Userpilot

?? Curious about the health of your SaaS metrics? Keep an eye out for our 2024 Benchmark Report, detailing essential metrics from 547 companies across various industries. Find out if you're leading or need to catch up ?? https://lnkd.in/ez3Uyp4p #saas #productmetrics #productmanagement

Your data says users dropped off—but why? Your funnel shows a spike in friction—but where? Numbers don’t show confusion. Graphs don’t capture frustration. With?Session Replay, you watch the full story: every rage click, hesitation, and abandoned journey. Watch our Head of Product Kevin O'Sullivan break it down. ???? You can watch the full session here ?? https://lnkd.in/ec8u82HF #analytics #saas #productmanagement

Why do so many #AI products sound like they were written?by?robots?for?robots? ?? Maja Voje breaks it down: AI companies are so obsessed with tech that they forget to use language real people actually?get. They default to jargon like “LLMs,” “transformer-based architectures,” and “neural embeddings” instead of answering the only question that matters—how does this make my life easier? The best AI products don’t just function smarter—they?communicate?smarter. Want to stand out? Drop the robotic talk and speak to humans like, well... humans. ?? Missed the live interview with Maja? Watch the recording here: https://lnkd.in/eTDKh99Z

??Your analytics setup is probably broken.?? Tracking clicks, scrolls, and button taps might seem like you're doing it right, but what if you're missing the?one?metric that actually drives your product’s growth? Notion, Slack, and Asana nailed it by focusing on what Timo Dechau calls the?"heartbeat metric". It’s the signal that reveals whether your product strategy is working or failing. Most teams fall into one of two traps: 1???They track EVERYTHING.?Endless data points, but no clear insights. 2???They track TOO LITTLE.?Missing the key events that reveal user behavior. The solution??Map your data to your product strategy. Here’s how Timo Dechau does it: ? Start by defining your?north star metric?— the one that reflects product success. ? Identify the?key actions?that drive that metric (e.g., project creation in Notion, channel joins in Slack). ? Track only those events that connect directly to these outcomes — no fluff. Curious how it works in action??Timo is going LIVE this Thursday?to break it down step by step. Don’t miss it! ?? https://lnkd.in/eGGKKApB #analytics #productstrategy #productmanagement

?? What is the?biggest roadblock stopping PMs from becoming AI-powered? PMs everywhere?want?to leverage AI, but something is holding them back. Is it the data? The mindset? The workflows? ?? Aakash Gupta?breaks it down in this short clip.?Want the full scoop? Watch the entire session here ?? https://lnkd.in/d4Ps3b4e #productmanagement?#AI?

?? Picking the wrong customer engagement software is like getting into a bad relationship… At first, it seems perfect. Smooth sales pitch, big promises. But soon, the red flags start popping up: ? Clunky setup that takes forever ? Hidden fees you didn’t see coming ? “24/7 support” that disappears when you actually need it Before you commit, run every tool through this 7-question reality check.?Because the right software should feel like an extension of your team—not a constant headache. Watch the video for the full breakdown, and if you want?no-BS recommendations,?check out the full guide here ?? https://lnkd.in/e5cFb-6g #userengagement #onboarding #SaaS

80% of users completed onboarding? Cool. But?how sure are you???? One small sample, one lucky test, and suddenly your "80%" could be?65%... or 92%. And that’s how bad data leads to?bad investments. Here’s the problem:?single numbers lie. Product teams see stats like: ? 120 seconds average checkout time ? 80% completion rate ? 72 on SUS …and assume they’re absolute truth. But in reality,?every number carries uncertainty. Without?confidence intervals, you’re making decisions on shaky ground. You might be investing in a ‘winning’ feature that isn’t really a winner—or scrapping an experiment that’s actually working. How do confidence intervals help? ? They show the?range?of possible outcomes, not just a single number. ? They prevent premature investments based on misleading data. ? They help you avoid making the wrong call on A/B test results. Alessio Romito explains why this matters (watch the video ??) and breaks it all down in our latest PITT (Product Innovation Think Tank) article: https://lnkd.in/gkR8pWGr Oh, and next week,?Alessio is going LIVE?with us to dive even deeper into this! Don’t miss it. ?? https://lnkd.in/ggrGtnWT #UX #productmanagement

???DATA vs. INTUITION: Which one wins? Tell me about a time when the numbers told one story, but your gut screamed something different.?What did you trust? And why? This ONE question reveals more about you as a PM than you think: ? The level of trade-offs you’ve actually faced ? How you interpret and act on data (or blindly follow it) ? Whether you refine your instincts—or just react to the numbers ? If you chase curiosity or obsess over shipping Sometimes, that?perfect?data point is just a mirage. Until you talk to real users, you won’t know if it’s gold—or fool’s gold. ibrahim bashir sees this tension all the time. In his latest PITT article, he breaks down how top PMs?decode?conflicting signals between internal metrics and external customer insights. ?? The truth??You don’t need more data. You need to know how to read it. Watch the session to learn: - Why your dashboards are LYING to you (and what’s missing) - How #AI is reshaping product intuition & user behavior analysis - The "zoomed-in vs. zoomed-out" framework that separates good PMs from GREAT ones Register here: https://lnkd.in/etrFF7eg #productmanager #analytics

Recently at Userpilot and within my product team, we have been exploring how we assess our releases. Like most product teams we are tracking the analytics, but are they actually helping us to make the right decisions? Here are?7 common analytics mistakes?that could be costing you—and here are some simple tip to help fix them (full post link in comments): 1?? Tracking Everything Without Clear Objectives Too much data? You’re drowning. Too little? You’re flying blind. How to Fix it:?Focus on?3-5 key metrics?that align with your product & business goals. Set realistic targets and iterate. 2?? Ignoring User Segmentation Aggregate data = misleading insights. How to?Fix it:?Segment users by?journey stage, NPS scores, company size, or usage frequency?to make data-driven decisions. 3?? Choosing the Wrong Data Visualization A bad chart can distort your insights. How to Fix it:?Use?line graphs for trends, bar charts for segment breakdowns, and avoid pie charts for anything time-based. 4?? Confusing Correlation with Causation Just because two metrics move together doesn’t mean one causes the other. How to Fix it:?Run A/B tests?before making product decisions based on assumptions. 5?? Relying Only on Quantitative Data Numbers tell?what?is happening, but not?why. How to Fix it:?Combine?quantitative data?with?user surveys, interviews, and session replays?for deeper insights. 6?? Not Acting on Analytics Insights Data without action is just a report. How to Fix it:?Set up?regular analytics reviews?to prioritize key insights and a timeline to drive product improvements. 7?? Keeping Product Analytics Siloed If insights stay within the product team, other departments (CS, Marketing, Sales) miss out. How to Fix it:?Share data across teams?so everyone makes informed, aligned decisions. ?? Turn analytics into action with Userpilot! Book a free demo to see how to make better, data-driven product decisions. https://lnkd.in/eJ3ADsbP #ProductAnalytics #Growth #SaaS #ProductManagement

"HOW SESSION REPLAY COULD HAVE SAVED ME $120,000" Real story shared by an ex-CSM. ?? #CSM #customersuccess