Foot Locker is deploying InMoment's Spotlight web-based intelligence applications to gain greater visibility and analysis of text-based feedback data.
InMoment's solution uses AI-powered natural language processing and text analytics and was developed by Lexalytics which InMoment acquired in 2021, according to a press release.
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 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 .
Using InMoment's solution, Foot Locker can 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.
Foot Locker also now has 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.
In addition Foot Locker can now pinpoint specific customers who have had negative experiences and proactively reach out to improve them, according to the release.