Development of the Customer Sentiment Index: Measuring Customers’ Attitudes

This is Part 1 of a series on the Development of the Customer Sentiment Index (see introduction here). The CSI assesses the degree to which customers possess a positive or negative attitude about you. This post covers the measurement of customers’ attitudes and the development of empirically-derived sentiment lexicons.

I was invited to give a talk at the Sentiment Analysis Symposium (in 2012) on the use of sentiment analysis in the measurement/prediction of customer satisfaction and loyalty. There was one problem. I am not expert in sentiment analysis. I have never had the need to apply the principles of sentiment analysis to customer feedback. Until now. The work presented below was inspired by this talk.

Measuring Customers’ Attitudes using Structured and Unstructured Data

You can measure customers’ attitudes in two ways. One way to measure customer satisfaction, for example, is through structured questions that require a rating from the customers (the method I use). While there are different ratings scales (1 to 5, 0 to 10, 1 to 7), the underlying premise of all of them is that the value of the rating scale is used to infer each customer’s level of satisfaction. Lower ratings indicate lower satisfaction than higher ratings (e.g., 0 = Extremely Dissatisfied to 10 = Extremely Satisfied). Customers convey their satisfaction through the ratings they choose to provide; customers who give higher ratings (say, a rating of 10) are more satisfied (have a more positive attitude) than customers who give lower ratings (say, a rating of 3).

Another way to measure attitudes is to apply sentiment analysis to unstructured text regarding what customers say about you. Formally, Wikipedia says “sentiment analysis (also known as opinion mining) refers to the use of natural language processing (NLP), text analysis and computational linguistics to identify and extract subjective information in source materials.” Unlike the use of structured questions and ratings, in sentiment analysis, algorithms are used to assign a numerical value to what customers say. This numerical value represents the customer’s attitude (from positive to negative) about you.

In a Word

I crafted a question that I use in customer surveys for my clients. This question asks the customer (respondent) to provide one word that best describes the company’s products/services. Customers are free to write anything for their response. The question is:

What one word best describes this company’s products/services?

Development of the Customer Sentiment Index: Measuring Customers’ Attitudes