Forento

AppSumo

Forento has received positive feedback from customers, who appreciate its user-friendly interface, comprehensive LMS features, and responsive customer support. While some users have mentioned limited payment integrations and additional fees for certain core functions, overall, Forento is a solid choice for individuals looking to launch courses, sell e-books, or offer coaching sessions. With a 60-day money-back guarantee, it's worth giving Forento a try.

Visit product View on AppSumoApr 22, 2023

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Actual performance

112reviews

Made the leaderboard

Traction signals

Rating4.8 / 5

Purchases9,073

Launch Intel predictions

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

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

78%78% 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

72%72% predicted probability of success on Product Hunt, 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

41%41% predicted probability of success on Hacker News, based on ML models trained on real launch data.

TrustMRRLess likely to generate early MRR · Strong signals: users · 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

17%17% 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

7%7% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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