A website where people write 200 words every day and improve together

Hacker News

Hello everyone, Last week the Product Hunt Makers Fest happened and I built 200 Words a Day, a community website where people get into a habit of writing and improving together by publishing 200 words per day. I managed to launch a MVP in 5 days and gather 80 subscribers since last week. Full origin story here: https://medium.com/@basilesamel/product-hunt-makers-fest-mak... website: https://200wordsaday.com As you all know, writing is a mandatory skill to have when it comes to grow a business, whether it is through blogging or pitching. I made this product to help you with that. 25 days ago I decided I had to start writing much more, and so I set on a journey to write 200 words every day, published on Twitter. This is how I got the idea for the product. If you always wanted to write or couldn't find a way to keep writing, this is a community for you where you will be able to improve with other fellow writers. I am also posting the best quotes from each 200 words every day on Twitter( https://twitter.com/200wordsaday ), if you had like to read them. Can't wait to read YOU! In the meantime, take care.

Visit product View on Hacker NewsNov 30, 2018

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Hacker NewsStrong engagement from HN community · Strong signals: ide · Missing: https docs, excited, just released

57%57% 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: way · Missing: mobile apps, ios, personal

47%47% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

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

43%43% predicted probability of success on Product Hunt, 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 · Strong signals: subscribers · Missing: arr, mrr, revenue

18%18% 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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