Using Real-Time Data to Improve Grocery Store Layout
Grocery stores want to capitalize on strong seasonal trends, product crazes that can boost revenue. But with some products, pumpkins among them, knowing the best place or way to position a product can make a big difference on the bottom line.
Using real-time data to improve grocery store layout is a growing practice among grocers of all sizes, and one that major supermarket groups in Europe and the Americas are already using to improve sales.
Maximizing a Tradition
Grocery stores are constantly adapting layout, even more than other retail categories. The nature of the product means shorter shelf lives and seasonal fluctuations that demand nearly constant movement and short testing periods.
In these environments, manual recording of A/B testing on positioning and store layout generally struggles to keep pace with the week-to-week changes in consumer preferences. Pumpkins, or pumpkin-themed items, displayed on an endcap in mid-October may be optimal, but less so just a few days later.
Seasonal shopping, spending related to holidays and changes in the weather, are a boon for retailers of all stripes. And grocers remain alert to well-worn shopping traditions but also want to make the most of faster changes. Real-time objective data can help retailers:
- Place high-margin items in prominent locations: Placing the most profitable products in prominent locations, such as near the entrance of the store or at the end of aisles.
- Group complementary products together: Placing products are most likely to be purchased in the same location.
- Create a traffic flow: Understanding how shoppers move through their stores helps retailers create a traffic flow that encourages shoppers to visit all parts of the store.
Cool Weather, Hot Maps
Shortening testing periods requires accurate, objective data about customer engagement during the testing period. Relying on point-of-sale (POS) data to revise hypothesis overlook category and subcategory-specific behaviors that offer a more complete picture of customer interest.
Accurately measuring dwell time and view direction is a better indicator of how customers are responding to layouts and product placement. Quick tests during seasonal shopping periods can help retailers achieve optimal positioning and displays quicker.
Retailers can also use objective data to create a heatmap of their store, an easy visualization of the areas of the store most popular with customers and those that are less popular. Heatmap info can be used to create a layout that maximizes sales and improves the customer experience.
Analyzing objective, anonymized data, both real-time and historical, can also help grocers understand when store layout is interfering with sales. Are products being inadvertently covered by other displays? What is the sales impact of having certain products on lower shelves? The questions are many, and the benefits of getting the right responses significant.
Xovis Loves Autumn
A Swiss company with an affinity for forests and chocolate, Xovis is big fan of autumn shopping. We love to see how retailers use our accurate, AI-powered sensors to improve conversions and sales during peak shopping seasons. And the indoor shopping rush that accompanies autumn shopping gives us a chance to shine—brighter than a candle in a jack-o-lantern!
Tags: | retail | people counting | staff management | in-store analytics | category optimization |
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