Looking for a privacy-friendly analytics tool without monthly fees?

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Hey folks! I created IndieData to solve a problem I faced: finding an affordable analytics tool that respects user privacy for my side projects. Google Analytics is free but uses cookies and isn’t very privacy-conscious. Plausible is privacy-friendly but costs $9/month, which isn’t ideal if your project isn’t generating revenue yet. Enter IndieData: A free and privacy-friendly analytics tool for indie hackers. Privacy-friendly: No cookies. No tracking individuals. We use an anonymous VisitorId that resets daily, fully GDPR-compliant. Decentralized: Data is stored in your Supabase database, not ours. This gives you full control and eliminates monthly fees. Currently, with Supabase’s free plan, you can store over 500k events without paying a cent. Simple Setup in 3 Easy Steps Setting up IndieData is quick and easy. In just three steps, you’ll have: Connect your Supabase – It’s seamless and easy. Embed a small tracking script – No complex integrations. Only 2kb. Start seeing your analytics in a modern, intuitive dashboard. You get all the benefits of full control over your data, with a modern dashboard that’s simple and intuitive to use and make data-driven decisions to your projects. Check it out at indiedata.io and let me know what you think!

Visit product View on Hacker NewsJan 27, 2025

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Actual performance

2points

Did not reach leaderboard

Launch Intel predictions

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Indie HackersFits the IH revenue-focused audience · Strong signals: created · Missing: supports, reddit linkedin, podcasting

92%92% 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.

Hacker NewsStrong engagement from HN community · Strong signals: ide, io · Missing: https docs, excited, just released

63%63% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

Product HuntOn track for Day 1 leaderboard · Strong signals: google, user · Missing: mac, agents, macos

51%51% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

TrustMRRLess likely to generate early MRR · Strong signals: month, google, monthly · Missing: mobile apps, ios, personal

41%41% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

AppSumoMay struggle as an AppSumo deal · Strong signals: intuitive, friendly · Missing: plus, platform, reviews

37%37% predicted probability of success on AppSumo, based on ML models trained on real launch data.

Acquire.comPre-revenue stage for this audience · Strong signals: revenue · Missing: arr, mrr, profit

16%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, crypto

0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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