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Quartiles Definition

The division of the observation distribution into quarters (in the same way the median divides the distribution in half).

Quartiles are statistical values that divide a dataset into four equal parts, each containing 25% of the total observations. In marketing research, quartiles help analyze the distribution of numerical data – such as income, satisfaction scores or purchase frequency – by identifying the spread and central tendencies within a sample.

What are key aspects of quartiles in marketing research?

• Divide data into four equal segments.
• Include Q1 (25th percentile), Q2 (median), Q3 (75th percentile).
• Useful for detecting skewness or outliers.
• Help summarize data dispersion and concentration.
• Often used with boxplots and descriptive statistics.

Why are quartiles important in market research?

Quartiles are important because they offer a clear, accessible way to understand how data is distributed across a sample. They highlight central tendencies and variability, helping researchers make informed decisions, especially when comparing segments or evaluating market potential.

Who relies on quartiles in marketing research?

• Data analysts and statisticians.
• Consumer insights teams.
• Segmentation and targeting specialists.
• Marketing strategists.
• UX and CX researchers.

How do market researchers use quartiles?

Market researchers use quartiles to identify high- and low-performing segments, assess variability in consumer behavior and detect patterns in key metrics like spend, satisfaction or engagement. Quartiles can also inform pricing strategies, customer tiering and the identification of target groups for campaigns.