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Replyt – Track which Reddit discussions become customers

Hacker News

Replyt – Track which Reddit discussions become customers

I kept finding Reddit threads where people were discussing problems my products solved, usually weeks after the discussion happened. Even when I joined those conversations, I had no idea whether they led to anything. A signup? A paying customer? Nothing? So I built Replyt. Replyt continuously watches Reddit for discussions related to a product, surfaces relevant conversations, and helps engage through public replies or contextual DMs. What became interesting was not finding the conversations, but measuring them. Replyt tracks visits, signups, and paying customers back to the Reddit discussions that generated them. Some threads continue bringing traffic months later because they rank in Google, so those are tracked too. Every reply and DM is reviewed before being sent. Nothing is posted automatically. There's a live scan on the homepage if you'd like to try it without creating an account. I'm using Replyt to grow Replyt itself and would love feedback, especially from people who have used Reddit to find early users or customers. Happy to answer any questions.

Visit productView on Hacker NewsJun 25, 2026
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Actual performance

4points
1comments
Did not reach leaderboard

Launch Intel predictions

Analyze your own launch →
Product HuntOn track for Day 1 leaderboard · Strong signals: google, user, context · Missing: mac, agents, macos
80%80% 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 · Missing: supports, reddit linkedin, podcasting
61%61% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
Hacker NewsMay not resonate with HN audience · Strong signals: ide, io · Missing: https docs, excited, just released
49%49% 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: month, google, users · Missing: mobile apps, ios, personal
46%46% 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
45%45% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue
28%28% 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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