Finding contractor, the other way

Hacker News

We have all came across looking for service providers, We know about the pain and how much time we spend on doing it when we can spend that time on something more useful. Calling them, getting quote, comparing them, asking for price match and do it all over again and at the end we may not be satisfied. That's why we have invented a new way. Instead of you doing all this work, its easier if you post a request and they come to you (at the end, you are the person who's paying money). You can find by 4 simple steps: 1) Request you service 2) Receive offer from other users 3) Compare price and feedback 4) Accept an offer An the good news is, its all for free: https://lentrak.ca We would greatly appreciate any feedback

Visit product View on Hacker NewsNov 30, 2016

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Actual performance

1points

Did not reach leaderboard

Launch Intel predictions

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

69%69% 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: users, way · Missing: mobile apps, ios, personal

44%44% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

Product HuntUnlikely to reach the leaderboard · Strong signals: user, new · Missing: mac, agents, macos

38%38% 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 · Missing: https docs, excited, just released

35%35% 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: users · Missing: plus, platform, intuitive

31%31% predicted probability of success on AppSumo, based on ML models trained on real launch data.

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

18%18% 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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