Japanese Benefit from Artificial Intelligence in Market Control

In 2015, Lawson’s, one of Japan’s largest c-store retailers, started using artificial intelligence to help with product management. The software lets the retailer know how much to discount products based on a particular store’s sales, delivery times and local weather. Artificial intelligence informs the retailer at the best price if it is on sale.

Japan Times, according to its news; At the retail Lawson store in Tokyo’s Shinjuku, in the afternoon, a computer let employees know how much of a discount on which food items should be given. One screen says “with assorted sandwiches, 20 yen ($0.13) discount” and the other says “crispy lettuce sandwiches, 30 yen discount”. An employee then adds this information from artificial intelligence to the products as new price tags. The Times reports that although the AI ​​has eight types of sandwiches on the shelf, only one is discounted as it nears expiration time.

AI, the artificial intelligence system examines 270 product types four times a day, and the software works. Gross profit of stores in the six states that make up the Tohoku region in 2021 increased by 0.6% per store and the cost of food waste decreased by 2.5%.

Lawson’s uses AI, or artificial intelligence software, in 162 locations and is preparing to use this system across the company in 2023.

Aeon Retail, a large Asian supermarket based in Japan, uses an AI-powered discount system in around 350 stores. The technology controls the sales of each store and the prices that ensure prepared foods are sold until the store closes.

AUSTRIANS PREVENT WASTE WITH ARTIFICIAL INTELLIGENCE

Market Chain SPAR Austria recently reported that it is minimizing waste through digitization. Even if only 1% of the food offered in the store is not sold; The retailer wants to drive this further down by using data and artificial intelligence for goods ordering and supply chain management.

Using artificial intelligence, a new IT solution from SPAR ICS, it analyzes data on optimum product order quantities per store, sales volumes, weather conditions, marketing promotions, seasonality and other factors.