What is Store Clustering?

You may have noticed that stores across an area stock different items and are structured in different ways to suit certain groups of people. Stores, even ones of the same brand, may need to develop their consumer experience and stock different items to better appeal to their target audience, ensuring that they are able to uniquely appeal to those who visit their store. 


A classic example of retail store clustering when stores need to take into account different types of climates. A store that is located in a warmer area would need to stock different types of products compared to a store that is located in a cooler climate, which would need to appeal to the different needs of the customers in their area. This differentiation of products is referred to as store clustering and it is used for more than just different clothing in different climates, but rather can be used to adjust a wide variety of differences that stores may experience, from sizing to sales items. 

What Are The Benefits of Using Store Clusters?

The following are just a few of the benefits associated with store clustering. 


  • You can plan more effectively: Using store clusters allows businesses to create product plans for stores that are similar to each other, rather than for each individual store. This is a great way to save on time and resources when planning for product distribution and stock. 


  • Analytical information can be used more effectively: In retail, especially in fashion, the number of observations for each SKU and Store is often small when it comes to statistical decision making. A good clustering offers the chance to combine similar stores with one another and allows algorithm authors to combine small observations and develop algorithms for accurate statistical decision-making. Doing this using a wider and more relative base of information makes it easier to make decisions and allows for more accurate results when it comes to analytical analysis. 

What are The Types of Store Clustering?

Store Grading

In order for a retail business to better understand how well a store performs, metrics can be evaluated that provide information with regards to sales and quotas being met. While this system may seem a bit archaic, with letters or numbers being assigned to stores depending on their revenue, it can help a business to better understand why a certain store is possibly not performing as well as others. There could be issues with the product range, pricing systems or even the styles of products that are on offer, and knowing this can help a business evaluate and make changes that could lead to improvements. Store grading is a type of store clustering that is not as well preferred as other methods as it does not necessarily provide answers to why a store does well or not, but it can be used to help a business spot potential issues

Department/Category Store Segmentation

This type of store clustering is more focused on the customer experience as opposed to simply looking at revenue as store grading does. Department/category store segmentation outlines what the customer will experience when they visit a store. What is a good size for the area it is in? What is the main demographic of the area? These are just two examples of the kinds of questions that would need to be answered as department/category store segmentation involves relying on the customer for information about store clusters. 

Multi-variant Store Segmentation

This approach monitors different gaps, opportunities and thresholds that can be examined by stores to better align themselves with a specific target market. By looking at the gaps that may be noted within a store’s specific product range a business can identify which clusters certain stores should be in and why. This can further reinforce the different approaches that clusters would need to take to be more effective within their target market! Store clustering assortment planning becomes easier when you are aware of which stores fit in with certain clusters and why as this helps a business to better stock other kinds of clusters that may have similar features. 

Statistical Clustering

The last type of store clustering is the most advanced and this approach is known as statistical clustering. Statistics and analysis help a store to gain a better understanding of their consumer market, helping them to better meet the needs of those within a certain area. Cluster analysis improves how well a retailer is able to understand the needs of shoppers in certain areas and allows for stores to better prepare the stock that they carry according to these needs. This is known as a statistical classification technique whereby stores are subdivided into different groups,  with stores that are very similar to one another in one cluster and stores that are very different in other clusters.

Why Should You Do Store Clustering?

Store clustering is used to ensure variation in the products that are sold, uniquely supplying items for people in different locations. A store that is located in a town that predominantly sees an influx of holidaymakers may have very different items on sale compared to a shop located in a business district, and it is important that distinctions are made. Without store clustering, businesses would not differentiate between the changing needs of stores located in different communities, which could result in the needs of the target audience not being met. 

What are The Benefits of Store Clustering?

One of the main benefits of store clustering is that it allows for a business to better prepare a store and the products that they offer for their target market. Different people from different areas require variations of certain products that a business may have on offer. Having a good idea of who your intended customers are and what they need will help a business to sell more products.