June 4, 2018
When Piloting Colocation, Measure Impact To Location, Customers, And Operations
It’s been interesting to see creative real estate colocation ideas such as the recently announced pilot for ALDI in 10 Kohl’s stores. As Kevin Mansell, former CEO of Kohl’s, explained, “We believe the opportunity to leverage our real estate through this effort has benefits.” But retailers that experiment with colocation must understand the value of store space, customer demographics and behavior, and the operational impact. To learn as much as possible from the test, colocation metrics need to:
- Determine the value of store space. For starters, Kohl’s will be able to test how well its store performs with a smaller format (less square footage) for its own merchandise. The test also allows Kohl’s to generate income by subletting property that it either owns outright or that it leases. Per Cushman & Wakefield’s retail real estate report, the average US retailer drives $325 per square foot of sales space, and typical leasing rates across the US average $16.84 per square foot. The recent Waukesha, Wisconsin building plans show a decrease of approximately 25,000 square feet for Kohl’s’ 88,700-square-foot space, which could generate up to $375,000 in added income or subsidized leasing costs for the store. The key question that Kohl’s will need to answer is whether the smaller store size will generate higher sales per square foot — and whether those higher sales exceed the subsidized income.
- Track overlapping customer demographics and behavior. Understanding the customer overlap will let retail professionals estimate foot traffic and sales as a benchmark and compare against actual results when piloting. Companies usually select partners with customers that are either very similar (to increase market share) or very different (e.g., to expand to new markets). Measuring the overlap across key customer profile characteristics gives retailers the starting point to understand the change that colocation introduces. In the ALDI-Kohl’s colocation scenario, Kohl’s has a more affluent customer base, while ALDI remains a discount grocer with a less affluent following, so an increase in traffic will suggest that Kohl’s is expanding its market downstream.
- Map operational impact for margin. Colocation may create operational changes such as different associate shifts, store hours, delivery times, promotion and signage, layout, and cross-store customer tracking. Changes in customer types, frequency, assortments, available space, and more will contribute to the changes. For instance, if Kohl’s’ tests show that there is more customer traffic during the return-home rush hour, when grocery buying is higher, it would make sense to adjust associate schedules to match. To manage colocation changes, retailers will need to measure key aspects including foot traffic, cross-traffic, dwell times, sales per store, comparative sales with similar or standalone stores, and more. Data will be the ROI currency for retailers that will help in deciding how the test is progressing and whether changes are needed. For ALDI and Kohl’s, colocation testing store-in-store options instead of adjacency can also translate into upsell/cross-sell opportunities.
- business models
- customer data
- customer engagement
- customer experience
- customer experience strategy
- decision making
- operating models