Over $100 billion is lost annually by retailers due to shrinkage, AI systems can help prevent costly losses and improve the efficiency of retail operations in real-time, improve asset protection at points-of-sale, and can reduce shoplifting storewide.
According to the International Data Corporation (IDC), the retail industry is expected to spend $154 Billion on Artificial intelligence (AI) and synthetic data this year than any other sector. By 2025, the adoption rate of these technologies is expected to grow by 40%.
Companies are turning to AI and synthetic data to help them address various challenges such as the increasing number of staff shortages, shopper experience at the beginning and at checkout, theft, and more. In addition, the rising cost of labor and the impact of inflation are also threatening their profitability.
In addition to these issues, retailers are also looking into the use of AI and synthetic data to improve their operations and manage their supply chains. These tools can help them navigate through various changes that are expected to affect the retail industry in the long run. Some of these include the increasing number of buyers from different demographics and the rising cost of labor.
“Companies that are slow to adopt AI will be left behind – large and small. AI is best used in these companies to augment human abilities, automate repetitive tasks, provide personalized recommendations, and make data-driven decisions with speed and accuracy,” – Mike Glennon, senior market research analyst with IDC’s Customer Insights & Analysis team
Using AI for Loss Prevention
Despite the evolution of online shopping, brick-and-mortar stores still remain an important part of the retail industry. As technology and business leaders continue to work together, they are focusing on enhancing the customer experience and optimizing the performance of their stores. One of the most common factors that retailers consider when it comes to improving their operations is loss prevention.
The National Retail Federation (NRF) reported that over $100 billion is lost annually by retailers due to shrinkage, which is the industry term for waste, loss, and theft. Around half of this occurs in North America, and average shrink rates reach over 1.5%. For a large $20 billion grocery chain, this means a loss of around $300 million annually.
Inflation and COVID added to the problem. According to a survey, over 80% of respondents stated that their establishments experienced an increase in violence, theft, and employee theft.
As a response to this issue, many retailers are now adopting video analytics solutions that can help them reduce their shrink rates. These AI systems can help prevent costly losses and improve the efficiency of their operations in real-time, improve asset protection at points-of-sale, and can reduce shoplifting storewide. They can also help prevent theft and improve the safety of their own employees.
Warehouse to Checkout
Through the use of computer vision technology we are able to analyze and solve real-time shrinkage issues in real-time and without disruption of workflow and business. We are are able to transform any type of physical warehouse or physical retail space into a digital twin that is a data-driven and data-rich environment using synthetic data and AI.
The process allows retailers the ability to implement a comprehensive view of their own supply chain through the use of AI. This allows them to identify and resolve various end-to-end issues related to their warehouse and operations, and lets them tackle things such as the lack of inventory or the theft of goods.
We can also use intelligent video analytics systems to utilize cloud computing and AI together to give a comprehensive view of a retailer’s operations, allowing them to optimize their customer experience and reduce waste.
Using AI and synthetic data to create retail simulation, you can prevent errors and improve the efficiency of a retailer’s operations by instantly detecting and correcting both unintentional and deliberate actions at the self-checkout and staffed lanes.
Some of the highest margin items are located at the checkout line, and retailers want an experience that their customers can move through quickly to ensure a positive end-to-end shopping experience, but not too quick. Retailers want those customers to be tempted to pick up some of these impulse items as they wait for the next cashier or self-checkout spot.
This is where synthetic data and AI come to help stores simulate the checkout experience and see what checkout floor design keeps their customers moving. They’re able to do this in real-time, able to simulate thousands of scenarios and without having to disrupt current business.
Reinvent Your Business Process Through AI Powered Simulation
One of the biggest benefits of using AI and synthetic data to simulate the retail experience is you are able to take the data of millions of customer interactions with millions of products to help you reinvent your business processes. These benefits can include increased sales throughput, better customer experiences, reduced costs, and better distribution center operations.
You could use AI to simulate the shopping experience for 6,000 stores in different parts of the world all with different demographics, and create 80,000 check-out lanes to simulate the shopping experience from the moment a customers walks into a store and the checks out. You can then use that data to help reduce any type of shopping friction in your industry and bring more efficient and intuitive decision making to your business.
AI and Synthetic Data = Intelligent Stores
As retailers look to improve the experience of their customers and employees, many of them are exploring the use of digital twins and simulation to enhance the efficiency of their operations. For instance, Lowe’s uses AI-driven simulations to improve the layout and productivity of its stores. Kroger, on the other hand, uses the same technology to design the ideal shopping experience for its customers.
In-store promotions and ads can be delivered through intelligent targeting, which can help increase the cart size by offering suggestions that can be used to cross-sell and upsell. Dynamic digital signage can also help boost sales by delivering customized promotions to every shopper.
The rise of self-checkout areas, also referred to as smart “grab and go” stores, has led to the development of new technologies such as nano stores, fully autonomous stores, and shopping carts that are equipped with AI and computer vision. All of these solutions are designed to provide a more seamless and enjoyable shopping experience for customers.
Through the use of AI, retailers can create new product designs based on their customers’ feedback and market trends. This approach can help them align their offerings with the demands of their consumers.
AI, Synthetic Data, Simulation and E-Commerce Operations
There is no doubt that through this approach, retailers are able to accelerate innovation for each part of their business that would begin with buyers, impact warehouse operations, and then applied to the customer experience. This allows retailers to simulate their entire business so they can quickly adapt and fail to new situations without big costs to the company.
“AI technology will continue to bring empowering effects to users and industry sectors. With the support of pre-trained large models, multi-modal, and other technologies, AI capabilities will be applied to the whole process of production on a large scale, promoting the technology from the concept to large-scale application of landing,” said Xueqing Zhang, senior market analyst with IDC’s China Enterprise Research Department.
Instead of reinventing the retail wheel, businesses can use AI, synthetic data and simulated environments to minimize their risk.
FS Studio is a channel partner and part of the Nvidia Partner Network for Omniverse, AI, synthetic data, and simulation work.
