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    Longitudinal Survey

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

    Longitudinal designs are essential for causal inference, lifecycle analysis, and tracking how customer sentiment evolves. Three common variants: (1) trend studies survey different samples from the same population over time; (2) cohort studies follow a defined group (e.g., Q1 2026 signups) through their lifecycle; (3) panel studies survey the exact same individuals repeatedly. Longitudinal data reveals dynamics that cross-sectional snapshots cannot — e.g., that NPS decays 12-15 points within 90 days of a support failure, or that onboarding-cohort retention diverges by week 4. The trade-off is panel attrition and respondent fatigue.

    Example

    A B2B SaaS tracks the same 200 customers monthly for 12 months. Cohort signed up in January 2026; by month 6, panel attrition is 22%; weighted retention NPS at month 12 is +18 vs +34 at month 1, revealing a renewal-risk window in months 4-6.

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    Related terms

    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.

    Panel Survey

    A panel survey repeatedly surveys the same pre-recruited group of respondents over time, enabling within-person change analysis.

    Pulse Survey

    A pulse survey is a short, frequent survey (3-5 questions) used to track sentiment over time.

    NPS Trend

    NPS trend tracks how Net Promoter Score changes over time, surfacing directional shifts that a single-period score cannot reveal.

    Customer Journey Mapping

    Customer journey mapping is the practice of visualizing the end-to-end experience a customer has with a brand across stages, touchpoints, channels, and emotions.

    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.