Using The Semantic Differential Scale To Measure Customer Attitude

Lauren Heartsill Dowdle
ModernCompany
Published in
9 min readApr 25, 2017

If you’ve been following us from the beginning, you already know how important soliciting customer feedback is when working to improve the quality of your company’s services.

And, you probably know that surveys are a great way to collect that feedback.

But… the feedback you get from these outreach initiatives is only valuable if you take the time to truly put yourself in your customer’s shoes.

Unfortunately, this advice has been repeated so often that it’s pretty much lost all meaning. So let’s be very clear about what we actually mean when we say it:

When collecting and analyzing customer feedback, it’s essential that you not only consider the responses they provide, but what these responses actually mean.

One of the most effective ways to discover this meaning is by using the semantic differential scale.

The goal of the semantic differential scale is to gauge a person’s attitude toward a specific subject. This allows you to understand the value that person places on the subject at hand while also giving them the opportunity to report on how your services lived up to their expectations.

That might sound a bit complicated, so let’s make it a bit clearer by comparing the semantic differential scale to another survey type we’ve discussed in the past: the Likert scale.

Semantic Differential Scale vs. Likert Scale: What’s The Difference?

At first glance, semantic differential scales and Likert scales might seem quite similar:

  • Both ask respondents to report on a certain part of their experience by choosing an answer from a list of possible options (usually about five)
  • Both can be supplemented with further explanation if the customer chooses to do so
  • Both are used to gain a better understanding of what customers do or don’t like about your product, service, or brand as a whole

The differences between the two question types lie in how the questions are asked and which information the surveyor hopes to get from the customers’ responses.

Wording

On the surface, semantic differential scales differ from Likert scales in the way in which questions are asked.

Consider the following examples.

First, a Likert scale question:

Next, a semantic differential scale question:

The obvious difference between the two is the Likert scale question asked the customer to agree or disagree with a given statement, while the semantic differential scale question asked the customer to complete a statement, offering two polarized options along with some middle-of-the-road options.

Of course, both questions serve the same relative purpose: to determine how a customer would rate the checkout process of a specific store. But the way in which the question is asked (as well as how the answer choices are listed) can make a huge difference in how customers respond.

In the Likert scale example, the customer is given a statement that he must agree or disagree with (or respond neutrally to). But think about it: if absolutely anything about the checkout process was confusing, they simply can’t truthfully say they “strongly agree” that the process was straightforward (even if the problem they experienced was relatively minor).

In contrast, the semantic differential scale offers two descriptors as choices (along with “in the middle” options, as well): straightforward and confusing. In the case that a part of the process was slightly confusing, the customer doesn’t necessarily need to “strongly disagree” that the process was straightforward — they can simply skew their answer a bit to the right.

The way in which survey questions are worded can also distort responses due to the power of suggestion.

Consider the first example of the Likert scale-based question. Again, unless something went majorly wrong while a customer was checking out, they’ll probably agree the process was straightforward.

But, if the question instead said “The checkout process was confusing” and provided the same agree/disagree options, any seemingly minor incident during checkout would immediately come to mind, causing customers to “strongly agree” that the process was confusing.

The semantic differential scale example, on the other hand, provides polar opposite choices, allowing the customer to determine the degree to which the checkout process was straightforward or confusing.

(Again, it’s worth noting that you can elicit more in-depth responses from both types of surveys by including space for customers to expand upon their responses.)

Perspective

Semantic differential scale questions empower respondents to make their voices heard and their unique perspectives understood — much more so than Likert scale questions.

This is because the way in which Likert scale questions are worded unintentionally assume each respondent is “coming from the same place,” while semantic differential scale questions operate under the assumption that each respondent will understand the question differently — and thus answer according to his own understanding.

That was a bit convoluted, so let’s take a break to look at this picture of a sunset:

Don’t worry — there’s a point to this…

Take a good, long look at that photograph.

Now, complete the following Likert scale-like question about it:

The above photograph is beautiful. Disagree / No opinion / Agree

Now, do the same for this semantic differential scale-based question:

The above photograph is: Ugly ____ ____ ____ ____ ____ Beautiful

When I asked the Likert scale-based question, I defined the photograph as beautiful, and am simply asking whether or not you agree with me.

When I asked the semantic differential scale-based question, I kept my opinion to myself, and let you decide how to define the picture.

Semantic differential scale surveys allow your customers to define the value of a specific factor on their own. In turn, you ensure the responses they provide come from their own feelings and attitude, and have not been influenced by any outside factors.

When to Use Semantic Differential Scale Surveys

Though semantic differential scale surveys can be used for a variety of means, they’re most valuable when you need to:

  • Understand the weight of a specific aspect of your service (in terms of customer satisfaction)
  • Gain insight regarding your customer’s attitudes, needs and goals

These two points essentially go hand in hand: the aspects of your service your customers find most valuable are those which will best help them achieve their goals.

In terms of what this means for your business, semantic differential scale surveys can help you not only pinpoint your company’s strengths and weaknesses, but it will help you determine which of these aspects to focus on improving in the future.

Let’s again go back to our first example:

Of course, this is only one question out of possibly a dozen or so you might as your customers to respond to. Let’s assume, then, that their answer skews toward “confusing,” but their responses to most other questions (including one about their overall experience) are generally positive. This would tell you that, to this customer, the fact that the checkout process was a bit confusing wasn’t a deal-breaker, and had little to no impact on their experience with your store.

On the other hand, if most of their other responses were generally positive, but they reported their overall experience to be surprisingly negative, you’d be able to deduce that a streamlined checkout process is part of their expectations when doing business with your company — and that you should focus on improving this aspect of your service immediately.

As mentioned earlier, it takes time and effort to assess semantic differential scale survey responses, as the goal of doing so is to deduce qualitative information from quantitative data.

Rather than simply collecting data and taking it at face value, you should always take the time to understand why a customer responded a certain way — and what it means for your company moving forward.

Now that we understand the best use cases for semantic differential scale surveys, let’s take a look at the advantages and disadvantages of using them.

Pros and Cons of Semantic Differential Scale Surveys

We’ve discussed semantic differential scale surveys in a pretty positive light, so let’s summarize the benefits of using them in customer satisfaction surveys.

Most importantly, semantic differential scale questions are inherently user-facing, and their answers user-defined. As mentioned earlier, a customer’s response to a semantic differential scale question is their personal response.

Barring the inclusion of a narrative explanation of their responses, your customers’ responses to semantic differential scale questions are one of your most valuable assets in terms of truly getting to know your customers.

Furthermore, because semantic differential scale questions allow the customer to define their answers, there’s less chance that they’ll unwittingly misrepresent themselves, or that you (the surveyor) will misunderstand their answer.

Consider the picture of the sunset from above.

If you were given the Likert scale question and responded that you “disagree” that the picture is beautiful, that doesn’t necessarily mean you think it’s hideous. Maybe you have a high standard for what you consider beautiful, or maybe you don’t find nature all that appealing.

The only way a surveyor could know for sure what you think of the picture based on your answer to that question is if you answered in the affirmative.

On the other hand, the semantic differential scale question allows you to report exactly what you think: you either think the picture is beautiful or ugly — or you’re completely indifferent to it. Regardless of your response, the surveyor will understand your answer completely.

Of course, there are some disadvantages to using the semantic differential scale, as well.

Because the goal of using this type of questioning is to gain a more intimate understanding of your customers’ attitudes and goals. Because of this, you’ll need to go beyond simply scoring their responses and looking at the numerical data.

To get the most out of this data, you need to view their survey as a story — not isolated numbers. This will take time, effort, and other resources — which you may or may not have at the moment, depending on where your company currently stands.

Now, I know I just said that semantic differential scales are generally less convoluted or confusing than Likert scales. But there are two ways in which they can be:

  • When they provide too many response options
  • When they provide too few response options

On the one hand, too many options may overwhelm your customer. Imagine if, for example, the question about their checkout experience had ten different “middle ground” options instead of three. Now, imagine every question on the survey was like that. Safe to say, not many customers would take the time to dissect their shopping experience to that degree of certainty.

On the other hand, too few response options limit your customers’ responses — which is exactly what a semantic differential scale attempts to avoid in the first place.

Using the same example, imagine if there were only two options: “confusing” and “straightforward.” In this instance, it’s easy to imagine individuals getting caught in a thought loop: “Well, it wasn’t confusing, but there was a problem at one point…but I definitely knew what I needed to do…but still, it wasn’t exactly straightforward, either…” In turn, whichever answer they end up choosing is almost certainly not 100% accurate.

Conclusion

Semantic differential scale surveys can be a powerful tool to help you truly understand your customers not as personas, but as unique individuals with their own attitudes, goals, and needs.

Though collecting and analyzing the data gleaned from these surveys take a little more time and effort than Likert scales and other customer satisfaction surveys, the results will help you focus on improving the aspects of your service that your customers have defined as most important to them.

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Originally published at www.fieldboom.com on April 25, 2017.

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