ReferCodes
Indie HackersShare referral codes/links with your friends
I wanted a way for my friends and I to be able to find each others referral codes/links when we needed them. Beats the alternative of using random ones found online, often with misleading info, or not using one at all.
Share cardActual performance
2followers
Did not reach leaderboard
Launch Intel predictions
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AppSumoStrong fit for a featured deal · Missing: plus, platform, intuitive53%53% predicted probability of success on AppSumo, 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: using, code · Missing: mac, agents, macos47%47% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Strong signals: way · Missing: mobile apps, ios, personal43%43% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Indie HackersIH features products with proven revenue · Missing: supports, reddit linkedin, podcasting43%43% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
Hacker NewsMay not resonate with HN audience · Missing: https docs, excited, just released35%35% 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, revenue16%16% 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, crypto6%6% predicted probability of success on BetaList, based on ML models trained on real launch data.
Correct prediction on native model
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Discover, submit, and promote referral links and codes.
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Find the latest referral codes and save more!
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TMinus is where you share what you're counting down to with your friends41%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
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