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Stop repetitively typing times slots for meetings

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Stop repetitively typing times slots for meetings

I built this Chrome Extension because I was wasting minutes typing time slots when trying to schedule meetings. It all boiled over when I was trying to schedule meetings with a prospect that had teams in San Francisco, Berlin, and Bangalore (while I'm in Denver). I know scheduling links (like Calendly) are common today, but often scheduling meetings still depends on written time slots. Those situations are when this extension is useful. Specifically, the extension generates written time slots from selections on your Google Calendar and saves them to your clipboard, saving you time from the repetitive task of writing out meeting times. It formats multiple time slots in an easy-to-read, ascending order. And you can adjust the time zone by typing and selecting any city (with >40k population) worldwide.

Visit productView on Hacker NewsDec 7, 2023
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4points
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Launch Intel predictions

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Product HuntOn track for Day 1 leaderboard · Strong signals: google · 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
54%54% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive
42%42% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Hacker NewsMay not resonate with HN audience · Strong signals: ide, io · Missing: https docs, excited, just released
40%40% 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: google · Missing: mobile apps, ios, personal
39%39% 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
24%24% 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
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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