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.
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.
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:
- T = Trust rating
- P = Promoter rating
- ST = Number of points on the Trust scale
- SP = Number of points on the Promoter scale
- Strongest Loyalty: The strongest zone of loyalty contains cases where both the Trust and Promoter attributes received the highest possible rating.
- Strong Loyalty: The next zone is where the loyalty index lies within 35% of both the Trust and Loyalty axis.
- Moderate Loyalty: The zone of moderate loyalty is where the index lies within 60% of the highest possible Trust and Promoter ratings.
- Weak Loyalty: The zone of weak loyalty lies within 90% of the highest possible Trust and Promoter ratings.
- 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.
 Heskett, Sasser, and Schlesinger The Service Profit Chain, 1997, New York: The Free Press, p 21