Transforming Average Customers into Extraordinary Shoppers

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With contributions from Lindsey Mazza Is your customer an average shopper? Most retailers plan average assortments, for average stores with the average available space, and the average customer as their target shopper. Social media, customer demographics, and business analytics have enabled more average retailers to move away from planning using averages. Using technology with limited […]

With contributions from Lindsey Mazza

Is your customer an average shopper? Most retailers plan average assortments, for average stores with the average available space, and the average customer as their target shopper. Social media, customer demographics, and business analytics have enabled more average retailers to move away from planning using averages. Using technology with limited constraints to uncover previously hidden patterns in underlying data, retailers can now cluster stores based on product and customer affinities in order to improve the bottom line. Making the right products available to customers by tailoring store assortments to the local market has become the key to increasing revenue and margin while decreasing unproductive inventory for many retailers.

Although many retailers have taken the initial steps of differentiating their assortments by grouping stores, few have created truly local offerings. Traditionally, characteristics like region, volume, space, or climate are used to group stores. Clusters even based on averages within these categories often have little hope of driving success. For example, the average temperature in Boston, Toronto and London is the same, 51F degrees, however data tells us that these cities share very few patterns in customer buying behavior. According to syndicated data from Nielsen, a global information and measurement company, we know that people in Boston, Toronto, and London share little in common when it comes to fashion trends, sporting goods, technology adoption and food purchases.

Identifying the driving attribute – those characteristics that drive the business to increase sales – requires us to go deeper than a cursory, surface level view of store attributes. Coupling store attributes with characteristics of the customer is the key to unlocking the true potential of localized and even personalized assortments. By reviewing a small number of store groupings that represent the diversity in the chain and creating action plans developed at that group level for all stores in the group we are able to tailor local market assortments in a way that is scalable, customer-centric, easy to manage, and highly predictive.

Some retailers use more detailed attributes of the customer and yet fail to find those that are unique for their business. The trick to a great assortment plan is to make in/out decisions based on customer preferences for the retailer’s products- not for industry averages. For example, a fragrance retailer may choose scent profiles; a mobility retailer may pick the customer’s ability to adapt to new technology at launch; and a fashion retailer may select fabric types on trend right now. Picking the right master and transactional data on which to base decisions is critical because the product and customer characteristics help define the merchant visions, financial business mix and ultimately product assortments by store.

With considerations of new and unique attributes and driving characteristics, some retailers face a gap in skill-sets, or available time, when implementing these tools and processes. Although automation comes with the tools, the learning curve can be steep and a major pitfall of the process can be a failure to manage the scale of the change within the organization. As employees become more time constrained in today’s economy, it is critical to create scalable, manageable assortments adjusting only local components of an overall master assortment. Creating store clusters based on the right driving characteristics and supporting the customizations of only a local component of these assortments is a critical success factor.

Once a customized, local assortment is tailored for stores, a detailed space planning system and process and strong store execution practices are required to encourage success of the new product line-up in the field. Without execution of the plan at the store, retailers can struggle to achieve the planned sales, revenue and inventory targets.

By incorporating Merchandise Financial Planning, Store Clustering, Assortment Planning and Space Planning into the overall Assortment Planning process, retailers can develop location-based financial targets, tailored, localized assortments based on driving character tics, and strong store execution, ultimately culminating in revenue and margin improvements and inventory reductions for retailers across industries

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