Artificial intelligence drives success in retail

by Jennifer Meyer

The use of artificial intelligence (AI) has reached a new dimension in recent years. While many people think of chatbots or smart assistants when they hear about AI, a revolution is quietly taking place in retail. Especially at management level, where strategic decisions are made, AI tools are proving to be a success factor. Retailers who rely on this technology can make more precise predictions and are therefore able to make better-informed decisions. But how exactly does this work and who is already using AI?

For a long time, management decisions were primarily based on experience and intuition. These factors are still important, but AI offers solid data-based support. Retailers have vast amounts of data at their disposal, from sales figures to stock levels and market analyses. In the past, this data was often overwhelming and difficult to utilise. Today, AI tools can analyse it and turn it into valuable insights. In doing so, they recognise patterns that often remain invisible to the human eye.

In addition to analysing data, AI also enables well-founded forecasts. Companies can simulate how market trends, price changes, marketing campaigns or supply chains will affect their business. These predictions allow retailers to make more precise and forward-looking strategic decisions.

One company that recognised the value of AI early on is the H&M Group. The fashion company uses AI and data analysis to organise its global supply chains more efficiently and react flexibly to fashion trends, customer wishes and geopolitical developments. With the help of AI, the H&M Group has been able to optimise its inventory planning and personalise the purchasing process, among other things.

It is therefore hardly surprising that Alan Boehme, former Chief Technology Officer of the H&M Group, is convinced of one thing: “Data is everything!” In 2023, he enthused in the CIO Talk Network podcast: “Getting to know our customers better and developing unique offers – this is possible thanks to data. This not only gives us the opportunity to create a special shopping experience, but also to create a lifestyle that people identify with and want to be a part of.”

H&M also sees AI as an essential tool to achieve its vision of having a climate-positive supply chain by 2040. “With the help of AI-driven demand prediction, we can optimise our supply chain to make sure that we produce the right products for our customers, to the right store, at the right time”, says Linda Leopold, Head of Responsible AI & Data at the H&M Group. According to H&M, these AI-based predictions enable the company to avoid overstocking, which is good for the carbon footprint. At the same time, they ensure the availability of popular items – a decisive economic advantage in a market as dynamic as the fashion industry.

In food retail, AI is used particularly in inventory management. Retailers are faced with the challenge of optimising stock levels. Too few goods lead to bottlenecks, too many goods cause high costs and harbour the risk of surpluses and food waste. AI tools can analyse sales data, seasonal fluctuations, marketing campaigns and external factors such as weather conditions to create precise forecasts for reorders. SPAR Austria has already integrated AI into inventory management so successfully that the supermarket has been recognised for it.

AI also helps to optimise the shopping experience and sales when designing shop layouts. By analysing customer traffic, dwell time and purchasing behaviour, retailers can use the sales floor more efficiently. One innovative tool used here is the “digital twin”. This is a virtual replica of a shop that collects and analyses real-time data. Retailers can use this data to simulate various scenarios and make flexible adjustments without having to change the physical store.

AI also offers major advantages in the area of price and lifecycle management – i.e. the strategic management of product prices and their lifecycle in order to maximise sales and profits. AI-supported systems continuously analyse market data and competitor prices in order to develop dynamic pricing strategies. They help retailers to determine the optimum time for price changes, promotions or product sales. The fashion company Wöhrl is already successfully utilising this technology to avoid overstocking and better meet demand.

Despite all the benefits and opportunities, there are also challenges when using AI in retail management. Implementing such systems requires technical expertise and trust in the technology. Some managers may be reluctant to base their decisions on algorithms. In addition, companies must ensure that they handle the collected data sensitively and guarantee data protection.

Despite these challenges, the use of AI will continue to grow. Retailers that utilise the possibilities of this technology will probably be able to respond to the challenges of the future in a faster, more agile and, above all, more informed way.