Stage 01
Before fieldwork
- Audience and feasibility review
- Survey-link testing
- Screening-logic validation
- Quota review
- Device and technical checks
- Risk identification
6 controls at this stage
Quality and compliance
Quality controls designed to protect every research decision.
Research data is useful only when clients can trust how it was collected. Our framework combines respondent validation, active fieldwork monitoring, survey-level checks, and transparent reporting.
Quality framework
Checks before, during, and after fieldwork.
Twenty controls across three stages. Each one exists to stop a specific failure mode reaching your dataset.
Stage 02
During fieldwork
- Completion-time monitoring
- Duplicate detection
- Behavioural analysis
- Quota monitoring
- Dropout review
- Unusual response patterns
- Open-end monitoring
7 controls at this stage
Stage 03
After fieldwork
- Final validation
- Straight-line detection
- Logical consistency review
- Open-text quality assessment
- Duplicate and fraud review
- Exclusion documentation
- Clean data delivery
7 controls at this stage
What we screen out
The specific problems these controls exist to catch.
Naming the failure mode is more useful than claiming “high quality data”.
Duplicate respondents
The same person entering a study more than once under different identities.
Speeding
Completion times too short for the respondent to have read the questions.
Straight-lining
Identical answers down a grid regardless of what each statement asks.
Low-quality open ends
Gibberish, copy-paste, or off-topic text in free-response questions.
Privacy principles
Responsible handling throughout the research lifecycle.
Specific obligations vary by project and market. Our baseline approach is guided by purpose, transparency, proportionality, access control, and respect for participant rights.
- Purpose-based data collection
- Informed participation
- Data minimisation
- Secure handling
- Restricted access
- Defined retention
- Responsible deletion
- Respect for respondent rights
Transparency: certification badges are not displayed unless an active certification can be independently verified. Project requirements, consent standards, and market-specific obligations are reviewed for each engagement.
Quality questions
What clients ask about our data.
Yes. Exclusions are documented so you can see how many responses were removed, at which stage, and against which control — rather than receiving a silently cleaned file.
Both. Automated rules handle duplicate detection, timing, and pattern checks at scale; manual review is applied to open ends and to project-specific risk indicators where judgement is required.
We raise it during fieldwork rather than at delivery, and agree a course of action with you — tightening screening, replacing removed completes, or revisiting feasibility.
We do not display certification badges unless an active certification can be independently verified. We are happy to walk through our actual process in detail on request.
Participation is voluntary and study-specific information, eligibility, data use, and any incentive terms are provided before participation. Requirements are reviewed per market.
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Let’s turn your research brief into reliable results.
Tell us about your target audience, markets, methodology, and timeline. We’ll respond with a practical research approach.