Major Outdoor Equipment Retailer: InMoment Uses AI-Backed Text Analytics to Automate Experience Improvement

Let’s take a look at the journey of a retailer and eCommerce company that is one of America’s biggest sellers of outdoor clothing, equipment, and services.

Retail Team Identifies Data & Survey Feedback Challenges

Consumers know what they want, and a positive customer experience is the lifeblood of any company, especially in retail. A great way to understand how a customer feels about whether a brand delivers a positive experience is through survey verbatims—or the open-ended responses consumers give to a list of questions. Since this retailer conducts thousands of surveys per month, whether post-sale, digital, in-store, or commissioned via a third party, they needed a solution that could address the following challenges:

The retailer was trying to manage siloed data sources hand-categorized into different taxonomies. They also had a requirement to get granular with the taxonomies: while still a large, physical store brand, the company’s eCommerce arm had expanded quickly, so they needed to differentiate between the online and physical experiences and the multiple, disparate categories that fall under each. And, they wanted to keep their data in-house to analyze with other internal BI tools, alongside other aspects of their data, so they needed an API.

This retailer began to tackle the Natural Language Processing (NLP) challenge internally, but they quickly determined that building a solution in-house would be too time-consuming and extremely expensive. After a thorough evaluation of text analytics vendors, this outdoor retailer narrowed its options to InMoment.

Find out how InMoment was able to provide an AI-backed text analytics solution to organize this brands’ data and survey feedback by downloading the full PDF below.


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