A A A

Home >  Qualifications >  Project Portfolio >  Customer Analysis ...

Customer Analysis and Net Promoter Score

94
Technology
Text Analysis, Customer Communications Management
Retail
Marketing, Digital Commerce
Analyzing customer feedback at a global sports apparel company

A large sports apparel and footwear manufacturer was collecting more than one million customer responses per month. The company asked customers their opinions about the products and services in nearly every transaction. Feedback, in the form of structured data and unstructured, verbatim text comments, was captured from the company’s website, in-store surveys, call centers, and e-mail surveys.

The company collected real-time information to understand customer sentiment and to calculate the Net Promoter Score. The Net Promoter Score is a customer loyalty metric that is derived by asking customers how likely they are to recommend the company to a friend or colleague. Usually, the feedback consists of text comments.

The apparel company wanted to use this “voice-of-the-customer” data to quickly identify and respond to problems, improve the performance of internal operations, strengthen brand positioning and messaging, and enhance the brand image. However, with more than a million comments per month, the volume of customer comments was far too large to manually read and analyze.

The company purchased Attensity’s Analyze software product, a customer analytics and engagement application, and asked Iknow to configure the product and set up the data analysis methodology. Iknow worked with the company to process and analyze over five million comments, categorize them, and calculate the Net Promoter Score.

Iknow began this assignment by reviewing a representative data subset and developing the categories for classifying the comments. Working with the company’s marketing, digital commerce, and business intelligence staff, more than 130 categories were ultimately selected. Next, the Analyze learn-by-example (LBE) capability was used to automate the processing of text comments. The software is able to read and analyze each sentence, determine its meaning and sentiment, and classify it into one of the defined categories.

Iknow worked with the company to test and validate the results from the automated classification and to establish the internal reporting process. Results were routed to specific executives throughout the company so that they could address the problems that fell within their spans of control.

This project implemented an ongoing process for collecting, analyzing, and acting on voice-of-the-customer data and for calculating the Net Promoter Score. Prior to this project, the company read and responded to only a fraction of the feedback that it collected and its Net Promoter Score was calculated using only a small data sample. The company now electronically reads and reports on 100% of the customer comments and feedback it receives.

The apparel company expects to see significant improvements across its business operations by closing the feedback loop between its customers and the internal departments and functions that interact with these customers.