dunnhumby Assortment | Make faster, smarter, and consistent assortment choices with AI

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Make faster, smarter, and consistent assortment choices that truly reflect the preferences of your Customers with dunnhumby Assortment

dunnhumby Assortment utilizes dunnhumby’s world-leading ai-powered Customer Data Science platform to empower retailers to meet the ever changing and nuanced needs of their customers. Making faster, better-informed and consistent choices to put the right products, in the right stores to create an assortment that truly reflects Customer preferences down to the most local level.

How dunnhumby Assortment helps you

Retailers are under constant pressure to grow their sales and share against a backdrop of increasing competition, while also focusing on efficiency. There are constraints on the number of products that can be stocked due to store and supply chain limitations, which creates hard choices for retailers. Traditional approaches to assortment can delist the wrong products, and the cost reductions can be quickly outweighed by the larger sales loss

Our web-based tool ensures you can make better, faster, differentiated decisions on your product assortments, how best to manage inventory, and how to handle space on the shelf.

Actual Customer purchase data allows us to understand when product substitutions happen, and builds Customer Decision Trees in real time to help retailers better understand how their customers are shopping the category.
Automated and data-led - the add-order engine builds efficient recommendations based on a Customer relevancy score, maximizing Customers visiting the category to drive total store sales.
Optimizes the assortment recommendation based on the three drivers of coverage, performance and relevance.

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How it works

Performance

Review the performance of the assortment at SKU level over a given time period – from financial metrics like sales to consumer metrics such as penetration and favorite share. A composite rank gives you clear guidance on the best/ worst performers in the category.

Customer Decisions

Understanding different Customer needs in a category is essential to building a balanced assortment. Products are clustered based upon how substitutable they are with each other and groups of products which then allows us to build up a full Customer decision tree, helping you to understand how Customers shop that category and what are their most important decisions are.

Recommendations

The add-order engine is at the heart of our solution and ensures a Customer-focused assortment is produced - taking into account Customer needs, product performance and store relevancy. This step provides recommendations to help design an assortment that achieves maximum sales performance as well as relevance for Customers whilst offering users the ability to ‘lock’ products in or out of the new assortment.