Labor Day Fun Project, Find Reddit Comments to Promote Your Business

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For Labor Day I decided to play with OpenAI APIs and try to ship something (a prototype, a blog post, anything really). Whenever I launched a side project (e.g: https://www.probarsearch.com/ , https://ff.bitlet.org/ ) I realized how bad I am at marketing or even at mentioning my the project to friends/social. I noticed that most of the traffic we got was coming from reddit/HN comments we made where it was reasonable to mention the sideproject/business. Given that, I tried to use OpenAI APIs to do exactly that, given a business/project description, and a list of subreddits, monitor all comments and pick the ones where it makes sense to mention the business/project. While I had the project done in the labor day weekend, I decided to productionize it a bit (really just add a login system and a payment link to cover OpenAI costs) last weekend. If anyone is interested in giving a shot, you can play with it at https://sp.bitlet.org/ . Feedback is always welcome!

Visit product View on Hacker NewsSep 12, 2023

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

82%82% 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: openai, apis, open · Missing: mac, agents, macos

61%61% predicted probability of success on Product Hunt, 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

53%53% 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

45%45% predicted probability of success on AppSumo, based on ML models trained on real launch data.

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

38%38% 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

22%22% 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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