Decision-grade insight
Effect sizes, confidence intervals, and revenue impact—translated into clear go/no-go and “what to change” guidance for non-research stakeholders.
Custom research and behavioral insight work that most often supports broader data science and measurement-heavy consulting engagements.
Request a ConsultationThis capability most often supports Data Science work when teams need stronger measurement, better research design, and clearer evidence before acting on market, product, or audience decisions.
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Effect sizes, confidence intervals, and revenue impact—translated into clear go/no-go and “what to change” guidance for non-research stakeholders.
Psychometric construction (EFA/CFA, IRT, DIF) ensures scales actually capture persuasion, intent, and memory—so you’re modeling signal, not noise.
From pre/post and synthetic controls to uplift models, our pipelines are tuned to predict in-market performance and brand outcomes—not vanity scores.
Template libraries, best-practice question banks, and automated QC deliver a clean dataset and executive one-pager in days, not months.
Single/multi-cell tests, message/visual variants, brand fit and distinctiveness, recall & persuasion indices, Johnson–Neyman regions for targeted lift.
How we implement →Conjoint/choice-based, Gabor-Granger, Van Westendorp, willingness-to-pay distributions, and elasticity curves linked to conversion models.
Methods →Pre/post and exposed-control designs, aided/unaided recall, consideration, intent, brand personality movement, and halo/drag analysis.
Case snapshots →Mixture models / latent classes, needs-states, psychographic factors, and activation playbooks tied to channel and creative briefs.
Toolstack →Hierarchical regressions, key-driver analyses, path models and SEM to surface friction points and quantify what to fix first.
Methods →Construct mapping, EFA/CFA, reliability (α/ω), IRT & DIF for fairness, score bands and norms; critical incident prompts for ground-truth behaviors.
Logistic/ordinal, hierarchical & mixed effects, uplift and treatment heterogeneity, DiD & synthetic controls; SHAP/ICE for explainability.
AB/MB testing, sequential monitoring, sample-size calculators, guardrails, and pre-registration when requested.
Bias audits, privacy by design, respondent quality (bot/farm screens, straight-lining, response time), and decision logs.
Qualtrics, Alchemer, Typeform, Prolific, Dynata; custom screeners & quotas with fraud controls and region/language support.
R, Python, jamovi, SQL; reproducible notebooks, model cards, and technical appendices for your analysts and clients.
Executive one-pagers, web dashboards with uncertainty bands & drivers, stakeholder decks, and creative briefs distilled from findings.
Code + data packages, variable dictionaries, and activation runbooks for internal teams and agencies.
Variant with higher “distinctive memory cue” and “relevance” factors drove a +19% purchase-intent lift in exposed-control test.
Conjoint-guided packaging change increased projected revenue +8–11% at stable NPS; elasticity identified a safe promo band.
Needs-state cluster 3 responded to benefit-led copy; channel reallocation + creative swap reduced CPA 14% quarter-over-quarter.
Clarify decisions, success metrics, constraints, and target audiences. Align on power and timelines.
Instrument build from best-practice libraries, quotas/screeners, and automated respondent QC. Field within days.
Psychometric validation, drivers & effect sizes, scenario simulations; translate into creative/media actions.
Executive brief, deck, dashboard, and enablement workshop. Optional test-and-learn roadmap.
n≈250, core KPIs + drivers, 1 variant; executive one-pager in 5–7 business days.
Discuss Scope →n≈600–900, 2–4 variants, brand fit & distinctiveness factors, driver analysis, deck + dashboard.
Discuss Scope →Conjoint/MaxDiff, elasticity scenarios, segment activation guide, enablement workshop.
Discuss Scope →