Credit from Brian Barrett
McDonald’s is set to announce that it has reached an agreement to acquire Dynamic Yield, a startup based in Tel Aviv that provides retailers with algorithmically driven "decision logic" technology. When you add an item to an online shopping cart, it’s the tech that nudges you about what other customers bought as well. Dynamic Yield reportedly had been recently valued in the hundreds of millions of dollars; people familiar with the details of the McDonald’s offer put it at over $300 million. That would make it the company's largest purchase since it acquired Boston Market in 1999.
McDonald’s serves around 68 million customers every single day. The majority of those people never get out of their car, opting instead to place and pick up their orders at the drive-thru window. And that’s where McDonald’s will deploy Dynamic Yield first.
Look at the Dynamic Yield acquisition, then, not as the start of a digital transformation, but as the catalyst that evolves it.
Here’s what that looks like in practice: When you drive up to place your order at a McDonald’s today, a digital display greets you with a handful of banner items or promotions. As you inch up toward the ordering area, you eventually get to the full menu. Both of these, as currently implemented, are largely static, aside from the obvious changes like rotating in new offers, or switching over from breakfast to lunch.
But in a pilot program at a McDonald’s restaurant in Miami, powered by Dynamic Yield, those displays have taken on new dexterity. Algorithms crunch data as diverse as the weather, time of day, local traffic, nearby events, and of course historical sales data, both at that specific franchise and around the world. In the new McDonald’s machine-learning paradigm, significant display real estate goes toward showing customers what other items have been popular at that location, and prompting them with potential upsells. Thanks for your Happy Meal order; maybe you’d like a Sprite to go with it.
“We’ve never had an issue in this business with a lack of data,” says Easterbrook. “It’s drawing the insight and the intelligence out of it.”
McDonald’s was reticent to share any specific insights gleaned so far, or numbers around the personalization engine’s effect on sales. But it’s not hard to imagine some of the possible scenarios. If someone orders two Happy Meals at 5 o’clock, for instance, that’s probably a parent ordering for their kids; highlight a coffee or snack for them, and they might decide to treat themselves to a pick-me-up. And as with any machine-learning system, the real benefits will likely come from the unexpected.
McDonald’s defines those customer benefits broadly. Multiple executives noted that if the drive-thru is moving slowly, the menu can dynamically switch to show items that are simpler to prepare, to help speed things up. Likewise, the display could highlight more complex sandwiches during a slower period. And as with any online checkout experience, it’s unlikely that the drive-thru window will tell you that you’ve actually ordered too much. While customer satisfaction may be the goal, the avenues McDonald’s takes to get there will increase revenues along the way.
Think also beyond the store itself. A company that amasses as much data as McDonald’s will find no shortage of algorithmic avenues. “Ultimately you can see we’ll be able to use predictive analytics—we’re going to have real-time information, as we start to connect the kitchen together—further back through our supply chain. I’m sure that will happen,” says Easterbrook. “That isn’t part of this particular technology, but as you start to link the predictive nature of customer demand all the way through your stock levels in the restaurant and the kitchen, you can almost flex it back down through the supply chain." He notes that McDonald’s is a high-volume, low-margin business; anything that helps cut down on waste makes a big difference.
As you might have guessed, McDonald’s didn’t spend over $300 million on a machine-learning company just to juice its drive-thru.
Henry says he expects to see the technology in 1,000 locations within the next three months, eventually rolling out to the company’s 14,000 US restaurants and beyond. You can also expect McDonald’s to integrate its new machine-learning smarts not just broadly but deeply, albeit at a measured pace.
“Like anything else, we’re going to see that this has a capability for in-store kiosks, it has a capability for kitchens, for mobile order and pay,” says Henry. “If we try to do that at once, we may lose focus. And we need to stay focused.”
And then there’s Dynamic Yield. Founded in 2011, the company has headquarters in New York as well as Tel Aviv, and a healthy roster of blue-chip retail clients, including Ikea, Sephora, and Urban Outfitters. It will remain independently run even after the acquisition, and plans to continue growing its business outside of the Golden Arches’ shadow.
McDonald’s vetted around 30 firms offering similar personalization engine services, and landed on Dynamic Yield after proving out the technology in the Miami pilot. “It’s probably less about the product and more about the data scientists that come with it, the people that come with it, and their ability to move quickly with us,” says Henry.
Dynamic Yield essentially adds a personalization layer to the McDonald’s technology stack. The software that powers the display makes an API call with each order, and Dynamic Yield returns the results. That seamlessness has the added benefit of requiring little additional investment from McDonald’s franchisees to implement. The expensive part was the digital signs themselves.