Intelligent Clustering for Competitive Advantage

A smart approach to a familiar challenge shakes up category planning.

Success in retail is about finding balance between serving customers and the cost of doing so. Consider out of stocks. They can be eliminated by increasing inventory levels, but inventory is expensive. Supply chain efficiency can be improved through SKU rationalization, but customers want choice. They also want a pleasant store experience but providing high service levels requires costly labor.

Balance is also an issue with product assortments. Shoppers have an expectation that their store will offer local items, regional favorites, national brands, own brands, and specialty items, in desired sizes and adequate quantities. However, creating unique category plans for each store isn’t practical or efficient. It’s also not necessary thanks to the magic of clustering.

Clustering is a well-established aspect of category planning that involves the creation of optimal assortments geared to the behaviors of shoppers in a store’s trading area while incorporating supply chain and operational considerations essential to profitability.

An Intelligent Clustering Transformation

Traditional approaches to clustering have served the retail industry well for many decades. However, advanced technologies now make intelligent clustering possible at a time when shopper expectations are higher than ever, product trends are shifting quickly, and more data is available to inform clustering decisions.

So how is intelligent clustering smarter and different than traditional clustering and why is it a blessing for CPGs? For starters, intelligent clustering takes advantage of AI to incorporate an expanded range of variables into assortment decisions. CPGs can put the power of modeling to work against vast data sets to produce the optimal store clusters based on how a product or category is forecast  to perform versus how it has performed historically. This is a key advancement over legacy clustering solutions that based clustering recommendations on historical information versus a view of where the market is headed.

This latter point is crucial because where a category has been and the items within the assortment that drove the performance can be materially different than how a category is expected to perform and the likely contributions of various items. It’s an important distinction that AI helps make for CPG companies, so clusters are based on a vision of the future rather than a reaction to the past.

Automation, Accuracy, Efficiency

It is common for clustering decisions to be based on information like store size, distribution networks or historical sales. However, as noted above, this is an analog approach for the digital age because it means decisions on what shoppers may want to purchase are gleaned solely from historical information. Such information must be combined with store demographics to move beyond what may be driving consumer demand to identify where the best opportunities are to select the optimal assortment.

By integrating store demographics, it is possible to instantly identify customer and cluster characteristics to inform the next best action. Thanks to intelligent clustering workflows powered by AI, optimal clusters can be identified at scale – across categories, banners, and geographies. The result is greater category and reduced cost of managing more clusters than necessary. Through AI, CPGs can find the sweet spot of having the right mix of core items in every store, unique store-specific SKUs, and an optimal blend of complementary items for each demand-driven retail store cluster.

The Beauty of Integration

Another reason why intelligent clustering is deserving of its name is because of how it integrates with the supply chain. Since the advent of clustering, a key reason for its use was to achieve supply chain efficiency. Intelligent clustering takes efficiency to a new level by integrating with supply chain systems to gain visibility into the implications of various clustering possibilities. By understanding the proximity of distribution nodes to stores it is possible to ensure supply chain inefficiencies are not introduced to retail operations through well-intentioned efforts to satisfy shoppers. As a result, stores are likely to receive orders on time and the on-shelf availability of a CPG company’s products will benefit.

Intelligent clustering powered by AI is a game-changer for CPG companies who use it effectively, enhancing value with retail partners by balancing optimal assortments and supply chain efficiency to achieve total category growth.

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