How Marketing Executives Use Big Data: All Types of Data Sets At the Right Time

I recently spoke with several high level marketing executives about the near-ubiquitous topic, BIG DATA. The executives included Paul Golden, ex-CMO of Samsung Mobile, Barry Judge (ex-CMO of Best Buy, current CMO of LivingSocial, and Brad Todd, (Principal at The Richards Group). Each of the executives with whom we spoke had used all types of data sets in different ways.  Depending on the need of the business, they called on different types of data sets to achieve their purpose.  Given their focus on marketing, the types of data sets tended to be tied to customers.

As a principal at The Richards Group since its inception, Brad Todd has seen a lot of changes in how advertising clients have used data. He recalls the proliferation of data from the introduction and use of loyalty cards at grocery stores. Although grocers captured vast amounts of information about their customers—what they bought, how often they purchased, how they paid—very little of that data was used to improve the customer relationship.  The data was primarily used for managing inventory and shelf space.  Arguably, having fully-stocked shelves does help the customer experience, but the primary use of the data was to improve the bottom line.  Today, grocers and their CPG partners have begun to combine many types of data sets for more targeted marketing.

While CMO of Best Buy, Barry Judge and his team used different types of data sets–purchase history, clickstream analysis, email interactions, demographics and psychographics–to identify and deliver relevant product offerings to their customers.  However, integrating newer analytics tools into legacy systems posed roadblocks.  And incorporating data from the physical store, in order to have a truly holistic picture of each customer, was very difficult.

At Barry’s current company, Living Social, the relative newness of the company and the lack of a physical channel makes it easier to combine data.  They have used customer information to prioritize offers according to each customer’s purchase history and click behavior, thus making the customer experience much more relevant.

Paul Golden, while he was CMO at Samsung Mobile, used big data to improve the brand preference score for Samsung’s mobile phones.  Applying analytics to their big data allowed Paul and his team to identify key markets and determine the most relevant messages for those key markets.

Once you get past the hype and noise, big data can be very useful.  The important thing is to clearly define your objectives and use the data to meet those objectives.

Want to learn more about how to connect different types of data sets? Click here.

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