Revenue clarity, down to the game.
Most publishers know their total ad revenue. We show you which games, ad units, traffic sources, and demand partners are driving it — and which ones aren’t. Demand landscape data draws on the Yolla network’s 72M monthly uniques.
Four questions
most dashboards
can’t answer.
Is Game A or Game B generating more revenue per session?
Most dashboards report at the site level. Revenue attribution by individual game title requires embed-level tracking.
Why did CPMs drop on Tuesday?
Without demand landscape data, it is hard to tell demand-side compression from a floor miscalibration.
Which demand partner is actually winning on mobile?
A fill rate summary by device tells you an impression was served. It does not tell you which demand partner paid for it.
Are you losing revenue from embeds you can't see?
Standard analytics tools often treat cross-origin iframes as black boxes.
These are the questions our dashboard is built to answer.
Four
core views.
Revenue by game, site, and ad unit
Total revenue broken down to the granularity that is actually useful for decisions. Revenue by site, by individual game title within a site, by ad unit within a game, and by embed destination for distributed titles.
For a publisher running 20 game titles across 3 sites with embed distribution across 15 partner platforms, this turns "our revenue is flat" into "our revenue is flat because this specific game's adhesion unit has a low fill rate from one demand partner on mobile."
Demand landscape analysis
Every auction produces data: which partners bid, at what price, and who won. Publishers see demand concentration, floor ceiling effects, and intraday patterns.
Your demand landscape draws on aggregated auction data from across the Yolla network, so you see market-level demand patterns for casual gaming inventory, not just your own slice.
Traffic source revenue attribution
Ad revenue broken out by how the visitor arrived. Organic search, direct, social referrals, and embed partner traffic, matched against CPMs, fill rates, and demand partner performance.
This connects two data sets publishers typically track in isolation. Your SEO team optimizes for sessions. Your ad ops team optimizes for CPMs. We show them what the other is producing.
Embed tracking
Our embed tracker follows the ad tag into iframe and JavaScript embed environments. When your game runs on a third-party site with our ads, the tracker reports impressions, fill rates, and revenue back to your dashboard.
Cross-origin ad attribution needs first-party tracking built into the ad tag at the code level, and that is how ours works.
THE PIPELINE
Built for viral spikes.
Gaming traffic is not linear. A viral moment can multiply traffic in minutes. A pipeline that isn’t built for that can drop events when its queues overflow.
Our pipeline buffers incoming events, normalizes them against each publisher’s data model, and writes to the reporting database. It is designed to absorb spikes rather than drop events.
Near-real-time layer for current performance. Historical warehouse for trend analysis and reconciliation. Publishers do not manage this pipeline. Reports reflect what actually happened, not a sample.
Continuous
ads.txt monitoring.
ads.txt is your declaration of authorized sellers. When an authorized entry is removed or broken without your knowledge, demand partners begin routing around your inventory. CPMs drop. You may not notice for days.
We monitor ads.txt across all publisher domains continuously. When an unauthorized change appears, an alert fires to your dashboard. For publishers with distributed embed networks, this matters more than for single-site publishers.
See exactly where your revenue comes from.
Tell us about your sites. We'll show you what full revenue reporting looks like for them.