Link-in-Bio just for apps and devs

Hacker News

Link-in-Bio *just* for apps and devs

Hey all, we felt like existing link-in-bio tools cater to influencers, so we decided to build a tool just for apps and developers. It's called Launch.app! Launch.app is a more opinionated tool than others, built just for apps and app developers. Some features include: - A much better URL: Launch.app/app-name // Launch.app/@username - Verification badging (optional ID / email / location / etc checks) - Aggregate and showcase existing reviews across platforms - Quickly import your styling from existing web site - Dynamic device-based layouts (only show launch button for user device) - Dynamic device-based forwarding options (bring specific users directly to app stores) - Aggregated profile view (consolidated app listings on developer profile) - Free forever for one app! If you have a sec, try it out and let us know what you think! All feedback is greatly appreciated :-) Check it out here: https://www.launch.app/

Visit product View on Hacker NewsJan 28, 2025

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Launch Intel predictions

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

86%86% 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.

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

61%61% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

Hacker NewsMay not resonate with HN audience · Strong signals: exist, existing, ide · Missing: https docs, excited, just released

39%39% 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 · Strong signals: apps, users · Missing: mobile apps, ios, personal

39%39% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

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

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

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

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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