The retail industry has provided various ways to solve this problem by providing self-checkout, digital checkout on mobile phone and Just Walk Out technology. One of the most inconvenient things for customers is to wait in the checkout queue. Adjusting and taking action when there is increased customer traffic For example, analyzing customer traffic (on a monthly, quarterly and yearly basis) before, during and after a peak season or holiday could indicate which store is in demand based on location and service. Being able to evaluate and compare data, across stores, during different times could be of great value to retail stores and their management. Seasonal and holiday sales can bring higher customer traffic to the store. Efficient seasonal and holiday planning and reporting Understanding daily, and even hourly, patterns can help better optimize a store’s workforce. For example, store traffic data can be analyzed for a given time in the day or for particular days in a week. Such revenue losses can be minimized by better product placement.Ī store’s workforce can be planned more efficiently depending on the customer volume. Many times, revenue is lost when customers are unable to find the product they’re looking for and decide not to ask a store associate. This can help the store manager to place popular products in popular aisles. By tracking aisle traffic, store managers can understand which aisle receives the most customer visits. Typically, the store manager is responsible for ensuring all the products are available on the shelves in the right place and in enough quantities. Now, we will walk through each of the use cases to understand how utilizing computer vision technology can help retail sales and better customer experiences. Identifying safety issues and potential threats.Adjusting and taking action when there is increased customer traffic.Efficient seasonal and holiday planning and reporting.Utilizing computer vision technology, customer traffic can be recorded in the stores, which can be used for the following use cases: With customer traffic returning to stores post pandemic, there is a need to track and plan for customer’s preferences. For retail, Forrester Research predicts that total retail sale will reach $5.5 trillion by 2027 and 70% of that will be in-store sales. However, 72% of retail shopping is still done in brick-and-mortar stores ( According to research from Forrester), as this provides consumers the physical experience of seeing, trying and holding the products in their hand. As customers become more aware about different brands, and choices of products and services, there is an increased pressure for retail clients to thrive-with a definite need of a digital presence. From personalized customer experiences to sustainability the field is ever evolving. The rise of ecommerce, use of digital promotions and targeted marketing are just some examples where technology has contributed to the immense growth of the market. From small shops to large retail chains of stores. The retail industry has changed dramatically over the last couple of decades.
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