What is inductive coding in qualitative research?

Inductive coding is a data analysis process that involves reading and interpreting raw contextual data to develop themes, concepts, or a process model via interpretations based on data.

Inductive coding can also be defined as a bottom-up approach where you start with nothing, developing the code as you analyze the dataset.

Both deductive and inductive coding are used in qualitative research. Qualitative analysis methods such as grounded theory or thematic analysis primarily depend on inductive analysis. Approaches and methods such as program evaluation or content analysis rely primarily on deductive analysis.

The main difference between inductive and deductive coding is that inductive reasoning aims to develop a theory, whereas deductive reasoning aims to test an existing theory.

Qualitative coding can involve inductive coding, deductive coding, or a combination of both.

Before coding, it is important to decide if you want to develop the codes as you analyze the data (inductive), start with a set of codes and stick with them (deductive), or use a combination approach.

What is inductive coding?

Inductive coding is a ground-up approach where a researcher derives codes from the data. Researchers typically don't start with preconceived notions of what the codes ought to be, allowing the theory or narrative to emerge from the raw data.

This is ideal for exploratory research or times when researchers want to develop new theories, concepts, or ideas.

What is deductive coding?

This is a top-down approach where a researcher starts by developing a codebook with an initial set of codes. The set of codes could be based on the individual's research questions or an existing research framework/theory.

The researcher then reads through the data and assigns excerpts to codes. After analysis, the codes should still closely resemble the codebook they started with. This approach is ideal when a researcher has a predetermined structure for how they need their final findings to be.

The inductive approach typically consists of three stages:

1. Observation: for example, a user can’t find the purchase button.

2. Seeking patterns: for example, four-fifths of users tested couldn’t find the purchase button.

3. Developing a theory or general (preliminary) conclusion: for example, the purchase button needs to be redesigned or repositioned to be found more easily.

Let’s look at the steps in inductive coding (how inductive coding works):

1. Start by breaking down the qualitative data set into smaller samples.

2. Read a sample of the data.

3. Develop codes to cover the sample.

4. Reread the samples, then apply the codes.

5. Read a new data sample and simultaneously apply the codes you developed for the first sample.

6. Take note of where codes don't match or if you need extra codes.

7. Develop new codes based on the second sample.

8. Recode all responses again.

If you add a new code, split an existing code into two, or change a code's description, review how this change will affect the coding of all responses. Similar responses at different points in the survey could result in different codes.

Inductive coding is an iterative process. It takes longer and is more thorough than deductive coding. Regardless, inductive coding provides a more complete, unbiased view of the themes throughout the data.

Research studies typically combine deductive and inductive approaches to coding. You can deductively start with a set of codes, then inductively develop new ones and iterate on the existing codes as you sift through the data.

Researchers working on large projects typically start with an inductive approach to develop a relevant research topic and develop a strong working theory. Deductive research then follows to invalidate or confirm the conclusion. This can formulate a more structured project. It can also help to mitigate the risk of research bias creeping into the work.

Like any other qualitative research method, both deductive and inductive approaches are at risk of research bias, especially cognitive bias, and confirmation bias.

Inductive coding is an important approach in qualitative research. It allows the analysis of data when knowledge is limited.