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Analyzing CX Means Looking at the High Points, Wherever They Are

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‘Somebody said “In life there’s always peaks and valleys”/And if you’re lost they won’t show you the way’ —Prince (‘Dig U Better Dead’)

If you've existed as a human being with a presence on the Internet at any time in the past 20 years, I will wager that you’ve come across this quote from Maya Angelou: “I’ve learned that people will forget what you said, people will forget what you did, but people will never forget how you made them feel.” Whether on Facebook, Twitter, Instagram, or on blogs, Angelou’s humanist sentiment gets shared every four seconds, it seems. So OK, it’s widespread. But is it correct?

Well, maybe. Partially. The Nobel Prize-winning Israeli psychologist Daniel Kahneman postulated a theory knows as “the peak-end rule” for how we form our impressions of our experiences. Kahneman defined his theory this way: “The peak-end rule is a psychological heuristic in which people judge an experience largely based on how they felt at its peak (i.e., its most intense point) and at its end, rather than based on the total sum or average of every moment of the experience.” Kahneman doesn’t really contradict Angelou; rather, the peak-end rule explains how we come to form these feelings that we will never forget.

Kahneman’s theory applies to interpersonal relationships, but it also makes sense when applied to customer-brand relationships. I’ve been thinking a lot about the peak-end idea lately because a lot of my clients have been asking about how to measure the success of their conversational artificial intelligence (AI), virtual assistant, and chatbot initiatives. Some of the companies have assumed that if their automated system answers a customer’s question correctly, then they can chalk the experience up as positive. This of course ignores the emotional piece—“How did that make you feel?” as a good Rogerian psychotherapist might put it. A larger group of these Forrester Research customers have been looking at ways to measure customer sentiment after the interaction, which would at least get at the “end” part of peak-end.

None of them, however, has really dug into trying to do a peak-end analysis of their automation experiences. To do so would require an ongoing sentiment analysis based on customer utterances and an analysis of where the peak emotion occurred, as well as, obviously, the end state of sentiment for the interaction.

But even if they did that type of analysis, I’d argue that peak-end thinking requires them to rethink their fundamental question: It is not “How was the customer’s experience with our chatbot?” but rather “How was the customer’s experience for that particular issue?” If the chatbot experience started with an online FAQ and/or it was escalated to a human agent, the peak part of peak-end could have come in the pre- or post-chatbot segment of the interaction.

I know, I know—that type of analysis would require the teams in charge of self-service, the website, and maybe even the mobile app to talk to and coordinate with the contact center. And yup, that’s the truth, Ruth! But I’d also argue that if the entirety of the service organization starts to adopt peak-end thinking, they’d grow to be eager for this type of harmonization. After all, to accurately do their jobs, the team responsible for measuring agent performance would then need to recognize and measure the effect of a customer’s interactions with self-service systems that preceded the agent-led interaction.

So it seems Maya Angelou’s quote can help us with our customer experiences, but only if we really understand how the peak-end rule drives the formation of those experiences.  

Ian Jacobs is a principal analyst at Forrester Research.

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