26 Apr How to Effectively Use Product Clustering in Retail (2021)
Everything you need to know about product clustering/grouping
Product clustering (or grouping) is an increasingly common technique that leading retailers use to manage their planning, inventory, pricing, promotions, and markdowns.
It is an effective way to think about assortment. This approach offers retailers a smart way to scale operations and can be incredibly cost-efficient when used correctly.
(psst! Jump to the end to see product cluster examples.)
Definition of product clustering / grouping
Product clusters are groups of products that share similar attributes. Products can be clustered in different ways (and for different purposes). They can be clustered by type, shape, occasion, materials, features, price, style, design, color, size, family, brand, function, and more. Doing so allows retailers infinite flexibility to “slice-and-dice” their assortment, analyze performance, and optimize everything from inventory to pricing.
And clustering isn’t just limited to products. Large retailers may also cluster their stores, warehouses, DCs, manufacturers, vendors, etc.. Furthermore, retailers can create more advanced clusters like “a group of products that share an attribute and also belong to a select group of stores”.
Most commonly, retailers use geographical clusters to better account for demographics, distribution cost, climate, and other relevant factors to their business.. But that’s just the tip of the iceberg.
While product clustering can be incredibly effective for optimizing assortment, inventory, and pricing — it can be difficult to gain meaningful results from product clustering if retailers are not using the right tools. Especially for medium and large retailers that are dealing with tens of thousands of SKUs across hundreds of stores.
Are product clusters effective?
So the real question remains, are product clusters an effective way of thinking about your assortment?
And the answer is, “it depends”.
The primary problem with product clusters is that once they’re created, they often become static.
Static product clusters do not serve retailers well. The real world is too dynamic.
Take for example, a retailer that clusters their products by performance — A-Tier, B-Tier, C-Tier — to quickly create replenishment quantities. If they didn’t dynamically revise these clusters, a shift in consumer preferences might cause A-Products to underperform (or C-Products to jump in demand), leading to unnecessary markdowns, lost sales, or both.
In short, while incredibly useful in the moment, virtually all product clusters become less relevant to the company’s actual performance as market conditions change.
That’s why retailers review static clusters. But at best, this only happens once a quarter (and often at longer intervals).
This approach is inaccurate, inconsistent and labor-consuming.
How to dynamically optimize product clustering
To get the most from their product clustering strategy, leading retailers are turning to advanced analytics and AI.
Retailers leveraging these technologies are able to build flexible product, store, or vendor clusters based on common attributes or behaviour, performance, and even custom characteristics.
Perhaps more importantly, retail AI allows for these clusters to be dynamic, reacting to the reality of the ground and — not waiting for an analyst to review the group at the end of the quarter or longer.
The system monitors product, vendor, and store performance while also evaluating changes in forecasted demand. The solution can adjust automatically to intelligently re-calibrate the clusters, and move products, stores, or vendors in and out of these groups.
Unlock the true power of this strategy with the right tools.
Retalon’s AI-driven retail analytics solution lets retailers use dynamic clustering to optimize their end-to-end business from planning and inventory management to pricing and promotions.
Examples of product clusters
The power of product clustering comes from the variety of attributes retailers can use when grouping products.
Retail analysts are no longer limited to the general, high-level and static product groups provided by traditional systems. Instead, they can cluster products by combining relevant attributes.
Product grouping examples:
Price bands – Retailers can group products within a certain price range. A retailer may want to see performance of all toys that sell below $25. Or from $50 – $100.
Performance groups – Retailers can group products based on their contribution to sales. A-products maybe those that generate 80% of sales while B, C, and D products produce the remaining 20%.
Mutually substitutive products – Customers treat some products in the assortment interchangeably. If one item is out of stock, they won’t hesitate to replace it with the other. Retailers may cluster these substitute products together to manage inventory more efficiently.
Product families – A product may have multiple variations, sizes, or be from the same product line. It’s important to account for these related products when making any decisions that affect one of the “family members”. Product clusters help do this with a breeze.
Occasion attributes – Another product group can be formed based on products that behave similarly during specific holidays, seasons, or promotions. For example a group of products that experience a peak during valentine’s day.
Lifestyle – In many verticals (especially furniture), products may be clustered by lifestyle, or likelihood they would appeal to specific demographics and types of shoppers.
Market basket – A very common practice in retail, products can also be clustered by the likelihood of customers purchasing them together (i.e. conditioner and shampoo).
Vendors – Retailers can create a product groping definition based on vendor type or vendor behaviour.
Locations – geographical product grouping is not limited to a retailer’s regional or district organization. Stores can be grouped by format, climate, or demographics.
There are many ways to use product clusters.
In fact, Retalon’s AI solution is able to help you identify and build clusters too.
Retailers take advantage of our AI-powered product clustering to optimize every aspect of their operations. Talk to one of our team members for a personalized demo for your retail business.