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I made an iOS app to view Plausible Analytics on home screen widgets

Hacker News

I made an iOS app to view Plausible Analytics on home screen widgets

As someone who loves to keep a close eye on website performance, I’ve often found myself wishing for a simple, mobile-friendly way to monitor key website stats on the go. Sure, Plausible has a great web dashboard, but when you want quick insights without opening a browser, something is missing. That’s why I built Applausible. I wanted a dedicated app that gives me instant access to key metrics like current visitors, top pages, and visitor sources—right from my iPhone or iPad. The goal was to create something minimal, fast, and reliable for Plausible users who need instant insights wherever they are. With Applausible, you can: See website visitor counts Quickly check top-performing pages and top countries Effortlessly monitor stats with a clean, intuitive interface Use home screen widgets to keep your stats always in view Sync your configured settings seamlessly across all your devices using iCloud The app's UI has been optimized for both iPhone and iPad, ensuring a smooth and enjoyable experience no matter which device you’re using. You can try Applausible free for 7 days and explore all its features. This is still an early version, and I know there’s plenty of room for improvement. If you’re a Plausible user and want a simpler way to keep track of your website stats, go ahead and try Applausible. I’d love to hear your experience and feedback!

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Actual performance

1points
Did not reach leaderboard

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Indie HackersFits the IH revenue-focused audience · Strong signals: ios · Missing: supports, reddit linkedin, podcasting
94%94% 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 · Strong signals: user, using, open · Missing: mac, agents, macos
92%92% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
TrustMRRFits verified-revenue profile · Strong signals: ios, users, widgets · Missing: mobile apps, personal, entrepreneurs
57%57% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
AppSumoStrong fit for a featured deal · Strong signals: intuitive, friendly, interface · Missing: plus, platform, reviews
56%56% 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 released
42%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.
Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue
12%12% 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.

Correct prediction on native model

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