Testimonial Hunter
Indie HackersSearch any agency. See every client they've worked with.
Testimonial Hunter exists because while analyzing 100+ digital agencies I realized that testimonials, logos, case studies reveal a hidden, public map of who is already buying services i realised this data is scattered.
Share cardActual performance
1followers
Did not reach leaderboard
Launch Intel predictions
Analyze your own launch →Indie HackersIH features products with proven revenue · Missing: supports, reddit linkedin, podcasting40%40% predicted probability of success on Indie Hackers, 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, macos33%33% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive33%33% predicted probability of success on AppSumo, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Missing: mobile apps, ios, personal30%30% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Hacker NewsMay not resonate with HN audience · Strong signals: exist · Missing: https docs, excited, just released25%25% predicted probability of success on Hacker News, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue17%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, crypto2%2% predicted probability of success on BetaList, based on ML models trained on real launch data.
Correct prediction on native model
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