Using Big Data in Retail: The CMO’s Resolution

As 2013 begins to ramp up, Big Data is a topic that’s on many marketer’s minds.

In fact, it’s the number one key change that keeps marketing executives up at night. More than 70 percent of CMOs said they felt most underprepared to harness the power of the explosion of data to make intelligent marketing decisions, according to a recent IBM survey of 1,700 chief marketing officers.

The Omni-Channel Shopping Revolution

Retailers know that shopping is no longer a linear process. Before the rise of Big Data, business intelligence decisions were made from significantly smaller amounts of structured data from past customer interactions.

But today, there’s been an explosion of data. In fact, every day we create 2.5 quintillion bytes of data. Think of it this way: We create as much information in two days as we did from the dawn of civilization up until 2003, according to Google’s executive chairman Eric Schmidt.

In marketing, this data is coming from a proliferation of consumer touchpoints that include the web, social media, call centers, point-of-sale, mobile, and transactional data. When this data is analyzed together in real time, insights can be garnered that can actually predict consumer behavior, among other key benefits.

Using Big Data strategically is an unlocking move for brick-and-mortar retailers looking to compete against online retailers. Retailers are combining sets of data in real-time from social listening platforms, loyalty programs, competitors and transactions to create promotional campaigns with improved targeting and reach. For consumers, this means more relevant marketing messages, more competitively priced products and an improved shopping experience, both online and in store.

Brick-and-mortar retailers even have access to advanced in-store analytics through companies like RetailNext and Immersive Labs.

Immersive Labs’ facial recognition technology (FRT), called CARA, can even tell retailers the gender, age, attention time, and traffic patterns of their customers.

This data, combined with information from other channels, helps retailers understand and predict consumer behavior.

Data-Driven Discovery

Big Data has brought about a shift in retail toward data-driven discovery and decision making. According to research from Edgell Knowledge Network (EKN), 60 percent of retailers are initiating strategies aimed at harnessing the power of Big Data.

However, only 47 percent of retailers are clear about the implications of Big Data for their businesses. Overwhelmed with data, retailers of all sizes are fumbling to find the right way to integrate data into their marketing decisions.

The CMO’s Resolution: Use Big Data Strategically

To stay ahead, marketers need to focus on using Good Data rather than Big Data, according to Justin Goodman, a speaker at last month’s Dallas Digital Summit.

Good Data is based on a framework designed to help you understand how each marketing activity is performing based on key business objectives, Goodman says. “If you are measuring everything for all people and all things, you are simply spreading inefficiency through data.” Good Data is organized, actionable, and valuable.

Start by identifying your current and potential data assets, their maturity, and how they impact key areas of opportunity: segmentation, marketing, promotions, and pricing. Tie your business objectives to your data strategy. Keep data as simple and scalable as possible. Consistently test, measure, and optimize. Create actionable insights based on the data in real time. Don’t assume you can do it all yourself; hire internal talent or work with reputable data vendors.

Lastly, don’t discount the importance of intuition and experience when factoring data into decision making. Data can often dehumanize consumer behavior. In the end, it’s about fostering a deeper understanding of the consumer in service of increasing conversions.