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Don’t Make These Mistakes on Your Next Customer Satisfaction Questionnaire

The following seven mistakes appear too often in a customer satisfaction questionnaire. In fact, they are easy to avoid if you know what to look for.

Mistake #1. Fuzzy Business Objectives

Before starting a customer survey, you should establish clear business goals. Those goals will guide you through the multitude of trade-offs you’ll face when developing the questionnaire.

“But shouldn’t we ask about that, too [insert random question here]..?”

If your goals are unclear, you’ll find yourself including questions about topics that might be nice to know, but that will provide little direction to your subsequent marketing efforts. If you can’t write down two or three clear business objectives for your customer survey, you need to pause!

Error #2. Asking Too Many Questions

Keep the customer experience in mind when thinking about a new questionnaire. If the satisfaction questionnaire goes on and on, with endless rating scales, you are likely to get a high dropout rate (participants who choose to exit the survey before completion) and/or questionable data from disinterested respondents who are just trying to get. until the last question.

Shorten your questionnaire!

Your clients and customers will give your survey more attention, which in turn, will yield better data and more customizable results.

Error #3. Questions the Respondent Cannot Answer

One of the temptations for beginning survey writers is to ask for data or information that a respondent is unlikely to know or have nearby. Or ask for information that might feel too personal or confidential to release in an investigation — even from a known sender with promises of anonymity.

In the first case, the client is forced to come up with an answer to continue, or skip the question altogether. Either way, the ‘data’ you will receive will be suspect. Better to find a less taxing question that can be answered more easily – and reliably.

In the case of confidential information, a respondent may begin to lose faith in the researcher’s intent, which almost always results in high dropout rates.

Error #4. Including Vague, Overlapping or Incomplete Response Categories

It is common to find a customer satisfaction questionnaire which include classification questions (demographics, etc.) with unclear or overlapping answer choices. Consider the following example.

Here are the possible answers for a question that asks respondents about their marital status:

A.) single

B.) not married, with children

C.) married with children

D.) never married

E.) divorced

In such a situation, the respondent is left trying to interpret the intent of the question and second-guess what was going on in the mind of the researcher who wrote the question. If you are divorced, for example, should you answer ‘single’ or ‘divorced’? On the other hand, if you are a widowed parent, would you answer “single” or “not married, with children”? You will see several other equally disturbing possibilities.

Here is another example, this one of a question asking the age of respondents.

A.) 18 – 20 years

B.) 20 – 30 years

C.) 30 – 40 years

D.) 40 – 50 years

E.) 50 – 60 years

F.) 60 + years

Two problems here. First, there is no possible answer for a 17-year-old. (Perhaps you intend to limit the survey to those 18 or older, but with the current response options, you have no way to exclude a 17-year-old using a skip pattern.)

The second problem runs through the answer choices. Can you spot it? Anyone who ages into a decade (20, 30, 40…) has two possible answers. I guess most of us would choose the younger bracket!

Error #5. Not Including Open Questions

In our haste to classify customers or prospects into specific groups and keep the analytical task manageable, it is easy to avoid open-ended questions. These are questions that ask the respondent to enter their opinions on a specific topic in a text box.

Such questions are notoriously difficult to analyze and often tend to be dismissed if you have a quantitative mindset. But if chosen correctly, they can provide extremely valuable insights that are rarely captured by closed questions.

The problem with closed questions is that we write them and we set the answer choices. In turn, those response choices will likely reflect our organization’s internal view of the market — one that comes embedded with our existing paradigms.

Allow your clients or customers the opportunity to share their insights in open-ended questions. You will be surprised at how perceptive they can be and how differently they see the world.

Error #6. Failure to Test the Questionnaire

Choosing not to test your questionnaire before releasing it to customers is asking for trouble. Any of the above mistakes can be caught by thoroughly proofreading and pre-testing your customer satisfaction questionnaire.

Just as importantly, to ensure that your survey will perform as expected, all survey settings for online questionnaires must also be tested. That means testing the invite link, any script logic or piping, data collection, exit URLs, and report output to make sure your data is saved as intended.

Once the questionnaire is up and running, it is usually possible to make small changes, but any major change, even if allowed by the questionnaire, can result in a data set that becomes almost unusable.

Remember the carpenters’ adage “measure twice, cut once.” You don’t get a second chance with a customer survey, so check it twice before sending it the invitations.

Error #7. Forgetting to Thank the Customer

Last, but not least, remember that you are asking customers to help you improve your own business. Be sure to thank them for their time and effort and keep their survey experience pleasant, short and engaging. They’ll feel better about you asking for their opinions if it’s clear that you appreciate the time it takes them to respond.

Use this checklist as you develop your next one customer satisfaction questionnaire. Avoiding these seven mistakes should improve your data quality, lead to more effective strategies and programs, and result in more satisfied customers in the long run. Which in turn, should produce better business results.

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