Spotify Wrapped for Your iMessages

Hacker News

Inspired by Spotify Wrapped, I built Messages Wrapped to generate beautiful insights from your iMessage history, showing who ghosts you, your spammiest group chats, fastest responders, who you text the most, and more - all with shareable visualizations. Built with React, Next.js, Framer animations, Electron, and Rust for processing. Initially, it was fully browser based using Rust WASM, but even that was slow and made user onboarding difficult. After converting it to a Mac app, processing became 160x faster. All processing happens locally on your Mac for privacy & security - only encrypted story data leaves your device.

Visit product View on Hacker NewsDec 17, 2024

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Actual performance

2points

1comments

Did not reach leaderboard

Launch Intel predictions

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

94%94% predicted probability of success on Product Hunt, 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: io · Missing: https docs, excited, just released

60%60% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

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

57%57% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

AppSumoStrong fit for a featured deal · Strong signals: host · Missing: plus, platform, intuitive

54%54% predicted probability of success on AppSumo, based on ML models trained on real launch data.

TrustMRRLess likely to generate early MRR · Missing: mobile apps, ios, personal

27%27% 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, revenue

14%14% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

BetaListMay not resonate with beta-testers · Strong signals: chat · Missing: web3, crypto, cryptocurrency

5%5% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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