H&M: Utilizing Big Data and Artificial Intelligence
Changes to H&M’s business operations strategy
Introduction
With the boom of online shopping in the digital age, it is not news that brick-and-mortar retail stores are suffering due to decreased foot traffic. With COVID-19 and shelter in place, retail stores completely shut their doors, resulting in even less revenue. One retailer, H&M, saw shares go down 56% in the past three years due to slow in-store sales (Chaudhuri).
H&M plans to revamp the way the brand utilizes information technology to turn business around. The company’s goal is to win back customers through artificial intelligence and big data. Instead of stocking stores around the world with similar merchandise, H&M plans to utilize big data to customize what it sells at individual stores.
Changes to H&M’s Business Strategy
Two hundred data scientists work together to understand purchasing patterns and trends for every item in each of its stores. H&M hopes by investing in big data and analyzing customer wants at the local level, the company will increase revenue and stakeholder trust.
The management team at H&M needed to find a new way to create value for their customers. They shifted their focus to market opportunities and develop solutions to meet these opportunities. Managers and team members looked for new ways to generate value and found big data to be a promising solution.
Like most traditional brick-and-mortar retail stores, H&M utilizes a team of designers to figure out what shoppers want to buy. The designers then develop pieces that cater to shoppers' interests. However, this model proved unsuccessful and H&M now is utilizing algorithms to analyze store receipts, returns, and loyalty-card data.
Rather than taking a one-size-fits-all approach to designing clothes and stocking the stores, H&M’s new strategy tailors merchandise to local wants. Through their analysis, H&M found that value to the customer meant a more personal and high-quality experience. Customers desired products made of quality materials and fashion-forward styles.
H&M does not plan to cut the merchandising team but instead equip them with the tools and technology to make better-informed decisions. The company hopes that big data will allow H&M to avoid huge price cuts and decrease the number of unsold goods, two major issues hurting the company’s overall profits.
Proven Results
In Ostermalm, Stockholm, one H&M store historically focused on selling basics for men, women, and children. This store was one of the early adopters of the new technology. With big data and artificial intelligence, the store found that most of the customers were actually women and favored fashion-focused clothing, for example, floral skirts.
In addition, through behavioral analysis, H&M found that shoppers preferred higher-priced items. Now $118 leather bags and $107 cashmere sweaters are displayed next to the usual $6 T-shirts and $12 shorts. The store also added a coffee shop and started selling flowers, as the data revealed customers desired these services during their shopping experience.
By analyzing customer purchase and return history, the store capitalized on behavioral data and sold products that catered to the core market. H&M says that sales have improved significantly at this store, as it now supplies products more in line with the tastes of the local people.
H&M is also using big data to predict trends three to eight months in advance. Data was collected from five billion visits to the store and an online website, in addition to information from external sources. The team analyzed data across the web, ranging from blog posts to search engines. With all this information, the company now can understand the patterns and trends in fashion and produce pieces that will sell.
Moreover, the retailer utilizes algorithms to understand currency fluctuations and the cost of raw materials. This way, the company will ensure that goods are priced correctly in each store. Many competitors are also using technology to win back customers: Zara is using robots to make online order pick-ups quicker and GAP is relying on market research data and Google Analytics to understand customer preferences.
Conclusion
H&M is investing in information technology because it wants its employees to rely on data rather than their gut instincts. The algorithms work around the clock and adjust continuously to customers’ behavior and expectations. With artificial intelligence and big data, emotion is removed from decisions. The company believes this is a positive because one’s capabilities are only so limited.
H&M understands that through big data and behavioral analytics, the company will equip its employees with the best and most relevant information possible to drive the company forward. The company believes that it can increase value by selling products that are more tailored to customer’s needs. Big data empowers H&M to be more sharp, accurate, and relevant to its customers.
References
Chaudhuri, S. (2018). H&M Pivots to Big Data to Spot Next Big Fast-Fashion Trends. The Wall Street Journal. Retrieved from https://www.wsj.com/articles/h-m-pivots-to-big-data-to-spot-next-big-fast-fashion-trends-1525694400
