The point of a customer survey is to learn what you don’t know, and gain insight into what’s driving customer satisfaction and dissatisfaction. And while billions of customer surveys are issued each year—typically including open-ended comment fields—most survey programs lack research protocols for listening to and understanding what customers are actually saying in those comments.
After all, as Seth Godin said in a recent blog: “If you’re not going to read the answers and take action, why are you asking?” In a moment, we’ll get to why reading isn’t enough, but Seth is on the right path.
There are a few reasons behind why companies often ignore their valuable customer comments.
First, many executives don’t know there are research methods for systematically and efficiently unpacking customer comments. Certainly, executives know that they could read comments or apply software-based text analytics—but what’s really needed to unpack meaning is intelligent text analysis. Unfortunately, most research agencies have not been good at educating the marketplace on the advantages of this kind of verbatim analysis.
Second, many companies—in spite of their banners and slogans pledging their customer focus—just aren’t that focused on customers and their experiences, because in the short term, it can be difficult to see how customer research is profitable.
But common sense and extensive research proves that “the market works”; customers reward companies that provide superior experiences. Nevertheless, the reality for many companies is that the voice of the customer can seem like something off in the distance, compared to the “right now” importance of shaving costs, boosting margins, etc.
So there are several reasons that customer comments get the short end of the stick, but when intelligent text analysis is applied to comments, that’s when you start to uncover incredibly valuable, actionable insights into specific ways to improve.
Is text analysis similar to just reading customer comments? Not at all. The problem with reading comments is that the brain’s working memory starts cutting off at seven items. So even if you read thousands of comments, there’s really no point, because you simply can’t remember and synthesize all that information.
You may see a few obvious problems you already knew about, but you won’t see the details or possible solutions. Furthermore, you’ll overlook more subtle existing problems, and new problems you’re not prepared to recognize. Even worse, you can’t quantify anything about this data. So if you’re only reading your survey comments, you won’t learn about unknown problems and ways to improve—and you won’t have a compelling report because business audiences demand numbers, not meandering stories.
Software-based text analytics is another way to handle customer comments—and because software can identify some types of customer issues in real time, it’s a step in the right direction. However, software text analytics runs the risk of missing problems you’re not aware of, because it’s limited (even biased) by the words, expressions and facts that you already know to look for.
In the same way that customer experiences are varied and complex, customer comments are messy and unpredictable. They can be brief or lengthy, vague or hyper specific. Some comments stay on-topic; others trail off from the question. And of course, customers refer to similar issues in different ways—and within all this complexity lies valuable, game-changing insights.
Intelligent text analysis requires a team of expert analysts so that comments can be deciphered from multiple perspectives. It also requires protocols for:
• Filtering out non-codeable text
• Building an initial framework of codes
• Establishing a statistically valid sample of codeable comments
• Adding new codes for emergent themes (good text analysis must be performed in an iterative, non-linear way)
• Scoring the coded sample to enable prioritization of themes
• Presenting prioritized themes with clear examples and solutions
Loyal customers who come back and buy again—that’s the end goal. To get there, you need actionable customer surveys with intelligent text analysis. If you spend resources on a customer survey (like most companies do), it makes no sense to ignore the answers. So ask. Then listen. Don’t let your customer survey comments be a sunk cost.
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