For years the retailers have tried to figure out, how the shoppers interact with products between entering the store and purchase at cashier. Only now there is a way to measure and manage customers’ in-store activity and a new way to optimize store layouts, operations and activities.
Retail owners and chains invest vast amount money on yearly basis to plan better store layouts and research resources to maximize the amount of customers exposed high margin products at the store. But despite all of this, the results have been missing factual data to back up changes needed at the store level. The industry has not had a mechanism to measure well traffic flows at the store and of the conversion rates around the store aisles. With few exceptions, retailers do not know who their shoppers are at any given time in the store, until the shopper is at checkout—and only then for retailers that have some type of loyalty program. Stores currently require shopper identified transaction data to be fed into the CRM system before they can make any identification.
Retailers use also a great deal of time to plan and develop product categories, a task that should help them to make decisions of which products belong on the shelves and how to price them. Nevertheless, bringing such plans to life at store level is very much a challenging task due to ever-changing store environment. Even when the retailer does find right products to the store category, he or she has to take care that there is enough products in the shelves. Lost sales due to no stock is retailers’ worst case scenario. The typical figure in retail shops is 8 percent of sales lost. Most probably the real figure is likely higher. Many shoppers simply leave the store, if the item is not available the shelf.
By using intelligent retail solutions, the shop owners can continuously capture and analyze customer presence and activity at the store or at any individual aisles. Retailers can then use this data as a guiding line to adopt new store features and benchmark the stores customer shopping patterns and layout to other stores within the chain. This kind of test stores can reveal information of new ways to design stores and how the merchandizing should be placed within the store. Captured data can be also being used as a baseline for new marketing or promotional activities within the chain. By learning and benchmarking from the test stores, the store-owners can find a very cost effective way to pinpoint the categories for the store visitors and what at the end of the day is important, to increase ROI.