Research-grade methodology, end to end

1. Research Design

Collaborative design phase with methodology consultants who match your research objectives to the optimal approach, sample structure, and analysis plan.

2. Sampling & Recruitment

Statistically rigorous sample design with quota controls, stratification, and multi-source panel blending for representative coverage.

3. Survey Fielding

Real-time fielding with adaptive quotas, automated quality checks, and live response monitoring across all markets simultaneously.

4. Quality Control

Automated quality screening with AI fraud detection, attention verification, and open-end quality scoring applied to every response.

5. Analysis & Weighting

Multi-stage statistical analysis with appropriate weighting (rim, propensity, or hybrid), significance testing, and driver modelling.

6. Reporting & Delivery

Automated report generation with AI-written insights, interactive dashboards, and formatted data exports in your preferred format.

Census-Representative

Quota-controlled sampling matched to census demographics for population-level insights.

Stratified Random

Population divided into homogeneous subgroups before random sampling within each stratum.

Snowball Sampling

Respondent-driven recruitment for hard-to-reach populations and niche B2B audiences.

Intercept Sampling

Real-time recruitment on websites, apps, and digital platforms for in-context research.

Panel-Based

Pre-recruited, profiled, and quality-scored panel members for fast, reliable fieldwork.

Hybrid Blending

Multi-source blending of panel, river, and client lists for optimal coverage and representativity.

Attention Checks

Embedded trap questions and instructional manipulation checks to verify respondent engagement.

Speeding Detection

Minimum time thresholds per question block with adaptive flagging for speed-through behaviour.

Straight-Lining

Pattern detection for non-differentiation in grid and matrix questions.

Bot & AI Detection

Multi-signal classifier to flag automated, AI-generated, and professional survey-taker responses.

Consistency Scoring

Cross-question logic checks and test-retest reliability scoring for data integrity.

Open-End NLP

Natural language processing to score verbatim responses for coherence, relevance, and originality.