The retail industry is undergoing another major shift — to e-commerce. The world’s largest clothing brand is turning to artificial intelligence to win back shoppers, reports The Wall Street Journal (May 8, 2018), as it works to reverse one of the worst sales slumps in its history. H&M retail chain is ramping up its use of data to customize what it sells in individual stores, breaking with its longstanding practice of stocking stores around the globe with similar merchandise. A spike in online shopping has led to fewer customers visiting stores, and digital startups are putting up fierce competition. H&M has repeatedly slashed prices to clear out $4 billion of unsold inventory. H&M, like most retailers, relies on a team of designers to figure out what shoppers want to buy. Now, it’s using algorithms to analyze store receipts, returns and loyalty-card data to better align supply and demand, with the goal of reducing markdowns. As a result, some stores have started carrying more fashion and fewer basics. But H&M’s strategy of using granular data to tailor merchandise in each store to local tastes, rather than take a cookie-cutter approach that groups stores by location or size, is largely untested in the retail industry. Getting every store right is a mammoth task given H&M’s size. The brand has 4,288 stores, compared with Zara’s 2,127 and Gap’s 1,301. To detect trends 3-to-8 months in advance, H&M is analyzing data on a large scale from blog posts, search engines and other sources rather than relying on staff. With the help of 200 data scientists and analysts, H&M also is using analytics to look back on purchasing patterns for every item in each of its stores. The data pool includes information collected from 5 billion visits last year to its stores and websites, along with what it buys or scrapes from external sources. The chain uses algorithms to take into account factors such as currency fluctuations and the cost of raw materials, to ensure goods are priced right when they arrive in stores. Link to the Wall Street Journal article: https://www.wsj.com/articles/h-m-pivots-to-big-data-to-spot-next-big-fast-fashion-trends-1525694400 Discussion questions: How can AI and data analytics help firms like H&M? What is the impact of AI on inventory control?
The retail industry is undergoing another major shift — to e-commerce.
The world’s largest clothing brand is turning to artificial intelligence to win back shoppers, reports The Wall Street Journal (May 8, 2018), as it works to reverse one of the worst sales slumps in its history. H&M retail chain is ramping up its use of data to customize what it sells in individual stores, breaking with its longstanding practice of stocking stores around the globe with similar merchandise. A spike in online shopping has led to fewer customers visiting stores, and digital startups are putting up fierce competition. H&M has repeatedly slashed prices to clear out $4 billion of unsold inventory.
H&M, like most retailers, relies on a team of designers to figure out what shoppers want to buy. Now, it’s using algorithms to analyze store receipts, returns and loyalty-card data to better align supply and demand, with the goal of reducing markdowns. As a result, some stores have started carrying more fashion and fewer basics. But H&M’s strategy of using granular data to tailor merchandise in each store to local tastes, rather than take a cookie-cutter approach that groups stores by location or size, is largely untested in the retail industry.
Getting every store right is a mammoth task given H&M’s size. The brand has 4,288 stores, compared with Zara’s 2,127 and Gap’s 1,301. To detect trends 3-to-8 months in advance, H&M is analyzing data on a large scale from blog posts, search engines and other sources rather than relying on staff. With the help of 200 data scientists and analysts, H&M also is using analytics to look back on purchasing patterns for every item in each of its stores. The data pool includes information collected from 5 billion visits last year to its stores and websites, along with what it buys or scrapes from external sources. The chain uses algorithms to take into account factors such as currency fluctuations and the cost of raw materials, to ensure goods are priced right when they arrive in stores.
Link to the Wall Street Journal article: https://www.wsj.com/articles/h-m-pivots-to-big-data-to-spot-next-big-fast-fashion-trends-1525694400
Discussion questions:
- How can
AI and data analytics help firms like H&M? - What is the impact of AI on inventory control?
Step by step
Solved in 3 steps
