Dive Brief:
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H&M earned its title as the world's largest fashion brand, but to maintain such a standing and its customers base, the retailer is changing how it uses data analysis to better understand individual store locations, according to The Wall Street Journal. Prior to using AI for a store's custom inventory, H&M stocked its shelves relatively uniformly across the globe.
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In lieu of using just H&M's team of designers to understand emerging trends to offer shoppers, the retailer is using algorithms to help assess customer receipts, returns and loyalty card data, according to the report. This gives H&M a better understanding of the supply and demand of a particular store and its regular patrons.
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The international retailer has 4,288 stores to account for, and 200 data scientists, analysts and engineers are working to help manage the data collected from purchase patterns for every item on the store sales floors, according to the report. Just as that data goes through analysis, the algorithms continuously work to follow shoppers' "ever-changing behavior and expectations," Nils Vinge, H&M's investor relations head, told the WSJ.
Dive Insight:
More data does not necessarily mean more problems. Quite the contrary, actually. Collecting massive amounts of data serves a greater purpose in a business's vitality. However, about 92% of executives remain concerned about how their organizations' use of data analytics will impact its reputation.
For example, L.L. Bean was forced to drop its "data collections analytics project" in the form of blockchain ledgers sewn into coats and boots because it drew too much public backlash.
But when big data is harnessed properly and with transparency, it has the ability to create a type of free consultation executives can use to better streamline business practices. This includes getting to know a company's customers.
Those in the retail space make their profit from understanding consumer needs. When there is a gap or delay in that understanding, sales could stagnate or even fall. It is this reason big data is now considered a company asset, not just something that sits in the cloud collecting dust.
But just like the huge clothing inventory H&M possess, big data can be hard to handle without a form of AI automation in place. This begins will moving data from on-premise servers to the cloud, which enables big data insights. Price reductions for storing big data are already declining while its processing speeds are doubling.