Multi-Grain Audience Indexing
Audience index scores are relative. What they're relative to determines what they actually tell you.
We’re excited to introduce Multi-Grain Audience Indexing, a key upgrade to how audience insights work in AdQuick. Today' we'll go through a brief intro to better understand how it works and the methodology we used to build it.
Audience index scores don't exist in a vacuum. They're always relative to something — and the reference point you choose determines the insight you get.
When AdQuick calculates an audience score for a unit, the process starts at the census Tiger Block Group (TBG) level. The raw score is straightforward: (devices in audience segment within the TBG) ÷ (total devices in the TBG). That ratio represents the true concentration of a target audience in a given geography. What happens next is where grain enters the picture.
Every score is then normalized — ranked against a reference set of other TBGs. The grain is that reference set. Change the grain, and you change what the score is measuring.
Why grain changes the answer
Consider a campaign targeting coffee enthusiasts. At a national grain, every TBG in the country is ranked against every other. A high score in a Los Angeles neighborhood tells you that neighborhood over-indexes for coffee lovers relative to the rest of the country.
But if you're planning a campaign exclusively in Los Angeles, that's not the question you need answered. You need to know which parts of LA concentrate coffee lovers relative to the rest of LA — not relative to neighborhoods in Nashville or Boston. A national normalization flattens the within-market variation that matters most for a market-specific buy.
The insight changes because the reference changes. The right grain is the one that matches the scope of what you're planning.
This isn't an edge case. It's the core planning scenario for any geographically scoped OOH campaign — which is most of them.
Four grains, four lenses
National grain scores units by how their audience concentration compares to every other unit across the country. The right lens for multi-market campaigns where you want to surface the highest-indexing placements regardless of where they sit geographically.
Market (DMA) grain normalizes within each designated market area, scoring units against others in the same DMA. The right lens when you're committed to a market and want to optimize within it — finding the strongest placements relative to the market itself, not the country.
County and City grains pull the comparison closer, ranking TBGs against others within the same county or city boundary. For hyper-local campaigns where neighborhood-level concentration is what matters, these grains surface signals that national and market views would flatten into noise.
Grain is a planning decision and it should match the geographic scope of the campaign you're building.
An audience library built for OOH
Multi-grain scoring applies across AdQuick's full audience library: 126K+ active audiences from Experian, Claritas, Acxiom, Geopath, and Census — with access to thousands more through Liveramp and Transunion/Neustar data marketplace integrations. Search by name, filter by provider or availability status, and add an audience to a plan in a single click.
Once an audience is selected, the heatmap overlays scores directly on the map — coloring each geographic area by how strongly it indexes for the target, on a 1–200 scale. The highest-concentration areas surface immediately. The units sitting inside them are right there to evaluate.
126,000 audiences. Four scoring grains. A heatmap that makes the concentration visible at a glance.
AND/OR logic lets planners combine audiences — reaching the intersection of two segments, or the union across them. The Filter Units toggle removes everything from the map that doesn't meet the audience criteria, leaving only the inventory worth considering.
The audience is the same. The insight depends on the grain.
Audience data is only as useful as the question it's set up to answer. A national normalization answers a national question. A market normalization answers a market question. City and county grains answer questions that neither of those can.
Multi-grain indexing makes that distinction explicit — and gives planners the control to match the scoring logic to the actual scope of the campaign. The result is audience-based OOH planning that's calibrated to the geography that actually matters, not the broadest reference set available.