At one point or another, we’ll find ourselves staring into an auto mechanic’s garage. I remember the first time I looked into one, I was amazed. Taken aback really. It seemed like there were tools from floor to ceiling. I found myself wondering if they even knew how to use each tool. How did they decide which tool to use for which job? But after a few moments watching, you see each mechanic in action, grabbing, using, and seamlessly switching, and you realize they are all part of a plan.
Today, marketers face their own garages every day, but instead of tools, they see data. As tools are to the mechanic, so data should be to the marketer. There are all different types of data, because different data serves different purposes and solves different problems. Like a mechanic, a skilled marketer knows when and where to wield each tool, accessing data strategically to solve problems.
And there’s a hell of a lot of data out there to master. Brands and publishers are able to access vast resources of customer data, supplementing basic demographics with further insights into buyer behavior. But it’s not just about where to find or buy the data—it’s about cultivating an organizational understanding and unified approach to knowing where and when each set of data can best assist. As Charlie Shin, VP of Data Strategy & Analytics at Major League Soccer, says,
“The organizational culture surrounding the data (sets) can dramatically accelerate the application of data and analytics and really amplify its power.”
When relying on data for guidance, an organization must also develop a data culture in orer to maximize the potential from its investment. Similar to tools in a garage, each data set has its own unique purpose and advantages, and proper utilization will deliver the most effective results. First-party data, such as transactional purchase data, can allow marketers to track customer loyalty, and with the right massaging, aid in predicting future buyers and viewers. Second-party data can fill in the blanks and further assist in behavioral prediction. For example, Major League Soccer uses second-party data from their partnership with video game publisher EA to identify gamers who selected MLS as their favorite team. Third-party data fills in further blanks, cookie data assists in remarketing, mobile IDs can provide location signals, and social data can help marketers put together a 360º picture of an individual’s interests or purchase intent across multiple categories or industries. Each data set has a specific strength and role, from fine-tuning targeting to overhauling outreach. And as a seasoned mechanic instinctively reaches for the right tool, a data-driven marketer knows the right set of data and the right application.
It is important to realize that there isn’t a generalized template for campaign success—Rachel Herbstman, VP Platform Analytics at Cadent, notes,
“What works for one brand is not necessarily going to work with another brand, even in the same category.”
Buyers vary greatly from brand to brand, regardless of vertical, but the multitude of different data sets, and in some cases the ability to combine more than one data set, marketers are able to build a cohesive view of specific audiences regardless of brand, category, or vertical.
We recently took part in this conversation during the NATPE Analytics and Addressability Conference. Click the video below to view our full panel discussion on demystifying data by developing internal standardizations and applications for approaching it.
There’s great power in data, but also great responsibility in structuring organizations to properly apply it. Empowering every level of an organization with easily understandable definitions of the benefits of each type of data can help with faster adoption which can lead to more advanced strategies and higher returns on investment.