Automated lead gen generator for SaaS

Hacker News

Hey HN, I'm a bootstrap SaaS founder that trying to grow my micro SaaS. I've been doing pivot many times and this may be the last straw. I realized that marketing and sales are key in building business but cold outbound is suck! So I built a tool to help SaaS founders identify unhappy customers from their competitors to pitch their SaaS. This feature is specifically requested by Peer - Cal.com CEO from my interaction with him here - https://x.com/heykaiyo/status/1821216800610382013 I hope this small tool would be helpful. Would love your feedback pls. Anyone interested to get early-bird access, please buy a small fee for just $29/month here: https://buy.stripe.com/3cs5opbycfDBbO814j I'm trying to validate the idea and keep the lights on for my small business.

Visit product View on Hacker NewsAug 19, 2024

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

90%90% 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 HuntUnlikely to reach the leaderboard · Strong signals: stripe · Missing: mac, agents, macos

50%50% 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

42%42% 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 · Missing: plus, platform, intuitive

39%39% predicted probability of success on AppSumo, based on ML models trained on real launch data.

TrustMRRLess likely to generate early MRR · Strong signals: month · Missing: mobile apps, ios, personal

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

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

21%21% 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.

Incorrect prediction on native model

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