Behind the Tech: KÜHL Takes on a New ML-Driven Consumer Experience Adventure
KÜHL is a manufacturer of high-performance outdoor apparel. As the line so boldly reads on the homepage of its website, the brand boasts that it is "fueled by freedom." The website also explains that KÜHL doesn’t have shareholders or VC investors. "Our livelihood depends on you and your satisfaction with our product. We never forget it."
So, it is no surprise that it recently embarked on a new partnership adventure to deliver a best-in-class digital (and more personalized) experience for its consumers.
“We had a vision to deliver a high-quality personalized experience for our customers that our existing platform just couldn’t handle. Quite frankly, our search wasn’t cutting it,” explains Timothy Boyle, e-commerce officer for KÜHL. “Relevancy and ranking were poor, and we saw a missed opportunity to meet customer’s intent with more personalized recommendations and enhanced product discovery."
Boyle owns the website experience, development and the revenue that it brings into the business — everything from SEO to product discovery to checkout. He also leads the technology roadmap and vision for his team’s e-commerce strategy alongside the rest of the executive team.
With this search challenge in the back of his mind, Boyle bumped into Lucidworks at a trade show where he felt an instant connection to the team, “and the relationship kept rolling from there,” he said.
The Path to Implementation
Boyle recognized the knowledge and expertise of the Lucidworks team and felt like they understood their vision. KÜHL needed a platform that could learn from user behaviors and incorporate those into the experience without requiring manual curation or intervention.
“Partnering with Lucidworks is like finding your adventure partner whose business model, service, and product delivers an equally incredible value. Given how sophisticated the platform is, their support and the capabilities allow our small e-commerce team to deliver personalized, relevant, and dynamic shopping experiences,” Boyle explains.
Thus, Boyle and his team decided to take on a self-implementation of the Fusion platform. The platform collects shopper signals to influence result ranking, has pre-configured machine learning (ML) models, and creates the compelling experiences stakeholders and consumers demand from, driving higher conversion and higher AOV.
One lesson Boyle immediately realized is that they should have done this a whole lot sooner — and there’s still a lot of opportunity to improve. Implementation started out by biting off small chunks, but if they had to do it again, he says they would have swung for the fences and tried to accomplish more right away. “Continuous improvement is the name of the game. Hypothesize, test, iterate, solve,” he advises.
A Continuous Improvement Journey
Right off the bat Boyle saw massive improvements in the site load and speed. As they migrated to browse, they saw anywhere from a 10% to 62% lift in category revenue from categories that were driven by the platform’s browse.
Conversely, categories that weren’t being driven by the new tool stayed stagnant or underperformed. With the machine learning capabilities, Boyle and his team has been able to deliver the personalized, relevant, and dynamic shopping experiences that they envisioned while driving AOV and conversions.
“We have a relatively small team, so we need to get the most out of every single technology investment,” explains Boyle. “My main focus is the customer experience and driving revenue, but one of the most exciting benefits of using Lucidworks is that it also improves our e-commerce team’s experience making decisions and planning.”
With the platform, the apparel brand owns and can access all of its data to identify trends and issues, and hypothesize and test solutions, and empower more informed decision making. “We’re able to more deeply connect employees and customers, and it improves the experience for both,” Boyle says.
For example, one of the metrics that they can learn from to enhance product discovery is searches that result in PDP (product detail page) click-through journeys that don’t end in add-to-cart. With this solution, KÜHL can do that type of analysis at scale to identify themes and adjust product discovery accordingly to help consumers find what they search.
Plans for the Next Adventure
Boyle adds that the apparel brand is currently in the process of upgrading to the newest version of Fusion. “We already have signals set up for search and browse, and we plan to incorporate them across the entire site experience so that we can continue to learn about our customers and improve the experience.”
Boyle and his team also have in-session individualization and geo-segmentation on the roadmap and in order to make sure that they are empowered to use all of the analytics and insights that the tool captures.
The team is also working on setting up an out of the box recommenders tool that serves up relevant product recommendations to shoppers. They also have future plans to use the Data Science Toolkit integration to connect models that were previously built
Boyle notes that it has “been a fun ride” throughout this process but reinforces that the collaboration is key. “There’s so much opportunity we still have to continue building personalized experiences for our customers across all channels, and we’re confident that Lucidworks will continue to be an incredible partner."