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Exploring Your Data: Brand Affinity
This report is powered by Quantcast's Audience Grid and includes data on this persona's offline purchase behavior in several different categories (such as Automotive, Packaged Goods, etc.).
Data Sources
Reports powered by Quantcast's Audience Grid make use of data provided by one or more data partners. You can find more information about the data partners and how their data is generated here.
Calculations
Composition
The composition value is the percentage of page views generated by visitors who fall into a particular brand segment for this property. We provide you with a page view composition to best represent the composition of potential impressions for users in a given Shopping Interests segment for your property.
Index
The index is a comparison of the audience composition of this property to the Internet population.
For example, if In Market Make & Model > BMW has a 12.24% composition, with an Index of 137:
This means 12.24% of the page views on this property are generated by users in the market for a BMW.
You are 1.37x more likely to have a user who is in the market for a BMW view your property than the average Internet site.
Using This Report
The Brand Affinity report helps you understand the offline purchase habits of a property's audience.
Support Advertising Sales Efforts
By getting a full Brand Affinity profile of your property, you can use Quantcast to validate the shopping behavior of your audience to marketers.
Inform Your Content Creation Strategy
When constructing the story and unique content strategy to pitch to your marketer partner, leverage these data points to validate and inform your creative team on the shopping behavior of users who visit specific properties across your Network.
Methodology
We directly collect anonymous browsing data through the publishers and networks that use Quantcast Measure and have placed our pixel or SDK on their properties. We combine this with anonymous reference data from data partners participating in Quantcast's Audience Grid, allowing our statistical models to accurately infer the media consumption habits of a property's audience in aggregate. Some data in reports may be removed when thresholds are applied to prevent inferring the identity of an individual user (see our privacy policy). When looking at large data sets, we will sometimes use statistical sampling.