Started tracking NPS in our funnel analytics.
It’s giving us a new perspective on user satisfaction at different stages.
Curious how others are integrating NPS data with traditional funnel metrics. Does it change how you prioritize optimization efforts?
NPS is a nice bonus. I focus on actual usage and revenue. Test real changes see what moves the needle.
NPS is useful, but don’t let it distract from core metrics. I’ve seen teams obsess over NPS and miss the real issues. Focus on retention, revenue per user, and activation rates first. Those directly impact your bottom line. Use NPS as a supporting metric. It can flag problem areas in your funnel, but it won’t tell you how to fix them. If you’re seeing low NPS at a certain stage, dig into why users are dropping off there. Then test solutions based on actual user behavior, not just their sentiment.
NPS has been a game-changer for us, but it took some trial and error to use it right.
We started by tracking NPS at key funnel stages - post-signup, after first use, and post-purchase. It flagged issues we hadn’t caught with regular metrics.
For example, we saw high NPS right after signup but a big dip after first use. Turns out our onboarding was overselling features users couldn’t easily access. We simplified it, and both NPS and activation rates improved.
Now we use NPS to guide where we dig deeper. Low score? We hit those users with targeted surveys and watch session replays to find the real problems.
Just remember - NPS alone won’t fix your funnel. It’s a starting point to know where to look. Always pair it with hard data on what users actually do in your app.
NPS can highlight satisfaction issues, but it’s just one piece of the puzzle. I combine it with conversion rates and user flow data to spot weak points. Then I dive into those areas, looking at user behavior and feedback. This helps me figure out what’s actually causing drop-offs or low satisfaction. From there, I can make targeted improvements that boost both NPS and key metrics.
NPS is okay. I combine it with user behavior data to spot funnel issues. It helps flag problems but shouldn’t be the main metric.