I have come across a few cases of organizations attempting to measure customer loyalty in transactional (event-based) CEM programs. As you would expect, all of them utilize the “Likelihood to Recommend” question, specifically “How likely is it that you would recommend Company XYZ to a friend or colleague?”
Let’s try to understand what is going on in this case and what the potential risks might be.
Although there is a considerable amount of research devoted to the concept of customer loyalty, this is what it comes down to: Customer loyalty exists when a company can retain their customers long enough to retaliate against competitive offerings before the customer “jumps ship”, improve product/service features, correct errors and resolve outstanding issues. Loyal customers will give you a second (and potentially a third) chance, risking the costs of doing so by trusting that your company will deliver. A “just satisfied” customer won’t.
By definition, loyal customers are more passionate about your organization and its products and services and, as a result, they tend to talk more about it. Spreading the news via word of mouth, to some extent, as a natural extension of your marketing/advertising campaigns.
Research goes on to show that customer loyalty is the result of the sum of a customer’s experiences (the branded experience), formed over the long term of his or her engagement with your organization. In simple words, companies cannot build true customer loyalty if they perform well (or even excite their customers) in a single transaction. They will need to excite their customers over and over again as they engage in repeat business transactions. Over time, a consistent, customer experience will result in higher customer tolerance to occasional errors, and/or falling behind the competition in terms of features, price or both.
Said another way, a sign of a strong brand is customer forgiveness.
Accordingly, when an organization decides to measure the level of loyalty in its client base, it would make sense to obtain feedback from customers who have been engaged in business repeatedly, not just one time. Depending on the nature of your business and industry, this could mean reaching out to customers who have been around for a period of time, long enough at least to allow for multiple business transactions, often 6-12 months or longer. Obtaining feedback from these customers would represent a more trustworthy indicator of customer loyalty.
Upon the completion of the CEM program, you can safely argue that Customer XYZ is loyal because he has engaged in, for instance, seven business interactions over the course of the past twelve months and, as a result of the sum of the his experiences, he gave a “likelihood to recommend” rating of 9/10. You can trust that Customer XYZ will excuse an occasional error in your product or outage in your service so that when a competitor pops up with a more attractive value proposition, he will stick with you for a reasonable amount of time, at least enough to give you the opportunity to respond with an offer of your own.
On the other hand, attempting to measure customer loyalty based on a single business transaction will almost certainly generate very high variation of results, which will ultimately lead to inaccurate and untrustworthy feedback. When asking a customer to rate his or her likelihood to recommend your company based on a single transaction, you tie this answer, and thus your customer loyalty rating, to that transaction. This contradicts the very nature of the customer loyalty concept altogether. Let’s assume the very first transaction went well. Customer feedback will point to a very high likelihood to recommend, which will lead you to perceive the specific customer as loyal. Now, let’s assume the second transaction did not go as expected. Customer feedback will point to low likelihood to recommend, which will lead you to perceive the same customer as not loyal. So, at the end of the day, should you count this customer as loyal or not? High recommend rating variation will ultimately prevent you from being able to trust customer feedback and incorporate it to strategic decisions.
To summarize, customers become loyal over the course of multiple business transactions with your organization, not based on a single interaction. Organizations build customer loyalty over the course of many months, or even years. Asking the recommend question, which has been designed to capture customer loyalty, in transactional programs does not generate trustworthy results because it ties a single transaction to a metric inherently based on multiple transactions.