I
I built a gaming giveaways platform to help gamers get loot
Hacker NewsI built a gaming giveaways platform to help gamers get loot
Hi HN, I’ve been working on DungeonLoot a passion project that’s not the usual SaaS or AI tool. The goal is simple: bring more loot to gamers, and help game developers get discovered in the process. Not the trendiest idea, but sometimes we just do what we like. Link: https://www.dungeonloot.com/ Let me know what you think.
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1points
Did not reach leaderboard
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Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting71%71% 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.
Hacker NewsStrong engagement from HN community · Strong signals: ide, io · Missing: https docs, excited, just released51%51% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
Product HuntUnlikely to reach the leaderboard · Missing: mac, agents, macos42%42% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Strong signals: platform · Missing: plus, intuitive, reviews41%41% predicted probability of success on AppSumo, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Strong signals: way · Missing: mobile apps, ios, personal39%39% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Strong signals: saas · Missing: arr, mrr, revenue10%10% 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, crypto0%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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