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4 Steps for Using Data to Spice Up the Healthy Food Mix

$html.esc($author.firstName) McVie By Graeme McVie on December 13, 2016

When it comes to choosing the best healthy products to stock on shelf, supermarkets should use the oregano rule: How many types do you really need?

Adding items to the shelf, even in-demand products, means removing others. Maximizing space can be tricky, as Walmart proved with its failed effort to reduce inventory a few years ago. It removed many items its shoppers wanted, so they took their entire baskets elsewhere.

Fortunately, data can help retailers avoid this outcome. Here are four steps to determine the best product mix – and tradeoffs – on the shelf.

Spice it up: The product assortment should generally vary by store or cluster based on the customers and the uniqueness of each item. Three key elements will help identify products that can be safely removed:

  • Products that, if removed from shelf, shoppers will easily substitute with a different label (think Dasani and Aquafina waters).
  • Items that do not generate complementary purchases, the way chips tend to do with salsa.
  • Items that are not important to valuable customers. If you pull a product of high importance, you risk losing that shopper’s entire basket.

Choose the best ingredients: By analyzing detailed customer data, a retailer can understand the product attributes that disproportionately appeal to different customers and segments. Armed with these insights, the grocer will know where to:

  • Expand the distribution of specific, appealing items that have been introduced into some stores but not others.
  • Introduce new items that have qualities that disproportionately appeal to the specific customers who shop in each store.
  • Develop and stock private-label offerings that contain the product attributes desirable to each store’s customers.

Check the temperature: After introducing a new item into the assortment, the supermarket should monitor its performance. If the retailer has a unique customer identifier, such as a rewards program, it can perform trial-and-repeat analyses to determine which customers initially try and then repurchase the product. The data also will supply insights about which products and attributes appeal to which specific customers.

Measure results: All steps require the grocer to score every item along multiple dimensions to incorporate attributes like “healthy” into the product data. In this case, a grocery would measure the co-occurrence of similar healthy items and the absence of non-healthy items by customer, and then assign a “true” healthy attribute score to each product.

Meet The Author

Graeme McVie

As Vice President of Business Development for Precima, a leading retail analytics solution owned by LoyaltyOne, Graeme leads the customer analytics and loyalty services sales efforts across North America. Drawing on almost two decades of consulting, Software-as-a-Service (SaaS) and analytics experience, Graeme has a proven track record of helping clients drive improved sales and profits through insight-driven, customer-centric strategies and solutions.

Prior to joining LoyaltyOne in 2012, Graeme held the position of Senior Vice President of Sales at Symphony Analytics. In this role, he delivered pricing, sales and marketing strategies and SaaS solutions for many leading consumer packaged goods (CPG) retailers and manufacturers. Graeme has also assumed several other senior level roles including Senior Vice President at Applied Predictive Technologies and Vice President, Strategic Alliances at DemandTec. Graeme started his career as a consultant at Bain & Company, an industry leading strategy consulting firm.

An engaging speaker, Graeme regularly presents at industry events and has been featured in media outlets across North America. He received his M.Eng w dist, Engineering from the University of Strathclyde in Scotland.

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