I made a fool that finds potential customers for you

Hacker News

Hey everyone! I wanted to share a tool I built to help you quickly find potential customers across social media for your product. It's a really simple concept: you simply paste in your landing page URL, and it shows you highly relevant posts across Reddit (Working to integrate few more) from people who likely need your product or service. For example, if you have a minimal to-do list app, it will show you posts like "Anyone know of a minimal to-do list app?" or "Really starting to dislike how complex Notion is." These posts are from the last 48 hours, updated in real-time, and uniquely tailored to your product. You can then get your product in front of these potential customers by replying or sending a direct message. I’ve found both methods to be successful, depending on the nature of the post. I originally built this for myself to find users for my SaaS. Manually using Reddit advanced filters to search for relevant terms was time-consuming, so I automated the process and sharing here to help you. Replyhub works great for SaaS, consumer products, service businesses, and agencies. It helped me get 1-3 new paying customers per day for my service, and I want it to help you do the same! It's free to try at [1]. Cheers! :) [1] https://replyhub.co

Visit product View on Hacker NewsJun 18, 2024

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

95%95% 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, new, using · Missing: mac, agents, macos

80%80% predicted probability of success on Product Hunt, 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.

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

50%50% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

AppSumoMay struggle as an AppSumo deal · Strong signals: users · Missing: plus, platform, intuitive

42%42% predicted probability of success on AppSumo, based on ML models trained on real launch data.

Acquire.comPre-revenue stage for this audience · Strong signals: saas · Missing: arr, mrr, revenue

20%20% 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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