Over the last year or so we’ve seen retailers and ecommerce sellers adopting AI tools at a frenetic pace. From backend inventory optimization to identifying salesfloor hotspots to highly targeted marketing programs, we’re seeing an influx of great retailing practices, all being driven by AI.
For retailers with high-functioning CRM systems, AI tools are being used to identify opportunities, and increase the lifetime value of customers through compelling offers. Delivered over email or messaging applications, they help drive traffic to the store or website and engender brand loyalty.
Online retailers are using AI to create intent-based promotions. There, the AI engine measures customer intent within moments of the user arriving on-site and presents offers designed to meet that intent and close a sale. Customers who are determined to have low intent, for example, may receive an offer that they can’t refuse, while customers who are clearly going to make a purchase may be incentivized to buy more than they intended.
In physical stores, we’re seeing AI used to improve the customer experience. Computer vision can track products that consumers remove from the shelves and place in their cart. When connected to a payment device such as a credit card, this can enable consumers to load merchandise directly into shopping bags in their cart, and bring it out to their car without waiting in line.
Practical Benefits of AI in Grocery
AI has a lot to offer grocery stores, especially in inventory management. Every week grocery stores discard thousands of dollars’ worth of unsellable merchandise. This includes produce, baked goods, dairy products, meat and other items with limited shelf life.
AI tools reduce the lost inventory in one of two ways. Inventory optimization tools can improve ordering quantities, assuring that you don’t order too much or too few items. Using historical data as well as current sales numbers, it can project the number of items that will be sold over a set time period.
Pricing is another way AI fights food waste. As items move closer to their sell-by or expiration date, AI tools can optimize pricing for specific items. For example, pastries with a one-day shelf life can use AI to precisely create a sliding price point throughout the day. Prices would be highest in the morning and early afternoon and then go down at different points in the afternoon. Similarly, as milk gets closer to its expiration date, AI can be used to reduce the price of those cartons of milk, to incentivize customers to buy them instead of the milk with the longer shelf life.
AI also is being used to analyze customer purchasing behavior and use that data to increase sales. For example, the AI engine can predict when customers are about to run out of an item based on previous purchases and create offers and bundles containing these products.
AI helps grocery managers optimize staff, advising on how many employees and checkout lanes are required. It can also increase self-checkout, reducing the number of employees required to keep the store running effectively.
For shoppers, AI helps improve the customer experience. Some tools ensure that products are in stock and on the shelf, while chatbots can help customers locate items on shelves or get alerts when items are back in stock. It personalizes the shopping experience so that each shopper feels special.
Price Optimization is for all Retailers
Pricing optimization is a misunderstood AI technology, as it is often confused with dynamic pricing. Whereas dynamic pricing is used by airlines and hotels to adjust prices based on demand, pricing optimization engines use AI to determine the right price for a given item.
Today, most retailers are only able to optimize the prices for 5%-15% of the items they sell. For the remaining 85%-95% of their merchandise, they rely on rule-based tools that look at the wholesale price, factor in some expenses and add profit margin to arrive at the price. Hundreds of thousands of items are sold without ever looking at the market, considering consumer demand or factoring in the value that the item offers to consumers. Worse, factors such as geography and different inventory costs aren’t considered for retailers that operate stores in different markets.
Before AI, pricing optimization for a store that carried thousands of items was an impossible task. Today, AI-based pricing optimization tools can be used by all retailers with physical stores and those selling online. The system factors in business rules when identifying a price, but it also uses AI to analyze ERP product data, competitive and market intelligence, and user behavior analytics to recommend an optimized price point for every item sold.
While there are advantages to using pricing optimization tools with an Electronic Shelf Label (ESL), ESLs make it easier to post prices and improve the customer experience. True AI pricing optimization can be implemented on a retail floor using price tags.
AI-based pricing optimization automates pricing and provides stores with 100% optimization of their entire catalog. It’s been shown to increase revenue by up to 22% and lift profits by 8%.
Over the last two decades, we’ve seen major disruption to the retail world as shoppers took their dollars online. However, AI tools are leveling the playing field, enabling real-world stores to provide a near-digitized, real-world shopping experience.
Pini Mandel is a technology industry executive with more than 15 years of experience in leadership and executive management positions. He is the CEO and Co-founder of Quicklizard, a startup that turns data into real-time pricing decisions. Mandel manages Quicklizard’s fast-growing business worldwide, leading a team of employees and partners across Europe and North America.