As a Customer Experience (CX) consultant, I often find myself discussing the intricacies of survey design with clients. Just last week, a client mentioned an issue that struck a chord with me: they’d received feedback from customers who were so puzzled by the questions in their surveys that they actually contacted the company for clarification. This highlights a critical issue in CX programmes—ambiguous survey questions.
When you send a survey to your customers, the intent is clear: you want their feedback. Whether it’s to identify pain points, highlight winning strategies, or simply gauge satisfaction, you’re asking customers to share their thoughts so that you can take meaningful action. But here’s where it gets tricky—your ability to act effectively on that feedback depends entirely on the clarity and accuracy of the data you collect.
The Problem with Ambiguity
Imagine making yourself a cup of coffee. You start with a rich, dark brew—strong and uniform. But then you add a few drops of milk. The colour begins to change, becoming lighter and lighter with each drop. Eventually, the coffee is a pale shadow of what it was. This is precisely what happens when you send out a survey filled with ambiguous questions: your data, once potentially rich and insightful, becomes diluted and unclear.
When customers receive a survey with questions that are open to interpretation, their responses will vary widely—not just in sentiment, but in the fundamental understanding of what’s being asked. Some may interpret the question one way, while others see it differently. The result? A data set that’s a mishmash of responses to slightly different questions. And just like that cup of milky coffee, it becomes impossible to separate one element from the other. The analysis will be, at best, inconclusive and, at worst, downright misleading.
This doesn’t just waste time and resources; it can also have a detrimental impact on your brand’s reputation. Customers who feel their time has been wasted with unclear surveys might view the brand less favourably, and the misleading data could lead to decisions that don’t actually address customer needs.
Take, for example, the question, “Do you find our app easy to download and use?” How do you know whether to focus on the download process or the actual usage of the app? The two experiences are quite different, and without clear guidance, respondents may interpret the question in various ways. Some might focus on the ease of downloading, while others may think about how user-friendly the app is after installation. The result will be a mixed bag of responses that don’t clearly indicate which aspect needs improvement, leading to a pool of data that’s difficult, if not impossible, to analyse effectively.
Conclusion
Within the field of Customer Experience, the clarity of your data is crucial. Ambiguous survey questions can dilute the quality of your insights, leading to inconclusive analysis and potentially harmful business decisions. By taking the time to craft clear, focused questions, you ensure that the feedback you receive is both valuable and actionable. You can, by the way, use some useful AI tools out there to help you on this task. Either way, remember, a well-designed survey not only respects your customers’ time but also paves the way for genuine improvements in their experience with your brand.
Table of Contents
-
Are Discounts for New Customers Worth It?
Have you ever seen an offer or discount ‘for new customers only’? It’s a great marketing and sales tactic to attract new customers, but what about existing ones? How do you feel when your bank or supermarket offers discounts and promotions to new customers but excludes you? Do you take this as an invitation to…
-
Feedback Bias: Navigating the Complexities of Honest Insights
Introduction: The Complexity of Feedback in Close Relationships Have you ever found it hard to be completely honest with someone you care about, even when they ask for your opinion? Now imagine that on a professional scale, where exclusivity and gratitude complicate the feedback process. Feedback isn’t just a simple transaction of thoughts. The relationship…
-
Revisiting the Apostles Model: Understanding Customer Behaviour in Today’s Context
The Apostles Model was introduced by James L. Heskett, W. Earl Sasser, and Leonard A. Schlesinger at Harvard Business School in “Customer Satisfaction Is Key to the Extraordinary Success of Service Businesses” (1991). Their foundational work has been pivotal in shaping CX strategies, and their insights remain relevant even as other metrics are more commonly…