We all need a boost of positive energy!

Hacker News

Startups are hard. They are also lonely (even with cofounders) especially when you go through the lows that all startups experience. Family and friends might support us but it is not the same. I remember having a real bad day; I was in line at the bank to withdraw the last $500 in my account to pay rent when an old lady in front of me asked why I was so gloomy. I told her because of work troubles and she basically smiled and said you will figure it out. That really stuck with me! She had no idea who I was or what I was going through but that random boost of positive energy was just what I needed. That's what we hope to capture with Positive Cheer. We send simple, brief, personally written emails at random (a little surprise in your inbox!) just to send some positive energy your way. You can even submit and share your own messages with our users. www.positivecheer.com We would love any and all feedback, do you like our concept? design? font? We wanted to project something more reflective then cheesy. You can also email us at positivecheer@gmail.com or twitter @positive_cheer. Good luck to all you YC applicants! Best wishes always, Positive Cheer Team We used www.kickofflabs.com to set up our site (not affiliated) but it is great with a lot of tools, worth checking out for your startup.

Visit product View on Hacker NewsMar 12, 2012

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Launch Intel predictions

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

90%90% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

best fitHighest predicted score across all platforms for this description.

Product HuntOn track for Day 1 leaderboard · Strong signals: user, inbox, email · Missing: mac, agents, macos

70%70% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

AppSumoStrong fit for a featured deal · Strong signals: users · Missing: plus, platform, intuitive

52%52% predicted probability of success on AppSumo, based on ML models trained on real launch data.

Hacker NewsMay not resonate with HN audience · Strong signals: ide · Missing: https docs, excited, just released

42%42% 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 · Strong signals: personal, users, way · Missing: mobile apps, ios, entrepreneurs

33%33% 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

12%12% 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.

Correct prediction on native model

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