Loyalty Model – part 2

In the previous blog, the general form for the construction of a loyalty model was postulated.  A base equation hypothesized that loyalty could be described by measuring the strength of the relationship between the company and its customers.   A sub-model was proposed to show that the strength of the company-customer relationship could be explained by various factors.  In this blog, the two major components of the model will be discussed.

The two components that describe the company-customer relationship are those that strengthen of the relationship and those that diminish the relationship.

Factors that enhance and strengthen the company-customer relationship may be considered relationship builders; “satisfiers.” Satisfiers represent activities or involvements that yield positive experiences by the customer and also provide value to the company. In the service business, response time tends to act as a satisfier.  For example, when services are requested, the time to respond will strengthen the relationship between the customer the company as long as the response time meets or exceeds the customer’s expectation. Consistently meeting a customer’s expectation of response time for service has been shown to strengthen the relationship with the company. More discussion of satisfiers will be provided in a separate blog.

Factors that diminish the company-customer relationship may be considered “dis-satisfiers.” A dis-satisfier is generally not the opposite extreme of a satisfier. As an example, consider customers who frequent a fast food establishment. Customers expect a reasonable quality of food to be delivered quickly. If either the quality of the food or the service delivery time does not meet the normal expectations, the customers may be disappointed but probably not dis-satisfied. However, if the restroom at the same fast food establishment has not been adequately maintained, many customers may refrain from returning to the restaurant due to a concern that lack of good hygiene in the restroom may be an indicator of lack of good hygiene in the kitchen. In this case, the quality of the hygiene in the restroom can be a dis-satisfier; but the hygiene quality of the restroom is surely not the major attraction of the fast food establishment and is not considered a satisfier. More discussions of dis-satisfiers will be discussed in a separate blog.

Company-customer relationships are not linear.  They are not a function of adding the satisfiers and subtracting the dissatisfiers, which is similar to the NPS metric when it subtracts the detractors from the promoters.  This simplification of the loyalty model makes no sense since it is equally equating positive values (satisfiers) to negative values (of the satisfiers or possibly dissatisfiers).  Beyond the basic NPS score, many analysts mistakenly assume that the relationship between each component of the model has a linear relationship with the strength of the relationship. 

As we examine the components that increase the value of the customer relationship do not assume that each component is independent and has a linear relationship with the strength of the customer relationship. There will be some satisfiers that may increase the strength of the customer relationship dramatically, whereas other satisfiers will only provide an incremental increase of improvement in the strength of the relationship.

The same logic also holds true when we discuss the dis-satisfiers in the future blogs. Always challenge the assumptions! Be curious.   

Building a Loyalty Model

The kind of loyalty model I will be discussing in the next several blogs is a basic business model that is often used in strategic management. The basic premise of the model is that customer loyalty leads to profitability. The purpose of this model is to develop an understanding of the business components that contribute to the loyalty of the customers.

In this blog I will describe the general loyalty model and a sub-model which feeds into the general loyalty model.

The hypothesis upon which the loyalty model is based is that loyalty is a direct function of the strength of the relationship between the company and its customers. Logically this makes sense since a strong relationship between the company and its customers should produce greater loyalty than a weak relationship. The heart of the loyalty model is built around understanding the components that make up the strength of the relationship. There are many variables that contribute positively or negatively to the strength of the relationship. Recent experiences between the customer and company would be an obvious component of the strength of the relationship.  A single experience between customer and the company may not significantly influence the strength of the business relationship. In fact, there is a “zone of tolerance” that ranges from minimally acceptable to extremely exceptional. As long as the other factors exist even an incident that was less than minimally acceptable may not change the strength of the relationship. Of course, this assumes that any negative experience may be resolved by the company. Otherwise, there may indeed be a negative change to the strength of the relationship between that individual customer and the company.

Therefore the simplest form of the loyalty model is as follows:

            Loyalty = constant x (strength of the relationship).

The value of the constant associated with the strength of the relationship will vary with respect to product, geography, and possibly other variables. Thus, a company with multiple products may have a different strength of relationship with their customers based solely on the product. An example would be the strength of the relationship between the Apple iPhone and its customers versus the strength of the relationship between the Apple iPad and its customers. iPhone users are known to have a very strong loyalty connection with Apple; whereas, iPad users may not have the same level of loyalty.

The strength of the relationship (loyalty) is another way of describing the business relationship between the company and its customers. The model proposed would consider variables such as level of satisfaction, recent experience, product quality, commitment to the relationship by either the company or, the customers, and the bonds may exist between the company and its customers.

The bonds that exist between the company and its customers may fall into a number of categories; such as, legal bonds (contracts), technology bonds (shared or licensed technology), knowledge bonds (shared information), social bonds, geographical bonds, cultural or ethnic bonds, and economic bonds. There may be other bonds as well.  The fact is there are many bonds that may exist and give strength to the relationship between the company and its customers (such as loyalty points).

The general form of the model for the strength of relationship is:

            S (Strength of relationship) = function of (recent experience, level of satisfaction, product     quality, service quality, commitment to the relationship, and appropriate bonds).

This model presents a challenge of quantifying each variable and assessing the strength of the relationships between each variable. This model can be simplified by assuming minimum interaction between the variables contributing to the strength of the relationship and assuming the variables are linearly related.

This discussion will be continued in the next blog where a simplified version of this loyalty model will be presented with an example. At this point, a simple loyalty model is presented that includes most of the significant variables that are usually included in loyalty discussions. Be curious.

Another look at your customers

In my previous blog I discussed the tyranny of the urgent and why is such a limiting perspective in understanding customers. I closed the blog by pointing out that the focus should always be on all your customers not just the ones who have urgent concerns. In this blog I will point out several techniques which may be useful in understanding the needs of our customers.

Several years ago I was working with the company that had a very complex product which required significant service support. The concern of the company was that the users of the product were not the decision-makers but had significant influence about decisions regarding the product. The product was a complex computer that used very sophisticated software. The end users of the product were scientists. The computer was managed by the IT department. Neither the users of the product nor the IT department made the decisions regarding the product. The decisions were made at a management level above the IT department and the users department (which included all the scientists).

The challenge with this assignment was that there was no department that was responsible for evaluating the performance of the product. Each of the three groups (users, IT, and management) were involved in the decision-making process regarding the performance of the computer. The measure of satisfaction for any one group is not sufficient to understand how well the product is meeting the needs of the customer. This product required a multidimensional model of customer satisfaction that incorporated satisfaction metrics from each of the three departments. The objectives of the metrics were to assess the satisfaction with each organization department and evaluate any inconsistencies in the measures of satisfaction between them. In other words, although satisfaction of each department was important, it was equally important to determine if there were inconsistencies or discrepancies between the scientists, IT department and upper management.

While the metrics for a current customer is important, and is the basis of most customer surveys, some additional areas of interest include the following:

1.       1. measurement of concerns from lost customers,

2.       2. specific measurements directed toward ultra-valuable customers, and

3.       3. measurement of the gaps between customer expectations and the performance delivered.

Reflecting back on the previous blog, the intention here is to provide some areas of interest beyond the basic customer satisfaction survey. The previous blog pointed out the need to separate normal survey responses from responses to customers with urgent needs for support. Curiosity is the watchword for surveys. There are many dimensions of involvement between the company and its customers. Not all contacts between the customer and company are from the end-user.

As an example, consider a previous assignment with another technology company led to the surprising conclusion that the Accounts Receivable department did not have customer skills training and was the primary reason for customer irritation. In fact, the Accounts Receivable department put IBM on credit hold because their payment was overdue. Needless to say IBM was not happy with this treatment.

If your curiosity is great enough, you may find more connections between your company and the customer that may be worth exploring. You may also find that many of the employees involved in those connections do not have customer management skills training.  Be Curious!

Who are you listening to?

The “tyranny of the urgent” is a phrase that is commonly used when working in a service environment.  The phrase reminds people that “urgent” requests often take priority over “important” requests.  Service managers often find themselves in the role of “firefighting” - putting out “the fires” of customer complaints.  Before the manager realizes it, the firefighting consumes all of his time. The executives will note what a wonderful job the service manager is doing by managing customer complaints.

In this situation the only customers whose voices are heard are those who are complaining. The large and small customers who were not complaining are overlooked. When the urgent requests consume most or all of the service manager’s time, there is little time remaining to consider what is not urgent.

In his book Exit, Voice and Loyalty, Albert Hirschman argues that unsatisfactory conditions (such as service problems) may lead customers to (1) to exit or leave the company without trying to resolve an issue, or (2) speak up and try to remedy the situation.  The “nice” customer will exit without telling you why and never return.   A “good” customer, on the other hand, is willing to speak up and tell you what is wrong and is willing to work with you to resolve an issue. A “good” customer is really your best consultant because he will tell you exactly what is wrong.

It is often said that the urgent requests are like customers pounding on the chest of the service providers and managers while the other customers who do not require immediate assistance or attention are ignored.  The fact is that customers’ lack of urgency requests may actually have more important information to share with the company. Many companies spend too much time listening to the urgent customers while ignoring other customers.

Urgent needs of some customers inhibit service managers’ time to anticipate, plan and develop future service requirements. Too many managers spend most of their time in a reactive mode. To get beyond the “tyranny of the urgent,” companies, especially service organizations, need to fundamentally change the way in which they listen to customers.

From a strategic perspective, a balance is needed between urgent problems and important problems. The urgent solutions generate “at-a-boys” for the service personnel while the non-urgent solutions pave the way for long-term success.  A simple first step to managing the “tyranny of the urgent” is to set aside a specific amount of time each week or each month to solve the problems of how to increase productivity, review service skills, parts inventory, and technology.

The bottom line is to focus on the needs of all your customers.  There are three tactics that will provide the first steps to leave the “tyranny of the urgent”.

Step one: Conduct interviews with customers who have left your company.

Step two: Engage those customer segments that are not being addressed by those customers with urgent needs.

Step three: Understand why customers left you in the past. 

Be curious! You may discover/uncover challenges and opportunities you never realize existed.

A Different Perspective

I found this short comment from the Brisbane, Australia newspaper.  I am not sure when it was published –but it is reasonable to assume this aspect of loyalty is still around.  I doubt this has happened only once – it may be more pervasive than we want to believe.  There is a naïve perspective that perfection of loyalty programs is near – maybe not.

Be a loyal customer, be taken for a fool

I was a passive consumer, believing loyalty is virtuous and appreciated by business. Having chosen products and providers I stick with them, anticipating that long-term allegiances will have their rewards.

I have learnt, however, that a more apt description of my conduct was ''mug punter''.

For more than 15 years I have happily coughed up for cable internet that served its purpose adequately. The cost disappeared painlessly from our bank account each month and we rarely troubled our allotted usage limitation.

Then we did. On the last day of the month our internet connection slowed to a crawl. Thinking it a technical malfunction, I rang a fellow at an Indian help desk only to learn that I had been ''throttled back'' for the day, having finally burst through a 12-gigabyte glass ceiling.

After 15 years of good behavior I thought that I might have earned a little leeway. Why, even the RTA and the courts have a heart. Perhaps a small draw down from the huge bank of unused gigabytes built up over the years.

I started to look around. My limit had become minuscule with the passing of the years and technological advances. Non-customers were being tempted with gigabytes beyond imagining, at breakneck speeds, for a pittance. Whither my perceived reward for loyalty?

I spoke to another friend in India. He immediately more than quadrupled my limit, increased my speed fivefold and knocked $10 a month off my bill.

Rather than feeling a surge of gratitude, I felt cheated. They had been ripping me off, probably for years. I decided to test all the waters in which I swim. My gas and electricity tariffs dropped. My insurance renewal premium quote was instantly reduced. All goodwill I might have felt towards those I once thought of as preferred suppliers evaporated. Worse, I now have ill will towards those who took advantage of my loyalty.

I now realize one can't sit idly by and expect anyone to realize the absolute value of a lifetime customer. So I whine and moan and price check. It's a waste of my time and ultimately an expensive way for business to do business, but at least I know that if it chews up the gigabytes, I only have to blast a call center somewhere to rectify the problem.

Illegal Loyalty Programs

What could be illegal about a customer loyalty program? It seems that almost every business has some form of loyalty program.  There are loyalty programs for grocery and clothing stores, airlines, and just about every other business that would like to create some form of relationship (loyalty) with their customers. An article written by Tim J. Smith, PhD identifies a dimension of customer loyalty that the government finds illegal.

A particular case noted in his article is Eaton Corporation that was found guilty of antitrust on the grounds that Eaton’s loyalty program harmed their competitor in 2014. Apparently Eaton was found guilty of improper pricing because they held 80% market share that totally dominated only a few competitors. In addition the pricing structure included rebates which encouraged their customers to continue to buy from Eaton and not from their competitor. The Eaton loyalty program required customers to use a high percentage of the Eaton transmissions, and to require customers to identify Eaton as their preferred transmission supplier while also encouraging their customers to price Eaton transmissions below those manufactured by its competitors.

Apparently the loyalty program itself is not illegal; however the fact that Eaton was a dominant provider in the market impacted the competitors that had much smaller market shares. It turns out that Eaton was not found to be selling their transmissions below cost but the program did harm Eaton’s competitors by locking in their (Easton’s) customers which effectively limited the market. The damage as a result of this antitrust lawsuit is expected to exceed more than $1 billion.

The key ingredient to defining a loyalty program as being illegal is that the company has a dominant market position and effectively controls the market. If your company is a giant in the marketplace with a significant market share, it is certainly susceptible to an antitrust lawsuit. Dr. Smith points out that there is no clear definition of what level of market share makes you a giant in the market. Basically, if the government can determine that your loyalty pricing program has done harm to a competitor, it may be vulnerable.

A similar lawsuit was brought against Intel in 2009. Intel’s smaller competitor AMD was paid $1.25 billion in damages. Intel’s loyalty program was based on requiring customers to use a high percentage of Intel chips in their products. Intel was not selling their chips below cost; however, since Intel held a dominant market share of 80% in the global microprocessor market with its considerable influence on the market, this was deemed sufficient to warrant the lawsuit and fine.

The bottom line is for companies that dominate the marketplace to be very careful and include a legal review of their loyalty program. For those who do not dominate there does not appear to be any legal constraints on your loyalty program or the how it is run unless the loyalty program would lead to selling your equipment or services below cost.  For example, if your loyalty program includes credit for a trade-in, the combined purchase price minus the trade-in may lead to a net of selling below cost which continues to be illegal in the United States.  Otherwise, the market is yours for the taking.

Words have value too!

A lot of time and energy is spent quantitatively analyzing the results of surveys. The survey may be based on metrics such as customer satisfaction, NPS, customer effort, or customer experience. This quantitative analysis may take on many dimensions of statistical methodology. However, the comments that are made associated with the individual scores are seldom included in the statistical quantitative analysis. There are several methodologies available for including the analysis of the comments (referred to as content analysis) with the numerical analysis.  It can be a worthwhile endeavor to compare the results of the quantitative and content analyses. 

A McKinsey study suggests that positive emotions correlate strongly with profits. The study indicated that after a positive customer experience more than 85% of the customers purchased more and after a negative experience more than 70% purchased less.

In this blog two different types of qualitative analyses are discussed; namely, descriptive measures of word usage and content analysis (which is also referred to as sentiment analysis).

Analysis of word usage includes grouping for individual words or word groups into categories. Words or word groups are usually grouped into three categories; namely, negative comments, positive comments or general comments. If the comment relates to a specific activity then those comments will be grouped by specific survey question(s). Within this grouping of word usage, descriptive measures provide a complementary presentation to the quantitative results. The descriptive measures are limited primarily to the number of comments associated with a specific question or questions on the survey.

The general hypothesis is that the descriptive measure of positive comments will be similar to that measured quantitatively. Obviously, the hypothesis is also extended to the negative remarks which should be reflected by the negative scores on the survey. This qualitative procedure does not interpret the intensity of any feelings implicit in the wording. In adition, the words will not pick up such subtleties as sarcasm or other emotions.

Content analysis (Sentiment analysis) is used to determine how customers feel with respect to a product or service. The primary purpose of sentiment analysis is to capture strong feelings that may be embedded in emotionally laden words. The two dimensions of sentiment analysis identify the feelings as being either positive or negative and the individual words or word phrases can be used to calibrate the magnitude of the sentiment.

Content analysis for product support is generally focused on the statistics associated with word usage (positive and negative). Typically the primary goal of content analysis is to validate the quantitative aspects of the survey metrics. Hence, the need for sentiment analysis is often limited. Only when word usage analysis indicates conflicting results with the quantitative analysis does sentiment analysis become a worthwhile addition to add to the perspective of the customers.

Too often surveys are conducted to understand the strengths and weaknesses of product support. The comments included with surveys are often reviewed individually but rarely analyzed in sufficient detail to provide verification of the quantitative measures taken.

The bottom line is that qualitative analysis is often overlooked when examining the relationship between customers and the products and services provided to them by the company. It may be time to reconsider what aspects of survey analysis should be included. It is likely that the best answer is both quantitative and qualitative analyses provide the greatest insight about the customers.

A note to remember is that feelings persist much longer than the score presented on the survey. An unkempt restroom at a restaurant can have a lasting effect on the customers that use it. It may be the only reason the customer never comes back. An emergency service provided beyond expectation may create a customer for life. Emotions are powerful.

Why bother with loyalty?

Some research suggests the customer loyalty may not be enough. A study was done by Timothy Keiningham, Lerzan Aksoy, Alexander Buoye, and Bruce Cooil that has some interesting findings. They performed a two-year longitudinal study of more than 17,000 consumers and examining purchases in more than a dozen industries in nine countries. According to the study, they asked a broad range of questions and purchase histories including satisfaction and loyalty measurements. Their analysis was based on the largest and most rigorous of its kind of survey at the time which indicated an interesting correlation; namely, the rank consumers assigned to a brand relative to other brands in the industry can be used as a predictor of “share of wallet.” They refer to the results of this outcome as the Wallet Allocation Rule (published by Wiley, 2015).  The details of survey methodology, survey questions, and statistical tools used in the analysis were not available.  This blog is based on their article published in the Harvard Business Review (which should be sufficient evidence that the methodology meets Harvard’s criteria for a valid survey).

Here are two of the findings that should be considered.

1.     Correlation between changes in satisfaction or intention to recommend and “share of wallet” was 0.1 – suggesting that satisfaction has little impact on changes in “share of wallet.”

2.     Correlation between changes in “share of wallet” score using their metric compared with a customer’s actual measured “share of wallet” was 0.8.

The Wallet Allocation Rule is proposed by the authors to be a better metric than customer satisfaction or NPS. In the survey they asked the consumers to assign a rank of the brand relative to other brands that the customers were using. The result was that ranking with respect to competitors was demonstrated as being more important than customer satisfaction when it comes to increasing “share of wallet.” The point they make is that the parameters which drive changes in “share of wallet” may not be the same parameters that drive the change in customer satisfaction.

This methodology is particularly useful from a sales perspective.  However, this methodology has limited usefulness when operating in a supportive environment with limited, if any, competition of other brands of products (such as occurs with product support).

The evidence from the survey provides a strong case that ranking in the marketplace has more value than customer satisfaction when compared with the competition.

A secondary consideration is the impact of ranking on loyalty. The implication of loyalty follows from focusing on the parameters that have the greatest impact on rank. If the consumers are increasingly drawn to a particular brand, it is not unreasonable to believe there will be a component of loyalty that will follow that move of higher rank with the brand.  The assumption that ranking has a greater long-term impact on loyalty that customer satisfaction needs further investigation. 

  

The bottom line is that “share of wallet” may be the best metric when focused on increasing ranking with respect to competition.  Although this study provides valid statistical support, its value is diminished when used as a metric for product support where “ranking” with competition has little meaning.

Whoever heard of bad loyalty?

Did you ever imagine that there could be an issue with customer loyalty? Could there be a time when customer loyalty may not be the best answer? When we think of customer loyalty we often think of it as a way to help a company survive difficult market conditions. We think of customer loyalty synonymously with the phrase customer retention. Many marketing personnel will support the notion that selling to a loyal customer is more cost-effective than creating a new customer.

One of my favorite phrases is that customers are what make paydays possible. So to think that customer loyalty might have a negative component is surprising. Tim Keiningham and Lerzan Aksoy wrote a note several years ago that discussed the negative component of customer loyalty.  This blog attempts to capture the essence of their note.

What we would like our loyal customers to be is customers who can clearly understand why it is important to support us during the good times and the bad. This clearly occurs most often when the customers can differentiate our company’s offerings of products and services from a competitor. They will know what the company stands for.

So, what kind of loyalty is bad loyalty? The authors have suggested that price driven loyalty is the lowest form of loyalty. They make the point that the company is not offering any differentiated value to customers. It also implies the price-driven loyalty does not bring levels of profitability that often occur when selling to loyal customers.  Many marketing studies confirm that the cost of selling to a loyal customer is usually less than the cost of acquiring a new customer. Hence a price-driven loyal customer is more likely to provide a lower margin/profit to the company.

The obvious conclusion is that price-driven loyalty is not really loyalty at all. Customer loyalty is created when the company can provide products and services that are differentiated from its competition. Thus the customer finds the value derived from this relationship better meet its needs.

The bottom line is that real customer loyalty is good loyalty only when the company provides consistent differentiation of its products and services from the competitors. The notion that price creates loyalty does not meet the standard for long-term differentiation. Yes, there is bad customer loyalty.