Research Design & Data Collection

  • Survey Design and Programming

    Design questionnaires with clear constructs, bias controls, trend-safe wording, and disciplined routing, then program with validation checks so every metric has a definable base, consistent scales, and clean handling of missingness.

  • Online Data Collection

    Select methods and samples that match the decision, then apply QA protocols such as speeders, straightlining, attention checks, and quota monitoring so results reflect real respondent intent, not panel artifacts or fieldwork drift.

  • Consumer Panels

    Choose sample partners, set performance standards, and define comparability rules across waves and markets, so tracking remains stable even when panel supply changes, and the team can explain differences without blaming the sample.

  • Data Processing

    Clean, label, and document datasets with reproducible rules, codebooks, and transformation logs so every derived field is traceable back to raw inputs, and a third party can audit the logic without informal institutional knowledge.

  • Advanced Data Analysis

    Apply practical analytics such as driver modeling, segmentation, indexing, and trend decomposition, then validate sensitivity and stability so outputs are decision-safe and interpretation stays grounded, plainspoken, and resistant to overfitting.

  • Market-Ready Insights and Deliverables

    Produce executive-ready outputs that tie evidence to actions leaders control, state assumptions and limits explicitly, and include the minimum visuals needed to support the claim so stakeholders can reuse the work confidently.

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