Qualitative Coding: How to Convert complex data into logical Information
Are you drowning in textual information and confused about where to begin? This analysis technique will help you understand the meaning of various qualitative data.
There are many powerful insights to be gained from qualitative research. However, the richly nuanced, complex data from techniques like diary studies, user interviews, and qualitative usability tests aren’t always easy to analyse systematically.
If you’ve accumulated many open-ended transcripts from interviews or survey responses and are unsure where to start, don’t worry. Qualitative coding is an effective tool for making sense of complex data and drawing systematic, independent, objective conclusions.
We’ll discuss:
- The steps of the process of qualitative code
- The various types of principles (inductive and deductive)
- Tools to code data and perform qualitative analysis
- Examples of quantitative data coded
- What is qualitative coding?
Qualitative coding is the method of categorising, labelling, and organising data qualitatively to find patterns and study connections between the data.
Coding lets you transform qualitative data (such as transcripts of interviews or diary entries or open-ended surveys) into quantifiable forms to allow for more organised, systematic analysis.
Coding can also be helpful when you wish to cut your data into various sections (such as ICP role, ICP and sentiments etc.) to find thematic patterns or patterns.
As you will see, we have distilled every single response into a consistent “code” or theme to help us understand the qualitative information we gathered. Though nearly a third of respondents said they didn’t have a system for tracking the impact of their user research, a large percentage of respondents said they had used techniques like analysis, stakeholder feedback, involvement with research artefacts and much more.
The general procedure for qualitative code
1. Make descriptive codes for certain specific concepts or words.
You could, for instance, make codes such as “1 – Career” for open responses to surveys related to the careers of participants and “2 – Family” for diary entries that detail the families of participants.
At first, they can be relatively broad. However, when you get deeper into the subject, it is possible to define sub-categories (e.g. “Career – hiring” or “Family – extended”).
As a rule of thumb, don’t make too precise codes to prevent confusion (for instance, “Family – extended” is acceptable; however, the addition of codes to identify first and second cousins, third cousins such as. is likely to be too complicated for use).
2. Codes are assigned to observed or observed behaviour.
If you find data of a qualitative nature that matches the themes you picked out, Tag it with the code.
If it is appropriate, you could assign multiple codes to the same information (for instance, a survey response that reads, “I love working remotely because it gives me flexibility over my schedule and working environment, helps me work more efficiently, and leaves me with more time to spend with my family” can be identified with multiple codes such as “Remote Work,” “Flexibility,” “Efficiency” and “Family.”)
3. Find out how often each code is used.
For instance, if 25 percent of responses were identified as “Career” and 50% were labelled “Family,” you can conclude that themes relating to family are more prominent within this specific study.
4. Sort your codes into categories and find patterns.
Now, you’re in the process of analysis of qualitative coding.
Create categories that are similar to similar types of code (e.g. “Laptop,” “Office,” “Salary,” and “Resume” could all fall under the heading of “Careers”) to organise your data more efficiently and to discover new connections between information points.
If you compare the categories and codes against each and each other, you’ll be able to discover themes and create an explanation of what the data you collect means.
This is the standard way to code qualitatively, but it might differ slightly based on the kind of coding technique you decide to employ.
Different types of coding used for qualitative studies: inductive and deductive. deductive
There are two kinds of codes used in qualitative data analysis inductive (a.k.a “ground-up,” “concept-driven or open) inductive (a.k.a. ‘top-down’ or ‘data-driven’).
Inductive data coding
Inductive coding is a method of quantitative data analysis that creates codes entirely from scratch based on the information you’ve collected. Inductive code is an iterative and slow process. However, it gives you a complete and accurate understanding of the data.
How can you use inductive coding for qualitative research? Inductive coding is usually used in the initial analysis phase or for exploratory study when analysing a specific type of data in the first instance with no expectations before or with set parameters. This method lets you look through your data qualitatively and assign the appropriate numbers as you move. You will likely need to go through the data several times to make adjustments where codes must be split, separated, combined, removed or new.
Deductive data coding
Deductive coding is a method for analysing qualitative data that employs a predetermined set code. It is an easier and faster method to analyse qualitative data. (Usually, however, these codes are predetermined from an earlier process called inductive).
How can you use deductive code in qualitative research?
Deductive codes are typically best for the later phases of analysis, like when conducting the field of evaluative research.
For instance, you could start with a set of subjects you’re interested in studying, such as Stakeholders, Analytics and Engagement. When you go through your information, you will assign these codes where they are.
Deductive coding may be faster and more efficient than inductive coding, aware of bias. When you have a predefined set of codes, it’s easy to get unaware of other important topics that might pop up in your data collection. Don’t focus too much on proving the theories that you overlook.
The hybrid approach
Researchers prefer to utilise a mix that combines both inductive and deductive analysis in most cases. This means that you can ensure the research questions you have identified are solved while also opening up to new topics.
Best quantitative data coding software
You can do quantitative coding using Google Sheets, Excel, or–if you’re a glutton for punishment–by hand. If you’re dealing with large amounts of data or want to simplify the procedure as much as you can, there are some fantastic automated coding tools that you can use:
Delve allows you to create and interpret qualitative data gathered from conversations, focus groups, ethnographic research, and other techniques which generate large quantities of transcript data. People love Delve for its user-friendly interface, training tools, and responsive support team but have encountered difficulties with problems with usability.
MAXQDA is a complete instrument for multi-media and qualitative analysis of data. Users love it due to its simplicity of use and its robust capabilities. However, they are frustrated by the absence of readily available training resources.
Dedoose is a cross-platform application to analyse qualitative and mixed methods data. Users love Dedoose because of its collaborative tools and accessibility via the web but find it challenging to operate and unsatisfied with their customer service.
NVivo is a tool for qualitative, quantitative, and mixed-method data analysis. Its users love it due to its extensive features and easy-to-use; however, they mention some issues and poor customer support.
The data from qualitative research–quantitative research’s ‘touchy-feely’ counterpart–is sometimes dismissed for having a higher risk of bias and subjectivity.
By using qualitative coding in your method of analysis, it is possible to make it easier to standardise the data you collect, which will help limit (but not eliminate) the possibility of bias and increase the accuracy and reproducibility of your findings.
