BidSpot
Indie HackersLive bidding leaderboard for startup visibility
Startup directories rank you with an algorithm you can't see. I wanted the opposite — a leaderboard where visibility is 100% transparent. You bid real money, highest bid wins rank #1, and if you're outbid you see it live
Share cardActual performance
Did not reach leaderboard
Launch Intel predictions
Analyze your own launch →Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting53%53% predicted probability of success on Indie Hackers, 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, intuitive35%35% predicted probability of success on AppSumo, based on ML models trained on real launch data.
BetaListMay not resonate with beta-testers · Missing: web3, chat, crypto33%33% predicted probability of success on BetaList, based on ML models trained on real launch data.
Hacker NewsMay not resonate with HN audience · Missing: https docs, excited, just released31%31% predicted probability of success on Hacker News, based on ML models trained on real launch data.
Product HuntUnlikely to reach the leaderboard · Missing: mac, agents, macos26%26% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue23%23% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Missing: mobile apps, ios, personal14%14% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Incorrect prediction on native model
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