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The Big Little Data Source

In the universe of big data, it is important to take the time to evaluate and review all data sources.  If you are not already, then you need to be in the know about a valuable type of 3rd party data that can easily get overlooked among the many types available.  Imagine a single source of information that provides first-hand individual level insight with over 70,000 data elements.  Yes you heard right, 70,000 data elements.  A data source that is the closest to getting into a consumer’s mind!  What is this source?  I’m talking about Syndicated Research from GfK MRI.  I call it the “Big Little” data source because there are huge insights nicely contained within a manageable universe of 50k records.  This allows for ease of use combined with maximum value.

GfK MRI creates the “MRI File” from its Survey of the American Consumer; a detailed view of 226 million adult consumers in the U.S. – their media choices, demographics, lifestyles and attitudes, along with their usage of almost 6,000 products in 550 categories.  GfK MRI conducts 4 survey waves per year (adults 18+ years drawn across the US from 48 states), then allows companies to license the raw survey data, including respondent name and address, for market research use.  Merkle maintains a “double-base” covering the last 2 years of results updated annually and containing approximately 70,000 data elements.  Included with the file is weighting information to allow you to extrapolate back to the entire U.S. population any counts of interest. 

Let’s look at the MRI File in action…

With 35 different categories of information that can be evaluated, the file provides a very rich profile to understand users of a particular service or product as well as segments created from other sources of information.

For example within the Electronics category there are 1,569 data elements alone.  Under Cellular/Mobile Phones/Smartphones sub-category we find 130 data elements with insight such as how much was spent on a smartphone, what type of agreement was made and what the average monthly bill was.  This may all seem much too specific for your needs, but given how much insight is contained in the file you will be glad for this level of detail when you look for your particular need.  My team has used the file to create a number of derived segments that can more easily be applied to files of interest.

These derived segments provide great information as part of a profile and have proven predictive in a wide range of models.  Through the use of custom profiling tools we can automatically read in and identify the top MRI data elements that differentiate a sample file of interest from the general population.  For example we will look at a client’s best customers compared to the U.S. and see not only how they differ by important demographic information but also learn their media choices and product usage to further help the client understand who these people are.

The MRI file really is the “Big Little” data source that needs to be on your list when looking for valuable sources of insight. 

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