/or service. These are referred to in other models as defectors or terrorists.
2. Mercenary - those customers with high levels of customer satisfaction but low loyalty. These customers want high satisfaction but give very lttle loyalty.
3. Loyalist - those customers with relatively high levels of satisfaction and moderate loyalty. They will generally remain but can be persuaded to leave.
4. Viral Loyalist - those customers who are more satisfied and loyal than Loyalists. They also spread positive word of mouth.
5. Apostles - those customers who are more satisfied and more loyal than Viral Loyalists and are more vocal. These custoemrs will argue for the company's products and services.
While these categories provide much more granularity, they also require a more precise definition for each (better than my approximation). The key in this model is that customers are shown to follow an ever increasing curve that relates customer satisfaction to loyalty Thus as satisfaction increases loyalty tends to increase. This relationship further implies that loyalty and satisfaction correlate high with the likelihood of recommendation. More and more data seems to be providing validation for this assumption of the relationship between likelihood of recommendation and satisfaction and/or loyalty.
My preference is the five category scale used in the Sasser article. I have a difficult time believing that someone who rates a product or service a nine on an 11 point scale has the same status as one who rates the same product or service a 10. Both of these scores would be categorized as a Promoter but, in my opinion, they are not the same kind of promoter. That granular difference between the two scales can translate into a large impact on revenue and profit.
The bottom line is that the categories defined by survey scales provide the lens by which we can accurately see the customers for who they really are. The more granular the scale the greater the accuracy of our vision.
The purpose of this blog is to look at these two competing scales for customers. One of the problems I see occurring is that companies will try to compare statistics when the scales for each statistic are not identical. While there are other scales being used, these two seem to dominate the literature today.
The NPS categorization has little granularity and puts customers into three very large buckets. It would appear that all detractors fall into the Detractor bucket and all Promoters fall into the Promoter bucket. There may be further refinement for these terms, however, I am not aware of any at this time.
On the other hand, the Apostle model has five categories. I believe the following definitions are reasonable representations:
1. Antagonist - those customers with low satisfaction scores who spread negative word of mouth about the product and/or service. These are referred to in other models as defectors or terrorists.
2. Mercenary - those customers with high levels of customer satisfaction but low loyalty. These customers want high satisfaction but give very lttle loyalty.
3. Loyalist - those customers with relatively high levels of satisfaction and moderate loyalty. They will generally remain but can be persuaded to leave.
4. Viral Loyalist - those customers who are more satisfied and loyal than Loyalists. They also spread positive word of mouth.
5. Apostles - those customers who are more satisfied and more loyal than Viral Loyalists and are more vocal. These custoemrs will argue for the company's products and services.
While these categories provide much more granularity, they also require a more precise definition for each (better than my approximation). The key in this model is that customers are shown to follow an ever increasing curve that relates customer satisfaction to loyalty Thus as satisfaction increases loyalty tends to increase. This relationship further implies that loyalty and satisfaction correlate high with the likelihood of recommendation. More and more data seems to be providing validation for this assumption of the relationship between likelihood of recommendation and satisfaction and/or loyalty.
My preference is the five category scale used in the Sasser article. I have a difficult time believing that someone who rates a product or service a nine on an 11 point scale has the same status as one who rates the same product or service a 10. Both of these scores would be categorized as a Promoter but, in my opinion, they are not the same kind of promoter. That granular difference between the two scales can translate into a large impact on revenue and profit.
The bottom line is that the categories defined by survey scales provide the lens by which we can accurately see the customers for who they really are. The more granular the scale the greater the accuracy of our vision.
Wednesday, October 22, 2008
Three Kinds of Loyalty
Christie Nordhielm, a clinical associate professor of marketing at the Ross School of Business, University of Michigan has offered another way of defining loyal customers (from her perspective she means brand loyalty). Her point is that companies are taking the approach that they cannot be all things to all people. Further she suggests, they should target their marketing efforts toward the three types of brand loyalty.
She suggests the following types of brand loyalty; namely head loyalty, heart loyalty and hands loyalty. The definition of each of these is given below:
1. Head loyalty - the consumer is just interested in the features of the product. The company would likely implement lots of product improvements and then introduce and promote them heavily.
2. Heart loyalty - the consumer has a really strong emotional brand loyalty. The company would show the heart loyal consumers that they are being heard and understood.
3. Hand loyalty - the consumer seeks familiarity. The company works to maintain the habit, so product changes should be more subtle and gradual. The emphasis should be on maintaining distribution and product quality.
The challenge with this approach is that the skills and resources the firm needs to maintain these different types of loyalty are very different.
Dr. Nordhielm offers an example of each and they seem to make sense.
An example of head loyalty is Toyota. The Toyota consumers regularly list off rational reasons why they buy the car.
An example of heart loyalty is Apple. The Apple consumers are often very emotionally invested in the Apple products.
An example of hand loyalty is Morton salt. The consumers buy salt out of habit, despite the premium price, and they are unwilling to go to the trouble of looking for alternatives.
The bottom line is this is definitely a new way of looking at loyalty. The problem might be that consumers may start with one kind of loyalty and shift to another and it may be very difficult to detect the shift. If the marketing programs are aimed at one type of loyalty and the consumers in that category shift, the results of the shift may not be detected until there is some severe loss to the company both in terms of loyalty and financially.
She suggests the following types of brand loyalty; namely head loyalty, heart loyalty and hands loyalty. The definition of each of these is given below:
1. Head loyalty - the consumer is just interested in the features of the product. The company would likely implement lots of product improvements and then introduce and promote them heavily.
2. Heart loyalty - the consumer has a really strong emotional brand loyalty. The company would show the heart loyal consumers that they are being heard and understood.
3. Hand loyalty - the consumer seeks familiarity. The company works to maintain the habit, so product changes should be more subtle and gradual. The emphasis should be on maintaining distribution and product quality.
The challenge with this approach is that the skills and resources the firm needs to maintain these different types of loyalty are very different.
Dr. Nordhielm offers an example of each and they seem to make sense.
An example of head loyalty is Toyota. The Toyota consumers regularly list off rational reasons why they buy the car.
An example of heart loyalty is Apple. The Apple consumers are often very emotionally invested in the Apple products.
An example of hand loyalty is Morton salt. The consumers buy salt out of habit, despite the premium price, and they are unwilling to go to the trouble of looking for alternatives.
The bottom line is this is definitely a new way of looking at loyalty. The problem might be that consumers may start with one kind of loyalty and shift to another and it may be very difficult to detect the shift. If the marketing programs are aimed at one type of loyalty and the consumers in that category shift, the results of the shift may not be detected until there is some severe loss to the company both in terms of loyalty and financially.
Tuesday, October 21, 2008
Is India Different?
J.D. Power just released its 2008 India Customer Service Index (CSI) Study for automobiles. They received responses from 5,594 owners of nearly 41 different vehicle models. The study measured satisfaction among vehicle owners who visited their authorized dealership service center for maintenance or repair work during the first 12 to 18 months of ownership.
Some of the more interesting findings are:
1. 77 percent of owners said they definitely would recommend their vehicle make, compared with 82 percent in 2007.
2. 64 percent of owners in 2008 said they would definitely repurchase their vehicle make, compared to 63 percent in 2007.
3. 94 percent of highly satisfied customers definitely would recommend their vehicle make, compared to 55 percent of customers with the lowest levels of satisfaction.
4. 84 percent of highly satisfied customers said they definitely would repurchase their vehicle make, compared to 43 percent of customers with the lowest satisfaction scores.
5. The cost of gasoline powered vehicles have risen by 7 percent since 2007, compared to diesel powered vehicles that had only a minimal increase since 2007.
Overall satisfaction is determined by J. D. Power on a 1000 point scale and includes measures of problems experienced , service quality, user-friendly service, service advisor, service initiation, service delivery and in-service experience. The highest score was achieved by Maruti Suzuki with a score of 820 points. The industry average increased by 3 points since 2007.
These scores look very similar to the US. Once again the impact of excellent service on loyalty and the willingness to recommend correlate highly.
The bottom line is that car manufacturers and dealers can easily see from these statistics that loyalty and repurchase relate to the overall satisfaction increases. The report seems to indicate that it only covered satisfaction from the service perspective. The concern that always comes to my mind is whether or not the survey should also measure salesman's influence as well as other business features such as ease of financing, location of the dealership and the general appearance of the dealership. These were not discussed in the limited version I saw of the report so I must add the caveat that I have not had access to the entire report. If they were not included this may have limited value since these other factors may be equally, if not more, important to loyalty; otherwise, if these other factors were included and had little or no impact, it might make an even stronger case for the value of service. I wonder what the NPS would tell them?
Some of the more interesting findings are:
1. 77 percent of owners said they definitely would recommend their vehicle make, compared with 82 percent in 2007.
2. 64 percent of owners in 2008 said they would definitely repurchase their vehicle make, compared to 63 percent in 2007.
3. 94 percent of highly satisfied customers definitely would recommend their vehicle make, compared to 55 percent of customers with the lowest levels of satisfaction.
4. 84 percent of highly satisfied customers said they definitely would repurchase their vehicle make, compared to 43 percent of customers with the lowest satisfaction scores.
5. The cost of gasoline powered vehicles have risen by 7 percent since 2007, compared to diesel powered vehicles that had only a minimal increase since 2007.
Overall satisfaction is determined by J. D. Power on a 1000 point scale and includes measures of problems experienced , service quality, user-friendly service, service advisor, service initiation, service delivery and in-service experience. The highest score was achieved by Maruti Suzuki with a score of 820 points. The industry average increased by 3 points since 2007.
These scores look very similar to the US. Once again the impact of excellent service on loyalty and the willingness to recommend correlate highly.
The bottom line is that car manufacturers and dealers can easily see from these statistics that loyalty and repurchase relate to the overall satisfaction increases. The report seems to indicate that it only covered satisfaction from the service perspective. The concern that always comes to my mind is whether or not the survey should also measure salesman's influence as well as other business features such as ease of financing, location of the dealership and the general appearance of the dealership. These were not discussed in the limited version I saw of the report so I must add the caveat that I have not had access to the entire report. If they were not included this may have limited value since these other factors may be equally, if not more, important to loyalty; otherwise, if these other factors were included and had little or no impact, it might make an even stronger case for the value of service. I wonder what the NPS would tell them?
Monday, October 20, 2008
Loyalty Falling for Banks and Insurance Companies
A recent survey of 500 consumers across the US and UK by Thunderhead, a provider of enterprise solutions, indicates some very disturbing statistics.
For example:
1. 61 percent of consumers are actively considering "switching" insurance providers in the next twelve months.
2. 63 percent of consumers are actively considering "switching" banks in the next twelve months.
3. 26 percent of overall respondents said they felt their current bank or insurance company sent them"personalized" communications that were relevant to their needs.
4. 17 percent of consumers feel a sense of loyalty to their insurance provider
5. 16 percent of consumers feel a sense of loyalty to their bank
6. 50 percent of consumers said that receiving communications in real-time was very important to them
7. 76 percent said they would like the option to receive communications via email
8. 40 percent preferred the option of having relevant, timely information delivered to them via personalized web portals
9. 50 percent wanted to continue to receive communications from their bank or insurance company via snail mail.
There is definitely a sense of bias in this survey since it was performed by a company that sells enterprise solutions (another way of saying they will provide a company with ways to communicate with their customers. A survey of 500 consumers from the US and the UK may not be representative of the two countries. It is not clear whether or not communication is what is causing the low levels of loyalty. There may be little or no correlation between communication satisfaction and company loyalty. This can happen when a survey has multiple metrics. It can be that the factors are related but the key is to remember a statistical relationship does not necessarily imply cause and effect.
Nevertheless, there is a strong message here that says banks and insurance companies don't seem to have very high levels of loyalty. Loyalty of 16 percent for banks and 17 percent for insurance companies is worse than the automobile industry in the US.
The bottom line is that banks and insurance companies are spending a great deal of time and money to improve loyalty but according to this survey it doesn't appear to be working very well.
For example:
1. 61 percent of consumers are actively considering "switching" insurance providers in the next twelve months.
2. 63 percent of consumers are actively considering "switching" banks in the next twelve months.
3. 26 percent of overall respondents said they felt their current bank or insurance company sent them"personalized" communications that were relevant to their needs.
4. 17 percent of consumers feel a sense of loyalty to their insurance provider
5. 16 percent of consumers feel a sense of loyalty to their bank
6. 50 percent of consumers said that receiving communications in real-time was very important to them
7. 76 percent said they would like the option to receive communications via email
8. 40 percent preferred the option of having relevant, timely information delivered to them via personalized web portals
9. 50 percent wanted to continue to receive communications from their bank or insurance company via snail mail.
There is definitely a sense of bias in this survey since it was performed by a company that sells enterprise solutions (another way of saying they will provide a company with ways to communicate with their customers. A survey of 500 consumers from the US and the UK may not be representative of the two countries. It is not clear whether or not communication is what is causing the low levels of loyalty. There may be little or no correlation between communication satisfaction and company loyalty. This can happen when a survey has multiple metrics. It can be that the factors are related but the key is to remember a statistical relationship does not necessarily imply cause and effect.
Nevertheless, there is a strong message here that says banks and insurance companies don't seem to have very high levels of loyalty. Loyalty of 16 percent for banks and 17 percent for insurance companies is worse than the automobile industry in the US.
The bottom line is that banks and insurance companies are spending a great deal of time and money to improve loyalty but according to this survey it doesn't appear to be working very well.
Loyalty is Falling for Banks and Insurance Co.
A recent survey of 500 consumers across the US and UK by Thunderhead, a provider of enterprise solutions, indicates some very disturbing statistics.
For example:
1. 61 percent of consumers are actively considering "switching" insurance providers in the next twelve months.
2. 63 percent of consumers are actively considering "switching" banks in the next twelve months.
3. 26 percent of overall respondents said they felt their current bank or insurance company sent them"personalized" communications that were relevant to their needs.
4. 17 percent of consumers feel a sense of loyalty to their insurance provider
5. 16 percent of consumers feel a sense of loyalty to their bank
6. 50 percent of consumers said that receiving communications in real-time was very important to them
7. 76 percent said they would like the option to receive communications via email
8. 40 percent preferred the option of having relevant, timely information delivered to them via personalized web portals
9. 50 percent wanted to continue to receive communications from their bank or insurance company via snail mail.
There is definitely a sense of bias in this survey since it was performed by a company that sells enterprise solutions (another way of saying they will provide a company with ways to communicate with their customers. A survey of 500 consumers from the US and the UK may not be representative of the two countries. It is not clear whether or not communication is what is causing the low levels of loyalty
Nevertheless, there is a strong message here that says banks and insurance companies don't seem to have very high levels of loyalty. Loyalty of 16 percent for banks and 17 percent for insurance companies is worse than the automobile industry in the US.
For example:
1. 61 percent of consumers are actively considering "switching" insurance providers in the next twelve months.
2. 63 percent of consumers are actively considering "switching" banks in the next twelve months.
3. 26 percent of overall respondents said they felt their current bank or insurance company sent them"personalized" communications that were relevant to their needs.
4. 17 percent of consumers feel a sense of loyalty to their insurance provider
5. 16 percent of consumers feel a sense of loyalty to their bank
6. 50 percent of consumers said that receiving communications in real-time was very important to them
7. 76 percent said they would like the option to receive communications via email
8. 40 percent preferred the option of having relevant, timely information delivered to them via personalized web portals
9. 50 percent wanted to continue to receive communications from their bank or insurance company via snail mail.
There is definitely a sense of bias in this survey since it was performed by a company that sells enterprise solutions (another way of saying they will provide a company with ways to communicate with their customers. A survey of 500 consumers from the US and the UK may not be representative of the two countries. It is not clear whether or not communication is what is causing the low levels of loyalty
Nevertheless, there is a strong message here that says banks and insurance companies don't seem to have very high levels of loyalty. Loyalty of 16 percent for banks and 17 percent for insurance companies is worse than the automobile industry in the US.
Friday, October 17, 2008
Customers Are Your Greatest Asset
I think we miss a very important point when we think of customers. We miss the fact that they are an asset. When we look at the balance sheet of companies, we see the buildings as an asset, the equipment as an asset, the inventory as an asset and cash as an asset. We don't usually see the customers noted as an asset. Companies will often note personnel skills as an intangible asset, the brand name as an intangible asset and sometimes the customer data base as an intangible asset.
I believe the IRS added Section 197 to the Revenue Reconciliation Act of 1993 which now provides that customer and subscription lists, goodwill and going-concern value are now regarded as intangible assets and may be amortized over a 15 year period.
When I look at the customer as an asset I see an asset that is very complex, that changes value over time, that changes value with the size of the company, that changes value with the level of customer service (support), and changes value with age of the products or services offered.
I had a client who had a bright orange 8 1/2 x 11 inch poster distributed to each of his managers that read "CUSTOMERS ARE WHAT MAKE PAYDAYS POSSIBLE." He asked that each manager hang the poster over his desk as a constant reminder.
The Oxford dictionary defines asset as: property available to meet debts; any possession; any useful quality. MY DEFINITION of the customer asset is: TREASURE. Meaning precious; something valued for its rarity as a beloved or highly valued person.
I can use the Oxford Dictionary definition to get:
Customers are a form of "property" that provide revenue "to meet debts"; and
Customers represent a "possession" without which there is no business.
The impact of managing the customer asset under ideal conditions would lead to customers who would never leave to go to a competitor. The reality is that the better customers are managed, the higher the retention rate and the greater the opportunity to grow your market share (with an implied improvement in total profit).
When the customer asset is well managed customers who are a positive asset are identified and the company can focus on retaining those customers. At the same time, those customers who are not a positive asset can be eliminated.
Operations Impact
When the customer asset is being managed the role of Operations is
1. focus on maintaining good communications and relationships with customers
2. focus on meeting current and future needs and desires of customers
3. focus on a strong compliant resolution system
4. focus on continuous improvement in quality of products and services
Measurement Impact
When the customer asset is being managed, the impact on the internal measurement system will be to:
1. measure retention
2. measure defection - where did they go and why
3. measure complaint resolution
4. Measure delivery performance (products and services)
5. Measure the variance/gap between performance and needs/desires of customers
The bottom line is that customers are very important assets. The customers should be continuously evaluated to determine the quality of the customer asset base. If the company does an audit of its assets (plant, equipment, inventory, etc.) on a regular basis, why not take an audit of the customer asset on a regular basis? The objective is to determine whether or not the customer asset value is increasing or decreasing in value. Most companies cannot answer this question quantitatively.
I believe the IRS added Section 197 to the Revenue Reconciliation Act of 1993 which now provides that customer and subscription lists, goodwill and going-concern value are now regarded as intangible assets and may be amortized over a 15 year period.
When I look at the customer as an asset I see an asset that is very complex, that changes value over time, that changes value with the size of the company, that changes value with the level of customer service (support), and changes value with age of the products or services offered.
I had a client who had a bright orange 8 1/2 x 11 inch poster distributed to each of his managers that read "CUSTOMERS ARE WHAT MAKE PAYDAYS POSSIBLE." He asked that each manager hang the poster over his desk as a constant reminder.
The Oxford dictionary defines asset as: property available to meet debts; any possession; any useful quality. MY DEFINITION of the customer asset is: TREASURE. Meaning precious; something valued for its rarity as a beloved or highly valued person.
I can use the Oxford Dictionary definition to get:
Customers are a form of "property" that provide revenue "to meet debts"; and
Customers represent a "possession" without which there is no business.
The impact of managing the customer asset under ideal conditions would lead to customers who would never leave to go to a competitor. The reality is that the better customers are managed, the higher the retention rate and the greater the opportunity to grow your market share (with an implied improvement in total profit).
When the customer asset is well managed customers who are a positive asset are identified and the company can focus on retaining those customers. At the same time, those customers who are not a positive asset can be eliminated.
Operations Impact
When the customer asset is being managed the role of Operations is
1. focus on maintaining good communications and relationships with customers
2. focus on meeting current and future needs and desires of customers
3. focus on a strong compliant resolution system
4. focus on continuous improvement in quality of products and services
Measurement Impact
When the customer asset is being managed, the impact on the internal measurement system will be to:
1. measure retention
2. measure defection - where did they go and why
3. measure complaint resolution
4. Measure delivery performance (products and services)
5. Measure the variance/gap between performance and needs/desires of customers
The bottom line is that customers are very important assets. The customers should be continuously evaluated to determine the quality of the customer asset base. If the company does an audit of its assets (plant, equipment, inventory, etc.) on a regular basis, why not take an audit of the customer asset on a regular basis? The objective is to determine whether or not the customer asset value is increasing or decreasing in value. Most companies cannot answer this question quantitatively.
Thursday, October 16, 2008
Bad Metrics
There was an article in the March 3, 2008 issue of BusinessWeek that announced the 2008 winners of customer service. They list the top 25 companies that are, according to BusinessWeek, the Customer Service Champs. Sounds good. The top company is USAA with a score of 1030.66 points The last company on the list of the top 25 is True Value with a score of 857.21
My guess there are a lot of happy customer service executives that were happy to see their company on the top 25 list. In general, I think the companies listed do provide excellent customer service and may, in fact, be the customer service champs. When I look further into the way the companies were selected and then how the scoring was accomplished I cringe. This is a bad metric - it has too many flaws to be accurate.
The first problem is that there is no indication that the more than 1000 readers who responded to the survey represent a probability sample. Without a probability sample the results are questionable at best. Then J. D. Power created a web-based survey for the brands and surveyed at least 100 customers (for each brand?) to get a comparable score (whatever that means).
Then J. D. Power ranked all brands using scores from both their database and the supplemental surveys (ranking based on what?). Next the folks at BusinessWeek combined the "people" and the "process" scores from J. D. Power's data to create the service index with people weighted at 60% and process at 40%. There is no description of how the scores were combined (probably added). Further, the question is why choose a 60/40 split. No rationale is given for the ratio. Why not 50/50 or maybe 90/10?
That is not the end of this nightmare. Brands that were ranked first in their category received 100 bonus points (why not 82 or any other number - no rationale given). Those that ranked second received an additional 50 points (why not - this makes no more sense than the 100 points for first place). Hold on, those companies that fell below third place had 50 points subtracted (I can't believe a publisher would allow this to be published when company reputations are on the line).
Finally, those companies that did particularly well in the reader poll were awarded an extra 25 points if their vote-to-complaint ratios were in the top 10%. I guess 25points makes as much sense as the 50 and 100 points that are being thrown around.
The bottom line is that this is a bad metric because it is unlikely to be a good probability sample and then the scoring is absolutely arbitrary. Company reputations are being helped or hindered based on a metric that is not well founded.
My guess there are a lot of happy customer service executives that were happy to see their company on the top 25 list. In general, I think the companies listed do provide excellent customer service and may, in fact, be the customer service champs. When I look further into the way the companies were selected and then how the scoring was accomplished I cringe. This is a bad metric - it has too many flaws to be accurate.
The first problem is that there is no indication that the more than 1000 readers who responded to the survey represent a probability sample. Without a probability sample the results are questionable at best. Then J. D. Power created a web-based survey for the brands and surveyed at least 100 customers (for each brand?) to get a comparable score (whatever that means).
Then J. D. Power ranked all brands using scores from both their database and the supplemental surveys (ranking based on what?). Next the folks at BusinessWeek combined the "people" and the "process" scores from J. D. Power's data to create the service index with people weighted at 60% and process at 40%. There is no description of how the scores were combined (probably added). Further, the question is why choose a 60/40 split. No rationale is given for the ratio. Why not 50/50 or maybe 90/10?
That is not the end of this nightmare. Brands that were ranked first in their category received 100 bonus points (why not 82 or any other number - no rationale given). Those that ranked second received an additional 50 points (why not - this makes no more sense than the 100 points for first place). Hold on, those companies that fell below third place had 50 points subtracted (I can't believe a publisher would allow this to be published when company reputations are on the line).
Finally, those companies that did particularly well in the reader poll were awarded an extra 25 points if their vote-to-complaint ratios were in the top 10%. I guess 25points makes as much sense as the 50 and 100 points that are being thrown around.
The bottom line is that this is a bad metric because it is unlikely to be a good probability sample and then the scoring is absolutely arbitrary. Company reputations are being helped or hindered based on a metric that is not well founded.
Monday, October 13, 2008
NPS revisited
Here we go again. There is another article about NPS - also critical. The article was published in the October, 2008 issue of Quirk's Marketing Research Review under the title "Customer Loyalty 2.0" NPS (Net Promoter Score) is a simple methodology for indicating a degree of loyalty that, according to the developer of NPS, is a good predictor of company growth by asking one question; namely "how likely is it that you would recommnd this company to your friend or colleague."
This methodology has come under some very severe criticism by both the academic community and the consultants who specialize on the measurement of customer loyalty. Some of the researchers found that customer satisfaction is just as good at predicting growth. Other researchers have found that measures such as likelihood to repurchase are also comparable to NPS for predicting growth.
The author of the article makes the statement that there is no published empirical evidence supporting the superiority of NPS over the other conventional loyalty metrics. The basis for this statement is that recent scientific, peer-reviewed studies do not appear to support the claims of NPS. The author makes two very strong requests of the developers of NPS; namely,
1. Present their analysis to back up their claims.
2. Refute the current scientific research that brings their methodological rigor into question.
It seems that most researchers have found that customer satisfaction is consistently correlated with growth. I have found (and published) results that show that high levels of customer satisfaction yield better financial performance for companies than those with low levels of customer satisfaction.
The author and researcher then conducted a statistical test using 1,000 respondents in the United States (18 years and older). [I assume it was a valid statistical sample]. The test asked them the following four questions:
1. How satisfied are you with Company ABC
2. How likely are you to recommend Comapny ABC
3. How likely are you to continue to purchasing the same product and/or service from Company ABC
4. If you were selecting a company for the first time, how likely is it that you would choose Company ABC.
The result was that all four questions appeared to measure one underlying construct, customer loyalty. There was a correlation of .87 among the four questions. Needless to say the statistics appear to indicate the four questions could be considered interchangeable as a direct measure of loyalty and using the NPS logic each of the four could also be used as a good predictor of company growth.
I think the author of the article makes a great point when he points out that a single item measure is less reliable than a multiple item meaure. He uses the example of using a single question to determine the SAT score. If that were the case then why bother with the other questions. In fact, the author averages the scores of all four questionsshown above and suggests that the average of all four measures is a more precise measure of loyalty than any of the four questions used alone.
One point that the author makes is that the customers who score 7 or 8 may be potential disloyal customers and are currently overlooked by NPS. He cites a study of wireless service providers where he found that 31 percent of those who scored 7 or 8 were likely to switch to a different wireless service provider even though they were not identified as a detractor.
In conclusion, the author suggests that companies should use a variety of loyalty questions so that those customers who may be likely to switch can be identified. To quote the author "how well we are able to predict business performance masures depends on the match between the business metric and the loyalty questions."
The bottom line is that the people who are selling NPS, while it is being touted as the best measure, need to publish more data to support their claims. There are some serious claims being made that strongly suggests that NPS is not all it is advertised to be. Time will tell.
This methodology has come under some very severe criticism by both the academic community and the consultants who specialize on the measurement of customer loyalty. Some of the researchers found that customer satisfaction is just as good at predicting growth. Other researchers have found that measures such as likelihood to repurchase are also comparable to NPS for predicting growth.
The author of the article makes the statement that there is no published empirical evidence supporting the superiority of NPS over the other conventional loyalty metrics. The basis for this statement is that recent scientific, peer-reviewed studies do not appear to support the claims of NPS. The author makes two very strong requests of the developers of NPS; namely,
1. Present their analysis to back up their claims.
2. Refute the current scientific research that brings their methodological rigor into question.
It seems that most researchers have found that customer satisfaction is consistently correlated with growth. I have found (and published) results that show that high levels of customer satisfaction yield better financial performance for companies than those with low levels of customer satisfaction.
The author and researcher then conducted a statistical test using 1,000 respondents in the United States (18 years and older). [I assume it was a valid statistical sample]. The test asked them the following four questions:
1. How satisfied are you with Company ABC
2. How likely are you to recommend Comapny ABC
3. How likely are you to continue to purchasing the same product and/or service from Company ABC
4. If you were selecting a company for the first time, how likely is it that you would choose Company ABC.
The result was that all four questions appeared to measure one underlying construct, customer loyalty. There was a correlation of .87 among the four questions. Needless to say the statistics appear to indicate the four questions could be considered interchangeable as a direct measure of loyalty and using the NPS logic each of the four could also be used as a good predictor of company growth.
I think the author of the article makes a great point when he points out that a single item measure is less reliable than a multiple item meaure. He uses the example of using a single question to determine the SAT score. If that were the case then why bother with the other questions. In fact, the author averages the scores of all four questionsshown above and suggests that the average of all four measures is a more precise measure of loyalty than any of the four questions used alone.
One point that the author makes is that the customers who score 7 or 8 may be potential disloyal customers and are currently overlooked by NPS. He cites a study of wireless service providers where he found that 31 percent of those who scored 7 or 8 were likely to switch to a different wireless service provider even though they were not identified as a detractor.
In conclusion, the author suggests that companies should use a variety of loyalty questions so that those customers who may be likely to switch can be identified. To quote the author "how well we are able to predict business performance masures depends on the match between the business metric and the loyalty questions."
The bottom line is that the people who are selling NPS, while it is being touted as the best measure, need to publish more data to support their claims. There are some serious claims being made that strongly suggests that NPS is not all it is advertised to be. Time will tell.
Saturday, October 11, 2008
Customer Service Counts in Pharmacies
Wilson Health Information, LLC will present its 1st Independent Pharmacy Satisfaction Report at the National Community Pharmacists Association meeting this week in Tampa Florida. They have written an 8 page report based on a sample of 34,454 repondents from a total mailing of 70,000 households. The sample was balanced by geographic region, market size, age, household type, income, size and state. Based on this sample the margin for error is +/- 0.5 percent at a 95% confidence level. They required at least 40 responses within a market in order to draw comparative and quantitative conclusions.
The primary conclusion they drew from the survey was that independent pharmacies rank higher in customer satisfaction than the chains. The American consumer rated independent pharmacies the most highly satisfied and most trusted healthcare advisors and customer-service providers in the retail pharmacy industry.
The independent pharmacies seem to outperform the chains as well as scoring high in customer satisfaction. Some of the statistics from the survey are:
1. Independent pharmacies received 7.8 new scripts compared to the chains that received 6.8.
2. Independent pharmacies received 27.7 refills in the past year compared with the chains that received 23.8.
"Information from their research indicates that independent pharmacists succeed because they stick to the basics and provide superior one-on-one customer service as they have for most of this nation's history" according to Jim Wilson, president. "They take the time to build personal relationships with their patients, counsel them on their medication needs and go the extra mile to make sure those needs are served."
The bottom line is that aiming at the individual customer has financial rewards as demonstrated by higher new scripts and refills.
The primary conclusion they drew from the survey was that independent pharmacies rank higher in customer satisfaction than the chains. The American consumer rated independent pharmacies the most highly satisfied and most trusted healthcare advisors and customer-service providers in the retail pharmacy industry.
The independent pharmacies seem to outperform the chains as well as scoring high in customer satisfaction. Some of the statistics from the survey are:
1. Independent pharmacies received 7.8 new scripts compared to the chains that received 6.8.
2. Independent pharmacies received 27.7 refills in the past year compared with the chains that received 23.8.
"Information from their research indicates that independent pharmacists succeed because they stick to the basics and provide superior one-on-one customer service as they have for most of this nation's history" according to Jim Wilson, president. "They take the time to build personal relationships with their patients, counsel them on their medication needs and go the extra mile to make sure those needs are served."
The bottom line is that aiming at the individual customer has financial rewards as demonstrated by higher new scripts and refills.
Friday, September 5, 2008
The Dollars and Sense of Good Customer Service
I recently read an article published by the Database Marketing Institute dated August 30th that gives specific financial evidence that good customer service pays off. The point of the article is that all customers are not alike. The article starts out by identifying several factors that are driving changes in the market place. The four factors they note are:
1. Loyal customers buy more, buy more often, are cheaper to serve, have higher retention rates, and are more profitable than newly acquired customers.
2. Two of the better ways to influence the level of customer loyalty is recruit the right kind of customers to begin with and treat them very well once acquired.
3. Excellent customer care is the most important method for improving customer loyalty.
4. to provide excellent customer service the customer contact personnel have to be empowered with information and authority to make decisions and to act in the customer's behalf.
Here is where the Dollars show up.
Example #1
A large bank divided up their customers every month based on actual profitability. They discovered 16% of their customers contributed 105% of the bank's profit and the bottom 84% reduced the bank's profit by 5%. The bottom 20% of their customers eroded profits by a total of 22%.
The lesson the bank learned was that they should not be treating all customers the same because all customers are not alike. In other words, you cannot afford to give the bottom 84% of your customers the same level of service as you give the top 16%.
Example #2
A company that manufactures building products has 45,000 large building contractors as customers. Their standard procedure was to publish an annual catalog, mail it out and wait for the phone to ring. The company was very profitable.
They tried an experiment by taking the top 1,200 customers and dived ed them into two exactly equal groups: 600 in a test group and 600 in a control group. The control group would be treated exactly as we treat all of other customers.
For the test group they did outbound relationship building. The assigned one customer service specialist and one building products engineer for a 6 months test. These two people called every decision maker, influencer, and product user they could find in the 600 test companies. They did not try to sell. They did not offer discounts. They tried friendship and providing information. they provided the following:
1. Ask about customer needs
2. Follow up on bids and quotes
3. Schedule product training
4. Remind them of pricing specials
5. Give product comparison information
6. Give new product information & samples.
The results from this 6 month test are as follows:
1. The test group made 12% more orders than they had in the previous 6 months
2. The control group made 18% fewer orders
3. The test group placed 14% larger orders and the control group 14% smaller orders than before.
4. The test group bought products worth $2.6 million more than the control group during the 6 month period.
5. The total cost of the test was about $50,000.
The bottom line is that good customer service is a great investment. This is not rocket science.
1. Loyal customers buy more, buy more often, are cheaper to serve, have higher retention rates, and are more profitable than newly acquired customers.
2. Two of the better ways to influence the level of customer loyalty is recruit the right kind of customers to begin with and treat them very well once acquired.
3. Excellent customer care is the most important method for improving customer loyalty.
4. to provide excellent customer service the customer contact personnel have to be empowered with information and authority to make decisions and to act in the customer's behalf.
Here is where the Dollars show up.
Example #1
A large bank divided up their customers every month based on actual profitability. They discovered 16% of their customers contributed 105% of the bank's profit and the bottom 84% reduced the bank's profit by 5%. The bottom 20% of their customers eroded profits by a total of 22%.
The lesson the bank learned was that they should not be treating all customers the same because all customers are not alike. In other words, you cannot afford to give the bottom 84% of your customers the same level of service as you give the top 16%.
Example #2
A company that manufactures building products has 45,000 large building contractors as customers. Their standard procedure was to publish an annual catalog, mail it out and wait for the phone to ring. The company was very profitable.
They tried an experiment by taking the top 1,200 customers and dived ed them into two exactly equal groups: 600 in a test group and 600 in a control group. The control group would be treated exactly as we treat all of other customers.
For the test group they did outbound relationship building. The assigned one customer service specialist and one building products engineer for a 6 months test. These two people called every decision maker, influencer, and product user they could find in the 600 test companies. They did not try to sell. They did not offer discounts. They tried friendship and providing information. they provided the following:
1. Ask about customer needs
2. Follow up on bids and quotes
3. Schedule product training
4. Remind them of pricing specials
5. Give product comparison information
6. Give new product information & samples.
The results from this 6 month test are as follows:
1. The test group made 12% more orders than they had in the previous 6 months
2. The control group made 18% fewer orders
3. The test group placed 14% larger orders and the control group 14% smaller orders than before.
4. The test group bought products worth $2.6 million more than the control group during the 6 month period.
5. The total cost of the test was about $50,000.
The bottom line is that good customer service is a great investment. This is not rocket science.
Friday, August 29, 2008
Customer Service Does Matter
A new study from Accenture was based on a survey of 3500 consumers on five continents. Two of the key findings are;
1. 59%of the customers had actually stopped doing business with companines in the past year due to poor service.
2. Just slightly less than half of those surveyed said that their expectations were met only sometimes, rarely or never.
There are some other surveys that provide similar results. For example, an annual survey of 137 retail firms conducted by the National Retail Federation and IBM found the following:
1. 10% of retailers measure customer satisfaction on a weekly basis.
2. 8% of retailers measure customer satisfaction on an annual basis.
3. 6% of retailers don't have any set schedule for tracking customer satisfaction.
ForeSee, a consulting firm that measures customer loyalty for web sites found that customer satisfaction fell 1.3% to 74% in 2007. They also found that customer satisfaction ratings declined for nearly half of the 40 on-line retailers last year. ForeSee CEO, Larry Freed suggests the decline may be due to higher customer expectations. The exceptions to the decline were Wal-Mart, Barnes & Noble and Best Buy.
From another perspective, a survey of telecoms found that 96% of US customers said they wouldn't hesitate to switch carriers to get a better experience. 72% had already made a switch due to a negative experience. This was based on a survey of 2000 mobile phone users in the US.
Finally, Amdocs, a call center technology company, found from a survey of more than 2000 consumers in the US and Britain, that about 80% of consumers were satisfied with their service yet about 33% said they would switch to another carrier to get better services for mobile games, entertainment and ads.
The bottom line is that customer service seems to be playing a larger and larger role in building and maintaining customer loyalty. Some of the reasons the consultants say are impacting these statistics are;
1. Companies are cutting costs at the expense of customers.
2. Companies are misguided when they keep people on hold longer or slash store hours just to save money.
3. Companies can improve their customer service experience by appointing a high-level executive with real authority to enforce service levels - often called the chief customer officer.
4. A simple tactic is to make sure that all complaints get resolved on a single call.
5. Focus on brand consistency, increase product selection and enhance the user experience are some of the ways to gain ground in customer satisfaction according to Mark Mahaney, a Citi research analyst.
It all boils down to taking care of the customer. The better you take care of the customer the more you can count on the customer to came back. This is not rocket science.
1. 59%of the customers had actually stopped doing business with companines in the past year due to poor service.
2. Just slightly less than half of those surveyed said that their expectations were met only sometimes, rarely or never.
There are some other surveys that provide similar results. For example, an annual survey of 137 retail firms conducted by the National Retail Federation and IBM found the following:
1. 10% of retailers measure customer satisfaction on a weekly basis.
2. 8% of retailers measure customer satisfaction on an annual basis.
3. 6% of retailers don't have any set schedule for tracking customer satisfaction.
ForeSee, a consulting firm that measures customer loyalty for web sites found that customer satisfaction fell 1.3% to 74% in 2007. They also found that customer satisfaction ratings declined for nearly half of the 40 on-line retailers last year. ForeSee CEO, Larry Freed suggests the decline may be due to higher customer expectations. The exceptions to the decline were Wal-Mart, Barnes & Noble and Best Buy.
From another perspective, a survey of telecoms found that 96% of US customers said they wouldn't hesitate to switch carriers to get a better experience. 72% had already made a switch due to a negative experience. This was based on a survey of 2000 mobile phone users in the US.
Finally, Amdocs, a call center technology company, found from a survey of more than 2000 consumers in the US and Britain, that about 80% of consumers were satisfied with their service yet about 33% said they would switch to another carrier to get better services for mobile games, entertainment and ads.
The bottom line is that customer service seems to be playing a larger and larger role in building and maintaining customer loyalty. Some of the reasons the consultants say are impacting these statistics are;
1. Companies are cutting costs at the expense of customers.
2. Companies are misguided when they keep people on hold longer or slash store hours just to save money.
3. Companies can improve their customer service experience by appointing a high-level executive with real authority to enforce service levels - often called the chief customer officer.
4. A simple tactic is to make sure that all complaints get resolved on a single call.
5. Focus on brand consistency, increase product selection and enhance the user experience are some of the ways to gain ground in customer satisfaction according to Mark Mahaney, a Citi research analyst.
It all boils down to taking care of the customer. The better you take care of the customer the more you can count on the customer to came back. This is not rocket science.
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