LinkedIn alternative About me Profile

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Our platform offers a super exposing Profile and features with you to offer a wide variety of service to your clients or get future clients with impressive options. Your profile has your own domain or sub-domain: http://phpdeveloper.usercv.com http://raven.usercv.com http://freelancer.freelancercv.com You can share your all social media links like: Facebook, Twitter, Instagram, Gothub, StackOverfkow, and other links including email, Skype, WhatsApp, etc., Every profile has an option to list your service, you offer based on your skills and get hired directly inside the platform with project management tool and order tracking page between buyer and sellers as you. Your profile is not limited to service offers, but also can sale ready to use digital non-free products or apps owned by you. At Github, you offer free code, At usercv.com, you offer paid code that are ready to use by clients by just paying and downloading for their use case. On top, you have your own blogging platform to write blogs and attract more users to your profile. E.g, http://freelancer.freelancercv.com/blogs See various Authors blog here - https://freelancercv.com/blogs Your 1 profile has: - Custom domain profile URL - Social media URL showcase - Contact details sharing option. - Service listing option with Project management and Order tracking. - Paid apps hosting solutions (Github solution for paid code hosting) - Personal Blogging platform On top, each profile is optimized for your best local search engine reach to people's around your city and country.

Visit product View on Hacker NewsMar 18, 2021

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

96%96% 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.

AppSumoStrong fit for a featured deal · Strong signals: platform, host, users · Missing: plus, intuitive, reviews

55%55% predicted probability of success on AppSumo, based on ML models trained on real launch data.

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

51%51% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

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

47%47% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

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

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

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

12%12% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

BetaListMay not resonate with beta-testers · Strong signals: paid · Missing: web3, chat, crypto

0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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