Commented

AppSumo

Customers appreciate Commented for its intuitive and engaging user interface, seamless collaboration, and responsive customer support. Many users highlight the ease of gathering feedback and the fun, engaging nature of the platform. However, a few have mentioned the need for improvements in certain features and responsiveness. Considering the overwhelming positive feedback and high ratings, it's clear that Commented is a valuable tool for anyone seeking efficient collaboration and feedback management for digital products.

Visit product View on AppSumoJan 29, 2024

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Actual performance

15reviews

Did not reach leaderboard

Launch Intel predictions

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

79%79% 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

55%55% 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: user · Missing: mac, agents, macos

51%51% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

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

40%40% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

Hacker NewsMay not resonate with HN audience · Strong signals: lua, ide, 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.

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

11%11% 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.

Incorrect prediction on native model

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