Ulta Beauty embraces low-code to deliver better CX

Product search is also incredibly important, but equally complicated to get right. If a customer searches for “light red lipstick,” for example, there could be hundreds that are essentially light red but not labelled as such, and so their customers won’t find them. Ulta used low-code to build out new data models that make is possible to better map different product search words and plug in custom components, as well as off-the-shelf components, to simplify what customers are looking for.

While one could assume their capabilities have dramatically improved with the rise of platforms like ChatGPT, Pacynski is quick to point out these tools aren’t mature enough to do what they need them to do. And where they can deliver, she says, they need to be used strategically. For example, if a customer is looking for the best moisturizer for someone with oily skin that doesn’t contain certain ingredients, it’s important the algorithm only pulls results from the Ulta product catalogue and doesn’t suggest products they don’t carry in their stores. This kind of thing needs to be part of the product scoping process, she says.

Securing business buy-in

Developing applications in this way may have been part of the innovation team’s DNA for several years, but taking this approach to the enterprise hasn’t been easy. “It’s a journey we’re still on,” Pacynski says. “We’ve had many conversations about low-code tools broadly in the enterprise, but there’s a lot more planning, thought, training, and education needed to bring in new ones, especially because these teams already have existing solutions and methodologies.”