Edworking

Edworking

AppSumo

Customers are all about Edworking, praising its seamless integration of tasks, files, videocalls, chats, workspaces, and stories, making collaboration a breeze. They love the user-friendly interface, prompt support, and the founder's personal involvement.

Customers are all about Edworking, praising its seamless integration of tasks, files, videocalls, chats, workspaces, and stories, making collaboration a breeze. They love the user-friendly interface, prompt support, and the founder's personal involvement. There are a few hiccups like minor glitches and slow speed at times, just small bumps on the road. Weighing the raves against the occasional grumbles, Edworking is hitting the mark and is a solid buy for those in need of an all-in-one productivity solution. And with a 60-day money-back guarantee, it's worth giving it a try.

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Actual performance

117reviews
Made the leaderboard

Launch Intel predictions

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AppSumoStrong fit for a featured deal · Strong signals: friendly, occasional, interface · Missing: plus, platform, intuitive
83%83% 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
72%72% 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, tasks · Missing: mac, agents, macos
70%70% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Strong signals: personal, video · Missing: mobile apps, ios, entrepreneurs
45%45% predicted probability of success on TrustMRR, 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
34%34% 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
10%10% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
BetaListMay not resonate with beta-testers · Strong signals: chat · Missing: web3, crypto, cryptocurrency
1%1% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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