Use of AI based Video Analytics in Retail Stores

AI promises to mimic human skill of seeing and decision making. For this it uses the camera feeds to analyse the live feeds. AI is now used in various sectors such Healthcare, Automobile, Robotics, Finance etc. 

AI in retail services helps to provide a modern experience to the customers which continue to drive interest among them as, it will keep customers connected to the stores. The data which are collected through video surveillance is used by AI in retail services to know about consumers and make business decisions. Video analytics helps to go over hours of surveillance video that a guard or system manager never have time to watch. 

The AI technology in video analytics gives data about the consumer who walks through the door of the store. With the help of AI video analytics, the retail industry can research their customer needs, studying buying patterns or predict any future demand and supply. 

Usually, video surveillance was installed only for security purposes, but now with the assistance of AI in video analytics, it can observe consumer behaviour and recognize faces as well. Let’s look at how AI in video analytics helps in the growth of the retail industry:-

  1. Security Purposes:

Every company or organization’s most important aspect is safety for their customers and staff. AI in video analytics can detect thefts, shoplifting and any other intrusions. 

The surveillance can activate notification and alarm systems automatically if any threat is detected. For example overcrowding or can detect unknown individual entering a no-entry.

  1. Customer Demographics:
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AI-powered video analytics can collect information about the consumers through face recognition such as age, gender or whether they are children or adults to find what type of traffic comes into the store. Marketing and advertising teams can use this information to create campaigns for product among those demographics groups. 

  1. Advertisement Metrics:

AI based video analytics helps in analyzing customer’s behaviour and measuring customer’s dwell time on the promotions. Video analytics also helps in drawing correlations with the dwell time and purchasing of the consumer. 

  1. Queue Management:

It can monitor the queue in retail stores at billing counters, It alerts if there is any delay in the service for the customers and if new counters need to be opened or which service representative is taking more time thus help to reduce unnecessary queues in the store and improve customer service. 

  1. Traffic flow in the shop:

Retailers love it when there is a flow of traffic in their shop but it is difficult to maintain it. With the help of AI-based video surveillance, you can understand the in-store traffic patterns. It allows to identify traffic patterns respond, react in time and keeping customers engaged. 

  1. Store Layout and Product Placement:

AI based video analytics can uncover the store layout which has more traffic and which products are more popular. Retail stores can position the store by the preference of consumers. The data can be collected of the number of people that enter the store and time they have spent in the shopping. 

For example stores can use AI-based video surveillance use to analyse the customer path, dwell time at the display, object contact and how many shoppers visited the shop. 

  1. Sale-day Analysis:
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During the sale season in retail stores, a large number of customers walk in through the store to buy the products. At the time of sales, video analytics identify the customer’s information such as age, gender etc data would be collected for the store to help understand about customer’s behaviour. With the number of customer’s walking in, the store can be useful to find out buying pattern of the product.

  1. People in out count:

The number of customers walking in and out of the store is valuable information for the store. The AI based analytics helps to provide operational insights and branding insights, revealing other aspects of the customer visit.

  1. Inventory Management:

Retailers lose so much money in sales due to the unavailability of a product in the stores. The biggest challenge for the retail stores is to keep their shelves filled even at peak hours. Video surveillance using AI can recognize the object to identify and fill the gaps. 

  1. Customer Experience:

AI can even detect the mood of the customer during shopping with Emotion detection. Cameras installed in every lane can be useful to detect the emotion and if the consumer is irritated then staff members can be assigned to talk to him/her/them. Emotion tracking can be helpful to build a long-lasting relationship with the consumers that will make them visit the store again. 

  1. Staff Management:

AI based video analytics would differentiate staff from customers based on facial recognition and uniform detection. With no one to assist customers, will make them lose trust in the store. This would be useful to relocate the staff in different sections of the store to attend the customer’s needs. It counts the customers in the store and transfer the staff in that place.

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Conclusion:

AI based Video Surveillance for retail can be highly beneficial  with the right implementation It can enhance customer services, advance store layout, merchandising strategies and drive data driven marketing to achieve high efficiency for the store. Unlike other video surveillance, AI powered video analytics requires no expensive setup and works without interaction with customers. 

Amazon Company is using artificial intelligence in the retail market of both its physical stores and e-commerce website to stay ahead in the competition. More companies are now investing in AI based video analytics, it can transform brick and mortar retail stores to compete with ecommerce giants.

Dhaval

Dhaval brings over 22 years of experience in Product Management and Customer Engagement.  His deep understanding of customer pain & technology led to the launch of multiple products that scaled to meet the needs of some of the largest global telcos & resulted in 10x growth for Elitecore. He was a founding team member of Elitecore (now STL Software), he built teams and led 700 employees to adopt successful agile product delivery practices. Passionate about AI & Computer vision, Dhaval founded AIVID with the vision to solve critical but repetitive tasks using automation leaving humans to focus on value creation.

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