Venue visitor patterns worldwide - API platform

TrustMRR

Global Foot Traffic (Venue Visitor) data platform. Helps to find lively social scenes efficiently, avoid crowds, automate city guides, or optimize visitor schedules. It forecasts hourly busyness for millions of public places. Using anonymized GPS data, it shows venue visitor patterns and peaks. Includes tools to analyze and filter countries/ cities/ neighborhoods on (live) visitor patterns, venue type, ratings, visit duration, popularity, etc. Includes API to build 3rd party apps on top of it.

Visit product View on TrustMRRMay 1, 2020SaaS B2B stripe

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Actual performance

139customers

$8,947MRR/mo

Made the leaderboard

Traction signals

Domain Rating46

MRR growth 30d+17.8%

Launch Intel predictions

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

75%75% predicted probability of success on Indie Hackers, 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 · Missing: mobile apps, ios, personal

66%66% predicted probability of success on TrustMRR, 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: apps, using · Missing: mac, agents, macos

63%63% 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: ide, io · Missing: https docs, excited, just released

49%49% predicted probability of success on Hacker News, based on ML models trained on real launch data.

AppSumoMay struggle as an AppSumo deal · Strong signals: platform, efficient · Missing: plus, intuitive, reviews

43%43% predicted probability of success on AppSumo, based on ML models trained on real launch data.

Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue

19%19% 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

8%8% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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