In order to provide information that is useful, open-ended survey questions
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Open-ended questions are great for getting authentic feedback because they give people a chance to describe what they’re experiencing in their own voice. Analyzing such survey questions yourself is an excellent opportunity to empathize with your audience, gather essential insights, and make the right decisions. Show But you may be wondering... How do you efficiently analyze more than 100 replies? Or even 1,000? Here’s a system we use at Hotjar to categorize and visually represent large volumes of qualitative data—and it’s easier than you might think! You’ll have to work with the technique a bit before you become comfortable with it, but once you get it, you’ll be sorting through mountains of qualitative data in no time. What you’ll need: To help you learn this technique, we created a data sample that you can download and use to follow along. Now let’s begin… Table of contentsStep 1: get your data into the template1) Export the data from your survey or poll into a .CSV or .XLS file. 2) Copy the data from your .CSV or .XLS file and paste it into the sheet ‘CSV Export’ of the template. 🏆 Pro tip: use 'Paste special' to paste 'Values Only' in the Hotjar analysis template, so no formulas or formatting are copied over. 3) Copy the column from the ‘CSV Export’ sheet containing the open-ended question you want to analyze first and paste it into the ‘Question 1’ sheet, in the cell marked with < Paste answers to first open-ended question here >. 4) Choose wrap text for the entire column, so the data fits the column width and is easier for you to read later on. A response category is a set of replies that can be grouped because they are part of the same theme, even if they’re worded differently. In the sample dataset we use for this tutorial, we asked Hotjar customers to explain how their employer measures their performance (e.g., revenue, conversions, traffic). In theory, you could go through every answer to identify your response categories one-by-one, but that wouldn’t be very efficient. Instead, we’re going to use a series of techniques that help you identify the broad categories. A) Use a text analyzer: text analyzers take your data and analyze it for the most commonly used words in your text, which helps you identify broad categories of responses. 🏆 Pro tip: Textalyser is a simple, free resource that does this well. Copy and paste your data into textalyser and click ‘analyze the text’ If you do this with the sample data we’ve provided above, you’ll find that ‘sales,’ ‘conversion,’ and ‘traffic’ are some of the most commonly used words in the data set: 'sales,’ ‘conversion,’ and ‘traffic’ are some of the most commonly used words in the data set and could be used as response categories As such, they represent some of the most popular replies to the question we asked. They don’t represent all the answers, of course, but they’re a good place to start when building the list of response categories. Add each category to the top of separate a separate column (replacing the text that reads, 'Response Category 01,' 'Response Category 02,' etc.): Note: some of the popular words in our text analyzer mean the same thing (e.g., 'sales' and 'revenue'), so you’ll want to create a single category for those responses called 'Sales/Revenue.' Other popular words will NOT become categories because, as stand-alone words, they tell us nothing useful (e.g., 'our,' 'rate'). B) Sort your responses alphabetically: when you sort alphabetically, you’ll notice that specific patterns emerge, and you can create more categories based on the trends you spot. In our sample data, every sentence beginning with the word 'Revenue' gets grouped when you sort alphabetically. Of course, we already have a category for 'Sales/Revenue,' so there’s no need to add that category in this case—but grouping the data alphabetically will allow groups to stand out. What is an openSo what are open-ended questions? Open-ended questions ask people to provide answers in their own words and are designed to elicit more information than is possible in a multiple choice or other closed-ended format.
Why use openOpen ended questions allow respondents taking your survey to include more information, giving you, the researcher, more useful, contextual feedback. Open ended questions allow you to better understand the respondent's true feelings and attitudes about the survey subject.
What are 3 examples of openExamples of open-ended questions include:. Tell me about your relationship with your supervisor.. How do you see your future?. Tell me about the children in this photograph.. What is the purpose of government?. Why did you choose that answer?. What is an openOpen-Ended Questions: Definition
Open-ended questions are free-form survey questions that allow respondents to answer in open-text format to answer based on their complete knowledge, feeling, and understanding. The response to this question is not limited to a set of options.
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