TempleReads

TempleReads

Product Hunt

Build habits based on the best selling non fiction books

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Actual performance

7upvotes
Did not reach leaderboard

Launch Intel predictions

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Indie HackersIH features products with proven revenue · Missing: supports, reddit linkedin, podcasting
49%49% 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 NewsMay not resonate with HN audience · Strong signals: io · Missing: https docs, excited, just released
48%48% predicted probability of success on Hacker News, based on ML models trained on real launch data.
BetaListMay not resonate with beta-testers · Missing: web3, chat, crypto
47%47% predicted probability of success on BetaList, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Missing: mobile apps, ios, personal
41%41% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive
41%41% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Product HuntUnlikely to reach the leaderboard · Missing: mac, agents, macos
40%40% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue
19%19% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

Correct prediction on native model

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