This report includes data on this persona's offline purchase behavior in several different categories (such as Automotive, Packaged Goods, etc.).
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Data Sources
These reports make use of data provided by one or more data partners. You will see the names of the data partners at the top right hand corner of the reports.
Calculations
Composition
The composition represents the percentage of page views generated by visitors who fall into this property's particular Shopping Interests segment. We provide you with a page view composition to best represent the composition of potential impressions for users in your property's given Shopping Interests segment.
Index
The Index is a comparison of the audience composition of this property to the Internet population.
For example, if the In Market Make & Model > BMW shows a 22.88% composition, with an index of 258:
22.88% of the page views on this property are generated by users in market for a BMW.
You are 2.58 times 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 Shopping Interests report helps you understand the offline purchase habits of a property's audience.
Support advertising sales efforts
By getting a full profile of the Shopping Interests of your property's users, you can use Quantcast to validate the shopping behavior of your audience for marketers.
Inform your content creation strategy for reaching this audience
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 on their properties. We combine this with anonymous reference data from data partners allowing our statistical models to accurately infer the shopping 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.