Launch Intel
Re

Recount - share your startup stories anonymously. We are not alone

Hacker News

Recount - share your startup stories anonymously. We are not alone

There are times when we just can't have open and honest conversations with people about the things we're going through. Anything we say publicly gets added to our personal brand. Like bubs mentioned in this article/thread http://news.ycombinator.com/item?id=5270460, we can start to feel like we're alone. We don't have to be alone! Recount is a community project aimed at bettering the lives of startups everywhere, through anonymous sharing of our stories. Share your startup high-and-lows, experiences, funny / embarassing moments, things you learned, and even confessions of things you probably shouldn't have done. Posting is done anonymously. No sign-up is required. We'll never track any info of people who post. (Commenting is via Facebook Comments though) Start reading here: http://www.recount.it/ Have a good story to tell? Start posting straightaway at: http://www.recount.it/posts/new Appreciate any feedback! :)

Visit productView on Hacker NewsFeb 27, 2013
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Actual performance

14points
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Launch Intel predictions

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Product HuntOn track for Day 1 leaderboard · Strong signals: new, open · 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
62%62% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
Hacker NewsStrong engagement from HN community · Strong signals: io · Missing: https docs, excited, just released
58%58% 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 · Missing: plus, platform, intuitive
47%47% predicted probability of success on AppSumo, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Strong signals: personal, way · Missing: mobile apps, ios, entrepreneurs
32%32% 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
11%11% 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
1%1% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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