TMessage – a CHAT app that can organize your work efficiently

Hacker News

Hello HN! I am super pumped to share with you guys about our product in this great community. I wanted to solve a problem that I personally faced. It was about the hassle of juggling between a chat app like Slack and various productivity tools like Trello, Asana, or Notion to deal with different kinds of work-related info. Our team design TMessage to be a chat app, but it can organize all your daily work information efficiently at one place. TMessage is a CHAT app with a built-in calendar. It is the fusion of Slack & Todoist. We name it a Chativity app (Chat + Productivity). Our app organizes your work information in 3 separated categories: Chat, Task, and Wiki. With TMessage, You are no longer worried about distracting or missing any important tasks, plans, or ideas when chatting with your colleagues. Please try our product & tell us how the product can be improved. Thanks

Visit product View on Hacker NewsAug 20, 2023

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Actual performance

1points

Did not reach leaderboard

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

88%88% 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.

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

82%82% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

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

55%55% 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, para · Missing: mobile apps, ios, entrepreneurs

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

AppSumoMay struggle as an AppSumo deal · Strong signals: efficient · Missing: plus, platform, intuitive

30%30% 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, revenue

17%17% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

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

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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