Boosting Basket Value by 18% by Mapping In-Store Customer Journeys

Our client, a leading national home improvement retailer, faced a persistent challenge. Despite healthy foot traffic, their average basket size had plateaued. Customers were coming in for their 'anchor' items—a gallon of paint, a set of 2x4s, a new faucet—but were consistently bypassing the higher-margin accessories that complete a project. Their vast, warehouse-style stores were efficient for logistics but confusing for shoppers, leading to what they called 'project tunnel vision'. They knew they were leaving money on the table but lacked the data to prove where and how to make changes.

The core problem was an inability to see the store through their customers' eyes. Traditional sales data showed what was sold, but not how customers moved, where they hesitated, or what opportunities were missed along their journey. Our team at Iceberg Data was brought in to illuminate these hidden pathways to purchase.

Our approach was to build a comprehensive digital twin of their in-store customer experience. This began outside their own walls. We started by scraping publicly available data sources that no one had thought to combine. We pulled architectural blueprints and store layout plans from municipal permit and planning department websites for dozens of their locations. This gave us the foundational 'map'. We then scraped publicly accessible data from their own and their competitors’ mobile apps, which often reveal the precise location of product categories, to overlay a product schema onto these raw blueprints.

With this detailed external map built, we turned to the client's internal data. They provided us with a stream of fully anonymized data from their in-store WiFi and Bluetooth beacon network. This data consisted of location pings from devices that had opted-in to store WiFi, stripped of all personal information—essentially, a collection of 'ghosts' moving through the store. Our challenge was to give these ghosts meaning.

Using a geospatial matching algorithm, we layered the anonymized movement data on top of our digitized store maps. Suddenly, abstract data points became tangible customer journeys. We could see the 'superhighways'—the most common paths from the entrance to the Lumber department or the Paint counter. More importantly, we could see the 'deserts'—underutilized spaces that were on high-traffic routes but contained low-interest products.

The insights were immediate and powerful. We discovered that over 60% of customers purchasing from the Lumber department walked down a specific main aisle to reach the checkout, passing a large end-cap display that was merchandised with seasonal, low-margin goods. They were walking right past a golden opportunity. Similarly, we identified a 'pause point' near the Paint department where customers often stopped to compare samples. This area was surrounded by generic shelving.

Armed with this path intelligence, we worked with the client to orchestrate a series of strategic merchandising 'interventions'. We recommended moving high-margin, high-attachment items directly into the customers' line of sight on these superhighways. That seasonal end-cap on the path from Lumber was replaced with a display of premium deck screws, wood glues, and high-quality work gloves. The 'pause point' by the Paint counter was transformed into a 'Project Prep Station' with painter's tape, rollers, and drop cloths. The goal was simple: place the solution right where the customer is thinking about the problem.

The results over the following quarter were staggering. The stores that implemented these data-driven changes saw an 18% increase in average transaction value . Sales of fasteners and adhesives in the test stores jumped by over 25%. By making the store layout more intuitive, they also saw a 22% reduction in aisle congestion during peak hours, as measured by device density in our path maps. We didn't just help them sell more products; we helped them create a smarter, more efficient shopping experience, turning hidden customer paths into visible streams of revenue.