Allow Research Insights to Emerge

Introducing Delve’s Code Groups

Extracting insights from a large set of transcripts is difficult. While it can be helpful to organize your raw data based on preconceived theories, this often leads to bias.

We built code groups in Delve to solve this problem, and to allow insights to naturally emerge from your data.

Group codes to find relationships in qualitative data

With code groups, you can organize codes together as you start to see the thematic relations in your qualitative data. This process is common in grounded theory, inductive coding, and affinity mapping.

By grouping similar or related codes, you can begin to visualize themes and allow insights to emerge.

For example, when we were building Delve, we interviewed dozens of policy researchers about their qualitative analysis workflow. We saw three common recurring themes in their transcripts: “Informing decision makers”, “Helping local community”, and “Educating the public” and coded snippets with these themes.

We found that these codes were all related to policy researcher’s desire to make an impact, so we created a fourth code, called “Desire to make an impact” and grouped the other three codes under it.

These four codes were just one branch of a larger tree that emerged from our raw data, giving us a structured way to understand the qualitative analysis process better.

Want to try Code Groups? Sign up for the Delve waitlist.

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