LinkedIn profile replacement and resume builder

Hacker News

Are you tired of being spammed by recruiters, having your personal information sold to strangers, and being forced into yet another news feed? We are, and that's why we built Standard Resume. Standard Resume imports your LinkedIn profile in one click and creates a web and PDF resume for you. The web resume works as a replacement for your LinkedIn profile for things like HN Who's hiring, informal referrals, and linking to from your personal website or GitHub profile. Our resume templates are professionally designed, and are reviewed by tech hiring managers. We also have a few monospace templates for developers. Check it out and let me know what you think. We are iterating on the product and are open to feature suggestions. Homepage: https://standardresume.co/ Example: https://rsm.io/rileyt

Visit product View on Hacker NewsJul 14, 2020

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Actual performance

6points

1comments

Did not reach leaderboard

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

70%70% 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 HuntOn track for Day 1 leaderboard · Strong signals: new, open · Missing: mac, agents, macos

60%60% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

Hacker NewsStrong engagement from HN community · Strong signals: io · Missing: https docs, excited, just released

52%52% 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: builder · Missing: plus, platform, intuitive

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

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

32%32% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

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.

Incorrect prediction on native model

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