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 Granularity
 
Leveling the playing field for magazines.

According to a 2008 ANA Accountability Study, 60-70% of advertisers use marketing mix models for allocating media budgets.  Marketing Mix Modeling has traditionally favored television, which reports gross rating points for TV on a weekly basis for local markets--the preferred inputs for most modelers because sales data is also provided on a weekly basis at the local level.

Granularity, a new syndicated product by GfK MRI, now levels the playing field for magazines with local market weekly print data for Marketing Mix Modeling.

With Granularity, modelers and marketers benefit from:
  • Better data--New and better model input resources including years of data from GfK MRI's Market-by-Market Study and the innovative Issue Specific Readership Study.  Better data virtually always leads to more sensitive and complete results, more explanatory power and better measured sales resources.
  • Enhanced modeling--Utilizing GfK MRI's Magazine Audience Accumulation Study (GRPs) to yield a better match between specific media inputs and marketing outcomes.  By improving modeling inputs, modelers eliminate the wide-ranging valuations that result in undervaluring the quality of the creative and the misrepresentation of the contribution of magazines.
  • Improved delivery system--A web portal now provides the ability to make the process of magazine data for Market Mix Modeling more efficient, less labor-intensive and less error-prone.  The Granularity deliverable will not only make these improved data available to modelers, but will also make them extremely easy to accurately input into proprietary systems.
The data is now available to allow magazines to move from a historically weak position to one of strength for Marketing Mix Modeling.

To learn more about Granularity and how it delivers more accurate conclusions about the ROI relationship between print media activity and response metrics download the MPA white paper.  Stay tuned for our Granularity Webcast.

 

 

 

 

 

 

 

 

 

 

 

 
 
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