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MVP for my site SoSforguys. Nice things to say to your wife

Hacker News

MVP for my site SoSforguys. Nice things to say to your wife

Hi fellow HN members,<p>I'd like to get your feedback on my MVP for SoSforguys. Two days a month, we will email you nice things to say to your wife / girlfriend.<p>The idea came from my personal life. Several times, my wife asked me to say nice things about her. Being cornered, I found it difficult to come up with something nice to say without being too corny.<p>It is for this reason that I came up with the idea of SoSforguys. On any two random days of the month, you will get an email with nice things that you can say to your wife or girlfriend.<p>What do you think ?

Visit productView on Hacker NewsJan 20, 2012
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Actual performance

1points
Did not reach leaderboard

Launch Intel predictions

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Hacker NewsStrong engagement from HN community · Strong signals: ide · 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.
Indie HackersFits the IH revenue-focused audience · Strong signals: wife · Missing: supports, reddit linkedin, podcasting
57%57% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
Product HuntOn track for Day 1 leaderboard · Strong signals: email · Missing: mac, agents, macos
55%55% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Strong signals: personal, month · Missing: mobile apps, ios, entrepreneurs
46%46% 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
36%36% 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
15%15% 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
7%7% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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