We are living in the age of algorithms. These formulas govern decisions across all parts of life and have allowed companies to become more customer-oriented and profitable — think Netflix’s subscriber-friendly personalization, or the daily purchases attributed to Amazon’s vast recommendation engine. But what happens when algorithms are used to evaluate customers?
Companies are increasingly adopting algorithms to evaluate information provided by customers and make favorable or unfavorable decisions about them. For example, Raya, the private dating and networking app, uses algorithms to decide which applicants to admit as new members, while Zendrive evaluates customers’ driving skills to determine their car insurance premiums, and the global financial institution ING uses algorithms to make decisions about loan applications.
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The prevalence of algorithms in customer-facing decisions raises an interesting set of questions about how customers react to personally relevant decisions taken by algorithms versus humans. For instance, would customers evaluate a bank differently depending on whether their loan application was accepted by a loan algorithm versus a loan officer? And what if their request was instead rejected? Understanding the impact of customer reactions can help managers make better decisions about when and how to deploy algorithms in customer-facing functions. We conducted a series of studies that showed that managers’ intuitions about this issue are frequently wrong.
Customer Reactions to Decisions by Algorithms Versus Humans
To learn more about how managers think about the effects of algorithms in customer-facing decisions, we first conducted a series of in-depth interviews and a survey with managers from different industries. We asked managers how they thought customers would react to being accepted or rejected by algorithms or humans. Most managers expected that customers would react less positively to being rejected by algorithms but react similarly to being accepted by algorithms versus humans. However, the data we gathered on customer reactions told a very different story.
In fact, our research revealed a pattern of results that is the exact opposite of the intuition of the managers we surveyed. We investigated customer reactions to favorable and unfavorable decisions made by algorithms versus humans across diverse contexts, such as loan and membership applications.