Seeing an unexpected retention curve dip after updating our funnel setup makes me rethink our analytics approach

We updated our funnel recently and saw a weird dip in the retention curve. It’s making me question our whole analytics setup.

Are we missing something obvious? Maybe our segmentation is off?

I’m starting to wonder if we need to overhaul our entire approach to measuring user behavior.

Could be the funnel change messed with user flow. Check if people are dropping off at new steps. Maybe A/B test the old funnel against the new one for a bit.

Retention dips can be tricky. Before overhauling everything, check your event tracking.

Make sure you’re capturing all key actions in the new funnel. Sometimes small changes mess up data collection.

If tracking looks good, compare behavior between old and new funnels. You might spot where users are getting stuck now.

Been there, felt that panic. Before you nuke your analytics, let’s dig in.

First, double-check your event tracking. I once freaked over a dip, only to find we’d missed tagging a new button. Rookie mistake, but it happens.

If tracking’s solid, slice your data by user segments. New vs. returning, paid vs. organic. The dip might be isolated to one group.

Also, look at engagement metrics beyond the funnel. Are people using the app less overall? Or just converting differently?

Last tip - run a quick survey. Ask users about their experience with the new funnel. Sometimes the data doesn’t tell the full story.

Remember, every change causes ripples. Give it some time before making big moves.

Hold up. Before jumping to overhaul everything, dig into what changed with the funnel update. Look at specific user segments and see where the dip is happening. Is it new users? A certain cohort? Check if any key events or user actions shifted. Maybe the update affected a critical step without you realizing. Run some A/B tests on the new funnel vs. the old one. That’ll tell you if it’s actually causing issues or if something else is at play. Don’t blow up your whole analytics system over one dip. Investigate first, then adjust.

Dips happen. Look at the actual user behavior first. Analytics can lie. Talk to some customers instead.