What Online Retailers Have Done Wrong About Algorithms and AI

Around the time the COVID-19 pandemic broke out in 2020, a group of companies in e-commerce, direct-to-consumer fashion, personal care and prepared meal kits were hailed as leading retailers who were reinventing the online shopping experience by cracking data on customer behavior.

In 2018, trade magazine for the industry RetailDive.com declared Katrina Lake “Disruption of the Year”for her role as founder and CEO of Stitch repair, a fashion site that offers a subscription service for goods curated by 3,900 part-time stylists. In an article published in the Harvard Business Review around the same time, Lake described her company as “a data science operation,” with revenues “dependent on great algorithm recommendations.”

Stitch Fix is ​​one of the more visible examples of the rise of so-called subscription box retailers. The list includes a retailer of beauty products birch box, that “curates” a collection of products and sends them to subscribers based on past purchases and algorithms that categorize consumers based on age, location, and other data points. blue aprona subscription service for ready meals, was another notable newcomer.

In early 2021, three years after the company went public, Stitch Fix’s market cap was a whopping $10 billion.

Today, just eighteen months later, the stock has lost about 95% of its value and the company is… is expected to post its first annual sales decline since the IPO in 2017.

likewise, blue apron has turned into an even uglier investment wreck — five years after the stock debuted at $140 a share, it’s trading at less than $4.

Why were the disruptors disrupted?

As it turns out, the warning signs were clear in 2018. In a piece that appeared on Quartz.comwarned Luis Perez-Breva, a lecturer and researcher at MIT’s School of Engineering, “Many retailers have forgotten what really helps customers: in-store help from human employees.”

According to Perez-Breva, “For example, to receive clean data for machine learning (artificial intelligence or AI), many retailers send customers questionnaires that are easier for computers to process.”

But, he says, “Customers are not AIs. Most never answer the questionnaires and many fill in everything they remember. This leaves retailers with erroneous… data.”

Also in 2018, consultancy giant McKinsey & Co. surveyed more than 5,000 American consumers on subscription services and found that “churn rates are high (nearly 40 percent) … and consumers are quick to cancel services that don’t offer superior end-to-end experiences.”

The McKinsey report concluded, “Consumers don’t have an inherent love for subscriptions. In any case, the requirement to sign up for a recurring subscription dampens demand and makes it more difficult to acquire customers.”

Meanwhile, several academics have written about the risks associated with collecting data on individual shoppers. It can be useful for a consumer that a retailer knows his shoe size and favorite color. But what happens if the data collected by AI and algorithms also includes the purchase of birth control pills?

For a longtime participant and observer of retail, an old maxim comes to mind: The more things change, the more they stay the same. AI is a powerful tool for managing logistics, inventory, and many other business management issues. In the case of anticipating consumer behavior, some of it is valuable, but only if used properly.

If retailers want to know what consumers want, they have a proven way to find out – by testing consumers’ products and prices before committing precious capital. Rather than crack data based on past behavior, or “curate” the profiles of consumer subgroups based on machine learning, retailers can more accurately predict trends and future demand by using real information gathered online in real time. with real shoppers. And if you’re going to apply an algorithm, you’d better prove over and over that it works.

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