I created a FREE Title Generator for Pinterest to help with marketing

Hacker News

Hey everyone, I'm Nic, and I've been working on helping other people create beautiful and efficient Pinterest Pins Pinterest is an incredible platform where you can get a lot of traffic on autopilot for free But it's not that easy. Pinterest is mostly a SEO engine, so it needs well-crafted titles and descriptions, filled with keywords to make sure you rank well. That's why I created this FREE mini tool to help you come up with some better titles/description and rank better Hope it helps. Would love to hear your feedback Nic

Visit product View on Hacker NewsMay 28, 2024

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Actual performance

2points

Did not reach leaderboard

Launch Intel predictions

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TrustMRRLess likely to generate early MRR · Missing: mobile apps, ios, personal

50%50% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

best fitHighest predicted score across all platforms for this description.

Indie HackersIH features products with proven revenue · Strong signals: created · Missing: supports, reddit linkedin, podcasting

46%46% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

AppSumoMay struggle as an AppSumo deal · Strong signals: platform, efficient · Missing: plus, intuitive, reviews

40%40% 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

34%34% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

Hacker NewsMay not resonate with HN audience · Strong signals: io · Missing: https docs, excited, just released

28%28% predicted probability of success on Hacker News, 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

18%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, crypto

0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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