Retail product placement: Tapping data to optimize merchandise displays
When it comes to retail product placement, stores have traditionally relied on historical sales trends, seasonal shopping patterns and garmentos' gut instincts to determine apparel inventory levels and merchandising strategies. Now, however, merchants are taking a more scientific approach to how they stock everything from the hottest athleisure items to evergreen basics, thanks to data and analytics.
Location, location, location. There's no doubt that a store's location is a critical factor in how it performs, and the same holds true for product placement. Data analytics is helping merchants more precisely assess and arrange visual displays and merchandising to maximize sales.
Dillard's, for example, turned to analytics to evaluate if the department store should merchandise Calvin Klein dresses in their own section, away from the general sales floor. Tests in 11 stores determined it was a bad idea, revealing that sales of other brands' dresses dropped when Calvin Klein dresses were removed from the selling floor, The Wall Street Journal reported.
Small changes, big results
Meanwhile, seemingly negligible retail product placement decisions can reap notable sales gains. For instance, the shoe department of a large chain store was performing poorly. A data dive revealed that if the retailer simply positioned its benches further from wall displays, shoppers could more easily try on shoes.
"It was a slight modification that resulted in a significant sales increase for the department, and the store," Alexei Agratchev, chief executive officer and co-founder of RetailNext, told Women's Wear Daily.
These kinds of low-cost, minor changes can generate sales gains of between 5 and 20 percent, Agratchev said.
Boosting UPT via big data
Retailers are also using data and analytics to increase their units per transaction (UPT) rates, the average number of items purchased by a consumer during a single store visit. Historically, stores only gained information about customer behavior from point-of-sale transactions, which is collected after shoppers make their purchases, according to RIS News. By contrast, today's behavioral and location-tracking technologies provide precise, real-time data on customer behavior that can be analyzed to highlight potential opportunities to increase UPT.
Tracking technologies enable retailers to measure traffic and conversion rates for individual departments and entire stores. These insights can lead to better-informed and complementary product placements and, in theory, more sales sparked by cross-merchandising. It can also spark ways to ensure that shoppers linger and spend more.
"If the layout changes often enough that customers can't whip through the aisles on autopilot, they end up spending more time in the store—which usually results in a higher final item count," according to RIS News. "Simulators and analytics show retailers optimal floor plans. They can even give you a clue as to which departments can be moved to improve the customer experience."
Overall, analytics gives retailers the ability to analyze store traffic in real-time to see which displays draw consumer interest and which layouts keep shoppers engaged for the most time. This information, paired with predictions about optimal merchandise displays, can help retailers to be proactive with their visual displays and product placements.