MySellerBot – Bot that answers 100s of questions without any training

Hacker News

Hi all! MySellerBot is a bot that can be setup with 5 minutes to answer 100s of technical questions about a particular domain. You don't need to type a single training sentence (unlike Dialogflow and the likes) It has pre-trained models for: 1. Electronics 2. Sports and Outdoors 3. Beauty 4. Health and Personal Care Demo for Electronics: https://mysellerbot.com/demopage?acc=YiuvVVUVzRgZeBoqbRLIOCK... Demo for Sports and Outdoors: https://mysellerbot.com/demopage?acc=UPBYLOUkmEAyzxiYhlVjnET... I decided to build this after a client bailed on a Dialogflow deal. The bot I spent 3 months to setup and provided 1000s of training sentences for, failed to answer some 20 questions it was trained to handle. MySellerBot instead just takes 5 minutes to answer 100s of questions from any of the above domain. Please offer me your feedback!

Visit product View on Hacker NewsFeb 14, 2019

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Actual performance

4points

9comments

Did not reach leaderboard

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TrustMRRFits verified-revenue profile · Strong signals: personal, month, answers · Missing: mobile apps, ios, entrepreneurs

67%67% predicted probability of success on TrustMRR, 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

55%55% 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, intuitive

43%43% predicted probability of success on AppSumo, based on ML models trained on real launch data.

Hacker NewsMay not resonate with HN audience · Strong signals: ide, 000, io · Missing: https docs, excited, just released

40%40% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

Product HuntUnlikely to reach the leaderboard · Strong signals: model, models, single · Missing: mac, agents, macos

34%34% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

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

22%22% 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

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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