Remember those surveys where you respond by selecting one of five options between Strongly agree and Strongly disagree? They all are based on a popular tactic called "Likert scale".
The Likert scale is a scientifically proven method to help you understand more about your customers’ feelings, attitudes, or behavior. And in this episode, we're giving you the ultimate guide to using it for your online business. You'll learn:
Ready to add the Likert scale to your website? Read a more detailed step-by-step tutorial here.
You may also want to check out: diverging stacked bar chart - a common visualization technique for analyzing Likert scales.
Hi, you're listening to Getsitecontrol Insider, a podcast where we discuss proven ways to optimize website conversions. In this episode we're going to talk about the Likert scale, a popular survey tactic that will help you understand more about your customers' feelings, attitudes, or behavior. Stay tuned to learn exactly what the Likert scale is, when it's a good idea to use it, and how to implement it on your website.:
Originally invented in 1932 by a psychologist called Rensis Likert, the Likert scale is a common tactic used for both scientific and business surveys. In fact, you've probably taken a survey that employed the Likert scale even if you didn't know it by name when you were giving your answers. The Likert scale works by presenting a simple question or a statement that the survey-taker is instructed to react to using various levels of agreement, disagreement, or neutrality.Speaker 1:
The original implementation is called a five-point Likert scale. This is what it looks like. You create a statement and then ask the survey-takers to respond by selecting one of five options: strongly disagree; disagree; neither agree nor disagree; agree; strongly agree.:
Now the original Likert scale has been expanded into a variety of additional uses following the same concept. Sometimes these different variations are called Likert-type scales. Essentially, they use different criteria than just the five-point agreement choices. For example, if you're running a survey about customer satisfaction, you might use satisfaction instead of agreement. Here's an example. "How satisfied are you with the service that you've received?" Very dissatisfied; somewhat dissatisfied; neither satisfied nor dissatisfied; somewhat satisfied; very satisfied. Some people even use the Likert scale to examine other concepts like the frequency that respondents perform a certain activity. For instance: "How often do you read in your spare time?" Never; Rarely; sometimes; often; always. The five-point Likert scale example is the most common implementation. However, the Likert scale doesn't have to use just five options. Two common alternatives are the 7-point and the 4-point Likert scales. Both variations use the same basic idea. The 7-point scale just gives respondents more choices, and the 4-point scale excludes the neutral option to force survey-takers to pick a side. In other words, a 4-point scale options might sound like: ● Strongly disagree ● Disagree ● Agree ● Strongly agree See? No neutral option. Now, here is an important question: When should you use the Likert scale? Again, the Likert scale helps you understand how people feel about a given subject, so there are quite a lot of use cases for it. You can gauge sentiment for… ● How customers feel about your latest product. ● How helpful people find your customer support. ● How your employees feel about certain company policies, like whether they're satisfied with the vacation policy. Because you provide the statement and then ask respondents to react, you can gauge how people feel about very specific aspects of a product... or your product in general. And then, you can use the data you gather to create a more accurate user persona. However, the Likert scale is not a good option for collecting qualitative data. Remember, it asks respondents to react to a specific question using a set of pre-chosen options. In other words, the Likert scale can help you understand that people don't find your knowledge base helpful, but it doesn't help you understand why. If you want to understand the reasoning, you'll either need to use a different format or add open-ended follow-up questions to your survey. Alright, that’s a lot of new information to digest. How about we do a quick recap? Here are the pros of the Likert scale: ● It helps you quantify feelings about a subject ● It lets you focus on broad topics or specific issues. ● It is easy for survey-takers because they can choose from preset responses. ● It can be adapted to a variety of different uses including customer satisfaction, helpfulness, etc. ● It is really easy to implement on your website with online survey tools like Getsitecontrol. Now that we’ve established that, let’s see how to use a Liker scale on your website. We'll start with how to plan and craft your questions and responses. Then, we'll talk about the nuances of using the survey on your website. Step 1. Plan what you want to measure To get started, think about what exactly it is that you want to measure. Do you want to learn how shoppers feel about your checkout process? Do you want to figure out how satisfied your employees are? Are you trying to measure how effective your customer service is? Likert scale surveys work better when they're focused on a specific topic, so try not to cram a bunch of disparate objectives together. You can always run separate surveys about different topics. Step 2. Create the question or the statement that people will respond to With the Likert scale, you can either phrase your questions as actual questions or as statements. For example: Question: "How satisfied were you with your customer service experience today?" with a scale going from "Extremely dissatisfied" to "Extremely satisfied". Statement: "I was satisfied with my customer experience today", and the scale here can go from "Strongly disagree" to "Strongly agree". Now here is what you need to know about these two approaches. Questions can often elicit more accurate responses over statements because humans tend to agree with statements more often than not. Beyond choosing how to phrase things, consider the different aspects of your main objective. For example, if you're gathering feedback about your customer service, an overarching question might be the "How satisfied were you with your customer service experience today?" However, you also might be interested in how respondents feel about more specific aspects like: ● How friendly was your customer service agent? ● OR How satisfied were you with the solution suggested? Step 3. Choose your response scale When you’re choosing the answers for each question or statement, there are a few things to pay attention to. First, you'll want to choose how many options to offer: 4, 5, or 7. When in doubt, start with the 5-point scale because it's the easiest to comprehend. Another big question here is whether you want bipolar or unipolar responses: ● A Bipolar scale means that respondents can fall on two sides of the spectrum. For instance, let’s say you want to find out how your customers feel about the support team. A bipolar scale would go from "friendly" to "rude". ● Unipolar means that the scale goes from "none" to the maximum. Or, in our case, from "not at all friendly" to "extremely friendly". The difference is that "not at all friendly" does not necessarily mean "rude". It indicates the "absence of friendliness" rather than the "presence of rudeness". In general, unipolar scales are preferred because the data is cleaner and it's easier for respondents to think about. So, when in doubt, consider using a unipolar scale. Finally, be careful about the adjectives that you use in your responses. You want to use clear, descriptive words that your audience will understand. You don't get extra points for pulling out a thesaurus! You also want visitors to understand exactly where each response ranks. For example, if you have two responses like "a little helpful" and "somewhat helpful", it can be hard for respondents to understand how those two options relate. A better example would be "somewhat helpful" and "extremely helpful". With this structure, it's much easier for respondents to understand which one fits their situation. Step 4. Collect survey data Once you have your questions and a response scale, the last step is to implement your survey and start collecting data. To display a Likert scale survey on your website, you can use Getsitecontrol survey form builder. It allows you to create any type of survey including multi-page forms with open-ended questions. And the best part – it requires zero technical skills. Just decide where and when on your website you want the survey to appear. For instance, you may want to display it when a visitor spends some time on a page, scrolls downs a certain percentage of the content, or decides to leave. You can also create a direct link to the survey form and send it to your customers using email or social media. Once you gather responses, you can export the data for analysis. The exact analysis method that you choose depends on your objectives, data, and the context of your questions. If you're not sure where to begin, you can start by calculating the percentage responses for each option. For example, Getsitecontrol displays that information in a form of a spreadsheet. There is another visualization technique for Likert scales, called a diverging stacked bar chart - we’ll link it in the episode description. Time to wrap things up Before you start collecting survey data with the Likert scale, you'll want to carefully… ● Determine your objective ● Craft your questions or statements ● Create a response scale, keeping in mind the bipolar and unipolar distinction From there, you can use the Getsitecontrol to implement the Likert scale survey on your website. Ready to start collecting the insight into how people feel about your business? Go to getsitecontrol.com, register an account, and launch your free trial. Then create a Likert scale survey to start better understanding your customers. And this is it for the episode. Thank you for listening. Until next time!