Quality controls and validation

Respondent quality is checked before data is shared.

DATA-ORCHID applies multiple quality controls including screening, identity checks, validation logic, attention checks and consent-led data handling. VeritasIdentity is included as part of the identity and respondent validation framework.

Build quality checkpoints around the project brief.

Quality expectations vary by audience, market, survey design and buyer acceptance rules. The right controls are agreed during project review.

Screening

Confirm topic relevance

Initial checks can cover age, location, category experience and relevant usage.

Identity

Validate participation signals

Email-based verification and respondent validation support cleaner participation.

Attention

Review response quality

Attention checks and response review can be included where the project requires them.

Feedback

Reconcile source performance

Buyer feedback supports source approvals, caps and partner payout decisions.

Illustrative quality control interface showing validation signals and response review

Practical controls for a cleaner operational handoff.

These are capability areas for project discussion, not a claim that every control is applied identically to every study.

01

Source and traffic review

Source, campaign and sub-ID context can be reviewed before volume is expanded.

02

Geographic fit

Market and location signals help align respondents with buyer targeting.

03

Duplicate controls

Deduplication and validation logic support more reliable respondent routing.

04

Buyer reconciliation

Starts, screen-outs, rejects and accepted completes create a feedback loop.

05

Consent-led handling

Respondent data practices are planned around transparency, purpose and security.

06

VeritasIdentity framework

Used as part of the respondent identity and validation framework where applicable.

Make the acceptance rules explicit.

For a useful quality review, share the survey link, target audience, markets, expected incidence, LOI, validation requirements and buyer-side rejection criteria.

Define what counts as an accepted complete.
Agree how source identifiers and sub-IDs will be recorded.
Confirm which validation signals are required before launch.
Set a review cadence for source-level feedback.

Need quality controls mapped to a buyer brief?

Start with the audience, study design and acceptance requirements.

Request a quality review