Tricer
TrustMRRTurn boring Scrum tasks into a game. Tricer tracks time automatically in the background, captures quick notes for your daily, and brings teams together with AI-powered, gamified retros. Track time, vo
Turn boring Scrum tasks into a game. Tricer tracks time automatically in the background, captures quick notes for your daily, and brings teams together with AI-powered, gamified retros. Track time, vote poker stories, and grow your team Dino!
Share cardActual performance
1customers
$19MRR/mo
Did not reach leaderboard
Traction signals
Domain Rating5
Launch Intel predictions
Analyze your own launch →
Product HuntOn track for Day 1 leaderboard · Strong signals: tasks, notes · Missing: mac, agents, macos76%76% 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, podcasting63%63% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
TrustMRRFits verified-revenue profile · Missing: mobile apps, ios, personal52%52% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
Hacker NewsMay not resonate with HN audience · Missing: https docs, excited, just released29%29% predicted probability of success on Hacker News, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive28%28% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue17%17% 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, crypto15%15% predicted probability of success on BetaList, based on ML models trained on real launch data.
Incorrect prediction on native model
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