Foot Locker prides itself on listening to its customers wherever and whenever they would like to leave feedback. Foot Locker is obsessed with putting the customer at the center of everything they do to remain competitive and relevant in the ever-expanding sneaker culture.
As a result, Foot Locker collects customer feedback data through numerous channels (email, call center logs, survey responses, social media, etc.). To collect, analyze, and visualize that data, it has traditionally used multiple SaaS vendors, depending on where the data resides. And while it has always had a groundbreaking CX program, it has faced numerous challenges with its analytics, including:
- The inability to automatically categorize documents using a common taxonomy
- The inability to have a uniform view of feedback data coming from disparate sources
- Collecting reams of unusable or inaccessible data
- The lack of visibility into why its systems were generating certain results without being able to easily configure or understand those systems
To help address these challenges, Foot Locker turned to InMoment, its long-time, trusted CX technology and services partner. InMoment proposed Spotlight, the company’s award-winning, web-based business intelligence application for analyzing and finding value in text-based feedback. Spotlight was developed by Lexalytics, a pioneer in machine learning and NLP, which InMoment acquired in September 2021.
Using this solution, Foot Locker can now pull all of its support and feedback streams into one place and has a single source of truth that offers uniform analytics, as opposed to a hodgepodge of “apples to oranges” insights.
In addition, while Foot Locker’s support team had been manually categorizing customer inquiries – which was time consuming and error prone—it now has a universal taxonomy across all of these data sources to capture key complaints, topics, themes, sentiment, intentions, and more, that it can now track over time. This helps streamline the process of improving their customers’ experiences and, ultimately, the business.
The use of this AI-driven solution, has now also given Foot Locker visibility into how it analyzes content and can easily modify its text analytics to meet changing data needs, a huge improvement from its previous “black box” system that didn’t expose back-end issues related to processes. As an example, Foot Locker modified its tagging process on the spot to remove the phrase “wait in queue” from a query, which solved a common problem of including unnecessary boilerplate data.
Finally, Foot Locker can now pinpoint specific customers who have had negative experiences and proactively reach out to improve them. Spotlight does this while removing all personal identifiable information (PII) and allows the company to tag the information back to the original tickets so they can quickly identify and contact the affected customers.
The value this AI-powered, NLP solution is already delivering is undeniable. It has broken down data silos by funneling all feedback through a single source, allowing uniform analysis over time; freed up customer support hours; offered an explainable, quickly configurable system; and made it easier to identify and rectify negative experiences to reduce churn and improve the bottom line.