SiteBehaviour

AppSumo

Customers appreciate SiteBehaviour for its intuitive dashboard, quick setup, and performance-friendly tracking. Some mention minor issues like delayed support and missing features.

Customers appreciate SiteBehaviour for its intuitive dashboard, quick setup, and performance-friendly tracking. Some mention minor issues like delayed support and missing features. With an overall rating of 4.0 from 79 reviews, it's a solid buy, especially with the 60-day money-back guarantee. Give it a try and simplify your campaign tracking with this alternative to Google Analytics.

Visit product View on AppSumoAug 25, 2025

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Actual performance

85reviews

Made the leaderboard

Launch Intel predictions

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

84%84% 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.

AppSumoStrong fit for a featured deal · Strong signals: intuitive, reviews, friendly · Missing: plus, platform, host

70%70% 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

58%58% predicted probability of success on Indie Hackers, 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

35%35% predicted probability of success on Hacker News, based on ML models trained on real launch data.

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

33%33% 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

10%10% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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