My

My first pay to download Android App

Hacker News

My first pay to download Android App

Hello, I have just finished my second app, which is also my first ever pay to download app. It's called StreamClock, It's like a radio alarm clock, but uses a Last.fm radio station, or Spotify Track chosen by the user. It took me 1 month of evenings and weekends, and I fell like I have learned a lot. I am particularly proud of the logo... To find it just search "StreamClock" in Google Play. I would really appreciate any feedback, comments, questions or suggestions. Thanks.

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Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting
72%72% 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: google, user · Missing: mac, agents, macos
60%60% 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 · Missing: mobile apps, ios, personal
46%46% predicted probability of success on TrustMRR, 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
45%45% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive
36%36% 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
18%18% 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
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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