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RealFeedback – ChatGPT-powered bot for genuine user feedbacks
Hacker NewsRealFeedback – ChatGPT-powered bot for genuine user feedbacks
Hello Hacker News community! My name is Laszlo and I am the creator of RealFeedback. RealFeedback is a ChatGPT-powered chatbot for websites, designed to collect user feedback conversationally. Easily embedded via script tag, it appears as a chat bubble, providing website owners with useful insights based on user interactions. Give RealFeedback a try and let me know what you think!
Share cardActual performance
3points
Did not reach leaderboard
Launch Intel predictions
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Product HuntOn track for Day 1 leaderboard · Strong signals: user, new, chatgpt · Missing: mac, agents, macos76%76% 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, podcasting72%72% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive35%35% 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, personal35%35% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Hacker NewsMay not resonate with HN audience · Strong signals: hacker news, io · Missing: https docs, excited, just released30%30% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue13%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: chat · Missing: web3, crypto, cryptocurrency12%12% predicted probability of success on BetaList, based on ML models trained on real launch data.
Correct prediction on native model
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