TidyCal

AppSumo

TidyCal is highly praised for its seamless integration with various calendars, user-friendly interface, and capability to book clients, sell packages, and collect payments. However, some users have experienced minor issues with Google Calendar syncing and have noted limited branding options. With an overall rating of 4.3 and positive feedback from 926 users, TidyCal is a solid choice, especially with the 60-day money-back guarantee. It's worth giving TidyCal a try to streamline your scheduling needs.

Visit product View on AppSumoSep 1, 2026

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Actual performance

928reviews

Made the leaderboard

Traction signals

Rating4.3 / 5

Purchases128,979

Launch Intel predictions

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AppSumoStrong fit for a featured deal · Strong signals: friendly, interface, overall rating · Missing: plus, platform, intuitive

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

nativeThis product was originally launched on this platform.

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

75%75% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

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

60%60% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

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

50%50% predicted probability of success on TrustMRR, 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

27%27% predicted probability of success on Hacker News, based on ML models trained on real launch data.

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

18%18% 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

2%2% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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