7 key applications of AI in grocery stores
AI in retail market size was valued at $6 billion in 2022. And it’s expected to exceed $100 billion by 2032, growing at a CAGR of over 30% from 2023 to 2032. The most prominent applications of AI in grocery stores are:
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Sparkling consumer interest through personalization
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Improving inventory management
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Detecting theft
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Reducing food waste
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Enabling self-checkout
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Introducing dynamic pricing
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Making more informed decisions with analytics
1. Sparking consumer interest through personalization
A survey of 1,000 adults in the US revealed that 80% of them expect personalization from retailers. Even though this is not an easy task for grocers, if they don’t get it right, customers are quick to depart for the competition. So, how can AI in grocery stores enable personalization?
Personalized marketing campaigns
A few years ago, promotions were advertised in catalogs, mobile apps, or through broadcasts. Both options were rather expensive and displayed the same information for all consumers coming to the store.
Retailers can get plenty of consumer data from sources like loyalty programs, purchase histories, online behavior, and mobile app interactions. Advanced analytics and machine learning in grocery retail analyze information on every individual buyer to discover their meal preferences, food allergies, motives behind their purchases, and more, giving store managers extensive knowledge of who is walking down their aisles. This allows retailers to craft customized promotions tailored to each customer’s needs.
For example, the Australian supermarket giant Woolworth employs AI to customize its marketing emails, considering not only consumers’ tastes but also their past shopping behavior. The retailer noticed that customers are five times more likely to buy a product that was advertised with AI compared to traditional promotion techniques.
Personalized reward systems
Grocers can also use artificial intelligence to craft personalized reward schemas. For instance, French retailer Carrefour employed machine learning in its grocery stores to build MyClub, a customized loyalty program that engages shoppers by displaying custom goals and challenges based on each client’s purchase history.
2. Improving inventory management
A recent survey in the grocery domain revealed that 86% of the respondents believe that inventory management is the most promising use case for AI in grocery stores.
Let’s see how technology can help.
Robots handling inventory
Supermarkets increasingly adopt robots to tackle inventory-related problems, such as preventing out-of-stocks, correcting labeling errors, improving packaging processes, and enhancing delivery efficiency. Below, you can find examples of commercially available robotic solutions that you can deploy in your store:
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RightHand Robotics built a grocery AI robot specialized in picking items for a reliable order fulfillment process. This robot uses superior grabbing and suctioning mechanisms to capture food items and place them in packages.
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Kiwibot supplies a delivery robot that can navigate autonomously in different environments and can be used as a last mile delivery option
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Simbe Robotics offers a robot that uses computer vision to navigate the store and identify out-of-stock items, as well as misplaced and incorrectly labeled products
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Badger Technologies developed a robot called Marty. It moves autonomously and inspects the store for hazards, such as spills
AI tools predicting demand
Another application of AI in grocery retail is demand forecasting systems. Such solutions do not purely depend on the historical data available at stores. They can learn, analyze real-time data and create forecasts even when the data is limited—for example, when introducing a new product or testing a new promotion technique.
Walmart relies on this innovative supermarket technology to forecast which products shoppers are likely to buy and restock accordingly. This analytics tool can even predict if the customer will come to the store or order the product online and have it delivered.
3. Detecting theft
Theft is a pressing concern for grocery retailers. Target cited theft as a reason for closing nine of its stores. And Jumbo, a supermarket chain in Belgium and the Netherlands, reported losing €100 million in damages because of shoplifting. This exceeds the company’s annual profit by 25%. And these are just a few examples. AI-powered supermarket technology can detect inappropriate behavior among both buyers and cashiers. Here are a few examples:
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Redner’s Markets uses AI to spot any suspicious activities from shoppers in the self-checkout line. With the help of this AI-driven tool, the grocery chain could catch a lady who was paying for her bananas while stealing meat. This customer was charged with stealing $5000 worth of goods.
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The UK’s supermarket chain Sainsbury’s deployed a computer vision solution from ThirdEye to spot suspicious behaviour. This solution runs on the existing store’s cameras and scans the aisles for theft. With this AI-powered monitoring, Sainsbury’s managed to reduce theft by half.
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Diebold Nixdorf, a checkout terminal manufacturer, implemented computer vision-based software that will notice if a shopper fails to scan an item or even scans the wrong barcode. As an added bonus, this AI in grocery solution can verify a customer’s age for age-sensitive products, such as alcohol.
4. Reducing food waste
One third of the food produced in the US goes to the garbage rather than consumer stomachs. AI has the potential to change this sad state of affairs while benefiting both the seller and the buyer. Here are a few inspiring examples of how deploying AI in grocery stores can help draw attention to products before they spoil.
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Wasteless, a promising Israeli startup, built an AI-powered tool that allows grocery retailers to recalculate product costs as they near their expiration date to sell them at an attractive price
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The New York-based startup Hungryroot built an AI-powered solution geared towards minimizing waste. It asks shoppers questions related to their diet and the frequency of meal intake. Based on this information, AI composes a shopping list with just enough items, preventing people from buying too much food that will spoil eventually. Users can still add items manually if they want. Grocery stores can tailor this solution to their needs. For instance, if a buyer has no apple preferences, the solution can recommend apples that are currently in surplus.
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Too Good To Go platform uses AI to help grocery stores pinpoint items on the verge of expiration and find customers willing to purchase these items at a discounted price
5. Enabling self-checkout
Statistically, people spend about 60 hours annually waiting in checkout lines. The conventional self-checkout system might speed up the process, but maybe not so much, as around 67% of buyers report experiencing problems. Also, such systems facilitate theft.
Grocery stores equipped with AI can correctly identify all the items collected by a particular consumer and charge that person’s bank card upon exit without any intervention from the store employees. You can enable self-checkout through AI-powered terminals or smart carts that can scan items. Let’s see how grocery stores are using this supermarket technology.
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Kroger deploys AI in its grocery stores to enable self-checkout. This platform can analyze unstructured videos and make decisions in real time. For instance, if a client fails to scan an item, the system displays a notification. If the buyer still doesn’t correct the error, the system alerts the store manager over a mobile device.
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Instacart, a grocery delivery company, built an AI-enabled shopping cart. When a buyer puts food items in this cart, it scans and weighs the products automatically. It also displays the total sum of all items, a feature that customers appreciate the most. But how sensitive must such a cart be if it can weigh products? All Instacart trolleys are equipped with Caper Cart scale that can detect tiny weights. If you have a full cart and add a single cherry on top, the scale will detect this cherry.
If you don’t want to let go of your staff or deprive your customers of human interaction, you can mirror what Walmart is doing. Cashiers at this store assume a new role of a “Host.” The host’s responsibility is to make sure all consumers are treated in their preferred way. If they favor self-checkout, a host will guide them to an open register. If they like the traditional checkout method, a host will pack their items and process the payment.
6. Introducing dynamic pricing
The dynamic pricing concept revolves around using AI to determine the best pricing strategy for different products. For this, algorithms analyze data from different sources, such as historical sales, competitor prices, stock levels, and special occasions.
The Netherlands’ supermarket chain Albert Heijn makes dynamic pricing a part of its artificial intelligence-enabled grocery shopping experience. Its analytics solution recalculates prices, taking into account demand and inventory levels, and offers different discount systems of 25%, 40%, and 70%. Shoppers see both the original and the discounted prices.
Another tactic of dynamic pricing is cross-selling a discounted item (e.g., buns) with a complimentary product (hot dogs) at a full price.
7. Making more informed decisions with analytics
AI excels at analyzing data and making suggestions on how to improve the state of affairs. You can easily use this by deploying an AI recommendation engine that will analyze your shop’s data, customer behavior, and other external factors.
Let’s see how the industry leaders are harnessing AI in grocery stores.
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Headquartered in Tel Aviv, ShopperAI built an AI solution that can analyze customer behavior and make suggestions to improve the store’s layout and product organization. The tool studied videos of customers shopping in a snack aisle in one store, and after following the AI’s recommendations, the store’s snack revenue increased by 18%. The tool also advised rearranging shampoo shelves, leading to a 25% growth in sales.
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A Japanese supermarket chain wanted to expand to China, and selecting store locations was a major concern. The management opted to use machine learning models to predict the optimal locations instead of conducting a manual study. They followed the recommendations and could open hundreds of stores per month.
How grocery stores can succeed in AI adoption
Despite the numerous AI implementation challenges, the future of AI in grocery stores looks bright. Here are the seven steps that will help you painlessly employ AI at your supermarket and reap the benefits faster.
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Define your vision for the role you expect this technology to play in your organization and the returns on investment. Deloitte recommends adopting the following paradigm: start small, scale fast, and build iteratively.
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Find the right talent to fill different expert roles. Throwing data scientists into a data lake and expecting them to present new strategies will not yield results. You will need to recruit diverse internal and external talent who can derive, transform, and sustain value in the long term.
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Adapt the organization’s culture to develop the right attitude towards AI. Many employees still view AI as an intimidating black box, which they fear and cannot understand. Make it clear that AI is there mainly to support humans and help them make informed decisions.
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Clean up your data. The amount of data that AI can use is constantly increasing as grocers gain access to information coming in video format, from social media, and via geo-location apps and devices. Despite the data growing in complexity, many retailers overlook the need for a clear data strategy.
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Gain an ecosystem advantage. Artificial intelligence capabilities for grocery stores are evolving fast, and working with an ecosystem partner will give you access to the right team to get the job done. For example, a grocery retailer can join forces with a predictive analytics and demand-sensing company.
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Even when investing heavily in technology, make sure you offer the necessary support to your less tech savvy customers. Deploying AI shouldn’t be about shifting the burden from store employees to customers. Keep the options open for your clients to use the conventional shopping process.
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Take the necessary measures to secure customer data and obtain consent if you want to use it. In a recent survey, 94% of shoppers expressed concerns about the security and privacy of their data, while 71% were willing to share this data in exchange for a more convenient grocery shopping experience.
Final thoughts
Even though some of these applications of AI in grocery stores sound futuristic, remember that customers can see what Amazon, Walmart, and other retail giants have done, and they expect something similar from other grocery stores.
Integration of AI in grocery retail is not a one-time project. It’s an ongoing transformation that has potential to reshape the retail landscape. Our AI development company will assist you every step of the way. With our extensive expertise in AI, we will help you build tailored solutions that address the unique challenges of the retail sector and offer your customers a seamless and engaging shopping experience that they will appreciate.
We also offer free reading material that will help you understand AI and what it takes to implement this technology. On our blog, you can learn more about how to build an AI system, how much it costs to implement AI, the prices associated with machine learning, and the costs of generative AI. Also, check out our recent post on generative AI in retail, if you are interested in Gen AI technology.
