Back of the Napkin VC
Indie HackersRefreshingly simple framework for evaluating startups
I love evaluating businesses opportunities as a founder and an investor. In doing this, I have found myself trying to distill everything down to a few simple models. I'm excited to explore this framework more in public.
Share cardActual performance
1followers
Did not reach leaderboard
Launch Intel predictions
Analyze your own launch →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.
nativeThis product was originally launched on this platform.
AppSumoStrong fit for a featured deal · Missing: plus, platform, intuitive62%62% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Hacker NewsStrong engagement from HN community · Strong signals: excited, lua · Missing: https docs, just released, exist55%55% predicted probability of success on Hacker News, based on ML models trained on real launch data.
Product HuntUnlikely to reach the leaderboard · Strong signals: model, models · Missing: mac, agents, macos35%35% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Missing: mobile apps, ios, personal29%29% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue18%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, crypto3%3% predicted probability of success on BetaList, based on ML models trained on real launch data.
Incorrect prediction on native model
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