A Tool for Gathering Genuine Product Reviews from Reddit and YouTube

Hacker News

I wanted to share a side project I've been working on: http://webpulse.today/review-waitlist A tool that gathers genuine feedback on any product by analyzing discussions from Reddit and YouTube. It provides in-depth analysis results, please check examples below: - Ray-Ban Meta Smart Glasses: http://webpulse.today/review-waitlist?u=Ray-Ban%20Meta%20Sma... - Black Myth: Wukong: http://webpulse.today/review-waitlist?u=Black%20Myth:%20Wuko... - Toyota GR86: http://webpulse.today/review-waitlist?u=Toyota%20GR86&f=y - Llama 3.1: http://webpulse.today/review-waitlist?u=Llama%203.1&f=y In today's world, it can be tough to find trustworthy reviews. Personally, I find myself relying more on Reddit and YouTube for authentic opinions, especially since search engines like Google are often cluttered with click-driven results and sensational headlines. With that in mind, I built this tool to make it easier to access the kind of feedback I trust the most. It's still in beta, so please bear with me if it’s a bit slow or unstable. I would greatly appreciate any thoughts or feedback you might have—your input will help me improve it. Thanks for taking the time to check it out!

Visit product View on Hacker NewsAug 28, 2024

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

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best fitHighest predicted score across all platforms for this description.

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

66%66% 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: llama, ide, io · Missing: https docs, excited, just released

47%47% 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 · Strong signals: reviews · 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: personal, google · Missing: mobile apps, ios, entrepreneurs

22%22% 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 · Strong signals: smart · 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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