What is Product Clustering?

Product Clustering is the grouping of products on the basis of some type of shared characteristics. Such shared characteristics maybe product type, category, varietal, behavior, etc. Clustering aims to combine those products which have a similarity in their demand, attributes or response from customers in regard to an online business. This helps a business to create product clusters and figure out each cluster’s exact nature and status.

To form an ideal product cluster, it is also necessary to have the required data on the basis of which the clusters are meant to be made. For example: if an online business wants to group products on the basis of discount sensitivity, then it must have the sales data for each product. When the data is available and analyzed properly, product clustering can help in getting insights into the product’s demand and response from customers.

Product clustering works on the fact that although each product is different yet each product has some similarities with some other product. That’s why it is more beneficial to target the marketing efforts on a specific group of products that are most likely to sell and increase the sales of the store. A business must have a deeper understanding of its customer’s choices and product’s demand, so it can serve what customers want from the store and empty the shelves as soon as possible.

Although, there are many factors on which the similarity between products can be figured to form product clusters. But to yield the best from products from a business point of view (especially online retail), the best way is to go for product clustering based on product behavior.

Behavioral product clustering works on the concept of tracking each product’s behavior in the store and grouping them likewise. Analyzing product behavior is an insightful process for knowing products and serving them to those who are interested to buy. Let’s get ahead and know about the various product behaviors and how they help in effective product clustering.

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