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ChattySurvey – Super easy AI powered conversational surveys

Hacker News

ChattySurvey – Super easy AI powered conversational surveys

My name is Richard D'Lonesteen I'm the CTO of ChattySurvey. This is the 6th startup idea I'm working on in the last 12 months. In a way, it was born because of the pain of doing MOM tests and understanding how tricky it can be to create good surveys and conduct them without falling for the flattery trap. We are building perhaps the simplest to create surveys in the world(let me know if I'm wrong). Currently, you can get super powerful(NPS, CSAT, PMF etc..) surveys just by filling out 1 text field with the name of the subject. We are leveraging GPT to conduct the surveys and analyse them. And so far it's doing an unbelievable job, but don't take my word for it - check it out! We are looking for pilot users and problems that we can help to solve! Thank you!

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Actual performance

3points
2comments
Did not reach leaderboard

Launch Intel predictions

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Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting
88%88% 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 · Missing: mac, agents, macos
60%60% predicted probability of success on Product Hunt, 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
50%50% 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, users, way · Missing: mobile apps, ios, personal
43%43% 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
33%33% 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
18%18% 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, cryptocurrency
1%1% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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