User Feedback: To Follow…Or Not To Follow?
First, I believe it’s okay to ignore your users Furthermore, you might even want to do it more often than you think. We should always listen in an empathetic, neutral and intentional manner. However, what you choose to do with user feedback is something else altogether.
When I was at Capital One Labs, we wanted to create more meaningful relationships with national merchants by leveraging transaction data. We began by interviewing about 30 Fortune 500 level retailers, and our focus was primarily on marketing, financial planning & analysis, and store operations teams. We had no hypothesis up front, and this was purely discovery research.
The retailers’ biggest challenge was that they understood what customers did inside – but not outside – of their stores. So we came up with two product ideas based on our user feedback. Specifically, these solutions integrated with a larger product called Spend Analytics.
Product Idea 1: Customer Insights
In customer insights, the first use case was Find My Best Friend – which looked at potential co-marketing relationships. So if you’re JetBlue, for instance, do you want to be paired with Panera or Buffalo Wild Wings?
The next use case was “Speak My Language.” A lot of brands do hyper-local marketing where they want their ad copy to speak to the local community. We felt our data could help solve that need.
The last customer insight use case was Where’s Waldo. Here, you have an almost lapsed customer segment, and you want to prevent them from going lapsed. User feedback told us that they wanted to identify where these customers are and how to reach them.
Product Idea 2: Competitor Insights
Our first competitor insights use case (“Leaky Bucket’) analyzed where customer loss occurred and to whom.
The second competitor user case was “Cheating on Me” – which looked at how much you lost per customer to competitors in the same niche.
Finally, there was Biggest “Bang For The Buck.” This helped retailers understand their share of wallet and where they had the largest share of wallet opportunity. Then, when they looked at allocating their marketing spend, they didn’t distribute spend evenly. Instead, they weighted marketing spend by where they had the largest share of wallet opportunity.
Listening to user feedback, our dilemma was that we could build either the Customer or Competitor product, but we couldn’t build them both.
We ended up choosing to build Competitor Insights first. It was the wrong choice.
We chose Competitor Insights since other similar products were trending at the time. However, this generated very high expectations. A customer with high expectations is hard to satisfy. Instead, it’s best to look for low expectation bias and then deliver high quality. This improves your chances of success significantly. For instance, you might think you are 5x better than the competition – but if expectations are low, users might see you as 7-8x better.
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