IndieHackers stopped their podcast so I started my own

Hacker News

I started "Founder Stories with Priyanka" to continue the legacy of the Indie Hackers podcast and learn from bootstrapped founders. Each episode dives into: -The story behind their product ideation & getting their first few customers -Unconventional growth strategies -Practical conversion tactics -Raw truths about the bootstrapping journey(life lessons) As someone from a non-tech background, I created this podcast to gather and share insights on launching and growing profitable businesses without external funding. I'm Priyanka, the host. AMA about the podcast or the founders' stories! You can watch full video interviews on youtube here: https://www.youtube.com/@priyankaprasad25

Visit product View on Hacker NewsAug 28, 2024

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

83%83% 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.

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

44%44% predicted probability of success on TrustMRR, 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

44%44% 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: host · Missing: plus, platform, intuitive

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

Product HuntUnlikely to reach the leaderboard · Missing: mac, agents, macos

28%28% 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: profit, profitable, growth · Missing: arr, mrr, revenue

27%27% 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.

Correct prediction on native model

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