How to know your customer using data

In the 25 years I’ve been in retail, the industry has changed tremendously, from one that was primarily focused around product to one that is hyper-focused on knowing your customer. One of the big driving forces behind this change is access to an unprecedented amount of data. The leading retailers of the future will be decided not just by product assortment and pricing, but by how well they use data to know their customers and connect with them at every stage of the customer journey. It’s very exciting!

In the past, most of the data we had was around product sales, but it was aggregated information rolled up to a style or category. Merchandising, buying and inventory teams were aligned by product area, and metrics by location or channel was the lowest level the team had easy access to. 

We really didn’t have a lot of data about the customer. We only knew them indirectly through what was or wasn’t selling in our store or online. Because product attribute data was aggregated, you might know you were selling a lot of smalls in Chicago for example, but you didn’t know who you were selling them to. Pulling in external data, such as demographic data, was a difficult, manual exercise that limited its usefulness.

There’s even more data available today on the product side, with ERP systems offering hundreds of product attributes by item. But the biggest change is how much more data is available on the customer side. Retail moving to online was a big inflection point, providing us with a wealth of new insights into customer behavior. Now we have visibility and insights into specific customer selection, for example size, color and where purchased. This has allowed us to get to know the customer better. 

It’s taken a while for the industry to digest this change. The initial response to support the online business opportunity was to have one group of buyers and planners for brick and mortar stores, and a separate group for online, under the theory that these were different customers.

The data showed us that was not true. Now there is no more separating the online customer and the brick and mortar customer. We recognize that they are one and the same, and leading retailers have spent millions of dollars mining and merging online customer data, in-store data and loyalty program data. It’s now possible to know everything a customer has ever bought in your store and online. 

You can know how often they buy, what brands they like, what their typical basket size is and what they spend every year. And, you can combine that with data from search engines, social media and other external demographic data sources much more easily, to create a more robust customer profile than we’ve ever had before. By combining internal data with external data, retailers can more effectively adjust assortments, inventory and messaging to meet the customer where they are. 

COVID has brought us to another inflection point. It’s pushing any remaining holdouts to get online. It is estimated that online purchases could grow to 25 percent by 2023, up from 14 percent in 2019. This is significant.

We need to shift our focus once and for all away from segmenting customers by channel and having the right allocations in the right store, to having the right supply chain initiatives in place to service the customer wherever they are on their journey. And we need to put the right tools and people in place to allow teams to be strategic with all the data that’s now available to us.

The marketing team also plays a much bigger role in partnering with the merchandising team, consolidating and analyzing the data to see what’s working and what’s not. They should be creating  personalized messaging to reach each customer. For example, let’s say a customer was in a Nordstrom store last week for the big anniversary sale and spent $50. But the prior year they spent $300 at the sale. That change in basket size could potentially flag them as a lagging customer. An analyst can dig in to try to find out why they didn’t spend as much as the prior year. Did they not respond to the offers that were made? Did they shift to buying online?  

Marketing’s role is bigger than ever in figuring out the customer and delivering the right offers to drive store and web traffic. This is how you counter the “Amazon effect.” You can play with pricing, but we all know too well that is not a great model for success. The best way you can differentiate yourself is by presenting a consistent brand, offering carefully curated assortments, providing best (and maybe additional) services, and creating personalized messages that ensure you really connect with each customer.

COVID has brought so much change in customer shopping behavior, so continuing to add metrics and dig deeper into how people shop now is critical. For example, they may be shopping with lower frequency, but their average basket size is bigger. And what they’re buying is significantly changing—with COVID we’ve seen a trend toward more essentials, home improvement and home office. You need to understand the trends in your business and use all the product attributes at your disposal to try to get at the “why.” What is driving their shopping behavior? Is it necessity? Price? Brand? Innovation? There are many ways to bucket and classify your products to look for patterns and see how they are impacting your business and how you can respond.

Bringing in external data is extremely important. There’s an unlimited supply of data sources you can bring in—weather, unemployment, economic data, and COVID data to name a few. We did some work for a client where we looked at sales trends by zip code against data around COVID cases. We clearly saw how the number of cases impacted overall sales and what customers were buying. These are the kind of insights that give you a competitive edge in the marketplace.

Here’s another example: When COVID hit, golf courses were closed down. When they started opening up again, we were able to look at that public data and make recommendations about where to best allocate inventories of golf merchandise. If you are a sporting goods store, just think about how you could improve your instocks and turnover by having the right product available at the right time.

We are able to answer so many more questions today than ever. We’ve gone from working with aggregated data, to now being able to reach deep into the data and tie it tightly to the individual customer. We have to use that to our advantage. There’s no more sitting back and waiting for the customer to just show up. There’s no more, if you build the right assortment, they will come. You need to be reaching out to them and proactively offering the right assortment at the right price and at the right time.

It’s a big challenge, but we have the data to take it on, and with the right tools it’s easier to analyze and interpret it than ever. Our previously unsatisfiable curiosity about the customer can now be satisfied with data insights, giving retailers the ability to learn and grow alongside the customer. And that ability will be very important to your overall success.

Connie Walsh is Senior Director of Transformation Services at eCapital Advisors. She has 20+ years of experience helping organizations achieve meaningful growth through envisioning new technological possibilities and improving day to day operations. She loves to dive deep on what companies are currently doing and empower them to translate their data to grow business and increase bottom-line profitability.