LaunchVitamins – daily SMS messages to stay productive and accountable

Hacker News

I'm founder and creator of LaunchVitamins (https://launchvitamins.com/). Inspired by a tweet by Shaan Puri and a Brainstorms.io newsletter, I created Launch Vitamins. The premise is pretty simple, receive a daily SMS message to help keep you productive and accountable. It's a real human (me) on the other side. We are more productive when someone is watching, so if you are starting a side gig or deep in work in something established, check out my site. I'd really appreciate it! Craig Tweet mentioned: https://twitter.com/shaanvp/status/1381707640728809472?lang=en Newsletter mentioned: https://mailchi.mp/861b2465e014/a-business-thats-turning-down-customers

Visit product View on Hacker NewsJun 11, 2021

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Actual performance

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Launch Intel predictions

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Indie HackersFits the IH revenue-focused audience · Strong signals: created · Missing: supports, reddit linkedin, podcasting

60%60% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

Hacker NewsStrong engagement from HN community · Strong signals: ide, 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.

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

42%42% 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

25%25% 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

23%23% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

Product HuntUnlikely to reach the leaderboard · Strong signals: new · Missing: mac, agents, macos

16%16% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

BetaListMay not resonate with beta-testers · Missing: web3, chat, crypto

3%3% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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