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Not8 – continuous product improvement platform

Hacker News

Not8 – continuous product improvement platform

My co-founder and I are taking part in the acceleration program, and we're building not8 - a platform for team product reviews and user feedback collection. Right now we already have an MVP which is a Chrome extension that allows you to leave 'sticky notes' on live websites and share them in just one click. Our demo day is going to be in ~2 weeks, and we want to our user count to hit 1000 by that time. Actually, we want it so much that we are ready to offer our first 1000 users a forever free access to our product. Try out our extension now, and share a few notes with your team - I hope, you will love it. Here's how it works: https://www.loom.com/share/9e74f40086e741549e68740be236ee4b Here's where to download it: https://chrome.google.com/webstore/detail/not8/kdfppggcfpgdcdjcmfpmnfncifmdncfe

Visit productView on Hacker NewsAug 5, 2022
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Actual performance

3points
2comments
Did not reach leaderboard

Launch Intel predictions

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Product HuntOn track for Day 1 leaderboard · Strong signals: google, user, notes · Missing: mac, agents, macos
76%76% 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.
Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting
76%76% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
Hacker NewsStrong engagement from HN community · Strong signals: 000, io · Missing: https docs, excited, just released
50%50% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
AppSumoMay struggle as an AppSumo deal · Strong signals: platform, reviews, users · Missing: plus, intuitive, host
49%49% predicted probability of success on AppSumo, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Strong signals: google, users · Missing: mobile apps, ios, personal
39%39% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue
16%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, 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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