Eventin - Plus exclusive

AppSumo

Customers appreciate Eventin - Plus for its user-friendly interface, comprehensive features, and continuous updates. Some minor drawbacks include occasional delays in customer support and limited video tutorials. Despite this, the product has an overall rating of 4.7 and positive feedback from 39 reviews. With a 60-day money-back guarantee, it's worth giving Eventin a try for managing events and selling tickets on WordPress.

Visit product View on AppSumoApr 3, 2024

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Actual performance

40reviews

Did not reach leaderboard

Traction signals

Rating4.3 / 5

Purchases1,727

Launch Intel predictions

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

87%87% predicted probability of success on AppSumo, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

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

73%73% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

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

67%67% 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: 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.

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

29%29% 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

20%20% 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

12%12% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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