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I built a tool to gamify Twitter growth

Hacker News

I built a tool to gamify Twitter growth

Hi HN, I wanted to share a small tool I built for myself called Followers Games. It gamifies the process of growing on Twitter, turning what can be a grind into something more engaging. The idea came from my own experience as I started out on Twitter, I wanted a way to stay motivated, so I created this tool. It’s simple: you set weekly goals, track your progress with visual charts, and unlock achievements as you hit milestones. It’s still in the early stages, so I’m really interested in feedback from the community on how to improve it and add cool features. If you’re curious, I’d love for you to try it out and share your thoughts. Thanks!

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Indie HackersFits the IH revenue-focused audience · Strong signals: created, started · Missing: supports, reddit linkedin, podcasting
84%84% 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.
AppSumoStrong fit for a featured deal · Missing: plus, platform, intuitive
61%61% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Product HuntOn track for Day 1 leaderboard · Strong signals: visual · Missing: mac, agents, macos
57%57% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Strong signals: way · Missing: mobile apps, ios, personal
31%31% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Hacker NewsMay not resonate with HN audience · Strong signals: ide, io · Missing: https docs, excited, just released
21%21% 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 · Strong signals: growth · Missing: arr, mrr, revenue
17%17% 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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