For years, retailers have described customer data as their most valuable asset, yet many businesses still struggle to turn it into actionable insights. 

“Over the last couple of years, it feels like we’ve recognized the [need] to consume that data. Any partner that was available to help consume that data, we latched onto as brands and retailers. It has painted a lot of brands and retailers into a corner of paralysis by analysis. Too much data,” Cory Whitfield, Enterprise VP at Listrak, told Amie Larter, CEO of Inside Retail publisher Octomedia, on a recent episode of the podcast series, Retail Untangled, recorded at Shoptalk Fall in Chicago. 

The problem, according to Whitfield, is not only the sheer volume of data but also where it’s stored: “What am I supposed to do with it? I can’t make it actionable. It’s siloed with all my different vendors.”

While the lack of integration between vendors has historically made it difficult for retailers to connect all their data to personalize the customer experience or gain deeper insights into their business, new technologies are beginning to change the game. 

“With Listrak, for example, what we’re doing is leveraging some AI and some machine learning on the backend to unify all that data,” Whitfield said. 

“So all of those different touch points – thousands of behavioral touch points across the journey – now we’re able to unify those, add some AI to stitch them together [and] present them to marketers in a more actionable way.”

By understanding how an individual customer has interacted with their loyalty program and seeing what they’ve searched for on their website, retailers can build a more complete picture of that customer’s wants and needs and create a more intentional marketing message. 

‘Not good enough to have a great product’

While the opportunity for retailers to unify and action their customer data is clear, the risks of not doing so are even more significant. 

“If we’re not being very intentional with collecting that data and using it to be personalized, then we risk a seamless experience on site,” Whitfield said. 

“We risk being [in]authentic with our consumers. We risk losing market share to competitors that might be selling our own products through marketplaces and other sites just because they are being more precise and targeted. They may have a better rewards program. It’s not good enough anymore to have just a great product.”

He compared it to the SEO boom when retailers could no longer afford to simply build a great website; they had to use SEO to drive customers to their site. Now, retailers can no longer afford to simply drive customers to their site, they need to provide a personalized, engaging and authentic experience when customers get there. 

To make this happen, he said, retailers need to have a strong first-party data acquisition strategy since the use of third-party data has become increasingly regulated. 

“I think there’s an opportunity to be a little bit more targeted,” Whitfield said. “If you’re going to ask somebody for their first-party data and get them to consent or opt-in, which is what we do when we’re getting email addresses for collection and SMS and mobile numbers, you have an opportunity to be so personalized and understand where that traffic is coming from.” 

For example, if a customer lands on their website via an influencer, content creator, or affiliate, retailers could lean into that relationship to encourage them to sign up for email communications. 

“Something as simple as, ‘Sign up for email and stay more in touch with X influencer’s favorite products. We know they’re going to have a much higher propensity to consent,” Whitfield said. 

What the future holds

In some ways, the future of data-driven marketing in retail doesn’t look that different from today. 

“Ten years ago, we were talking about ‘right channel, right time, right message’. We’ve been talking about data unification and personalization for years, and I think that’s what we’re still going to be talking about in the future,” Whitfield said. 

The difference is that retailers now have access to advanced technologies like AI and machine learning that can help solve the problem of too much customer data dispersed across many different platforms. 

“What is the right message? What is the right channel? How do we know who that person is? I think AI and machine learning are going to help us be more immediate, real-time and personalized,” Whitfield said. 

• Listen to the podcast to hear Whitfield talk about the customer data gap, how retailers can improve their first-party data acquisition strategy and the future of data-driven marketing in retail.