The Benefits of AI Video Analytics for Retail Businesses

Data analytics is indispensable for any organization that wants to grow a competitive and successful business. That is particularly true for retail businesses that face increased competition and pressure. With in-store analytics of consumer behavior, retailers gain the opportunity to improve store performance and boost the productivity of their business. However, to reap the optimum value from gathered data, harnessing the power of AI is vital. In this article, we’ll explore the opportunities AI-based video analytics can give to retailers.

In essence, retail analytics implies the process of collecting and analyzing retail data related to sales, inventory, customers, etc. to get meaningful insights into the store performance. Retailers have been doing this analysis for years to discover their customer needs and current trends to make better marketing and operational decisions. New technologies such as artificial intelligence and machine learning help to facilitate this. Due to the automation and the ability to process large volumes of data, intelligent software makes retail analysis much faster and more effective. It provides store managers with full details of customer behavior and measures foot traffic in stores, thus helping them make decisions on how to optimize store operations and improve their customers’ experience.

In the battle for customers’ loyalty, more and more brick-and-mortar retailers adopt next-age technologies. According to a report by Research Nester, the global retail analytics market valued at USD 8.54 Billion in 2024 is expected to reach USD 79.78 Billion by the end of 2036, registering around 20.3% CAGR.

Store performance optimization

The first priority for any retailer is to satisfy customers’ needs, which is hard to do as shoppers are increasingly demanding. They expect to get the product they like the moment they need it and do not accept any out-of-stock scenarios or product substitutions. Thus, the key to optimizing store performance lies in better understanding customer needs in order to create the most preferred shopping environment for them and improve their shopping experience.

This is where AI analytics is useful. By analyzing data collected from traffic flow analysis, such as customers’ favorite shopping times or days, dwell-time in different store sections and preferred products, AI equips store managers with the insights required to make better, more informed decisions about their inventory, product price and placing merchandise in a store. It helps to manage supply chains, keep stocks to the optimal level and avoiding out-of-stock scenarios. With smart insights, stores can better prepare for seasonal peaks and low demand periods and determine which products to order and in what quantity. Retailers also use AI analytics to improve store design to guide customers to desired areas and products.

At the same time, AI automates and streamlines operational processes, which results in stronger performance outcomes and has a positive impact on the bottom line.

Increased store-team performance

The conversion rate is intrinsically linked with staff efficiency. Customers expect shop assistants to be available at the right time and provide good and fast service. It is observed that store associates’ performance is likely to go down when they have to serve more than seven customers at a time. That negatively affects customer satisfaction and the conversion rate drops significantly.

To understand whether employees handle their responsibilities properly, it’s critical to assess in-store traffic flow, determine where customers linger, identify when foot flow is highest, and optimize store-team performance accordingly. AI analytics steps in to assist retailers with this.

By analyzing customers’ behavior in the store, AI provides heat maps for foot traffic, which help with staffing decisions. Those are used to optimize store layouts and staff shifts according to the number of shoppers at a different time of the day, and increase the number of employees at peak times to make sure that the right number is present to handle the level of traffic. In addition, if a customer is detected standing for too long in one location, the system can notify the personnel so that they can provide assistance if it is needed.

Streamlined marketing

In-store analytics software is just the right tool to measure and streamline marketing attribution. With smart software, it is easier to understand trends, measure the number of visits, determine new and repeat visitors and assess the effectiveness of advertisement methods. Based on these insights, retailers improve their marketing programs and advertising campaigns, make decisions on ad placements or locations to produce better advertising effects on hit rate and average purchases. Studying historical patterns of consumer behavior and needs, retailers can adjust marketing promotions all year round and make them more relevant and personalized to their customers. Real-time analytics gives an extra advantage to retailers as allows them to react to poor performance live and make appropriate changes in their strategies.

Enhanced customer experience

In a retail business where customer experience rules, retailers are acknowledging the call for more effective personalization. In this regard, AI analytics is the right solution for stores that gear towards meeting customer needs and enhancing their shopping experience.

AI analytics can generate insights based on demographic traits such as location, gender, age, as well as customers’ interests, habits and values. With this consumer-related data, it is easier for retailers to identify their buyer personas and provide a curated merchandising experience, for example, stores can offer personalized discounts and adjust price strategies for different groups of customers. More than that, they can come up with personalized product recommendations based on the insights from a customer’s previous visits, thus making the customer feel even more welcome.