Stepsy

AppSumo

Customers appreciate Stepsy for its simplicity, time-saving capabilities, and effective documentation creation. The tool's ease of use, quick process, and Google Docs integration are the top positives. Some users have noted limitations with desktop app recording and minor technical glitches. Despite these, Stepsy is a solid buy, especially with its 60-day money-back guarantee. Give it a try and streamline your documentation process with Stepsy.

Visit product View on AppSumoApr 28, 2023

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Actual performance

48reviews

Did not reach leaderboard

Traction signals

Rating3.9 / 5

Purchases3,152

Launch Intel predictions

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

71%71% 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: google, user · Missing: mac, agents, macos

63%63% 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

62%62% 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

44%44% 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, users · Missing: mobile apps, ios, personal

42%42% 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

13%13% 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

1%1% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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