Launch Intel
I

I built a refund tool for late deliveries – here's what happened

Hacker News

I built a refund tool for late deliveries – here's what happened

I built a simple tool (LateClaim.org) that checks if your online delivery was late and helps you claim compensation. Thought it was a no-brainer. Everyone hates late packages. Free money, no app, no account. Should work, right? I ran Insta ads. Got almost nothing. Tried Reddit. Got shadowbanned. Messaged UGC creators. Still waiting. Turns out, the product isn’t enough. People don’t trust “free”. Or “new”. You need proof, faces, emotion. Working now on UGC + meme-style videos. Might pivot the brand. Validation is f*cking hard in B2C if you’re not known. If you’ve built something consumer-facing and tried to grow it from scratch: what actually worked for you?

Visit productView on Hacker NewsMay 31, 2025
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Actual performance

2points
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Launch Intel predictions

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Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting
78%78% 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 HuntUnlikely to reach the leaderboard · Strong signals: new · Missing: mac, agents, macos
50%50% predicted probability of success on Product Hunt, 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
46%46% 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: video · Missing: mobile apps, ios, personal
42%42% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive
31%31% 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
25%25% 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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