Allianz Investments: US 'Big' Home Improvement Retailers Are Using Artificial Intelligence to Gain a Leading Edge

The Zhitong Finance App learned that Allianz Investment published an article stating that in the fiercely competitive home improvement industry, large US companies are using artificial intelligence to gain a leading edge, and market participants in the home improvement industry are actively integrating artificial intelligence into their business fields. Research by Allianz Investments shows that major DIY retailers are investing heavily in artificial intelligence projects to improve the customer experience and back-end operations of their businesses. The retail industry's AI investment cycle has just begun. According to McKinsey's research, generative artificial intelligence could create $400 billion in additional value for the retail and consumer goods industry, and “big” home improvement retailers are already beginning to use this new technology in innovative ways.

Do-it-yourself (DIY) — do it yourself — is a huge and growing global industry. In the US alone, the total value of the home improvement industry is 545 billion US dollars, and it has grown at a compound annual rate of 6% over the past ten years. In the current environment, large brands are striving to improve customer experience and management costs through new technology (especially artificial intelligence) to expand market share.

Allianz Investors believes that companies have good reasons to invest heavily in artificial intelligence. McKinsey estimates that generative artificial intelligence can bring additional value of $400 billion to the retail and consumer goods industries, the easiest way to achieve this is through marketing. With this in mind, Allianz Investments' research team examined the artificial intelligence projects being carried out by two major US home improvement retailers. The combined market share of these two retailers is close to 40%:

Retailer A has approximately 1,700 stores in the US

Retailer B has approximately 2,400 stores in North America

AI-powered websites and specialized apps

Retailer A's website and app uses an AI-driven recommendation engine to recommend relevant products based on browsing history and past purchase records to help customers quickly find the items they need. The company believes artificial intelligence can help change how customers think about their brand — from a store selling products to a partner that helps customers solve problems. This approach also helps Retailer A to carry out after-sales follow-up and remind customers of maintenance and replacement times. The purpose is to change the relationship between the retailer and the customer from a single transaction to a long-term relationship.

digital twin

Retailer A uses a 3D simulation software platform from a major chip manufacturer to replicate a virtual store, which is known as a “digital twin” in the tech world. Artificial intelligence simulates a customer's journey within the store, helps optimize product layouts, and train sales staff to create a smoother shopping experience.

inventory management

Artificial intelligence can also help improve inventory management in such large stores. Most of these stores have large and heavy inventory, making transportation and storage complicated and costly. These are places where artificial intelligence can intervene in supply chain and inventory optimization.

Retailer B has developed a proprietary technology solution for its employees, combining mobile devices and specialized apps. Employees take pictures in the store, and the app uses machine vision and artificial intelligence to identify shelves that need to be replenished and quickly find specific products, reducing friction with customers during shopping and improving the store's inventory management.

Retailer A's approach goes a step further, and is testing a robot that patrols the store, using artificial intelligence and 3D maps to identify inventory differences and ensure accurate inventory data — no manual input at all. The robot is currently being tested at 11 stores in the San Francisco Bay Area.

Retailer A also uses artificial intelligence algorithms to analyze sales data and market trends to predict future demand for specific products, help optimize inventory levels, and avoid shortages. TD Cowen estimates that this technology (plus labor savings) may help increase gross margin by 20-60 pips and reduce sales, general, and administrative expenses as a share of revenue by 30-90 pips.