There is no question that we live in a data-fueled marketplace, and no better illustration of how the retail landscape has changed than the fact that Walmart employs more data scientists than NASA. They are not just interpreting the vast data signal from online behavior and loyalty app purchases, they are examining the entire business from the aisle to the parking lot — and everything in between.
Welcome to the new reality. What’s happening at the largest retailers is merely a reflection of a sea change in the marketplace — one that will lead to extinction for retailers and brands that fail to adapt and change. This demanding new landscape was created by three major forces that retailers must embrace to serve: data convergence and connection, machine learning and personalization at scale.
Converging And Connecting Data
Unleash The Machines
The thing about big data is that it’s, well, big. The kinds of powerful insights within are well beyond the reach of mere one-off queries. Given the sheer volume, complexity of data relationships, rate of change and the need for automated solutions, advanced retailers are turning to machine learning. To do this, however, we have to acknowledge that this does not require less expertise, but more. In order to compete and grow, retailers must establish modern data management capabilities that enable them to discover, make better decisions, learn faster and serve the customer better.
The goal of any machine learning-driven program should be to anticipate customer needs and do so at scale. For example, retailers don’t just need to know who customers are and what they’ve bought, they need to leverage insights based on everything from where they had lunch to what happened five minutes ago. That’s a level of relevancy we can and must achieve. Right now, Netflix knows what movies you’re going to like, Spotify identifies the music you prefer and large retailers like Target and Walmart know what you need as you need it. To survive in the 21st century, retailers must be able to see and act on this increasingly precise set of insights and preferences — on the fly — and at scale.
Staff Up Or Find The Right Partner
For all we hear about small, disruptive brands, the convergence of data, machine learning and scalable personalization benefits the large at the expense of the small. The proliferation of platforms makes it difficult for midsized or regional brands to meet all the requirements of the challenge. Larger companies can staff up to meet the demand. Small and mid-sized ones must partner with consultancies or agencies that have the data and analytical firepower — as well as commerce capabilities — to get it right. Just be sure that whoever you contact has a good and long track record of success — and is a partner you can trust.
No one likes to talk about existential threats or extinction events, but the stakes today are incredibly high and the skills are material. While the forces reshaping the retail landscape provide better, more personalized experiences for the consumer — they also place increased demands on everything from the storefront to the supply chain. By embracing data collection, machine learning and delivering experiences at scale, retailers will not only compete with the likes of Amazon and Walmart, they will also build their own identities. And this will lead them to not just survive, but thrive in this 21st century data-powered marketplace.
Michael Murray is President and Chief Product Officer of Wunderman Data Products, a division dedicated to helping clients manage one-to-one relationships with their customers at scale. Murray drives Wunderman's data strategy by enhancing its portfolio of solutions and developing a differentiated offering that meets the demands of the modern-day chief marketer and chief digital officer.