A company only remains in business because of one reason: Customers. To know your customers is to know your business inside and out. Digging into your company’s transactional data and learning about customer behavior is essential to understand where they were, where they are now, and to anticipate where your best business growth opportunities lie.
To properly determine customer segments from transactional data, the customers (by name), categories of products, and sales volume for every distinct combination are analyzed by two algorithms: K-means clustering and UMAP dimensional reduction. This approach allows multidimensional categories of product types, product lines, product feature sets, etc. to be included and displayed as a two-dimensional map.
The mapping of customer clusters reveals similarities within each group and also what differentiates groups (segments) of customer purchasing habits. This sort of data driven approach allows senior management to develop strategy for future business development.