Crunching the numbers first means that you have a foundation to use when reading through the open-ended responses. It’s usually best to look at the numbers before you review long-form answers. When the intervals are sized equally, you can calculate data averages to summarize the information. For example, you might ask a question about their preferred budget, with potential answers listing predetermined dollar amounts: <$20, $21 – $100, $101 – $200, and $201+. Using interval questions can be valuable in segmenting your customers so that each group gets relevant questions.
Ratio data can be helpful in looking at measures of variance or calculating averages. For example, you might ask about the customer’s budget, with an open-ended input field. Any question that asks for precise information falls in the category of ratio data. This information will help you see how often your customer is interacting with your product or service. An example is a survey question like “How often do you visit our restaurant?” with potential answers including rarely, once a year, once a quarter, once a month, and weekly. If the responses fall into a logical order, then you are gathering ordinal data. Categorical data is simple to evaluate because the analysis involves counting and dividing the information to identify the most popular responses. For example, “What is your favorite product feature?” might have responses such as ease of use, size, and affordability.
When the customer chooses an answer from a list of responses, this is known as categorical data. Most survey questions fit into one of these four categories: Customize this analysis based on the type of question. Now it’s time to look at the information gathered through the survey questions. Start collecting and analyzing online survey responses fast with Jotform! Analyze four types of survey questions