Success Story: New Itemization Breaks Grocery Chain Sales Records

A regional grocer repositioned an underperforming store to a new location less than 2 miles away. As part of the reposition, they leveraged Placer for itemization optimizations. Would a data-driven item mix boost sales?

Success Story: New Itemization Breaks Grocery Chain Sales Records

A regional grocer repositioned an underperforming store to a new location less than 2 miles away. As part of the reposition, they leveraged Placer for itemization optimizations. Would a data-driven item mix boost sales?
In This Article

“Prior to Placer, we didn’t know what we didn’t know about our customers. Placer’s demographic insights gave us the courage to explore adjusting our itemization to better fit one stores’ unique customer mix, and the results of the highest grossing sales and sales per square foot  were better than we could have imagined.”

~ Director of Marketing at Regional Grocery Chain

The Challenge

A well-known regional grocer with 100+ locations, over 60 years of operating history, and more than 10k employees continues to grow and expand in the region. A recent challenge arose when planning to reposition an underperforming store in one of their markets. Aware of a stronger target demographic nearby, they decided to close the location and build a new one approximately 2 miles north. A key question came to the Director of Marketing and other senior leaders: what would the optimal itemization for their new market be?

The Solution

Given the property was under construction, the team needed a strong proxy for analysis. They analyzed a competitor's grocery store, located directly across the street from their new store. Analyzing the customers from the store gave a clear picture into the ethnic makeup the regional grocer could expect at their new location, one with a high proportion of select ethnicities (over 200% the statewide average) and a lower proportion of others.

Learn more about Audience Profile

Placer data also showed the household income (HHI) for the nearby competitor store, suggesting an average HHI of $83k, with further detail on the amount of households using SNAP benefits.

Learn more about Household Income

Armed with this data, and insights from customer interviews, the team opted for a more nuanced store itemization mix, adding a sushi station and other items gleaned from local customer research.

The Outcome

The results were profound: launching the store with an itemization mix specifically tailored to their surrounding customer demographic, as opposed to a mainstream itemization that largely ignores demographic considerations, increased the store’s performance significantly. It become the #1 grossing and #1 sales per square foot of all stores with non-mainstream itemization (35-40 stores at the time).

Seeing the success of their new approach to itemization led the regional grocer to fully embrace using demographic insights to understand their customers and update their itemization strategy in all new and remodeled stores. They now use this itemization strategy at all new stores. The highlight of these changes were clear for another newly built store: equipped with new decor, departments, and the tailored itemization, the store is not only the top grossing out of the 100+ stores, it also has the highest sales per square foot of all 100+ stores as well.

Case Study

The Challenge

The Outcome

Case Study

The Challenge

The Outcome

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