Tag Archive | Customer Loyalty

Customer Loyalty Is an Illusion

A colleague of mine is fond of saying there is no such thing as customer loyalty. He argues loyalty…true loyalty…loyalty through thick and thin – requires an irrational customer, one who will stay with you regardless of the outcome.

The fact of the matter is customers are rational. What we perceive as loyalty is an illusion, rather it is actually the product of an ongoing calculation each customer makes to either initiate or maintain a relationship with a provider. This is the customer value equation.

Customer Value Equation

The customer value equation is simply the ratio of the benefits of a product or service over the costs of the product or service. If this ratio is greater than 1, the customer will act as if they are loyal. If this ratio is less than 1, the customer will behave as if they are disloyal.

The numerator in this equation contains all the possible benefits associated with the product or service. These include the obvious, such as the quality of the results and the process quality. However, they also include less obvious intangible benefits. The owner of a luxury car, for example, may perceive an intangible benefit of status associated with this luxury vehicle.

The denominator contains the sum of all the costs associated with the product or service. Again, the obvious costs are price. However, there may be other acquisition costs, such as installation or maintenance. Additionally, this should include intangible costs such as potential risk of switching.

As customer experience researchers, we are constantly considering the customer value equation to provide context from which to interpret our research.

Furthermore, understanding the customer value equation gives managers a rational framework to make investments in product, positioning, price and place to best match their offering with their customers’ value equation.

How might a manager use the concept of the customer value equation to manage the customer experience?


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Not All Service Attributes Are Equal: Retail Bank Transaction Drivers of Loyalty

Research has determined the business attribute with the highest correlation to profitability is customer loyalty.  Customer loyalty lowers sales and acquisition costs per customer by amortizing these costs across a longer lifetime – leading to some extraordinary financial results.  In one study of the retail banking industry, a 5% increase in customer loyalty translated into an 85% increase in profits.[1]

Customer loyalty is driven by the entire relationship with bank.  Image, positioning, products, price and service all mix together in the customer’s’ value equation as customers make a continual decision to remain loyal.

What customer service attributes drive customer loyalty?

This article summarizes research into specific transaction service attributes with the intent of identifying which transaction attributes drive customer loyalty, and provides an analytical tool to help managers determine which attributes will yield the highest potential for ROI in terms of improving customer loyalty.

In order to determine transaction attributes which drive customer loyalty, Kinesis surveyed bank customers who had recently conducted a transaction at a branch.

With respect to the transaction, customers were asked to rate the following service attributes:

  • Professional dress
  • Branch cleanliness
  • Prompt greeting
  • Greeting made customer feel welcome
  • Dependable and accurate
  • Prompt service
  • Willingness to help
  • Job knowledge
  • Interest in helping
  • Best interests in mind
  • Actively listened to needs
  • Ability of bank personnel to help achieve financial needs
  • Desire of bank personnel to help customers achieve financial goals
  • Commitment to community

The next step in the research is to capture a measurement of loyalty against which to compare these attributes.

Measuring customer loyalty in the context of a survey is difficult.   Surveys best measure attitudes and perceptions. Loyalty is a behavior based on rational decisions customers make continually through the lifecycle of their relationship with the bank.  Survey researchers therefore need to find a proxy measurement to determine customer loyalty.  A researcher might measure customer tenure under the assumption that length of relationship predicts loyalty.  However, customer tenure is a poor proxy.  A customer with a long tenure may leave the bank, or a new customer may be very satisfied and highly loyal.

Measuring customer loyalty in the context of a survey is difficult.   Surveys best measure attitudes and perceptions. Loyalty is a behavior based on rational decisions customers make continually through the lifecycle of their relationship with the bank.  Survey researchers therefore need to find a proxy measurement to determine customer loyalty.  A researcher might measure customer tenure under the assumption that length of relationship predicts loyalty.  However, customer tenure is a poor proxy.  A customer with a long tenure may leave the bank, or a new customer may be very satisfied and highly loyal.

Kinesis proposes a model for estimating customer loyalty based on two measurements: likelihood of referral and customer advocacy.  Likelihood of referral captures a measurement of the customer’s likelihood to refer the bank to friend, relative or colleague.  It stands to reason, if one is going to refer others to the bank, they will remain loyal as well.  Because customers who are promoters of the bank are putting their reputational risk on the line, this willingness to put their reputational risk on the line is founded on a feeling of loyalty and trust.  This concept of trust is perhaps more evident in the second measurement,: customer advocacy.  Customer advocacy is captured by measuring agreement with the following statement: “My bank cares about me, not just the bottom line.”  Customers who agree with this statement trust the bank to do right by them, and not subjugate their best interests to profits.  Customers who trust their bank to do the right thing are more likely to remain loyal.

Kinesis uses likelihood of referral, hereafter labeled “Promoter,” and customer advocacy, hereafter labeled “Trust,” to calculate an estimate of the customer’s loyalty.  Imagine a plot where each customer’s Promoter score is plotted along one axis and the Trust score plotted along the other.  Using this plot we can calculate the linear distance between the perfect state of the highest possible Trust and Promoter ratings.  This distance yields a loyalty estimate for each customer, where the lower the value, the higher the estimate of loyalty – low values are good.[i]

Trust Promoter Plot

See Using Promoter and Trust Measurements to Calculate a Customer Loyalty Index for a complete description of this methodology.

Calculating a loyalty index has value, but limited utility.  A loyalty index alone does not give management much direction upon which to take action.  One strategy to increase the actionably of the research is to use this index as a means to identify the service attributes that drive customer loyalty.  Not all service attributes are equal; some play a larger role than others in driving customer loyalty.

So…how does the research determine an attribute’s role or relationship to customer loyalty?  One tool is to capture satisfaction ratings of specific service attributes and determine their correlation to the loyalty statistic.  The Pearson correlation coefficient is a measure of the strength of a linear association between two variables.

Comparing the correlation of the above service attributes to this loyalty estimate yields the following Pearson Correlation for each attribute:

Pearson Coefficient

Want to help me achieve financial goals

-0.69

Commitment to community

-0.66

Ability to help achieve financial goals

-0.64

Best interests in mind

-0.60

Greeting made customer feel welcome

-0.56

Interested in helping

-0.56

Willing to help

-0.55

Prompt service

-0.51

Actively listened to needs

-0.50

Prompt greeting

-0.49

Dependable and accurate

-0.45

Professional dress

-0.42

Knew job Job knowledge

-0.41

Branch attractive

-0.39

Branch clean

-0.37

Note the Pearson values are negative; the loyalty estimate is an inverse, where lower values indicate a stronger estimate of loyalty.  As a result the stronger negative correlation translates into a correlation to our estimate of loyalty.

The four attributes with the highest correlation to loyalty are:

  1. Want to help me achieve financial goals,
  2. Commitment to community,
  3. Ability to help achieve financial goals, and
  4. Having my best interests in mind.

Two common themes in the top-four attributes are empathy and competence.  Bank customers value relationships with banks that care about their needs and have the ability to satisfy those needs.  Again, customer loyalty is driven by the entire relationship with bank.  However, in terms of transactional service, customers clearly value empathy and competency and will reward banks who deliver on these two attributes with loyalty.


[i] The mathematical equation for this distance is as follows:

Loyalty Index Equation

Where:

T = Trust rating

P = Promoter rating

ST = Number of points on the Trust scale

SP = Number of points on the Promoter scale

 


[1] Heskett, Sasser, and Schlesinger The Service Profit Chain, 1997, New York: The Free Press, p 21


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Using Promoter and Trust Measurements to Calculate a Customer Loyalty Index

Research has determined the business attribute with the highest correlation to profitability is customer loyalty.  Customer loyalty lowers sales and acquisition costs per customer by amortizing these costs across a longer lifetime – leading to some extraordinary financial results.  Depending on the industry, a small increase in customer loyalty (5%) translates into a 25% – 85% increase in profits.[1]

Customer loyalty is driven by the entire relationship with the company.  Image, positioning, products, price, cost of switching, and service all form a value equation each customer applies in their continuous decision to remain loyal.

Measuring customer loyalty, however, in the context of a survey is difficult.   Surveys best measure attitudes and perceptions. Loyalty is a behavior based on rational decisions customers make continually through the lifecycle of their relationship with the company.  Customer experience researchers therefore need to find a proxy measurement to determine customer loyalty.  One might measure customer tenure under the assumption that length of relationship predicts loyalty.  However, customer tenure is a poor proxy.  A customer with a long tenure may leave the firm, or a new customer may be very satisfied and highly loyal.

Kinesis has had success with a model for estimating customer loyalty based on two measurements: likelihood of referral and customer advocacy.  Likelihood of referral captures a measurement of the customer’s likelihood to refer the company to a friend, relative or colleague.  It stands to reason, if one is going to refer others to the bank, they will remain loyal as well.  These promoters are putting their reputational risk on the line founded on a feeling of loyalty and trust.  This concept of trust is perhaps more evident in the second measurement: customer advocacy.  Customer advocacy is captured by measuring agreement with the following statement: “The Company cares about me, not just the bottom line.”  Customers who agree with this statement trust the firm to do right by them, and will not subjugate their best interests to profits.  Customers who trust the company to do the right thing are more likely to remain loyal.   Trust Promoter Plot

Kinesis uses likelihood of referral, hereafter labeled “Promoter” and customer advocacy, hereafter labeled “Trust” to calculate an estimate of the customer’s loyalty.  Imagine a plot where each customer’s promoter score is plotted along one axis and the trust score plotted along the other.  Using this plot we can calculate the linear distance between the perfect state of the highest possible trust and promoter ratings.  This distance yields a loyalty estimate, where the lower the value, the higher the estimate of loyalty – low values are good.  The mathematical equation for this distance is as follows:

 Loyalty Index Equation

Where:

  • T = Trust rating
  • P = Promoter rating
  • ST = Number of points on the Trust scale
  • SP = Number of points on the Promoter scale
 Kinesis’ experience plotting these indices, across a variety of scales, typically yields five zones of loyalty defined as follows:Loyalty Ranges
  1. Strongest Loyalty: The strongest zone of loyalty contains cases where both the Trust and Promoter attributes received the highest possible rating.
  2. Strong Loyalty: The next zone is where the loyalty index lies within 35% of both the Trust and Loyalty axis.
  3. Moderate Loyalty: The zone of moderate loyalty is where the index lies within 60% of the highest possible Trust and Promoter ratings.
  4. Weak Loyalty: The zone of weak loyalty lies within 90% of the highest possible Trust and Promoter ratings.
  5. Weakest Loyalty: The zone with the weakest loyalty are cases where one or both of the Trust and Promoter scores are less than 90% of the highest possible for Trust and Promoter..

Given that for many industries the business attribute with the highest correlation to profitability is customer loyalty; it is incumbent upon survey researchers to gather a measure of customer loyalty as part of their customer experience measurement.  Kinesis’ approach of calculating a loyalty index based on “would recommend” and “customer advocacy” ratings has proven to be a useful tool for segmenting customers by an estimate of their loyalty.  The next step in this analysis is to put this segmentation to work identifying which service attributes will yield the most ROI in term of driving customer loyalty.

Next Article: Using Gap Analysis to Put Loyalty Index into Action


[1] Heskett, Sasser, and Schlesinger The Service Profit Chain, 1997, New York: The Free Press, p 21


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The Shape of Satisfaction

Measuring satisfaction with a rating scale virtually always creates a very distinctively skewed curve, such as the one below, where approximately 85% of the responses are split between the top-two responses (4 and 5), and the remaining 15% trail off to the bottom end of the scale.  This is what I like to call “The Shape of Satisfaction.”  The distribution illustrated below yields an average rating of 4.2.  Typically, in satisfaction measurement, we see average ratings in the 4.2 to 4.3 range.

Shape of Satisfaction

As a point of comparison to other providers, if we were to ask the same respondents to compare their satisfaction with the company to that of other providers with which they do business, we would typically get a normal distribution similar to the following – where an equal number of respondents say their satisfaction is higher or lower compared to other companies they do business with.

Satisfaction Compared to Other Providers

Therefore, a typical satisfaction rating in the 4.2 to 4.3 range is normal and does not necessarily represent a source of competitive differentiation.

Furthermore, when satisfaction data is compared to customer loyalty data, research has observed for a five-point scale similar to the one to the left, customers who assign a rating of “4” are approximately 60% less loyal than customers who assign a rating of “5”.

Various theories attempt to explain the phenomenon of the skewed satisfaction curve.  Of these, I believe the most logical and intuitive explanation is a self-selection process.  First, being a customer is a self-selective process where dissatisfied customers are more likely to leave the company.  Second, companies generally satisfy their customers, because if they are not competitive in terms of satisfaction, they would be destroyed by customer attrition and cease to exist.

What are the implications of the shape of satisfaction?

First, there are significant implications for the interpretation of customer satisfaction data.  Simply having an average rating of 4.2 on a five-point scale does not necessarily denote strength.  Rather, managers should understand a comparative advantage does not necessarily exist until the average on such a scale exceeds 4.3.

It is important to understand how your customer satisfaction compares to your competitors. One way to collect such a comparative context is to ask customers to compare your service to that of your competitors.  This is much less likely to be skewed as the satisfaction curve, and will determine if your satisfaction is strong relative to your competitors.

The second implication is the importance of measuring loyalty rather than satisfaction only.  Loyalty can be measured via a number of means: likelihood of referral, NetPromoter, primary provider, etc.

Third, it is important to focus on the other extreme low end of the satisfaction curve.  Drill into the 15% of customers who are not satisfied, and attempt to adjust your product and service mix to shift even just a few customers up the satisfaction curve.  Even slight improvements in shifting these customers up the curve will have significant improvements in customer loyalty and profitability.  Again, each point increase on a five-point scale increases customer loyalty by 1.7 times, and depending on the industry, a 5% increase in loyalty equates to 25% to 85% increase in profitability.


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