Many retailers’ assortment planning strategies are stuck in the pre-digital age, and they’re still tweaking assortments by grouping stores based on product attributes such as region, volume, space or climate. These companies are missing important customer-focused data from web-based kiosks, beacons, digital signage, smartphones, store associate tablets and social channels. By leveraging data from these emerging technologies in assortment planning, retailers can create segment- or customer-specific assortments. This is a critical step in improving customer engagement in an omnichannel world where purchases can be made anytime, anywhere. 

While creating customer-specific assortments is not a new concept, many retailers fall short in identifying the driving attributes or specific characteristics that help drive sales. Identifying these attributes is critical in tailoring assortments in a way that is scalable, customer-centric, manageable, while still remaining highly predictive. Uncovering these attributes is not an easy process, and requires both technological and change management initiatives. I’ve attempted to break them down into four steps:


1.       Create one data system of record among brands, channels, divisions and departments

2.       Analyze unstructured data from social listening, for example, in order to uncover key attributes

3.       Lead a cultural change within the organization that stresses the need to react to real-time changes in customer demand

4.       Refine metrics to measure performance across teams instead of within teams to encourage collaboration

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