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Better lead generation and business networking

Hacker News

Better lead generation and business networking

We want to help connect business people more efficiently, whether they are looking to connect to buy/sell something, or, to find/offer a job. We believe that the traditional methods for making these connections — telemarketing, schmoozing with people at unfocused networking events, blasting emails to 'opt-in' email lists from questionable sources, or, spamming via social media — are inefficient. We want to connect people using the oldest and the most trusted method: word-of-mouth, but with a twist. We discover hidden connections between people to connect people using small, invite-only, focused, word-of-mouth referrals. You expand your network slowly but ethically, without creating any unnecessary spam in this world. Come join us at <a href="http://threetincans.com">http://threetincans.com</a> to expand your business network.

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Actual performance

1points
Did not reach leaderboard

Launch Intel predictions

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TrustMRRFits verified-revenue profile · Missing: mobile apps, ios, personal
52%52% 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 · Strong signals: efficiently · Missing: supports, reddit linkedin, podcasting
51%51% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Strong signals: efficient · Missing: plus, platform, intuitive
47%47% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Product HuntUnlikely to reach the leaderboard · Strong signals: email, using · Missing: mac, agents, macos
33%33% 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: io · Missing: https docs, excited, just released
30%30% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue
15%15% 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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