I made a ‘no bullshit’ platform for professional communities

Hacker News

"On my way to this job interview, I was right on time when this homeless guy asked for my help. The job interview was for this company I had dreamt of joining for years. But I had to help, so I did, and I was late to the job interview. You won't believe what comes next: when I arrived at the job interview, the homeless guy was actually the manager interviewing me. And I got the job. Stay true to yourself. Peace." This is what LinkedIn has become. It looks like if you want to stand out and passively get opportunities, you need to regularly post that kind of bullsh*t content. What if there was a simple alternative? That's what we tried to do with Profile.studio: a place where anyone can create a private professional network, gather people in it, and search for the right person when there is a need. Test it out and tell me what you think!

Visit product View on Hacker NewsJun 21, 2023

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Actual performance

3points

13comments

Did not reach leaderboard

Launch Intel predictions

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

72%72% 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.

Hacker NewsMay not resonate with HN audience · Strong signals: 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.

AppSumoMay struggle as an AppSumo deal · Strong signals: platform · Missing: plus, intuitive, reviews

46%46% predicted probability of success on AppSumo, based on ML models trained on real launch data.

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

45%45% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

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

42%42% 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: arr · Missing: mrr, revenue, profit

12%12% 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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