“Going Steady:” Lessons in Customer Loyalty from Romantic Relationship Research

April 18, 2014

In my former life as an academic, I studied love. Well, romantic relationships, narrowly speaking. And I taught it too—every Monday, Wednesday and Friday at 8 am. Despite the early hour, every class was maxed out and, overall, exceptionally well-attended. While I’d like to attribute such high student engagement to my stellar teaching abilities, I know better: A class where you analyze nonverbal cues to assess another’s romantic interest, digest research on the “hook-up culture” and debate whether you should friend your ex on Facebook? What’s not to like?

The Relational Investment Model

Also covered in this class was a favorite model of mine: the (Original) Relational Investment Model (Rusbult, 1989). Here’s a quick recap, in case you slept through your own interpersonal communication class that day: High relationship satisfaction, high levels of investment and low quality of alternatives predict high relational commitment. Said another way, if your needs are being met in a relationship, you have already spent a lot of time or money to keep the relationship going and you don’t really have any other viable dating options at the moment, you’re more likely to stick it out with your current partner. Change any of the above equation, however, and level of commitment changes. (Insert your own example of a failed celebrity super couple here.)

The XO’s of Business & Customer

When devising studies for our clients, particularly those centered on customer loyalty and retainment, I often find myself returning to this model and other related relational theories. Now, we often incorporate similar measures (e.g., customer satisfaction, brand awareness), but overall the Relational Investment Model is an exceptionally useful framework for conceptualizing customer commitment. For instance, in the case of a “courtship” between Business X and Customer O, what “investments” does the customer currently make and how often? Has he invested a great deal of time into the relationship (e.g., tenure as a customer with Business X) or maybe Business X has already “met his family” (e.g., I’m thinking of family share plans in the telecommunications space)? Does Customer O have a lot of potential alternatives he could “date,” with whom he is “compatible?”

The model not only gives us a way to conceptualize customers’ current levels of commitment but also a way to potentially challenge those levels of commitment. Let’s say we know that Customer O’s commitment is low, but he is highly satisfied and has made tremendous investments in Business X.  A likely culprit barring the door to increased commitment may be quality of alternatives. What other alternatives does Customer O have and, equally important, what can be done to derogate those alternatives? These and other questions offer a foundation for where and what to explore in hopes of improving Customer O’s commitment.

The Social Effect

Certainly, the Relational Investment Model provides a unique lens through which to view the customer-business relationship. But, like most models, it’s not without limitations. For example, my research team is exploring how social media may factor into the equation (which, obviously, was not on Rusbult’s radar in 1989). With the ability to quickly bash or praise via Twitter or scope out competitors’ Facebook pages, it quickly becomes apparent that social media usage—of both businesses and customers—will impact satisfaction, investments and quality of alternatives, and, thus, tie to levels of customer commitment.

Indeed, the world of relational communication research is a rich resource for market researchers and savvy business people alike. It can inform so much of what we do and how we interact. And, who knows, maybe some of what we learn will brush off on our actual romantic relationships…

 

Want to discuss? Send us a note and let’s chat!

Send Us A Note

 

Elizabeth Baiocchi-Wagner, Ph.D.
Director, Health Insurance & Systems

Elizabeth (Liz) is a Director of Research and Consulting in Health Insurance & Systems at Escalent. She brings 15 years of quantitative and qualitative research experience to the table, along with solid industry knowledge in technology and telecommunications (after years of lead analyst work in that space). Liz is a former Communications professor (University of Missouri, University of Portland) teaching everything from Advanced Research Methods, to Gerontology, to Communicating in Romantic Relationships. Originally from Detroit, Liz joined the Escalent team in the summer of 2011 and moved to the Pacific NW. When she’s not working or teaching, she is leading marketing and outreach efforts for the nonprofit organization, GiGi’s Playhouse Portland, biking around her VERY hilly neighborhood, or playing DJ for a family dance party.