Companies must make important decisions about which features to include in the goods and services they offer to customers. Understanding the return on investment (ROI) for a feature is essential to increasing profitability. Adding features increases costs, but it may increase revenues as well, either by attracting new customers or retaining existing customers. Notably, as we describe in this article, the features that retain customers may be different from the features that initially attract customers.
Customer lifetime value is the net profit earned over the course of a company’s relationship with the customer.1 To maximize customer lifetime value, a company must not only convince customers to buy its product or service once; it must also retain them. Hotel and airline companies, for example, invest heavily in loyalty programs designed to encourage their best customers to come back again and again. About one-third of leisure guests and about one-half of business travelers say they are loyal to a hotel brand.2 Subscription-based services such as Netflix and Amazon Prime frequently offer free trials to attract customers, hoping that they will recoup their investment when customers sign up and become paying subscribers. Profits flow to video game app developers not when their apps are downloaded for free, but when users decide to keep playing and spend money to upgrade the app or make in-app purchases. Yet in many cases, the notion of generating revenue is no more than a pipe dream: According to one estimate, less than 40% of video game players return to a free-to-play game after the first session;3 another analysis found that, on average, three-quarters of people who download apps stop using those apps within 90 days.4
Given the importance of retaining customers, companies have an incentive to design goods and services with customer retention in mind. Unfortunately, they often add expensive features to their offerings without knowing whether or how much the new features will increase retention. Our research has shown that adding too many features can actually decrease customer satisfaction with products after customers have used them. In one of our studies, participants were initially more inclined to choose a digital video player that had 21 features over one that had only seven features.
1. R.T. Rust, K.N. Lemon, and V.A. Zeithaml, “Return on Marketing: Using Customer Equity to Focus Marketing Strategy,” Journal of Marketing 68, no. 1 (January 2004): 109-127.
2. Intelity, “The Link Between Hotel Technology and Establishing Hotel Guest Loyalty,” March 11, 2016, http://intelitycorp.com.
3. N. Lovato, “16 Things Game Developers Should Do to Improve Player Retention,” April 7, 2015, www.gamedonia.com.
4. A. Meola, “Here’s a Breakdown of Which Apps Have the Best User Retention Rates,” Business Insider, March 31, 2016, www.businessinsider.com.
5. D.V. Thompson, R.W. Hamilton, and R.T. Rust, “Feature Fatigue: When Product Capabilities Become Too Much of a Good Thing,” Journal of Marketing Research 42, no. 4 (November 2005): 431-442.
6. R.T. Rust, D.V. Thompson, and R. Hamilton, “Defeating Feature Fatigue,” Harvard Business Review 84, no. 2 (February 2006): 98-107; and Thompson, Hamilton, and Rust, “Feature Fatigue.”
7. N. Trejos, “The Ever-Changing Scene of Hotel Room Amenities,” Washington Post, March 18, 2011, http://articles.washingtonpost.com.
8. Lovato, “16 Things.”
9. Rust, Thompson, and Hamilton, “Defeating Feature Fatigue”; and Thompson, Hamilton, and Rust, “Feature Fatigue.”
10. R.D. Van Oest, H.J. van Heerde, and M.G. DeKimpe, “Return on Roller Coasters: A Model to Guide Investments in Theme Park Attractions,” Marketing Science 29, no. 4 (July/August 2010): 721-737.
11. Rust, Thompson, and Hamilton, “Defeating Feature Fatigue”; and Thompson, Hamilton, and Rust, “Feature Fatigue.”
12. R.W. Hamilton, R.T. Rust, M. Wedel, and C.S. Dev, “Return on Service Amenities,” Journal of Marketing Research, forthcoming.
13. G. Loewenstein, “Out of Control: Visceral Influences on Decision Making,” Organizational Behavior and Human Decision Processes 65, no. 3 (March 1996): 272-292.
14. Hamilton et al., “Return on Service Amenities.”
15. The discrete choice method is very similar to conjoint analysis.
16. L. Victorino, R. Verma, G. Plaschka, and C.S. Dev, “Service Innovation and Customer Choices in the Hospitality Industry,” Managing Service Quality 15, no. 6 (2005): 555–576.
i. Rust, Thompson, and Hamilton, “Defeating Feature Fatigue”; and Thompson, Hamilton, and Rust, “Feature Fatigue.”
ii. Hamilton et al., “Return on Service Amenities.”