Recent research has revealed that alerting customers to better options can actually backfire and increase churn.
A host of findings has examined how simply labeling an option as the default can reduce the likelihood that a person selects an alternative. This effect has been described as the ‘status quo bias’ or ‘default bias’, and has been explored in such domains as utility plan and investment portfolio selection (Hartman, Doane, & Woo, 1991; Samuelson & Zeckhauser, 1988). Perhaps most compellingly, the default bias has also been shown to affect organ donation rates. Johnson and Goldstein (2003) looked at how opt-in (i.e. organ donation is not the default option) versus opt-out (i.e. organ donation is the default option) programs affect donation. Consistent with the default bias, they found that across countries, and controlling for additional variables, opt-out systems increased organ donations by approximately 16%. In essence, people are often reluctant to deviate from the standard option.
By this point it might be clear that this bias will not always work in a person’s favor. The simple presence of a default may be sufficient to prevent people from seeking a preferable option. So what happens when a firm recognizes this, and takes measures to ensure that their customers are not suffering the negative consequences of this bias? One reasonable prediction might be that consumers would reward such efforts with increased loyalty and retention. But recent research highlighted in the Journal of Marketing Research (Ascarza, Iyengar, & Schleicher, 2016) shows that this may not always be the case.
The authors of this research were able to partner with a wireless communications provider in South America, observing the behavior of 64’000 clients. The experiment was simple: the researchers wanted to observe how alerting customers to optimal pricing plans might affect churn, or the rate at which customers cancelled their service. Accordingly, one group of participants was randomly assigned to receive a phone call encouraging them to upgrade to one of two new plans, one or both of which would save them money based on their current usage. To make the deal even sweeter, these participants were even offered a temporary financial incentive to switch. The remaining participants were not contacted at all, but were free to switch of their own volition (i.e. should they seek out other available plans). What happened next was likely a surprise to the firm, but not so much to the researchers involved: those who had been recommended a more cost-effective plan were more likely to switch providers. In particular, in the three months that followed, 10 percent of those who had been contacted left the company, compared to 6.5 percent who had not been contacted.
Why did this happen? Why did customers actually exhibit reduced loyalty in response to what was a proactive gesture on behalf of the communications provider? The authors provide two potential explanations. Firstly, making customers aware of the ease of switching likely disrupts their default bias, and once they see how easy it is to switch plans within the existing company, they are probably more likely to explore alternatives. Secondly, the promotion likely also drew attention to the amount the customers were already using. In particular, the authors showed that customers who already exhibited signs of churning (i.e. high variability in their use, consistently exceeding their monthly plan) were even more likely to depart when they had been contacted. The take-home message? Even well-meaning efforts on behalf of firms aimed at improving customer wellbeing can sometimes backfire. By disrupting the default bias and drawing attention to current non-optimal plans, customer relationship management can go awry and cause customers to leave the company.
As noted by the authors, this insight is increasingly relevant as telecommunications companies begin to put into place systems that help users manage and optimize their usage (i.e. through automatic alerts when overage is about to occur, or recommended plans based on past usage). But such findings may have implications well beyond services such as telecommunications. People are increasingly gaining access to quantitative information about their daily lives, and this includes data on their consumption. Consider smart thermostats that allow consumers to monitor their energy usage, or banking apps that provide immediate transparency to financial services. Such features will undoubtedly allow consumers to optimize their consumption habits, but as the research described in this article shows, may also interrupt inertia and lead them to competitors. In essence, consumers may become increasingly less reliant upon defaults as they gain more knowledge and awareness of their own consumption.
Ascarza, E., Iyengar, R., & Schleicher, M. (2016). The perils of proactive churn prevention using plan recommendations: Evidence from a field experiment. Journal of Marketing Research, 53(1), 46-60.
Hartman, R. S., Doane, M. J., & Woo, C. K. (1991). Consumer rationality and the status quo. The Quarterly Journal of Economics, 141-162.
Johnson, E. J., & Goldstein, D. (2003). Do defaults save lives? Science, 302(5649), 1338-1339.
Samuelson, W., & Zeckhauser, R. (1988). Status quo bias in decision making. Journal of risk and uncertainty, 1(1), 7-59.