I gamified coworker recognition using a reward system

Hacker News

Hello everyone! As a remote software engineer, I often felt disconnected and unrecognized. After talking with colleagues who felt the same, I built a tool to change that. It uses gamification—team members can give recognition, earn points, and collect badges. Leaders can send surveys for feedback, and everyone gets Slack notifications for recognition and surveys. Similar to how language learning apps like Duolingo and Memrise make studying fun by tapping into the brain's reward system, this tool brings that same concept to the workplace. Instead of the old, boring ways of recognizing co-workers, we added a game-like experience, focusing on making recognition more engaging and rewarding. I hope this helps others feel more connected and appreciated. I'd love to hear your feedback! Rami.

Visit product View on Hacker NewsOct 19, 2024

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Product HuntOn track for Day 1 leaderboard · Strong signals: slack, apps, using · Missing: mac, agents, macos

85%85% 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

84%84% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

TrustMRRFits verified-revenue profile · Strong signals: apps, way · Missing: mobile apps, ios, personal

59%59% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

AppSumoStrong fit for a featured deal · Missing: plus, platform, intuitive

54%54% predicted probability of success on AppSumo, 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

32%32% 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

14%14% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

BetaListMay not resonate with beta-testers · Strong signals: reward · 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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