AI-enabled approaches to retail category reviews surface opportunities and ensure assortments deliver on customer expectations

In this interview Matt Robinson, Director of Solution Marketing at Symphony RetailAI, explains why category managers need to look beyond traditional approaches and methods to category management, and move towards a collaborative AI-enabled approach to connect the relevant people to the right tasks at the right time with the right data to drive higher category performance.

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    There are many challenges that a category manager faces every day. One particular area is category reviews. The Assortment optimization process has always been designed to help retailers decide how many and which products should be offered in a category. However, the traditional approach to assortment optimization has been constrained in its inability to look past historical sales performance and existing customer behavioural patterns.

    Symphony RetailAI has already taken a major step forward in relation to increasing the effectiveness and sustainability of assortment optimization by delivering a collaborative platform for category planning, one that integrates not just data, but connects the relevant people to the right tasks at the right time to drive higher category performance.

    Our innovative approach to augment the value we deliver to our customers, doesn’t just tell you about the products and customers you already know about but reveals the relevant strategy you should take for a category in order to deliver continued success.

    By leveraging AI, we can provide a current, comprehensive and penetrative understanding of shoppers’ buying patterns. Its outputs can ensure shelves are always stocked with the right assortment mix and ensure that the supply chain is aligned to eliminate expensive out-of-stock or overstock scenarios.

    It can perform these tasks in an automated, predictive and real-time manner and determine when a category review is critically needed and just as importantly, when it is not. This makes the AI-enabled process far less cumbersome and disruptive than traditional, calendar-based reviews.

    In making product recommendations, AI-influenced algorithms will analyze the assortments and pricing of competing retailers. Then, those items are compared against the demographics and shopping history of your customers.

    The combination of social media feedback and internal and external data resources that AI can mine and interpret creates a “neural network” that provides a far more accurate assortment forecast than traditional calendar review methods.

    Going forward, category managers will be able to gain more control over the management of their categories, confident that they are abreast of future opportunities and deliver assortment propositions that resonate best with their most valuable customers.