Launch Intel
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Know what your ICP thinks about your competition

Hacker News

Know what your ICP thinks about your competition

We uncover product opportunities based on your ICP's thoughts on their existing tools. As founders, we've found it helpful to not only synthesise feedback from our own customers/prospects, but also understand what our ICP thinks about their existing tools. Sources like G2, X, or Slack have this data in the form of threads or comments, but it takes time to search and analyze. As we build out our tool, we want to learn as much as we can and provide value from day 1. Our offering: Give us your ICP, and up to 3 main competitors. We're happy to send you a summary of their needs, likes, and dislikes of existing tools. https://tally.so/r/3yyaVg Hope we’re helpful

Visit productView on Hacker NewsJun 25, 2024
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Actual performance

2points
Did not reach leaderboard

Launch Intel predictions

Analyze your own launch →
Product HuntOn track for Day 1 leaderboard · Strong signals: slack · Missing: mac, agents, macos
82%82% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
best fitHighest predicted score across all platforms for this description.
Hacker NewsStrong engagement from HN community · Strong signals: exist, existing, ide · Missing: https docs, excited, just released
62%62% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting
55%55% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Missing: mobile apps, ios, personal
38%38% 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
33%33% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue
14%14% 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.

Incorrect prediction on native model

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