Po

Post from Gmail to Your Blog

Hacker News

Post from Gmail to Your Blog

I made a tool to let you create a blog and post to it using your gmail. What’s unique is that your can attach downloadable content to it to share worksheets, PDFs, or other such extras (maybe class assignments?) which your readers can download and use locally. Link = https://moogle.cc How it works - * You sign up for Moogle * Get yourself a blog on a sub domain of moogle.cc * Write your post in Gmail. Include inline images, use different fonts and sizes allowed by Gmail * Email your post to blogpost @ moogle.cc * Some admin stuff explained @ https://moogle.cc/blog/post/1v6ouq/getting-started-with-moogle * And voila! Your post is live! Why did I make this? I hate writing posts in markdown so I was getting frustrated with my old blog which followed the .md—>GitHub —> blog route. This method reduces the friction involved in blogging. Examples of the generated blog posts —> https://moogle.cc/blog/

Visit product View on Hacker NewsJun 4, 2021

Actual performance

7points

6comments

Made the leaderboard

Launch Intel predictions

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

56%56% 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 · Strong signals: started · Missing: supports, reddit linkedin, podcasting

56%56% 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

51%51% 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

43%43% predicted probability of success on AppSumo, based on ML models trained on real launch data.

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

41%41% 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

13%13% 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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