I built the TrustPilot alternative for freelancers

Hacker News

Hey! I'm Buzz, here's my story: I've been a freelance Web Developer for around 3 years now, and I've noticed so many instances where other freelancers are struggling to keep ALL of their reviews from different websites and platforms such as Upwork, Fiverr, Discord etc in one place. I saw people screenshotting them and putting them in a "reviews" Discord channel, which is just super messy. So - I built the solution, Vouchley. Vouchley is a platform where you can super easily collect vouches and reviews from your customers as a freelancer. You can import reviews from other platforms, add dynamic widgets to your website, use the free API, add the Discord bot to automatically post new reviews, and tons more. At the moment, I've managed to gain over 2,000 users who use Vouchley as a freelancer. I'd love to hear your feedback on the platform, so please let me know what features/changes you think might improve Vouchley.

Visit product View on Hacker NewsApr 25, 2024

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Product HuntOn track for Day 1 leaderboard · Strong signals: user, new · Missing: mac, agents, macos

89%89% predicted probability of success on Product Hunt, 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 · Missing: supports, reddit linkedin, podcasting

73%73% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

Hacker NewsStrong engagement from HN community · Strong signals: 000, 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: platform, reviews, users · Missing: plus, intuitive, host

50%50% predicted probability of success on AppSumo, based on ML models trained on real launch data.

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

49%49% 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

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.

Incorrect prediction on native model

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