Unlocking the Secrets of Latent Shoppers: HIVERY's Demand Transfer Model Explained
The Demand Transfer Model is a tool that helps retailers understand how changes in their store's product assortment can impact sales. It uses data analysis techniques, including machine learning algorithms, to identify shopper behavior patterns and comparable group products into categories based on their competition for sales.
The model predicts the likelihood of a shopper buying a particular product in a store based on the popularity of that product in the category and the shoppers' preferences. It also considers the possibility that a shopper might not buy anything and predicts that some sales may be lost entirely and not transferred to other products.
By understanding the mix of product categories that influence shoppers' behavior at each store, the model helps retailers optimize their product assortments to maximize sales. For example, if a popular product is removed from a store, the model can predict how much demand will transfer to other products in the same category. This allows retailers to make informed decisions about their product assortment and ensure they meet their customers' needs and preferences.
One practical takeaway from this model is that retailers should regularly analyze their sales data and product assortment to identify patterns and trends in shopper behavior. This can help them make informed decisions about what products to add or remove from their store's assortment to maximize sales.
Another practical takeaway is that retailers should consider the competition between products within categories when making decisions about their product assortment. By grouping comparable products into categories and analyzing the competition for sales within each category, retailers can ensure they are offering a balanced assortment of products that meets the needs and preferences of their customers.
Overall, the Demand Transfer Model is a powerful tool for retailers to optimize their product assortment and maximize sales by understanding shopper behavior patterns and the competition between products within categories.