Open-ended answers from questionnaires, surveys, and interviews are included in qualitative data.You have to sort through the responses to find connections and results since the data doesn't have numerical value.While there isn't a perfect way to analyze your data, there are still a few guidelines to follow to ensure you draw accurate conclusions.We will go over how to find the important information in your results before moving on to some common ways to interpret the data so you can learn from it.
Step 1: Write what you want to find in your data.
Depending on your research topic, you can choose any of the questions.If you want to investigate the results of the study, you need to think about why you did it in the first place.Since you can always change the old questions as you work through your data, you only need 1–2 questions.If you are analyzing customer satisfaction surveys, you could ask questions like, "What are customers struggling with the most?" or " What processes are enhancing the customer experience?"
Step 2: Get a deeper understanding by familiarizing yourself with all the responses.
Each person will have their own answers to the qualitative data.You should read through all of the responses to get a better idea of what you have.Scan through the data a few more times to make sure you understand what each response means.If you rush through qualitative data, you will get inaccurate results.
Step 3: Your initial thoughts help sort the data.
As you read through your data, keep in mind what the response has to say.Write your interpretation of the responses and how they can answer your questions in a few seconds.You can reference your notes instead of looking at the response.You can organize your responses by entering them in a spreadsheet.The full response should be copied in one column.Write your impressions in the next column.
Step 4: You can assign shorthand codes to themes.
As you review the results of your research, highlight passages that answer your questions.Take a look at the overarching theme or meaning of each passage and write a 1- or 2-word code for it.You can use the code on other passages if you write it down on a separate piece of paper.If you are interpreting a customer satisfaction survey, you can use codes like positive experience, employee issues, and problems with store.Don't use multiple codes that mean the same thing.If you already have employee issues written down, you don't need a code for employee attitudes.When you first sort your responses, use a more general code.Once you see all the data you are working with, you can use them in more specific codes.
Step 5: Find out how the majority responded by rearranging the data.
The results with the same code should be put into their own groups.Go through the responses one at a time and think about the theme of each one.Place the data into the group that has the most similarities, or make a completely new group of information if it isn't a good fit elsewhere.If multiple responses on a customer satisfaction survey mention things like confusing store layout, disorganized products, and lack of cleanliness, you might sort the responses into a "Store Issues" group.Multiple passages that fit into different themes are contained in some responses.If that is the case, cut the response in half and sort it into the matching group.You should always keep a copy of the full response.It can take a bit of trial and error to find the right groupings.If you don't find answers to your questions, try rearranging your responses into new groups.
Step 6: Do you think a response to one question influenced others?
Some of the responses you received could be related to other groups.Pick out ways in which each group could be connected to one another.You can reference quotes from your responses later if you write down your thoughts on a separate piece of paper.If a response mentions employees don't give good customer service and another response says the store was messy, you could make a connection that the employees do not care enough.
Step 7: Keep the data that answers your questions.
As you sort through your information, keep an eye out for responses that don't answer your research questions or are completely different from the majority.Excluding the outliers from the groups that support your findings can skew your results.If only one person complains about how they didn't get good service, it's probably a one-time occurrence that doesn'T add to your findings.outliers can be interesting counterpoints to the majority of your data.If a few people complain about the layout of your store, you may want to investigate if there are small changes you could make.
Step 8: Understand the big picture by reflecting on answers as a whole.
Take a look at the entire response that someone left for you.The overarching theme that you interpreted from the passage should be written down when you reach the end.You can get an idea of what happened if you focus on the order of experiences in the response.If you compare the shopping trips from multiple people, you can sort them into positive and negative experiences.You can find examples in the responses, such as fast service or helpful employees, to find out why a person responded the way they did.
Step 9: Tone, hesitation, and word choice affect the meaning of someone's answer.
If you are working with transcripts or recordings, this works well.When the people responding change their tone, pause, or construct their sentences, listen.If you find something that intrigues you or answers one of your research questions, write down your interpretation.If someone pauses for a second before answering a question, you could say that they were uneasy about the subject.If someone responds with "I really did not like the aesthetic of the store" and they put emphasis on the word "not", you might assume that they have strong feelings about how the shop looks.
Step 10: Take a look at how different groups of people responded to your questions.
Reorganization of the responses based on age, gender, or background is a better way to go through your data.If the responses are the same between people in similar social groups, record any correlations you find.To see how different generations respond, you can sort your data into 17 and under, 18–35, 36–54, and 55+.If you use demographic data, you can determine if certain groups have different experiences.If you notice a lot of people 17 and under who don't want to shop at your store, you may try to sell more products that age range is interested in.
Step 11: You don't want to skew your results if you get second opinions.
It is easy to develop bias when you are interpreting your results.If you can get a few other researchers to comb through your data, try to avoid bias.Ask them if they notice any trends you haven't found.If the other people recommend anything, write it down.