Produktly

TrustMRR

SaaS for building product tours that improve onboarding, product adoption and retention. Customers can build engaging in-app product tours using our no-code editor and integrate those into their own websites/apps. We offer differently priced plans that are billed either monthly or yearly. So customers are charged when they choose a paid plan, and then either monthly or yearly as long as they stay active.

Visit product View on TrustMRRApr 10, 2021SaaS Software B2B

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Actual performance

49customers

$1,962MRR/mo

Made the leaderboard

Traction signals

Domain Rating45

MRR growth 30d-30.3%

Launch Intel predictions

Analyze your own launch →

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

84%84% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

best fitHighest predicted score across all platforms for this description.

TrustMRRFits verified-revenue profile · Strong signals: apps, month, monthly · Missing: mobile apps, ios, personal

67%67% predicted probability of success on TrustMRR, 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

59%59% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

Hacker NewsStrong engagement from HN community · Strong signals: io · Missing: https docs, excited, just released

56%56% predicted probability of success on Hacker News, based on ML models trained on real launch data.

Acquire.comPre-revenue stage for this audience · Strong signals: saas, active · Missing: arr, mrr, revenue

28%28% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive

20%20% predicted probability of success on AppSumo, based on ML models trained on real launch data.

BetaListMay not resonate with beta-testers · Strong signals: paid · Missing: web3, chat, crypto

16%16% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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