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Retailers Need Science to Curate and Calibrate Highly Tailored Assortments

VP site only OracleThe global spread of Internet-enabled devices (there are approximately nine billion now, a figure projected to rise to 50 billion in the near future) is bringing data, connectivity and choice to billions of people around the world. The accepted wisdom is that having more choices is a good thing for consumers, and for the most part it is — that is, until an almost limitless range of choices becomes confusing and overwhelming.

This “too many options” inflection point presents retailers with an important opportunity. It’s becoming increasingly clear that consumers are seeking tools and technologies to help them cope with the data avalanche available at their fingertips. Retailers that can curate their product assortments by tailoring them to the needs of various customer groups will gain a competitive advantage.

But curating product assortments with a constant view of the customer’s changing needs, and doing so at a granular, store-by-store level with rapid responsiveness and high levels of transparency, presents retailers with a stiff challenge. The complexity of decisions that buyers, planners, and allocators need to make will quickly exceed the capacity of today’s systems and workforces.

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What’s needed are the sophisticated mathematical algorithms and predictive capabilities of science-based solutions, which can balance meeting consumers’ needs with retailer goals of maximizing sales, turns and overall profitability.

Four Steps Toward Curated Assortments

Clustering is a key first step in the assortment curation process. Traditional clustering, based on attributes such as volume, store size and location, are still relevant, but they are not directly focused on the consumer.

Advanced clustering capabilities let retailers look at common customer attributes, e.g. “What did consumers that received products in this ZIP code search for, browse and buy online?” Adding this layer to their clustering efforts allows retailers to create targeted assortments for stores within that ZIP code. By converging channels with intelligence about either a fashion or consumer demographic trend, the retailer can target to get better sales, inventory turns and gross margins, while using fewer promotional resources to do so.

The next step involves analyzing how the consumer choice process actually works, i.e., how do shoppers make decisions around which products in an assortment they are going to buy? Consumer decision trees are an invaluable tool here. For example, retailers can discover if a consumer chooses brand before they choose price, or chooses price before they choose size. Retailers can then use these attributions to map the consumer’s choice process, which allows them to narrow the product range.

Creating narrower ranges is vital, particularly in light of research showing that in some cases, the more choices consumers have, the more paralyzed they become in terms of making purchase decisions. The science required to accomplish this involves understanding demand transference, i.e., what a consumer will accept as a substitute within a given category or range. A typical challenge for retailers is that they have 18 different items within a range, but for capital efficiency and better margins, they want to trim the range to 14 items.

Historically, retailers would look at either volume or gross margins and simply eliminate the four lowest-ranked performers. But one of those “bottom four” items might be associated with the retailer’s highest-value customers. Demand transference determines the incremental and substitution lift of any specific item within the range. Using this tool, the retailer may discover that the best way to optimize the total category’s performance is to delete items four, seven, 11, and 13. But this is not a cognitive problem that a retail knowledge worker is going to solve; it’s a math problem, requiring tools with algorithms that allow a retailer to perform these actions at scale, for thousands of items and categories in hundreds of stores.

The fourth step in creating targeted, curated assortments is to ensure that all these consumer-focused decisions can be driven down to optimized space plans for each brick-and-mortar store.

Creating curated, consumer-focused product assortments means taking a more scientific approach to decision-making around planning and merchandising. The rewards will be seen not only in higher sales, turns and margins, but in customers’ satisfaction at more easily finding the items they both need and want.


Mike Webster is Senior Vice President and General Manager of Oracle Retail and Hospitality Global Business Units.

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