Sprynkl – The simplest feedback app for everyone

Hacker News

Hi all, We built a free app ( https://www.sprynkl.io/ ) to help working professionals give and receive feedback from their team in a few seconds so that they improve their skills and eventually build a better teamwork. What does Sprynkl do: Proactively get feedback on what you are good at and what you should improve Openly or anonymously give feedback to others using our pre-made templates or create your own ones Get pro tips on how to develop on specific skills Thanks your teammates for their excellent work or support We are still in beta, and, of course, we are self-taught, so there are probably lots of unfound bugs. We are looking for comments/suggestions on what we can improve or tweak to make it better! We hope you give Sprynkl a try ;)

Visit product View on Hacker NewsSep 3, 2019

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

75%75% 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

64%64% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

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

60%60% 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 · Missing: plus, platform, intuitive

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

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

36%36% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

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

19%19% 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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