Revmore is an AI-powered platform that optimizes In-App Purchases (IAP) and In-App Advertising (IAA) revenue for mobile apps and games through automated testing and machine learning.
Marketing & Salesrevmore.ioTracked since 2026-08-211 discovery source
544Backlinks
83Referring domains
21Domain authority
-10.3%Referring domains · 90 days
Authority & distribution
How strong is Revmore’s web footprint?
Backlinks measure accumulated distribution; referring domains show how broadly that authority is spread. Both are observable on the open web, so both are published for every product here.
Backlinks
544Current snapshot
Referring domains
83Current snapshot
Authority
21Domain authority · category median 22
90-day move
-10.3%Referring domains, last 90 days
At 21, Revmore sits below the 22 median for its category.
Trajectory · Pro
The counts above are the latest of 370 daily observations. The curve through them is on the full profile.
Traffic makes more sense when you can connect it to the actual product promise.
“Revmore”
Revmore is an AI-powered platform that optimizes In-App Purchases (IAP) and In-App Advertising (IAA) revenue for mobile apps and games through automated testing and machine learning.
Marketing & SalesSeen 2026-08-21 → 2026-08-21Coverage tier C
What we have measured
4 of 8 signal groups are available for this product: identity, authority and backlinks, AI referrals, search demand.
Not measured for this domain: traffic and engagement, audience demographics, country distribution, acquisition mix. Those sections are left out of the page rather than filled with estimates.
Canonical website: https://revmore.io
Observed across 1 discovery source.
Research questions
What the evidence answers about Revmore.
Every answer is tied to a source we collected, and the questions with no evidence behind them are left unanswered rather than guessed.
What problem does Revmore solve?
Revmore solves the problem of optimizing In-App Purchases (IAP) and In-App Advertising (IAA) revenue for mobile apps and games. It uses automated testing and machine learning to increase revenue, as stated in its product description and homepage text.
What features does Revmore offer?
Revmore offers several optimization solutions, including customized package offerings based on machine learning, A/B testing for ad intervals, and SKU price optimization. It provides an integrated AI-driven SDK and an effortless multi-platform infrastructure integration process.
What performance metrics does Revmore claim for its users?
Revmore claims its platform has been associated with 120M user data, 23% revenue growth, and 15% user engagement growth.
What is Revmore used for, and in what situations?
Revmore is used to optimize monetization for mobile apps and games, specifically for growing IAP & IAA revenue. It is applied in situations where developers want to run price A/B tests, improve ad design, optimize ad intervals, or manage hybrid monetization strategies.
Who is Revmore for?
Revmore is for developers and companies that create mobile apps and games, particularly those looking to optimize their revenue through in-app purchases and advertising.
What is Revmore?
Revmore is an AI-powered platform that optimizes In-App Purchases (IAP) and In-App Advertising (IAA) revenue for mobile apps and games through automated testing and machine learning.
Behind the lock
Unlock full Revmore intelligence.
Backlink trajectoryThe figures above are the latest observation. The daily curve behind them holds 370.
AI referral detailHow much traffic assistants send.
Search structure and ranking depthOrganic against paid, brand against non-brand, and how many keywords rank in the top three against the long tail — which is what decides whether the demand is portable or tied to the name.
The rest of the marketPage through every leaderboard 100 rows at a time, put any five products side by side, and query the whole dataset over API / MCP.
Worldwide estimates · Data period 2026-05-01 → 2026-07-31. Figures are measured estimates intended for market research. Signals we have not measured for this domain are omitted, never estimated; a measured zero is still reported as zero. How this was measured