[patio11]

This sort of segmentation exists in many, many free trials. Sometimes the causational arrow can be difficult to tease out. For example, one's best customers often engage higher with the app on every conceivable dimension, so if you happen to test a particular feature, you'll see adoption of that feature correlates with conversions and might be inclined to e.g. try to juice adoption via promoting in onboarding. That works only some of the time.

In general, though, strong endorsement of figuring out what people care about quantitatively and qualitatively, instrumenting that, and then testing early in the funnel improvements to it. The gold standard is, of course, not doing retrospective analysis but rather split testing the intervention. I sympathize that this is difficult for a lot of SaaS apps as you need high trial volumes to make it work.

I can't share client results but my blog probably has two or three write ups of 10%+ lifts for BCC doing this.