The company’s RAMBO program leverages a proprietary, patent-pending algorithm that determines where to ship an e-commerce order. Developing during the retail store closures, the recommendation engine predicts whether a product will need to be discounted in the future, which in turn determines whether it’s more profitable to sell the item at full price and ship from a store — even if the cost of shipping will be higher than from a distribution center.
It also determines how to minimize the number of shipments from different places, further bolstering both customer service experiences and sustainability efforts.
Consumer Engagement Cues and Collection
Levi’s recommendation engine, first developed in 2019, works in real time to understand consumers’ online behavioral cues to provide personalized shopping recommendations. The tech is not only increasing its mobile app downloads, but it’s also raising average order value.
Its Red Tab consumer loyalty program, meanwhile, is collecting first-party data from its more than 5 million members that extends beyond straight demographics — such as interests, desires, and connections. Levi’s then applies machine learning to predict the most relevant benefits for each member so it can serve up exclusive offers, such as access to events and new products.
Boot Camp Marches On
Demystifying artificial intelligence across the enterprise is a common challenge for today’s consumer goods companies, and Levi’s is no different. To combat this, they’re taking steps to increase education and access to show what’s been accomplished and what’s possible.
Its machine learning boot camp is probably the most visible evidence of these efforts. Launched last year and open to all employees, it’s now graduated 101 members and is set to enroll 60 more in the spring. The program has digital upskilling portfolio with two dimensions — audience and skill set — with hands-on education in such writing scripts in Python and the upcoming session now adding statistics.
Not only does it pull people out of their daily responsibilities for eight weeks to focus on their education and work on real-life use cases, but it also offers the opportunity to work with people they may not have otherwise met. The program culminates with a presentation to the Levi’s executive team.
While boot camps are not necessarily a new concept, this one differs in that it’s open to all employees, says Walsh, who describes the application process and screening as very rigorous. “It’s hard to find people who will make it through the boot camp and apply their skills, but don't have any kind of coding or statistics skills as a prerequisite, [so] the application process screens for problem solving.”
In measuring its success, Walsh touts more than just the 100% graduation rate: About half of the graduates apply the skills they’ve learned least a quarter of their time — and this includes the associates who work in retail stores, not just Levi’s corporate.
For example, a retail store manager in a Denver premium outlet store created a neural network that identifies the optimal way to bundle products in the best outfit. Now when helping customers, she can make recommendations that draw from her previous experience and the data- and ML-powered predictions.
Another employee developed a model that predicts the likelihood of equipment failure in her distribution center — a particular pain point for that associate. She also created a streaming app to make the tech usable to other distribution center employees, enabling them to proactively dispatch technicians when they receive a warning the tech may malfunction. While they’re not yet using it other distribution centers, Walsh said it is something they can scale.