I am passionate about the need for algorithmic merchandising to transform from product to customer centricity. AI is key in enabling retailers’ shift into merchandising processes that move away from product and toward customer behavior hierarchies. Merchandising and planning teams will likely feel this is overwhelming. AI will be at the core of this transformation, both as a source of actionable information, and the vehicle that enables these teams to perform detailed actions.
My latest research, available to Gartner Clients, describes the critical need to apply AI to algorithmic merchandising to help assist in this transformation. Three key impacts are explored in the research:
Retailers that don’t implement critical artificial intelligence (AI)-led merchandising processes now to support the business’s transition to customer centricity will not survive.
Merchandising and planning teams must have access to usable behavioral segmentations or achieving customer centricity will remain impossible.
Merchandising and planning teams require automation of basic and intelligent tasks to avoid failing under the weight of new business process requirements.
Algorithmic Merchandising: A Key Recommendation
In collaboration with business leaders, prioritize and implement AI use cases for merchandising that align with industry segment needs and corporate strategic direction. Typically this will include investing in software tools including retail assortment management applications (RAMAs) for long or short life cycle, retail assortment optimization applications (RAOA), intelligent virtual store design (IVSD) and unified price, promotion and markdown optimization (UPPMO) for long or short life cycle. As seen in this Figure, these work together during the everyday business processes using algorithmic merchandising approaches.
By reorganizing merchandising and merchandise planning to represent key customer behavioral segments, and creating greater synergies with the marketing organization, retailers can focus on what is truly important to customers in the touchpoints with which they interact. Most importantly, retailers can understand and enable the way they prefer to shop. This obviously creates many complicated matrices consisting of behavioral segments, locations or touchpoints and the products required to support the business. This is where the leverage of AI and algorithmic merchandising take center stage.