H&M uses big data and AI to “save” sales decline
With the rise of the online shopping trend in the digital age, the reduction in physical store traffic has become the number one problem that plagues retail stores. In the double suppression of COVID-19 and social isolation policy, the entire retail industry has been further devastated. Take H&M, a well-known fast-moving consumer clothing brand, as an example. Due to limited store sales in the past three years, the company’s share price has fallen by 56%.
To this end, H&M plans to adjust the way it uses information technology to improve business performance. Their goal is to win customers’ favour again through artificial intelligence and big data. As for the specific strategy, they hope to use big data to plan apparel categories sold in different stores, instead of providing the same supply of goods to all stores around the world.
H&M’s business strategy adjustment
At present, H&M has convened 200 data scientists, hoping to understand the sales model and trend of each product in each store. H&M hopes that by investing in big data technology and combining customer demand sorting at the local level, it will help it increase its own revenue while gaining the trust of stakeholders.
To achieve this goal, H&M’s management team needs to find a new way to create value for customers. They began to shift their focus to exploring market opportunities and developed corresponding solutions to seize these new opportunities. After research, managers and team members found that big data seemed to be a solution with great potential for success.
Like most traditional brick-and-mortar retail companies, H&M originally analyzed the preferences of consumers through a team of designers, and then developed products that catered to buyers’ tastes. But in fact, this model is not successful. To this end, H&M began using algorithms to analyze store revenue, returns, and membership card data.
H&M’s new strategy no longer emphasizes universal apparel and store design, but tailors products according to local needs. Through analysis, H&M found that personalization and high-quality experience have become the only magic weapon to attract customers. Customers also hope to see high-quality materials and more fashionable design elements in apparel products.
It is worth mentioning that H&M does not intend to reduce the merchandise sales team, but to equip them with advanced tools and technologies to make more informed decisions. The company hopes big data can help H&
Verification results:
In Ostmalm, Stockholm, there is an H&M store that always sells basic clothing for all ages and genders. In the early stage of technology trial, this store found that most of the customers who come to shop through big data and artificial intelligence are women, and they prefer fashion clothes such as flower skirts.
In addition, through behavior analysis, H&M found that shoppers are more willing to choose higher-priced products. To this end, they began to display a $118 leather bag and a $107 cashmere sweater next to a $6 T-shirt and $12 shorts. In addition, they also added a coffee shop and sold flowers at the same time, because the data shows that customers want to rest in the place when shopping, or buy bouquets and clothing as gifts at the same time.
By analyzing the customer’s purchase and return records, this store has obtained a wealth of behavior data and favorite product types in the core market. H&M said that after the strategy adjustment, the store’s sales ushered in a significant increase, and now the products and experiences they provide are more in line with local preferences.
At the same time, H&M also uses big data to forecast sales trends three to eight months in advance. In addition to collecting information provided by external sources, they also collect data through 5 billion visits to stores and online websites. After analyzing the entire network data (including blog posts, search engines, etc.), the H&M team was able to understand the fashion trends and changing trends, thereby producing new items that are expected to become popular models.
More importantly, the retailer also uses algorithms to understand currency exchange rate fluctuations and raw material costs. In this way, they can ensure that the goods are correctly priced in each store. In fact, other competitors are also using similar technologies to win customers’ favor. For example, Zara is using robots to speed up online order taking, and GAP relies on market research data and Google Analytics to understand customer preferences.
Summary: Empower employees with the power of data and AI
In general, H&M has invested a lot of resources in information technology, the main purpose is to help employees really use data-not intuition-to make judgments. These algorithms operate around the clock and are constantly adjusted to suit customer behavior and expectations. With the help of artificial intelligence and big data, our decisions are no longer affected by human emotions. H&M believes that this is a positive signal and is expected to break through the limitations of human capabilities in the field of decision-making.
H&M realizes that through big data and behavior analysis technology, companies will provide employees with the most reliable and most relevant information, and use this to promote the development of the company. The company believes that this is the only way to fully match product design with customer needs and ultimately increase operating value. Now, the maturity and popularization of big data technology is giving H&M a clearer vision, a more accurate positioning, and a stronger customer understanding.
Originally published at https://techpomelo.com.
