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    Mixed-Methods Research

    Mixed-methods research combines quantitative (numeric, statistical) and qualitative (interview, open-text) data within a single study to triangulate findings.

    Mixed-methods designs use quant to size the problem and qual to explain why. Common patterns: (1) sequential explanatory — run a survey, then interview outliers to understand them; (2) sequential exploratory — interview first to surface themes, then survey to size; (3) concurrent triangulation — run both simultaneously and compare. Mixed methods are the dominant approach in serious CX, UX, and product research because pure quant misses mechanism and pure qual misses prevalence. Modern AI-coded open-text analysis has lowered the cost of mixed methods dramatically.

    Example

    A product team surveys 800 trial users (CSAT 72%) and identifies 'pricing confusion' as the top open-text theme via AI coding. They then conduct 12 60-minute interviews with confused respondents and discover three distinct mental models, two of which are addressable via UI changes.

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    Related terms

    Open-Ended Question

    An open-ended question allows respondents to answer in their own words with free-text input rather than choosing from pre-defined options.

    Closed-Ended Question

    A closed-ended question presents respondents with a fixed set of answer choices to select from.

    Voice of Customer (VoC)

    Voice of Customer (VoC) is a systematic program for collecting, analyzing, and acting on customer feedback across every touchpoint and channel.

    Longitudinal Survey

    A longitudinal survey collects data from the same respondents (or population) at multiple points in time to measure change.

    Cross-Sectional Survey

    A cross-sectional survey collects data from a population at a single point in time, providing a snapshot of attitudes, behaviors, or outcomes.

    Sample Size

    Sample size is the number of respondents needed for survey results to be statistically meaningful at a given confidence level and margin of error.