The Halo Effect on Satisfaction Metrics

There has been some very interesting research on the Halo effect on satisfaction metrics. The research was performed by Joachim Buschken, Thomas Otter and Greg M. Allenby. Their work is entitled "Do We Halo or Form? A Bayesian Mixture Model for Customer Satisfaction Data".

When we look at customer satisfaction data we often look at what are the drivers of overall satisfaction. We naively assume that each question is answered independently so that we can use techniques such as regression analysis to identify those factors that most strongly relate to overall satisfaction. When this assumption is satisfied the "drivers of satisfaction" are valid and management actions taken as a result should have a positive impact on the organization.

When the assumption of independence is not met, the identification of drivers loses its validity. One of the most serious deviations comes from "Halos". Halos occur when a customer responds to a survey such that all the scores are identical and usually all top box (or bottom box). The customer is saying that the company scores top box with respect to every question. In other words, the company is perfect and all the areas requested for evaluation have outstanding performance. When all the scores are identical the term often used to describe this response is Halo. There can be a negative Halo as well as a positive Halo. The same logic works for the negative Halo, the customer is saying that all areas of the company being evaluated are equally dramatically under performing.

The Halo effect occurs most often when the respondents recall their overall satisfaction and then assign scores for each question consistent with their assessment of the overall score. When this occurs the components are uninformative about the drivers of overall satisfaction. In this case regression of overall satisfaction or dissatisfaction is not possible because the components are co-linear.

When conducting statistical analysis to determine the influence of drivers on overall satisfaction the halo responses must be removed from the response data set.
While many survey analysts try to find ways to remove outliers, the Halos are responses that should be eliminated from any statistical analysis.

The researchers point out that respondents who are familiar with the product or service are more capable of providing insights are found to be more likely to Halo their responses. On the other hand those respondents who are less aware of the products or services and are less capable of providing informed are more likely to make their responses more independent and less likely to Halo their responses. The problem is that neither of these scenarios are what would be appropriate for driver analysis.

The bottom line is that Halos are bad news for satisfaction and loyalty surveys. It is clear that analysts who are doing driver analysis need to be aware of the impact of Halos. This is one exception to the rule that outliers must be included. As the researchers note "the analysis of customer satisfaction data for the purpose of understanding drivers of overall satisfaction requires removal of the Haloed responses. From a managerial standpoint, Haloed responses are uninformative about the drivers of overall satisfaction because the component-specific information is suppressed."

Impact of Lying on Surveys

Have you ever wondered what the impact of respondents lying on your survey might be? Repeated lying on surveys is known as farming and refers specifically to repeatedly completing a survey (correctly or otherwise). Thomas Chesney of Nottingham University Business School in Nottingham, UK and Kay Penny of Edinburgh Napier University in Edinburgh, UK have recently completed an interesting study to examine this possibility.

Web based businesses such as SurveyMonkey allow researchers or businesses to create and distribute online questionnaires quickly and at low costs. One of the main detractors to this method is the lack of certainty about who responded and how many times. As a secondary concern, how accurate are the demographic responses. Are the respondents who they claim to be? Some of the more sophisticated survey processes will not allow the same code to be used more than once; however, there may still be ways of providing multiple respondents. For example, it has been suggested that some respondents voted more than once for Sarah Palin's daughter when she was competing on the TV program "Dancing with the Stars."

There have been studies that show that an incentivize survey often leads to an increased response rate and the greater the incentive,the greater the increase in response. In the same way others have found that one big prize increases the response more than many small prizes despite the lower odds of winning. Another way to increase participation to use a prize draw rather than prepaid or promised monetary incentives.

A particular study by Morabia and Zheng in 2009 investigated the influence of entry into a raffle as an incentive for participation to an urban transportation survey in New York and found that approximately 4.7% of the participants were thought to have responded twice since they gave the same email address (are we talking dumb here).

A more subtle concern about lying on a survey is the respondent may be asked to answer questions that my impact their job. Something that business people often overlook is the possibility that one or more competitors may be responding to their surveys in ways that would distort the results and increase the possibility that decisions made as a result of the responses would be in error.

In reality there appears to be three basic types of farming; namely, the first is to repeatedly tell the truth, the second is to provide a random answer to each question and the third is to give perceived average responses to every response.

The finding of these researchers is that farming can lead to real and potential problems which cannot be predicted. The errors can be either a type I or type II error with no simple way to reduce or eliminate the errors.

The bottom line is that surveys on the web present real opportunities for lying and distorting the truth The best way to remove this possibility is good management. Of course, it can be virtually eliminated with phone or other direct survey techniques which are both more timely and expensive. Just another concern for those of us who attempt to extract accurate information from surveys.

Customer Advocacy

With the increasing use of social media, the concept of customer advocacy is starting to have legs. The Gartner research group has reported that more than $1.2 billion is spent on loyalty programs in the US. They also suggest that more than 75% of consumers have at least one loyalty card and more than 1/3 of the shopping population has two or more loyalty cards.

The idea of customer advocacy is based on the notion that someone who espouses a product, service or company is an advocate. Some loyalty scales used in the market describe people who score high on satisfaction surveys as advocates. The bad news is creating an advocate may not necessarily follow a score on a satisfaction survey. We have not seen enough evidence to validate the fact that a high satisfaction score creates an advocate; however, it is fairly certain that an advocate should be very satisfied before that person starts advocating a product, service or company.

The good news is that WOM is relatively inexpensive. There is some interesting research that bears prominently on this advocacy topic. The research was published in the September, 2009 issue of the Journal of Marketing. The study was titled "Effects of Word-of-Mouth Versus Traditional Marketing: Findings from an Internet Social Networking Site." The major finding was that WOM has a much longer carryover period. This suggests that WOM will persist long after normal activities designed to increase customer loyalty. The technical description of the result is that WOM is about 2.5 times higher than the average advertising elasticity.

The bottom line is that companies should start to focus their programs toward WOM on social networking sites and reward customer advocacy behavior. The challenge is going to be how best to get customers to become advocates. We will be searching the market for successes in finding and tracking customer advocates on the social networking sites.

Endowed Progress

Have you ever heard of "endowed progress"? If you never have, you might want to read a research paper by authors Nunes and Dreze entitled "The Endowed Progress Effect: How Artificial Advancement Increases Effort." These researchers uncovered another people trait that improves sales, profit and (probably) loyalty. Endowed progress means that people who are given an artificial advancement toward a goal (such as a free trip) show greater persistence toward reaching the goal than they otherwise would. Artificial advancement is a way of appearing to give a customer a head start toward a goal even though it still takes the same effort to reach the goal. The example they use is an offer of a free airline ticket after 8 trips will not have as many people reaching the goal of 8 trips as when the offer is for a free trip after 10 trips but with a two trip head start. While both offers are the same, these researchers proved that customers were more likely to complete the 8 trips in a 10 trip program with a two trip head start than just doing 8 trips.

What is happening is that the task is reframed as a program that is already started. The customer tends to increase the chance that 8 trips will be taken and in a shorter period of time. They found that as people progress toward a goal, their effort will increase to get completion and as a result completion time will decrease given the head start.

Another finding from the research is that customer persistence depends on the relative progress made by the customer but NOT on the amount of the reward points or miles or other goal. thus, we might expect the customer will work harder as the goal comes into sight.

Their third finding was that endowed progress appears to be more effective when the customers are provided with a reason for the endowment. The customers want to know that there is a reason you are giving them a head start. The reason may be as simple as "we are starting a new loyalty program and are offering you this incentive to join our rewards program".

While I have never been a proponent of rewards programs, if you must use them, you might want to take advantage of this research. Although it suggests we are like sheep, their research is compelling. Try it, it just might provide a way of increasing sales, profit and loyalty.

Loyalty versus Trust

Edelman is the world's leading independent Public relations firm (at least that is what they advertise). Of interest is their Edelman Trust Barometer. They have just released their 2010 Edelman Trust Barometer Survey results. They report that they sampled 4,875 informed participants in two age groups (25-34) and (35-64). In order to qualify for the survey each must be college-educated with a household income in the top quartile for their age in their country. They must also read or watch business/news media at least several times a week and follow public policy issues in the news at least several times a week. Each interview participates in a 25-minute telephone. The results published in the 2010 survey was based on interviews between September 29 and December 6, 2009. The measurement is based on a 9-point Likert-type scale for trust. The scale notes that 1 denotes the lowest trust and d9 represents the highest trust.

With this background, it appears that their measurement system appears to follow sound survey techniques. They have summarized some of the general results that maybe of interest, namely,
1. Global trust in business is up modestly for the year.
2. The gain may be due to a spiked increase in a handful of Western countries. The trust measurement increased 18 points to 54% for the United States.
3. Trust also remains high in Brazil, India and China who each have a trust measurement higher than 60%.
4. The quality of products and services ranks higher than financial returns. according to Mr. Edelman,"Trust is now an essential line of business to be developed and delivered.
5. There appears concern by the majority that there will be a return to business as usual by companies as the economy recovers.
6. Sweden, Canada and Germany remain the most trusted countries for global headquarters.
7. Trust in government appears to be stable. However, the trust in the US is up 16 points to 46% and in Russia trust has decreased by 10 points to 38%.
8. In 20 countries corporate or product advertising continues to be the least credible source of information at 17%.
9. Reports from industry analysts and articles in business magazines remain the most credible sources of information about a company. However, the trust in mainstream media is waning.

Mr. Edelman notes that "we're seeing a vastly different set of factors driving reputation that we did 10 years ago". This is consistent with measures of loyalty that appear to have very different factors driving loyalty with an individual company.

The bottom line is that we now have another measure by which we can assess a company's strength in the market. The next step will be to compare these measures of trust with financial performance as has already been done using the ACSI measurement.

To learn more about the Trust Barometer you can find Edelman on the web at www.edelman.com.

Customer Facts to Consider for Improved Loyalty

I am close to the edge of doing what offends me. I am tired of reading 5 ways to increase loyalty or 7 steps to improve customer satisfaction or 6 ways to avoid losing customers, etc. I am about to walk on the edge by noting some information that may help you improve your customer loyalty. I have taken these facts from a blog by Loyalty 360 titled "11 Key Customer Loyalty Trends for 2011". I will leave the blog alone except that within the blog there were some statistics that might provide some guidance for the new year.

Here are some statistics that, in my opinion, might have relevance to understanding customers:
1. Behavioral economists note that economic decision making is 70% emotional and 30%rational.
2. A 20009 Gallup survey found that those companies that are in the upper half of both customer and employee engagement get a 240% boost in bottom line results compared with those who are in the upper half of customer engagement or in the upper half of employee engagement who only get a 70% boost.
3. Customer engagement is the holy grail for loyalty initiatives because engagement yields loyalty, advocacy, trust and passion which are the components that directly impact the bottom line.
4. The 18 to 35 year-olds' are particularly responsive to social and green issues. 85% say they would switch brands because of such marketing and 73% said they would try a new brand.
5. The National Restaurant Association found that 84% of those members who responded plan to invest more in their loyalty initiatives in the future because of the proven ability to drive business growth.
6. A surprise finding is that traditional incentive marketing does not drive consumer participation as much as achieved by gaming. The statistics are that 200 million people play games on Facebook every month and 24 games have more than 10 million users per month. The point is that a good game can impact consumer participation and may help build a lasting relationship and/or brand loyalty.

While there is no BIG message in this blog, it does provide some insight about customers. The bottom line here is that customers continue to change and are becoming more connected using social media. Companies must be prepared to adjust their strategies to meet the changing face of the customer.

Is the Impact of the Internet on Loyalty Positive or Negative

Forrester Research has completed a study in the UK that suggests the Internet has created a platform that is having a negative effect on customer loyalty. A summary of the research was reported in ComputerWeekly.com in their 11/10/2010 issue. Some of the statistics that were derived from a survey of 500 shoppers in the UK are:
1. 60% of UK shoppers have not decided on the brand they will purchase before buying a product online.
2. 86% of the shoppers use ratings and reviews for online purchases.
3. 44% go online before buying products in-store.
4. 42% use their mobile phone while shopping of whom 16% used their phone to compare prices with other stores.

The UK is a relatively mature market. The average UK shopper spends about $900 annually compared with $750 in the US.

Based on these statistics one might conclude that shopping has become more of a commodity and buyers are either price or value shopping. There is little, if any, loyalty in price or value shopping unless the shopper adds value for a particular store or company.

On the other side of the coin there is an interesting note in facebooksniper.com that describes how companies can use Facebook and Twitter to increase incoming traffic to a website. Here are the steps that are suggested:
1. Sign up to Facebook.
2. Make friends in Facebook by joining groups or communities that match your market niche.
3. Send a friend request to people in the community or social network.
4. Use your existing customer's contact email in your email account.
5. Start promoting your business on Facebook - but do it tactically. One way is to promote your website is to create Fan pages representing your business and add people there.
6. Update your Fan pages with the latest happenings in your business.
7. Use Tweets to get the same message out.
8. Let users post their message so that it will be visible for all buddies in the friend list.

The bottom line is that the Internet can be a friend or enemy. It can be a friend if you learn how to use it to attract customers. It becomes an enemy when you allow your business to become a commodity with all your competitors. You choose.

In this new world of instant communication, those who understand the Internet will have a distinct and superior advantage to those who do not.

Who Cares About QBE?

I think many fall into the trap of naivete' when it comes to customer satisfaction surveys. The belief is that the customers are NOT influenced by the survey questions. In the normal course of purchasing and receiving products and services many people do not give much thought to their level of satisfaction, would they purchase again or would they recommend the product or service to a friend or colleague. It is not until the survey arrives (call/Internet or hard copy) that the customer begins to think a little deeper in order to answer the questions on the survey.

This phenomenon is referred to as QBE or "question behavior effects." In other words, the questions themselves induce responses which may cause customers to think more deeply about the answers and may even impact current or future behavior toward the company who sent the survey. This topic came up in a research article by Dholakia, Singhand Westbrook from Rice University titled "Understanding the Effects of Post-Service Experience Surveys on Delay and Acceleration of Customer Purchasing Behavior: Evidence from the Automotive Services Industry" and published in the Journal of Service Research Issue 13(4) pages 362-378.

One interesting outcome of the research was the difference noted in the quality evaluations when the customers are forewarned that they will soon receive a survey versus those who receive the survey with no forewarning. The customers who were forewarned reported lower evaluations and reduced their willingness to purchase and recommend the service. The authors suggest that this phenomenon is "negativity enhancement." What the authors are suggesting is that customers who are forewarned tend to focus primarily on negative aspects of their service experiences since they have the time to reflect on their event. Whereas those customers without the forewarning don't have the time to dwell on how they will respond and hence they are more likely to give a more balanced response.

The bottom line is the reminder that surveys are not simple. Yes, it is easy to write questions that may have simple flaws but even the best written surveys must be viewed with the perspective that there may be some customer behavior that will result from the questions themselves. I will have more to say about QBE in future blogs.

The Changing Face of Loyalty

There was an interesting article written by Mila D'Antonio in the August edition of
1to1 Magazine. The article posits the notion that customer loyalty is evolving. I agree! A brief look back in time brings to mind the memory of S&H Green Stamps that my mother diligently collected. That process is the first loyalty program that I can remember The second one that comes to mind is the American Airlines AAdvantage program of which I am still a member. But business is not the same as it was 40 years ago or even 10 years ago.

The appearance of the Internet and all the accompanying social media has changed the face of business. Some of the statistics that tells the story include the fact that 75% of consumers today are enrolled in at least one loyalty program and more than33% are enrolled in 2 or more programs. The Internet has helped the consumer to be well-informed. With all the information that is available, the consumer can use the Internet to get product and service information as well as reading reviews from other shoppers.

In January, 2010 the CMO Council reported that 60% of marketers say that loyalty program participants are the best and most profitable customers,only about 15% believe they have been highly effective in leveraging loyalty among its customers and 20% don't even employ a customer loyalty strategy.

What has changed is that customers now have many channels of information to access when making a decision for product purchases or services. Companies are now being forced to manage all the channels so that there is a consistent message. The social media, while new, brings as much, if not more, value to the customer that the traditional methods. Social media has and will continue to significantly impact customer loyalty. In fact, it appears that the social media may become one of the ways to establish emotional attachment to companies. Kevin Knowles, VP of merchant loyalty at First Data notes that "if you don't have a centralized model you run the risk of having your customer data fragmented."

This evolution of information availability has led a number of companies to evolve their loyalty programs to include managing social media, providing proactive customer service, and establishing ongoing programs to maintain contact with their customers. Some of the newer programs include including Twitter and chat capabilities with the company.

The bottom line is customer loyalty requires a long term relationship with customers. That relationship must be built on the episodes that occur during the customer's life cycle with the company. Therefore, companies must think of approaches that continuously build and strengthen the customer relationship. The connection between company and customer must proactive, NOT reactive.

As I have said to many clients, every time you touch a customer you will either add a strand to the bond of your customer relationship or will be break a strand of that bond. This includes every customer contact whether it is with someone from sales, customer service, accounts payable (the cashier), or any aspect of your social media. The stronger the bond the less likely the customer look for an alternative supplier.

Loyalty Programs Help Restaurants in Tough Times

An online survey was conducted in 2010 among members of the National Restaurant Association. There were approximately 1300 responses. The survey had several objectives; namely:
1. investigate the level of penetration of loyalty programs in the industry,
2. identify the types of loyalty programs,
3. collect the metrics being used to measure performance, and
4. determine the level of resources dedicated to support the effort.

There were a number of findings that appear to be significant. They are
1. 77% of the respondents said that loyalty programs helped drive business during the economic turn down,
2. 90% said that the loyalty programs gave them a competitive advantage
3. for those already using loyalty programs, 84% plan to maintain or increase their program investment
4. 74% of the respondents used social media to support their loyalty programs. Facebook was the most common site and was used by 65%, followed by Twitter at 40% and blogging at 17%.

The bottom line is that loyalty programs are clearly a competitive weapon. That weapon has been shown to be particularly effective during the economic downturn in the last two years as can so easily be noticed by the willingness to continue the programs. It is not difficult to image that its effectiveness will continue even as the economy improves. Loyalty programs can provide the added incentive to increase visits from individual customers.

What Price Loyalty

I saw a quote on the net the other day. It asked the question "Why do customers need to take the initiative to ultimately be rewarded for loyalty?" GREAT question! As we review the many loyalty programs that are offered by B2C and B2B companies the onus is almost always on the customer to initiate the program and often it is the customer's responsibility to manage it as well. Businesses have the resources and the tools necessary to do the work for the customer. It seems that treating the loyal customers with a little extra effort by taking care of the loyalty program for them is a natural step for showing them the benefits of being a loyal customer.

This is an open question to those companies who have a loyalty program. Are your customers responsible for initiating your loyalty program? if the answer is yes, why? One of the major objectives of just about all loyalty programs is to entice the customer to continue to return (as often as possible). Are there any hurdles that the customer must overcome to continue to capture rewards? Must the customer always have his loyalty card to get reward "points"? Are there other policy obstacles that might disallow the addition of loyalty points?

One of the prime rules of business that has become part of the gospel of customer loyalty is that the business must do everything it can to make it as easy as possible for the customer to do business. The obvious extension to this fundamental rule of business should be, in my opinion, to make it as easy as possible for the customer to accumulate loyalty points (or whatever is used) as easily as possible. To burden the loyal customer seems to be against the basic tenet of making it easy to do business with the company.

One of the latest marketing concepts is to segment the customers as finely as possible so that advertising programs and rewards can be finely tuned to the customer level. As long as the marketing program is tracking customers to determine their buying habits, would it not be reasonable to use that data to build the loyalty profile of the customers so that any loyalty program developed can be automatically applied to the appropriate customers?

I believe that the next step in loyalty programs is to take them off the backs of the customers and put them into the company where they belong. The idea is to make loyalty a benefit not an aggravation.

Is There a Dark Side to Analytics?

A case study in the Harvard Business Review issue of May 2007 was written by Thomas Davenport and Jeanne Harris. The case considers the possible uses of client information and suggests that there may be some unintended consequences that may be less than the "right thing to do". There were case commentaries by George Jones, President and CEO of Borders, Katherine Lemon, Associate Professor of marketing at Babson College's Carroll School of Management, David Norton, Senior VP at Harrah's Entertainment and Michael McCallisster, President and CEO of Humana to complement the case study.

One of the key points of the case study is that customers are generally not aware that much of the information they provide to businesses is often sold to other businesses. Some of the more egregious examples are prescription information from a large supermarket with a pharmacy who sells the information to insurance companies; another example is the amount of alcoholic beverages that is being bought by a specific individual or family which might also end up in the data base of the insurance company that holds the insurance policy for that individual or family and which could lead to increased premiums.

It doesn't take a lot of imagination to conjure up additional ways in which the data gathered for analysis can be used in ways that the customer never understood and who probably would not have given permission to share had the customer been aware of who was buying access to the data. With the amount of information given by individuals and companies and then being sold to other companies for analysis, it is becoming eminently clear that there is a need for better communication between the customer and/or business and the companies who are asking for that information.

As a first step companies who sell the information need to apprise their customers what information is being sold and to whom. The first step to resolve this issue is transparency that could provide the customer with the opportunity to request that information regarding their purchasing behavior either be limited to certain items or even eliminated from the data base.

As it turns out many of the retail stores that gather that customer information need to sell the information because of the low margins many retains stores operate on these days. This added income may be the difference between profit and loss. Nevertheless, withholding this knowledge that the company is gathering specific information regarding the buying habits of specific customers to sell to other companies that can analyze and make business decisions about those customers MUST NOT continue to be withheld. The opportunity to abuse and misuse the information casts a dark shadow on those of us who make a profession of using analytics to make better business decisions. It is worse than the old adage that people lie with statistics. In this case people are using statistics to possibly punish people who are unaware of what is happening.

The bottom line is that we who are in the analytics industry must find a way to bring sunshine onto our analytics. Any other way is both unethical and immoral!

Satisfaction Is Not Enough

There was an interesting thought by Dick Gorelick about satisfaction that needs some further discussion. His premise is that customer satisfaction is not enough. He starts out by stating that the majority of customers that defect are satisfied. It is a follow-on of the Harvard Business Review article by Jones and Sasser titled "Why Satisfied Customers Defect."

Mr. Gorelick surveyed print buyers for American Printer, an organization that services senior executives in commercial printing. He states that the problem is that customer satisfaction is a poor metric for predicting account retention or loss.In his survey he found that fewer than 3% of survey respondent's' comments mention products or equipment. He found that the important factors in a customer relationship are memorable and unique events and services - ranging from green pretzels on St. Patrick's Day to the personality of the receptionist.

The main point of his note is his conclusion that the "silent killer" of a customer relationship occurs when it appears that all is well with the customers based on feedback that indicated no pressing problems or deficiencies. His belief is that when a company believes that just "doing more of what we've been doing" is making the incorrect assumption that customer satisfaction is a static concept. Within this assumption is another incorrect assumption that competition is not getting better.

When competition increases the company that continues to provide the same level of performance will find a year-to-year erosion of the customer base.

The bottom line is that the real issue for business is customer defections and those defections will not usually be the result of product quality or defects. Customer retention occurs when memorable events continue.

NPS One More Time

It is with great hope that this is the last blog regarding Net Promoter Score (NPS) written by the Customer Institute. This blog has two components. The first is a short discussion of one of the problems noted by the Customer Institute and the second is a brief discussion abstracted from an article by Craig F. Kolb, a marketing research specialist with Ask Afrika, a marketing research firm in South Africa.

A concern of the Customer Institute

One of the key concerns of the Customer Institute is to understand measures of customer satisfaction and loyalty. NPS is promoted as "the fundamental perspective that every company's customer's can be divided into three categories: Promoters, Passives and Detractors. On a scale of 0 through 10 the categories are defined as Promoters score 9 or 10, Passives score 7 or 8 and Detractors score 0 through 6. By asking one simple question - How likely is it that you would recommend [Company X] to a friend or colleague? - you can track these groups and get a clear measure of your company's performance through it customer's eyes."

The calculation of NPS takes the percentage of customers who are Promoters and subtracts the percentage who are Detractors.

Here is the problem. Consider three companies A, B, C. Each has a NPS of 70%. Consider each company's score is computed as follows:
Company A has 80% Promoters and 10% Detractors for an NPS score of 70%
Company B has 75% Promoters and 5% Detractors for an NPS score of 70%
Company C has 70% Promoters and 0% Detractors for an NPS score of 70%.

Of course many combinations are available that will yield an NPS score of 70%. The business problem (perspective) is that these three companies (A, B, C) are in very different conditions and yet the executives of each company believes their company is equal in customer perception with the other two.

Concerns by Craig F. Kolb

Mr. Kolb makes a number of statements and backs them up with references that will not be repeated in this blog. The statements are listed and those interested in checking the validity can refer to his article "Re-Evaluating the Net Promoter Score" dated July 14, 2010. The concerns are:
1. The Ultimate Question is far from being ultimate and is not the best predictor of customer retention.
2. The NPS does not relate to the percentage of customers switching away from each institution. A survey of 8000 customers were asked the likelihood of recommending question along with a rival set of question is and then followed up a year later. The ultimate question was outperformed by a simple repeat purchase intention question.
3. With NPS "promoters" are not equally loyal.
4. The relationship with growth is not clear with NPS. A study by Morgan & Rego in 2006 found that NPS was not predictive of company growth rates and customer satisfaction outperformed NPS as a predictor.

The bottom line is that NPS needs to be viewed very carefully. There are a lot of questions that must be answered before companies can use the NPS score without reservation.

Service is Important - Proven Once Again

American Express Global Customer Service Barometer provided some results from their latest survey conducted in the United States and eleven other countries. The findings are further verification that customer service REALLY is important and plays a critical role in the success of any company. Here is a list of the major findings of the report.

1. 61% of Americans will spend an average of 9% more when they believe a company provided excellent service.
2. 91% of Americans consider the level of customer service important when deciding to do business with a company.
3. 81% of consumers are more likely to give a company repeat business after a good service experience.
4. 52% of consumers will never do business with a company again after a poor experience.
5. The three most influential factors when deciding which companies they do business with include personal experience (98%), a company's reputation (92%),and recommendations from friends and family (88%).
6. 86% of consumers report they're willing to give a company a second chance after a bad experience if they've historically experienced great customer service with that company.

The bottom line is that the research continues to show that good customer service has a financial benefit. It is not rocket science to figure out how to provide excellent service. The Customer Institute believes that good customer service starts with the CEO/Chairman.

The New Media Versus the Old Media

The Institute of Customer Service in the UK just completed a survey of UK consumers to examine customers perception of the space on the company's site to review products and services and leave a comment versus having a Twitter account and/or a Facebook page. The results are somewhat surprising as noted below.

1. Providing space for on site reviews or products and services is five times more important to UK consumers than a company having a Twitter account.
2. Providing that same space is three times more important than offering a Facebook page or group.
3. About 41% of the UK consumers view the on site facility as a standard element of any good corporate website and 54% of the consumers said they use such facility when it is provided.
4. When age is considered the younger consumers (18-24) expect a company to run a Facebook page compared to 13% of the 35-54 age group and only 7% for the over 55 age group.

Jo Causon, Chief Executive at the Institute of Customer Service commented: "Businesses must wake up to the fact that the relationship between companies and their customer has changed irrevocably." The research also found some more areas that will need to be addressed. Some of the findings suggest better followup to customers concerns are indicated. Some of the findings are:

1. While 55% of consumers expect a response the same day to an online complaint, only 29% actually receive one.
2. Even worse, they found that 12% reported having to wait at least a month for a response.
3. The study showed that 75% of UK consumers complain when encountering a problem with goods or services, yet only 15% of face-to-face telephone complaints are able to be dealt with on the spot
4. More than 52% complaints take over a week to resolve.
5. Worst of all, 26% of the complaints remain unresolved.

The bottom line is that providing customers with a way to complain is still important and even more important companies must find a way to reduce the turnaround time to resolve complaints. These data support the research at The Customer Institute that indicate the UK has lower customer satisfaction for support of technology equipment than the US, Canada, Australia and New Zealand.

While Twitter and Facebook seem to be taking hold of the company-consumer interface, they have not yet displaced what has always been the road to customer satisfaction when a complaint is offered. It may be just a matter of time.

Innovation

Tradition can be a constraint. When working in industry many years ago, I worked for a company that had been in business for 125 years. Needless to say, the company was loaded with "tradition." The favorite response to any desire to improve the business performance was "but we've always done it that way." I would walk down the brick-lined halls and I could feel the walls quietly saying "we've always done it that way." In many ways industry has become filled with tradition in the ways that we measure customer satisfaction and loyalty. Different measures of satisfaction and loyalty arise and become popular only to fall into the abyss of time when another measure is announced. As Yogi Berra said, it is deja vu all over again. We have been using mail surveys, phone surveys and most recently Internet surveys to gather customer information. The response rate seems to relate to the importance of the product or service to the customer. Surveys at McDonald's will not get the same response as surveys on cat-scan equipment at the hospital. Usually the survey response for the retail industry (such as McDonalds) falls far behind the response rate of B2B.

Well, a small company in Windsor, Ontario, Canada has developed an innovative method for dramatically increasing response rates for surveys. The company, Tellbob, Inc. collects instant customer feedback for retailers, businesses and institutions on web-based terminals (computer kiosks) and hand-held mobile units. The customers are instantly rewarded with either a coupon that can be used immediately or some other form of reward. The kiosk-based technology and mobile units with touch screen technology makes it easy for the customer to answer questions and submit comments before printing out a coupon.

The system gives immediate feedback on questions shortly after the point of sale. The obvious benefit is that the data is up-to-date without the time lapse that results when the customer answers a survey at some later point in time (filling out a response card or answering an Internet survey). A secondary, but no less important aspect is the survey can be modified quickly to capture customer trends or major problems before they get out-of-hand.

The preliminary results reported by one of Tellbob's customers, Marble Slab Creamery, indicated a redemption rate of 85%. Wow!!!

The bottom line is that the customer can give immediate feedback in an easy to use way and is instantly rewarded. This is definitely a step forward for the companies that deal directly with their customers face-to-face. I like it.

Measurements Raise More Questions Than Answers

As we read some of the publications that are found on the web some of the information raises interesting questions. This may be one of the most boring blogs written for The Customer Institute. I am basing my concern on a chart that had some very interesting and, in my opinion, some worthwhile information. The chart was titled "The Impact of Problem Resolution on Loyalty." The chart showed information taken from five different industries and noted how the "loyalty" changed depending whether problems left the customer satisfied, mollified or dissatisfied. It also added the score if there was no problem. The group of customers that had no problem recorded the highest level of loyalty.

I actually liked this chart and the reason I am using it as an example is that it is a great example of making a very important point but then gets lost when the scales on the axes don't follow the content of the chart. The concern I have with this particular chart is that the scale used on the y-axis of the chart is labeled "Repurchase Intention." WOW!

How do you get from measures of loyalty to repurchase intention? While it is easy to say there is some relationship between loyalty and retention, it requires a GIANT leap of faith to then put it into a chart that does not indicate loyalty on the y-axis. Some of the questions that come to mind are:

1. Is the relationship between loyalty and repurchase intention synonymous? If yes, then it is ok.
2. If they are not synonymous is there a linear relationship between the two terms?
3. If there is a known linear relationship between these two variables, I have yet to see the data and research to support it.

The bottom line is that we must always pay attention to the charts that always seem so compelling. There is no guarantee that the charts represent the information correctly. I have witnessed past transgressions that included showing a linear relationship between customer satisfaction and loyalty. While the scatter plot of the data implied a linear relationship, the r-square for the linear relationship was so low that the assumption that a linear relationship existed took a lot of courage to swallow.

We need some carefully designed experiments to demonstrate the relationships between these terms that we live with every day. What is the relationship between satisfaction, loyalty, repurchase, etc.?

On-going Validation that Satisfaction Matters

Thee was a short blog by Kevin Thomson on Webtrends on June 2, 2010. The author pointed out that investing $100 in the S&P 10 years ago would be worth $81 today whereas that same investment in stocks from companies that scored well in the ACSI index would be worth $372.13 today.

This tracks very well against an article published in the Summer 2007 edition of The Business Renaissance Quarterly by Bleuel and Stanley titled "Customer Focus: One Key to Financial Success" that demonstrated similar results. The authors reviewed 12 industries that were represented in the ASCI index. The authors compared the best and the worst (in terms of their ASCI index) in each of the industries and found statistically significant differences (at the 5% level) for the following financial measures:
1. Cash Flow (16.4 versus 3.4)
2. Price Growth (59.7 versus 34.6)
3. Earnings Predictability (76 versus 51.8)
4. Beta as a measure of risk (0.95 versus 1.23)

In addition there was a statistically significant difference between the average ACSI scores for the best companies versus the worst companies.

The bottom line from both of these examples is that companies that have a strategy that includes a strong customer service component tend to have better financial performance than those that do not.

Loyalty from the Perspective of Human Capital

While this blog usually focuses on theory and modeling customer satisfaction and loyalty, it will, from time-to-time, discuss topics that are a little outside the normal discourse. Such is the case today where brief discussion of customer capital has some relevance to the topic of satisfaction and loyalty. This blog is the result of re-reading a book published in 1997 titled "Intellectual Capital" and was written by Thomas A. Stewart. Reviewing some of his concepts about how companies and customers can interact gave me some ideas that relate customer capital to loyalty. The idea is that both the company and its customers have knowledge that may yield greater benefit and loyalty when combined.

Successful companies will invest in employees because they know that employees are knowledge sources for the company. As employees become better trained and knowledgeable, they also become more likely to create knowledge assets, usually referred to intellectual property.

But when we examine the company from a broader perspective the question becomes can the company also form a relationship with its customers that might create knowledge assets? The obvious answer is yes. The combined resources of the company and its customers can very likely create knowledge that may provide new asset value to both. This seems to be an opportunity that many companies are missing.

It is clear that when a company solves a customer problem there may be some new knowledge created from the solution. However, these circumstances where new knowledge is created are more spontaneous that planned and rarely make it into any category of either the company or its customer that would identify the new knowledge as capital. Some of the more dramatic company-customer solutions may lead to a shared patent or copyright as well as a stronger relation with the customer. Another benefit of these new knowledge solutions might be another way to differentiate a product or service from the competition and lead to increased margins.

The bottom line is the company-customer interface is rarely seen as a place to create new knowledge capital even though the benefits are obvious and may actually lead to significant product and service breakthroughs. The challenge is to change the way we look at customers. Customers are no longer simply a source of revenue. They also bring the opportunity to create knowledge capital jointly with the company that can lead to a stronger customer relationship with the company as well as create barriers to competition that are built from the new knowledge.

The Other Side of the Coin

In the previous blog, it was noted that when high performance agents became at-home agents, their performance deteriorated. Customer satisfaction decreased. There appears to be another side to this situation. The inContact consulting firm has written a white paper titled "The Work-at-Home Agent model for Improved Customer Loyalty". Some of the statistics presented include:
1. A national poll conducted by inContact in 20007 showed that 46% of respondents (presumably businesses with call centers) said they were using at-home agents.
2. A study published by The Telework Coalition noted that the at-home contribution on improving the bottom line included 91% of agents were happier, had increased productivity, a higher retention rate, and reduced office space and operational expenses.
3. Frost & Sullivan report the median age of an at-home worker is 38 while the average age of an on-premises call center agent is 23 and further noted that 80% of at-home agents have some college-level education compared to 35% of agents in the on-premises centers.
4. According to a Gartner Group survey, at-home agents measured 40% more productive.
5. IDC Consulting has published results that indicate an on-premises agent costs $31 per our while an at-home agent costs $21 per hour on average.
6. The Interantional Telework Association and Council have published statistics the show there is a space savings that can reach $12,000 per employee per year. They also appear to indicate that there is a decreased cost of $25,000 per at-home employee compared to a traditional call-center agent.

These are strong statistics which suggest there may be an impact on customer satisfaction and loyalty. However, please note there were no statistics that compared customer satisfaction between at-home agents and on-premises agents.

The bottom line is that while these statistics are encouraging, there is no measured difference between the in-home agent and the on-premises agent for customer satisfaction. The Customer Institute will continue to search for studies that attempt to measure the satisfaction impact of the at-home agent. While this white paper has good content and meaningful statistics, it can only suggest that at-home agents may improve customer loyalty.

Some Surprising Findings

Call centers represent one of the fastest growing segments of customer service. A recent blog by Carmit DiAndrea of Analytics & Client Services brought this to the attention of The Customer Institute. There has been a trend toward work-at-home agents and some of the data suggest the number of work-at-home agents is growing at the rate of 40% per year. Other studies indicate the attrition rate of work-at-home agents is much less than the typical call center. One of the prime reasons is that work-at-home agents eliminate the cost of work space. While this may be of interest to those who watch the financial aspect of call center operations, the point of this blog is that in one case study there were two surprises. These surprises lead to the question: "is this an anomaly or is there something to this that needs to be investigated."

The first surprise was the likelihood to recommend the company's services was somewhat lower for the work-at-home agent than the call center and the second surprise was that satisfaction with service provided was also lower for the work-at-home agent than the agent at the call center.

Let me enter a few caveats here; namely,
1. This is only one company that recorded these results and that company has chosen to remain anonymous.
2. The differences between the call center agents and the work-at-home agents were concluded to be different but there was no test to determine if the differences were statistically significant.
3. This was not a controlled experiment. Thus, there may be other factors that caused the differences.

The company tracked these two parameters metrics for one year and based on the data asked the following questions:
1. Why did these metrics drop when one call center sent their top performing agents home to work?
2. What would cause these top agents to struggle to perform at an average level?

While there were no clear answers to these questions, the following ideas were presented without any evidence that they may be significant:
1. How were the work-at-home agents selected? Is there a difference between agents in the call center and work-at-home agents? Does it take a different type of person?
2. Should the expectations be different for the call center agent than the work-at-home agent?
3. Can the type of training make a difference?
4. Should the management of call center agents be different than work-at-home agents?

The bottom line is that there appears to be a sea change in the work force for call centers. Some of the questions that need to be addressed are:
1. Do we need a new way to train managers to manage the work-at-home agent?
2. Do we need to train work-at-home agents differently than the call center agents?
3. Do we need new metrics for the work-at-home agent?
4. Should there be different hiring requirements for call center agents than work-at-home agents?

Since we know that call center agents have a direct impact on both customer satisfaction and loyalty, this topic needs more research. One case is not enough. We are interested in the outcome and will blog any further results that are published.

Butterfly Customers

I recently found a book published in 1997 titled "The Butterfly Customer - capturing the Loyalty of Today's Elusive Customer." The authors Joan A Pajunen and Susan O'Dell describe what now appears to be a very different customer. They describe butterfly customers as customers who flit from one store or supplier to another with the intent of finding a lower price or some other feature. They have no loyalty to any particular company and are always in search of a better deal or a new inducement.

The reason I am attracted to this concept is that I believe I am a butterfly customer. According to the authors butterflies have developed from the proliferation of shopping environments such as shopping malls and the Internet. The small company or retail store might offer convenience but cannot match the pricing of large companies. (When I worked in industry I worked for a division of a company that held 3rd place in market share. The two companies that fought out the 1st and 2nd place could sell products for less than our manufacturing cost).

The authors provide eight characteristics of butterflies.
1. They will readily accept offers to be loyal customers.
2. They move across market segments. They will buy a luxury item and then go to a discount store to save a few dollars.
3. They are intelligent, educated and informed.
4. They are cynical and skeptical, and always read the fine print.
5. They would rather switch than fight - which may be a reason for the decline in customer complaints.
6. They consider word-of-mouth as the most reliable source of information.
7. They are not embarrassed to be butterflies.
8. They know their own worth.

The authors describe a butterfly that can be loyal. The "Monarch" is a butterfly who will return again and again once he/she trusts the company. There are five characteristics of Monarchs.
1. Monarchs always return sooner or later.
2. Monarchs often send someone in their place.
3. Monarchs always have an opinion which they will share if asked.
4. Monarchs share their homework and may share their information on what the competition is doing.
5. Monarchs are very forgiving and giving. They have elasticity in their transactions which translates that they will overlook a mistake or bad transaction.

The solution offered for building an environment to create Monarch butterflies has three dimensions; namely media, physical (bricks and mortar) and people. When these three dimensions are working together the customer can develop trust in the company. If any of these dimensions are out of sync, the trust may not develop. For example, a company that provides a media image of high quality and provides a quality product but has surly personnel will create dissonance in the mind of the customer. Loyal Monarchs can be found dealing with companies that provide consistency in these three dimensions.

The bottom line is that customers may, in fact, be changing as a result of the media. The concept of butterflies resonates with me. The concept of butterfly customers has not taken off in terms of the literature. It is always surprising how many creative ways are being developed to describe customers and segment the market and butterflies may be a new segment. It will be interesting to see whether or not butterfly customers do become a segment. In any case, the butterfly customer just may require a new definition of loyalty.

More Thoughts on Disloyalty

Maritz Marketing Research published a research report titled "Customer Disloyalty". The report was written by Dr. Dan Lockhart. He starts out by saying that loyal customers have the following characteristics:
1. Like your product and/or service
2. Frequently purchase your product and/or service
3. Feel your product and/or service is worth what they paid for it
4. Feel that your product and/or service is better than your competitors'
5. Feel you product and/or service meets their expectations or desires
6. Recommend that others purchase your product and/or service.

He then defines disloyal customers as "anti-customers for the following reasons:
1. They dissuade others from patronizing our business
2. They bring law suits against you
3. They may complain about you to the media
4. In extreme cases they may picket your business.

According to Dr. Lockhart there are 4 stages of disloyalty:
Stage 1 - the customer is dissatisfied or has unmet expectations or desires.
Stage 2 - there is an attempt to correct the situation if the company is aware of the dissatisfaction or unmet expectation.
Stage 3 - If the company fails to correct the problem the customer may refuse to make any additional purchases
Stage 4 - If the customer feels he/she has no other option that customer may attempt to influence others not to buy from the company.

These four stages represent the downward spiral that begins with a dissatisfied customer and ends with a lost customer.

The research report uses a tree to show where customers get lost through the various stages of disloyalty. The tree starts with 1200 customers. The first stage (two branches) shows that 960 customers (80%) have no problem and 240 have a problem. Of the 240, (the second stage with two branches) there are 48 customers with a problem (this represents 20% of those with a problem who don't tell anyone and start down the path to disloyalty). Of the 192 that do tell someone (the third stage with two branches) 86 get excellent results (45%) and 102 do not get excellent results and start on the path to disloyalty. Finally in the fourth stage there are two branches that show half of those who received excellent response decide to purchase again and the other half chose not to repurchase. When all of these probabilities are combined there are 197 customers out of the original 1200 (16.4%) who end up on the road to disloyalty.

One of the obvious conclusions that can be drawn from this discussion is when companies do not handle complaints very well they are accelerating the decline from dissatisfaction to disloyalty. The data used in the research paper to create the probabilities was from a client and hence has some validity. While these probabilities represent the performance of just one company, the conclusion drawn by Dr. lockhart makes sense.

The bottom line is that managing customer complaints well appears to have a dramatic positive effect on customers with the implication that the company also benefits in terms of reducing the number of customers that may become disloyal. The challenge for companies is to examine the magnitude of these four stages that lead to disloyalty. One way to think about these four stages is to see them as cracks in the organizational structure. Then it becomes a management problem of how best to fill the cracks.

More About Customers as Assets

One of the goals of The Customer Institute is to publish a book which describes customers as assets and how to manage those assets. When customers are viewed as assets they take on a different perspective. For example Apple computer has taken the position that customers are assets and have developed them to the point where they can introduce a new product, such as the iPad and almost guarantee huge sales. Ben Fowler wrote an interesting piece dated April 6, 2010 in his blog (voiceofcustomerguru). Customers of Apple respond to Apple product announcements with little hesitation because they believe that Apple products deliver high quality.

Compare Apple to US automobile manufacturers during the 60s and 70s. They built cars with great styling and innovation but the product quality was inferior to those being sold by the Japanese whose products had less style and innovations but superior quality. The US automakers damaged their customer asset to the point that even today when their product quality is equal to the Japanese, they must offer incentives and lower prices to get sales.

The US economy has changed in the last 50 years. Whereas 50 years ago the size of manufacturing was twice the size of consumer service. Today the ratio is the same but with consumer service twice the size of manufacturing. Consumer service requires a different accounting system than the one used for manufacturing. When cars are sold there is an immediate transfer of asset from the car manufacturer to the new owner. The asset transfer is complete.

When we are dealing with the customer asset, we need to look at the value of that asset over time rather than in a single time period. There are have a number of books and articles written about measuring the value of a customer. One book that has been around for a while is "Managing Customer Value: Creating Quality and Service That Customers Can See" by Bradley Gale. The typical calculation of long-term customer value is based on the average life of a typical customer. If the customer life is three years, the value is based on three years. However, many of the books and articles written about calculating the value of a customer have not dealt with the value as an asset and its implications when looked at from an accounting perspective.

Note the following example and some of the accounting discussion is being done without the oversight of an accountant and must be viewed with some scepticism.

There is an excellent example of this weakness of viewing the customer asset in a book by C. Fornell titled "The Satisfied Customer: Winners and Losers in the Battle for Buyer Preference." The example the author uses examines the case where it costs $1000 to acquire a customer. If the customer lifetime is 3 years, the net income for those 3 years is -$100. If the company has acquired 1000 new customers for the year, the cost of acquisition is $1,000,000 and the net income from those new customers is $300,000. However, that is not the way the accounting system would report the performance of the company. The accounting system would show a loss of $700 for each customer acquired for the first year or a total loss of $700,000 for the 1000 new customers. The second year an additional 1000 new customers are acquired for another $1,000,000. This year the total sales is $600,000 so that the total loss for the year is only $400,000. When you include the third year the lost is $100,000 for each and every year thereafter as long as the average customer lifetime is 3 years.

The customer asset must be viewed in the light of the value to acquire it and the revenue expected from each customer. One of the keys to building the customer asset is consistent performance and value similar to Apple. Toyota has just dramatically reduced it customer asset by mismanaging its communications with its customers.

The bottom line is that customer retention is a key to success in the consumer service marketplace and the foundation for building the customer asset. Companies need to know the length of the average customer lifetime before they start a campaign to acquire new customers. What is usually missing in many companies is the cost to acquire a customer and the average customer lifetime. We have been taking the wrong measurements.

This analysis does not examine the process of building the customer asset. We will have to investigate further to understand how Apple has achieved so much asset value from its customers.

Benchmarks - How Good Are They?

In the latest issue of Quirk's Marketing Research Review (April 2010), there is a survey of researchers regarding benchmarking. The survey was performed in the Spring of 2009 with 97 responses from people involved in market research in their organizations (83 have a designated market research function). The survey was performed by Jennifer Van de Meulebroecke and Michele Sims both members of the staff at TRC Market Research in Fort Washington, PA. The researchers represented many markets including insurance, utilities, high-tech, health care and financial services.

The researchers noted that:
1. 75% of the researchers collected benchmark data as part of an internal study,
2. 56% of the researchers collected benchmark data separately or at a different time than other studies. Some also use an outside vendor for assistance.
3. 56% of the researchers used a syndicated source for their benchmark data.

The research went farther by asking the researchers to focus specifically on benchmarking data and describe their confidence in making comparisons for their company with benchmark data. The results indicated that 75% of the researchers who had less than 11 years in market research had confidence in using external benchmarking data; whereas only 58% of those with more than 11 years in market research had confidence in using the external benchmarking data for comparisons. The conclusion drawn from this piece of information is that it appears that the longer people are in market research, the less trust they have in using the external benchmark data to draw comparisons.

Since there are such low scores with respect to using external benchmark data, the question is what are the factors that people should be aware before using external benchmark data. The survey found the following factors and are ranked in order of importance by those who were surveyed:
1. 91% were concerned about the consistency of the scales and responses,
2. 83% were concerned with consistent question wording,
3. 77% were concerned with consistent screening,
4. 67% were concerned with the method of collecting the data (web, phone, etc),
5. 58% were concerned with type of sample that was used, and
6. 51% were concerned with the time period for data collection.

As an editorial comment I would note that many companies put extreme value on industry benchmarks. I had a consulting assignment several years ago with a high-tech company that had the lowest scores on their industry benchmark. The executives and managers were very concerned about their score. They believed, and rightly so, that thefact that the benchmark that showed they had the lowest scores in their industry would impact their sales. They asked for my help and within 3 years they were tied at the top of the industry benchmark. The problem was that they were scored low but did not have enough information to know where to make changes to their product nor support. Once we captured the information it was only a matter of time before they moved to the top.

The bottom line is that benchmarks are becoming more and more important to companies. Today many companies use benchmark data to assess their market position without understanding how the benchmark was created. In addition, the companies do not have the detail information necessary to accurately evaluate the meaning of the benchmark scores. The lesson is benchmarks are very valuable when used properly but can be VERY misleading when not properly understood.

Loyalty Versus Retention - Is There a Difference?

I noticed that the Irish Direct Marketing Association is hosting a conference on Loyalty and Retention. According to the news release there are a number of companies in Ireland that are trying to differentiate between customer loyalty and customer retention. The aim of the conference is to deliver clarity for the attendees on the difference between the two relationships, particularly with respect to marketing strategies.

This dilemma hasn't crossed the desk of The Customer Institute before, but it does raise an interesting question; namely, is there really a difference between customer loyalty and customer retention. Clearly there is no obvious answer, otherwise, there would be no need for a conference to discuss the issue.

With great hesitation, the following perspectives are offered without the imprimatur of academic certainty. It appears at first glance that customer loyalty has a greater reach than customer retention since many of those who support the concept of customer loyalty imply that the loyal customer brings word-of-mouth support of the company, its products and its services to other potential customers. On the other hand, customer retention appears to imply the customer will return (is being retained) but with no implied word-of-mouth component.

A simple definition of loyalty is "faithful to one's allegiance." The word retention comes from the root "retain" which is defined as "to keep possession of." These two definitions imply a very stark difference. Whereas loyalty seems to suggest that the connection comes from the customer, retention seems to come from the company. A customer becomes loyal for one or more reasons and chooses to return. On the other hand a customer is "retained" by the company. The retention can be in many forms without the need for physical restraint. The retention can come from special offers or preferential treatment.

The implications that can be drawn from these simple definitions are:
1. Customer loyalty comes from the customer and companies need to provide programs that build relationships with their customers (either heart or mind) that inspires them to return.
2. Customer retention comes from the company and is built on retaining a customer without the need for a change of heart or mind (becomes loyal). Retention then comes from providing incentives for the customer to return (is restrained from leaving) in the face of competitive actions.

The bottom line is the difference between loyalty and retention is much more complicated than this brief discussion and needs more study. The Customer Institute will continue to pursue these topics with the objective of discovering research that will provide quantitative understanding of these concepts with respect to customers.

The Customer Satisfaction Grid

This is a follow on blog to my previous blog. The source of the information for these two blogs is an article written by Earl Newmann and Donald W. Jackson, Jr. and published in Business Horizons. The previous blog discussed what they describe as the two-factor theory of customer satisfaction. In that previous blog I also discussed their logic and description of the two factors; namely hygiene and satisfiers.

In this blog I will discuss how the authors combine these factors into what they describe as a customer satisfaction grid. They further discuss how the grid can be used in the pre-sale, transaction and post-sale aspects of business.

The customer satisfaction grid shows the satisfiers on the x-axis and the hygiene attributes on the y-axis. The four segments of the grid are:

1. The lower left segment identifies company performance that doesn't meet the performance requirements of hygiene and also ignores the performance of those attributes that contribute to customer satisfaction. When customers are exposed to this level of performance in this segment of the grid these customers are strong candidates to seek a new vendor.

2. Firms that operate in the upper left segment of the grid have a much greater chance of holding onto their customers than those in the lower left. Unfortunately they are not performing well with the satisfiers. A restaurant which serves good food but has poor service and little atmosphere is definitely vulnerable to competition that provides some of the satisfiers for good service or an inviting atmosphere.

3. There are companies that operate in the lower right segment of the grid. These companies see the satisfiers as the way to build satisfied and loyal customers. These companies chose to focus their resources on the satisfiers while ignoring the hygiene factors. Their problem is they are ignoring the hygiene factors that significantly add to the value of the products and/or services. A movie theater that always brings in the latest and greatest films into a posh viewing area but does not clean their restrooms would be an excellent example of a company with a focus on the satisfiers but not the hygiene factor.

4. The upper right segment is where companies should be heading. This is where the industry leaders are located. These companies have figured out how to effectively meet the requirements for the hygiene factors and simultaneously provide a high level of performance for the satisfiers.

These two concepts (hygiene and satisfiers) are at play throughout the customer life cycle. The hygiene factors and satisfiers will change as customers go through the pre-sale phase, enter the acquisition phase and move into the post-sale phase. The companies who strive to get into the upper right segment and stay there will identify the hygiene and satisfiers in each of the life-cycle phases knowing that they change during the life cycle.

The bottom line is that this model is comparable to a number of others on the market. One of its values is that it offers a simple way of separating satisfiers and dissatisfiers by using the term hygiene components to explain the dissatisfiers. The key value of this paper is that it clearly points out that hygiene factors must be present before satisfiers have a significant effect on the customers.

A Two-Factor Theory of Customer Satisfaction

I recently re-read an article by Earl Neumann and Donald Jackson, Jr. about a two-factor model of customer satisfaction. While it is not significantly different from models currently being discussed and used, it does present the model using different words that make some sense. For this reason I offer a brief description of this model.

The essence of this model is the use of two factors to describe customer satisfaction. the two factors are hygiene elements and satisfiers. The hygiene elements are those attributes that customers expect to be part of the product or service. The absence of these elements generally result in customer dissatisfaction. (They may be described as dissatisfiers in some models). One key point is that the presence of hygiene elements generally does not contribute to customer satisfaction. One example of a hygiene element would be a clean restroom at the movie theater. Consistently maintaining a clean restroom may not contribute much to customer satisfaction. In general, a company must ensure that the hygiene elements consistently meet customer expectations. These elements are necessary but insufficient to create customer satisfaction. Satisfaction does not become important until the hygiene elements are present at a level that meets customer expectations.

J.M. Juran gave a rank-ordered list of elements based on a study of 2,500 passengers of Quantas Airways. From this list he demonstrated that the hygiene factors would cause the passengers extreme dissatisfaction. He also included the list of those elements that would lead to extreme positive satisfaction. Virtually all of the top elements were hygiene factors. In general, the satisfiers were ranked lower than the hygiene factors. The authors note that satisfaction levels are only achieved when the hygiene factors meet customer expectations and the satisfiers exceed customer expectations.

The conclusion is that while the hygiene elements are a must, the satisfiers are what lead to customer satisfaction. Some of the hygiene factors noted by Juran include: no lost luggage, no damaged luggage, clean toilets, clean and tidy cabin, comfortable cabin temperature and humidity, etc. On the other hand, some of the satisfiers include: comfortable seats, prompt baggage delivery, ample leg room, good quality meals, assistance with connections, quick/friendly airport check in, etc.

The authors present a generic grid of hygiene elements and satisfiers as shown below:
Hygiene elements include: credibility, reliability, accessibility, delivery and accuracy.
The satisfiers include: responsiveness, courtesy, empathy, exceptional quality and personnel who are thoroughly trained and knowledgeable.

The key issue to focus on for this model is understanding the term hygiene and its implications especially in terms of its position as the predecessor of satisfiers. This is a new perspective that I have not seen in other models. In my next blog I will describe their customer satisfaction grid and discuss how they use the grid to examine pre-sale, transaction and post-sale aspects of customer satisfaction.

The Kano Model for Measuring Customer Satisfaction

I recently ran across another model for measuring customer satisfaction. It is referred to as the Kano Model and is named after Professor Noriaki Kano. This post is based on material I found on the web. Some of the material came from a blog by E. George Woodley posted April 14, 2009. The Kano model is built on four identifiers; namely, threshold attributes, performance attributes, exciters or delighters attributes and indifferent attributes. It appears that the Kano model was developed for personnel in the quality function and gives them a methodology for evaluating products and services. Each of these attributes are discussed below.

The threshold attributes are also referred to as "must be" attributes suggesting that they must always be present. These product (or service) attributes are necessary in order for a product (or service) to find acceptance in a market. An example of threshold attributes for a hospital would be quality doctors and adequate equipment in order for the hospital to be considered acceptable.

Performance attributes are those which increase satisfaction of the customers as new services or features are added. For example, a great music system and air conditioning in cars increase customer satisfaction besides the threshold attributes of speed, mileage and brakes. If these performance attributes are removed, customer satisfaction will likely diminish. This suggests that once a performance attribute has been included in a product or service, it must be continued. Performance attributes tend to reflect the voice of the customer. The better the product or service is meeting these needs, the happier the customer is. The Kano model presents a format which allows the company to make trade-offs such as cost versus attribute improvements or trade-offs between various attributes. An example would be trading off improved acceleration performance versus gas mileage for a new model automobile.

Exciter or delighter attributes represent characteristics the customer was not expecting but receive as a bonus. Unlike performance attributes they do not affect customer satisfaction when they are discontinued from a product or service. An example would be the discontinuation of extra planes and train s during the holiday season which are discontinued at the end of the holiday season. The challenge is that some exciter/delighter attributes can become threshold attributes. An example is a dealership that always washes the customer car after servicing. At first it was a exciter/delighter but over time becomes an exciter.

The indifferent attributes do not affect customer satisfaction. They may include such items as the company logo on their stationery or the socks worn by company personnel.

Now that we have described the four identifiers, the model consists of plotting each product/service feature in a 2-dimensional diagram. The x-axis is the degree to which each particular feature is meeting the customer's requirements. The y-axis reflects the customer's level of satisfaction as a result of the level of achievement. The Kano model provides a graph that plots each point (feature) with the measure of how well the feature is meeting its objective and the associated measure of customer satisfaction. Thus, a feature such as gas mileage could have a hypothetical score of 90% indicating the percent of meeting the customer desire for high gas mileage with a corresponding customer satisfaction score of 8 (on a scale of 1 to 10). Thus, the company could evaluate the possibility of increasing mileage versus the cost.

There are a number of flaws in this model which with some effort some of these flaws may be possible to eliminate. For example,
1. There is an implicit assumption that all the individual product/service features are independent with respect to customer satisfaction.
2. Another assumption is that the relationship between feature performance and customer satisfaction is a linear relationship.
3. There is no direct way of rank-ordering the various product/service features in terms of impact on customer satisfaction to eliminate the occurrences when product/service features score low but have less impact than other product/service features.
4. Another assumption is the product/feature performance is linear (even though it appears to be since it is plotted on a scale of 0 to 100%). Is a 5% change at the 25%level the same as a 5% change at the 90% level? Just because a scale is linear does not imply that the characteristic is linear.

The bottom line is this a model that looks good and is probably used by people and companies that are not aware of the flaws in the model. There are many of these models on the market that look good but many are built on a foundation of sand.

I have not been able to find documentation that supports the validity of this model. If I find such documentation I will amend this blog accordingly.

The Elements of Success for Call Centers

The Ascent Group has published a white paper and detail report for those with the money to pay for the report. The report is the result of Ascent selecting companies that exhibit high levels of satisfaction. They based their selection of companies on rankings from ACSI, J.D. Power or other third parties (of which no others were named). They culled out the best practices and summarized them in their report. Since I have supported the ACSI as a reputable independent measure of customer satisfaction, and the Ascent Group appears to be acting independently (without bias), the results have value.

The report lists five prevalent (their words) underlying traits that were pervasive among all the companies. These traits are discussed in the following paragraphs.

1. Corporate Culture or Vision - Having a well-defined vision seems to give employees a clear road map of how to act and treat customers as well as colleagues. I recently was a member of a doctoral student whose dissertation topic was to determine if the vision of a founder of a start-up company was an important component of the success of the company. He found that sustaining the vision of the founder was, indeed, an important component of success.

2. Data Mining and CRM Tactics - They are suggesting that companies who are using data mining in combination with the tactical use of CRM are finding better ways to enhance the customer experience. Harrah's Entertainment is used as an example of how a company can use their CRM efforts as a more economical way to compete with lavish attractions or new facilities by their competitors. The CRM effort was combined with a data warehouse that collected patron information in all their properties. From this strategy they have increased their market segmentation and customer profiling. which is leading to a strong brand identity.

3. Actively Measuring Customer Satisfaction and Expectations - All the industry leaders paid a great deal of attention to the customer satisfaction measurements. Some of the companies also looked for dissatisfying situations in order to proactively eliminate them. My experience supports this approach of measuring dissatisfaction as well as satisfaction. The truth is that more customers leave from dissatisfaction than being lured away by other companies. Many companies are their own worst enemies and they don't know it because they focus their attention on the satisfiers and ignore (or unaware) of the dissatisfiers.

4. Hiring the Right Employees - This is so obvious that it requires little explanation. One statement that most would agree with is that employees are the face of the company. The best strategy for a call center to use is to hire the right employees and train them well. When the employees can believe in the company's vision and can be themselves, they become advocates of the company and form the basis of a winning team.

5. Extensive Training - Training is one of the key ingredients in optimizing call center performance. As my previous blogs indicate average handling time (AHT) is not something you want to minimize; rather it is something that you want to optimize. Optimization comes through extensive training. Some companies see this as an investment in quality and see it as a cost. Ritz-Carlton hotels provide 310 hours of training the first year. I find it amazing that companies will cut training budgets especially the on-going training. The assumption must be for these companies that once trained is enough. Using that logic, there is no need for management education after the initial training. Obviously, I don't agree.

The bottom line is this report makes sense. These five factors continue to appear in the literature and on the blogs of the many call center consultants. This attention adds to the credibility of these five factors. The report lists 12 other lesser characteristics, most of which seem equally relevant although not as important. I would stick with these five.

More Reasons NOT to Focus on AHT

In my previous blog, I gave some of the reasons I believe that call centers who focus on lower the AHT don't really understand customers. I read a blog by Ann All that gave me some more ammunition regarding the value of long AHTs. There were also some very pertinent facts included in her blog that, I believe, are worth repeating.

1. A survey by Jonathan Whitaker, an Assistant Professor at the University of Richmonith and two of his colleagues studied offshoring and outsourcing activities of 150 U.S. companies from 1998 to 2006 and found that whether or not the company outsourced offshore or to domestic providers, there were similar declines in satisfaction. While this has little to do directly with AHT, it does demonstrate the possible benefit of keeping support calls within the company - as noted in the examples below.
2. Burroughs Payments Systems, a Michigan company found that when the company switched from offshore to employees with actual hands-on experience the customer satisfaction levels increased sharply. The conclusion given by CEO Alan Howard was that customers prefer to talk to people who know what they are talking about. Mr. Howard noted that Burroughs' cost savings is greater than 10 times what they could have achieved with offshore customer service.

Many customer satisfaction surveys of call center operations have indicated that first call resolution is a key to achieving high levels of customer satisfaction. According to Dick Hunter, Dell's former VP of global customer support services, during a September DataInfoCom webcast the average time of technical support call increased from 22 to 32 minutes but with that increase in AHT the percent of first call resolutions increased from 44 percent to 65 percent.

The bottom line is that AHT is not just another measure of call center performance, it is the place where loyalty begins in the call center. As I noted in my previous blog,"killing the call" should be the primary focus of the call center (unless all they are doing is selling).

Customer Satisfaction versus Average Handle Time

I am seeing a lot of articles and blogs about the virtues and sins of average handle time (AHT) and how important it is. Much of the writing lately has been focused on call centers (and for good reason since they are becoming such a vital part of a company's performance and perception).

Customer service can be considered as four distinct categories; namely service at the customer site, service at the point of sale, service at a remote location and service via some electronic communications media (e.g. phone, fax, internet). The current research suggests that the electronic media is becoming the channel of choice. This leads to the reason for this blog and why I am taking time to respond to the notion that AHT is one of the most important aspects of customer service and, by inference, customer satisfaction and loyalty.

First let me state that AHT is probably not the most important driver of customer satisfaction and loyalty. My research certainly does not support that notion. It is one of the major factors but it is NOT the most important. I am sure there are others out there who will be ready to flog me and point out that I am unaware of the real market. Rather than taking on a fight, I would suggest that the time to answer (average speed of answer - ASA) is far more important if one is looking to improve customer satisfaction and loyalty. I recall a study several years ago that showed that ASA strongly correlates with customer satisfaction. The study showed that there was no perceptible drop in customer satisfaction for up to 2 minutes. However, once the time exceeded 2 minutes there was a precipitous drop in customer satisfaction.

I have seen studies that show if the AHT get very large there is a drop in customer satisfaction. Usually the time has to increase dramatically. Think about it. If you are a customer and you are getting your problem solved, will become dissatisfied when the customer service representative takes extra time to make sure your problem is resolved. I would pose that a longer handle time when done correctly will build customer satisfaction and loyalty. When I was in industry, I made it a policy to make sure that every one who touched a customer would take enough time to "kill each call." By that I meant that I wanted every call to take as long as necessary to make sure the customer thoroughly understood that the problem was resolved. That means the problem is DEAD.

It is very difficult to control incoming calls to an inbound call center. However, if you understand the basics of queuing theory, you can staff to take the calls in a reasonable time to be sure that your ASA is within the bounds you have set. That means you must also staff to give the service representatives sufficient time to "kill the calls."

The bottom line is that AHT is not something you want to reduce, it is what you need to build customer satisfaction and loyalty. The management focus should be on managing ASA and then train the service reps on how to kill a call. The results will surprise you. Of course many will say that you cannot reduce costs when AHT is high and that most companies are looking for ways to reduce costs. My purpose for writing this blog was to point out that ASA is more important to customer satisfaction and loyalty than AHT. Secondly, I wanted to make the suggest that there may be a significant down side to reducing AHT.

What is a "Bad" Customer?

I ran across a brief article titled "Get Rid of Bad Customers" that was published February 17th and was on the web under www.openforum.com/topics/managing/article/...
The essence of the article was that companies should get rid of bad customers. This is a statement that some companies have a difficult time accepting. The author lists four kinds of bad customers:
1. Slow-paying customers - if they continue to be a slow payer the author suggests they be put on a cash-only status. There is additional discussion but essentially the story is that a slow-paying customer is a "bad" customer although the author does not suggest getting rid of them.
2. Customers with constantly changing and ever-expanding needs - the author suggests these are not bad customers but ill-educated customers who don't know how to create project specifications and keep adding requirements. Once again the author does NOT suggest getting rid of them.
3. Price-sensitive, demanding customers - these customers resist standard pricing and insist on high levels of service and numerous product features. The author suggests that the company should decide what prices and terms are necessary to maintain the relationships. If the customers have already been given sufficient concessions, the author suggest it's time to refuse additional business at any price. (This is the first bad customer that the author actually suggests eliminating.)
4. Conniving customers - these customers "misrepresent problems to extract restitution in the form of full refunds or heavy discounts."

The author closes the article with the comment "Start making hard decisions, push away those who drag you down, and cultivate the right relationships."

While I generally agree with the author I think there are some additional points that should be made. The author seemed to limit the kinds of bad customers to those customers who had a direct impact on costs. The first point that seems appropriate is to suggest that customers are not "bad" or "good." Customers either fit your company or they do not. If they fit your company, then there should be a strategy in place to accommodate the needs of the customer. If a customer does not fit your company, it is a waste of your time and resource to try to "put a round peg into a square hole." By that I mean it is rarely cost-effective to stretch your resources to accommodate a customer whose needs are not a good fit with your products and/or services. More often both sides, customer and company, are not satisfied with the results.

It might be appropriate to add some other types of customers to the list of those that don't belong. For example,
1. A customer whose business strategy has changed and now is no longer a good fit with your products and/or services.
2. A customer who has out-grown you so that you cannot meet that customer's demands for products/services.
3. A customer who is not profitable when all the costs for customer support exceed the margin of the products/services purchased by the customer.
4. A customer whose needs have changed in such a way that your company would have to make significant changes to accommodate the customer (such as going to ISO 9000 certification when all of your other customers do not have that requirement).

The bottom line is there are no good or bad customers. The ideal customer is one whose needs for products and/or services matches the company. In addition companies want customers who they can trust and who trusts them. These customers will allow for occasional mistakes. They also understand that you must make a profit.

Most companies keep customers that are no longer worth keeping for any number of reasons - not that they are "bad." Too often an executive will say "we can't afford to lose another customer." This statement is naive and points out that the executive hasn't thought the process of what kind of customers the company needs to prosper and that not all customers will help the company prosper. One of the most difficult processes in business is knowing when it is time to say goodbye to a customer and how to say goodbye and still have the customer have a positive perception of you and your company. These are lessons that needs to be taught.

The Customer Perspective on Loyalty

As I have written in previous blogs, great companies do not need loyalty programs. Their customers are loyal because they are a great company. They leave the loyalty programs and the expense of implementation to the not-so-great companies. That being said, the Chief Marketing Officer (CMO) Council surveyed customers to find out how they feel about loyalty programs. The results are interesting but not surprising. Here are some of the findings from the survey.
1. 69% of the respondents said most of their own experience with such programs has been "pretty good."
2. 10% were very satisfied.
3. 21% were strongly motivated to come back for repeat visits.
4. 30% said it was a major factor in their decision making.

On the negative side they found:
1. 32% felt that the loyalty programs had little or no value.
2. 37% believed that the individual rewards had little value.

There are some generic concerns that are positive indicators that loyalty programs are still of interest according to the research firm Colloquy. For example,
1. 67% of consumers are involved in loyalty programs in 2009 compared with 57 percent in 2007.
2. Participation by young adults has increased 32 percent between 2007 and 2009.
3. Participation by women age 25-49 has increased 29 percent for the same period.

Another observation by Colloquy was that the average US household is enrolled in 14 loyalty programs but the typical household only uses (is involved in) 6.2 loyalty programs.

Customers were asked for the top three benefits they received from a loyalty program. The results are:
Greatest benefit - discounts and savings (66% of the respondents)
2nd greatest benefit - better deals and offers (43% of the respondents)
The rest of the top five are:
3rd free products or premiums (38%)
4th perks and privileges (36%)
5th cash back (33%)

Far down the list were the issues that most loyalty programs seem to focus; namely, "recognition and appreciation" was only mentioned 18% of the time and "more individualized attention was mentioned 12% of the time.

The most often mentioned concern by customers was that they received too much spam email and junk mail. When things go bad, customers will opt out of a loyalty program. In fact 54 percent of the respondents said they had left a loyalty program after poor product or service experiences.

The bottom line is that customers perceive the benefits of loyalty program in terms of cash or rewards. While customers do like to be recognized and not considered a stranger, they sign up for a loyalty program for the financial benefits.