Easy to say, hard to measure. Economists talk a lot about switching costs and assume they are all the same and all bad. Marketers are less judgmental and generally more positive – keeping your customers from leaving to move to another supplier is a good thing. Sadly, customer switching costs are hard to measure in ways that can produce data we can use to learn more about how they actually work. In a recently published paper we figured out a way to do just that using VoC data and creating measures of “excess loyalty” – repatronage intentions not explained by a customer’s satisfaction. We prove seven ways from Sunday (we love you academic paper reviewers) that this provides a very good proxy measure for the presence and magnitude of customer switching costs and is significantly better at predicting customer switching behavior than alternatives currently used by firms to identify “at risk” customers.
Using this data allows us to shed new light on the phenomenon and its consequences in a couple of studies in financial services using real customer data in a fieldwork study. Turns out there is merit in both economist and marketer perspectives on this. We identify three segments of customers in a financial services firms customer-base using the VoC measures – "rationals" (their future purchase intentions match their satisfaction), "stayers" (their future purchase intentions are higher than can be explained by their satisfaction), and "variety-seekers" (they do not intend to repurchase despite their level of satisfaction). Using subsequent purchase behavior and customer-level profitability data we show that stayers grow their relationship with the supplier and become more profitable while rationals and variety-seekers do not. So far, so good. But economists still see the existence of "stayers" (customers with higher switching costs) as a negative thing while marketers see it as a positive. Can they both be right?
Seems they can. Not all switching costs are equal (sorry economists). We identify customers in the data who are happy to stay with their current provider even when there may be better alternative suppliers they could switch to ("elective stayers") vs. those who stay despite being unhappy with the supplier because the pain and cost of switching is too great ("prisoners"). When we re-run our analyses, all of the future relationship growth and profitability growth from switching costs we observed in our initial study comes from the happy elective stayers, none from the prisoners. So, the moral of this empirical story is clear. Taking your customers prisoner by making it painful for them to leave doesn’t help you but making customers want to stay because they really like you does.
You can read all the gory details in
Bhattacharya, Abhi, Kelly Hewett, Neil A. Morgan, & Lopo L. Rego (2024), “Unlocking the Predictive Value of Excess and Deficit Customer Patronization Intentions,” Journal of Service Research, 10946705241247172.(
You can download it here: https://neil-a-morgan.com/wp-content/uploads/2025/05/Bhattacharya-Morgan-Rego-Hewett-JSR-2024.pdf
You sick of post-covid prognosticators yet?
Monday, May 4th, 2020
My email is getting filled up with teasers for “reports”, invitations to webinars, podcasts and the like all offering to share insights with respect to fundamental shifts in the consumer and business landscapes that will become the “new normal”. For those reports, etc. that are data-based (either survey or observational), it seems unlikely that what we observe right now will be representative of much or a good place to project forwards from. Much better to look at pre-covid trends and see which have accelerated/decelerated over the past two or three months. Then you have multiple data points to work with as a starting point for forward projections instead of one single “non-normal” observation.
