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A web analytics tool with visitor journeys, heatmaps, replays & more
Hacker NewsA web analytics tool with visitor journeys, heatmaps, replays & more
Just wanted to share a project I launched today. What it does, apart from visitor journeys, replays and heatmaps: - One-page dashboard (similar to Plausible, Umami and Fathom) - Goal tracking - Real-time analytics - UTM tracking - Teams - Data export + filters How I built it: with PHP, MySQL and PayPal for payments. Appreciate any questions or feedback. Thanks!
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Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting78%78% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
best fitHighest predicted score across all platforms for this description.
Product HuntOn track for Day 1 leaderboard · Missing: mac, agents, macos72%72% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive50%50% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Hacker NewsMay not resonate with HN audience · Strong signals: io · Missing: https docs, excited, just released42%42% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
TrustMRRLess likely to generate early MRR · Missing: mobile apps, ios, personal39%39% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue16%16% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
BetaListMay not resonate with beta-testers · Missing: web3, chat, crypto2%2% predicted probability of success on BetaList, based on ML models trained on real launch data.
Correct prediction on native model
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