We stopped measuring engagement and our product got better

@isaac_dominic1  Great question! We kept it really simple — two core questions after each session: "Do you feel more clarity about what you were reflecting on?" and "Is there something from this session you'd try in real life?" We also started sending a 3-day follow-up asking if they actually applied anything. The follow-up was the game-changer — it told us whether the app was creating lasting value, not just momentary relief.

@yara_simone  Honestly, yes — it was a tough conversation at first. When DAU dipped, our investors naturally had questions. What helped was showing them the NPS jump (34 to 61) alongside the qualitative feedback we were getting. We reframed the narrative: our users weren't leaving, they were just using the app more intentionally. Once we showed that retention actually improved and that users were reporting real behavioral changes, the conversation shifted from "why is DAU down" to "how do we scale this kind of impact."

@violet_amelia  It took about 6-8 weeks before we really started trusting it. The first few weeks were honestly nerve-wracking — the outcome data was messier than engagement metrics. Session length is a clean number; "did you feel more clarity" is subjective. But over time, patterns emerged. We noticed that users who scored high on our outcome questions were also the ones who stayed long-term and referred friends. That correlation gave us the confidence to commit fully to the new approach.

@delaney_rose1 i found this perspective really eye opening because I have always leaned on engagement metrics as a sign things are working. Seeing how they can hide actual dissatisfaction makes me rethink what I should be tracking.

@delaney_rose1 It's less about choosing one or the other and more about redefining what "engaging" means. We found that the features users called "engaging" were often just visually interesting — fun to play with but not actually changing anything. The simpler features that scored highest on outcomes also turned out to drive the strongest word-of-mouth. So our new rule of thumb: if it's simple and produces real clarity, it's engaging enough. The engagement just shows up differently — in referrals and long-term return rates rather than time-in-app.

@judit10  Love that you're experimenting with this in marketing too — tracking whether content leads to inbound conversations is such a better signal than impressions. To answer your question: it's a mix of both. We use short in-app prompts right after sessions (explicit), but we also look at behavioral proxies like whether someone returns within 7 days or refers a friend (inferred). The explicit reporting gets us the "why," the behavioral data gives us scale. Neither alone tells the full story. And yes — the boring feature outperforming everything was humbling but clarifying!

@ethan_marshall They fluctuate more than engagement metrics, especially early on. Engagement numbers feel steady because they're counting simple actions. Outcome metrics are noisier because you're measuring something subjective — "did this help?" varies by person and context. But we found that over 4-6 week windows, clear patterns emerged. The weekly noise averaged out and the directional signal was actually stronger than engagement ever was. The trick is resisting the urge to react to daily swings.

@cole_simmons Both, actually. The in-app outcome questions are automated — they trigger after sessions and as follow-ups. But interpreting the data still involves a lot of manual review. We read qualitative responses, look for patterns in the behavioral data, and cross-reference. We're slowly building more automated dashboards, but honestly the manual reading of user responses has been some of the most valuable product insight we've ever gotten.

@busmark_w_nika  That's a great example with Taplio! The "you saved $XY" framing is clever because it ties the value back to the user's real life rather than just showing activity stats. We're doing something similar — after each session, we ask if the user gained clarity they can apply, rather than just showing them how many sessions they completed. The difference is subtle but it completely changes how users think about the product's role in their life.

@aiden_jenkins An interactive visualization that let users explore their emotional patterns over time. Users loved playing with it, but it scored almost zero on our outcome metrics — it wasn't actually helping anyone understand themselves better. It was just... pretty. Removing it felt risky because it had high engagement, but nothing changed in our outcome scores when it was gone. That was probably the moment we fully trusted the new approach.

@umairnadeem  Exactly this. The dashboard addiction is real. We spent months watching numbers climb and feeling productive without ever asking whether users were actually better off. Once we broke that cycle and focused on NPS and real-world application, it changed everything about how we build.