The power of segmentation – 7 ways to cut data

Here at McCrindle, we believe every piece of data tells a story. That’s why when we deploy surveys, we’re not only interested in the questions we collect, but the context of each respondent’s experience.

In our analysis we regularly employ segmentation and data cutting techniques to query down into the fine detail of the insights we collect. Below we’ll share seven unique ways we segment data to tell a story.

Generation

As leaders and experts in understanding the generations, one of the key ways we segment data is by cross tabbing questions and their data into different generations. By doing so we can see a clear picture of the differences between the generations and how each age group approaches different contexts, which is influenced by the era which shaped them.

Location

Not only does age have an impact of someone’s experience, so does location. We ask our respondents where they live as it helps paint a picture for the different experiences and challenges they may be facing. As an example, someone’s experience in Western Australia may be different to that of those living in Victoria. Including questions to understand location can validate differences across a country.

Capital city or region

One’s environment and surroundings contributes to the lens they use to view the world, and capital city living is vastly different to regional or rural living in many ways, as we see in our data. This is why a question on metropolitan area is included, to explore the differences between the impacts of liveability type has on people.

Gender

Male and females have a unique perspective of how they view the world. Despite our societal drive to find true equality, males and females still have underlying unique perspectives and attitudes. Including gender in your demographic questions can highlight gender perspectives that provides depth to your data.

Household

Household disposition and who lives at home with you creates a picture of the context of each individual’s life. A couple family with dependent children is a completely different environment compared to for example, a sole individual living at home. While they might display some similarities, priorities and decisions along with attitudes often differ in many ways, and providing context for household type can provide a clearer lens into understanding this better.

Income

A household’s combined income bracket can add to the picture of a person’s unique setting. Different income brackets can uncover differing priorities and, in many cases, diverse financial decisions. Including an income question to segment data can clarify the priorities households have financially and how they differ across each income bracket.

Employment

Understanding how respondents spend their time during a week can provide a clear context for the individuals within your data set. From home duties, to full-time work, to retirement and more, capturing employment delves into the nuances of people and their context and uncovers how their perspective might be shaped through differing employment.

Segmenting your data provides multiple options to view and uncover new insights. If you’re interested in learning how to look for fresh stories within your data, reach out to our team who can show you how.