Pitfalls of Conversion-Rate-Only Concern

There’s a lot of pressure on user experience professionals to be data driven, and at times it can feel like there’s a hyper focus on conversion rate optimization. Here are three common pitfalls of conversion, only concern and how to avoid them.

The first pitfall is believing that quantitative test results will provide all of the answers. The key benefit to quantitative research is that it boils down to a complex situation into a single number that’s easy to grasp and discuss. Avoid relying too heavily on quantitative metrics, as numbers alone won’t tell us how to solve the problems that our user experience. The second pitfall is building features based on opinions and AB test results don’t blindly build features just because they performed well in a lab test. Teams that demonstrate this behavior end up in a never ending cycle of chasing disjointed quick fix features. When you kick off an AB test, conduct qualitative research right alongside it and report the quantitative and qualitative findings together.

This combination of insightful information gives you exactly what you need to make informed decisions about what to build next, and you’ll know exactly how your customers feel about it. The third pitfall is assuming that a design is only successful if conversion rates are high. Successful designs are those that have a favorable conversion rate while also delighting customers. It’s a mistake to assume that your design is successful just because your conversion rates are high after launch. If your users hate the experience, they won’t come back, observe how they behave on your site and listen to their feedback. With so many online options available today, users are looking for more than a transaction. Strive to make a real connection with your users by talking to them, understanding them and creating an experience that meets their needs.

Balance the quest for positive conversion rates with solving your users problems, and you’ll create value that’s sustained for the long term.

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