« All Events

Can You Trust Your Data? A New Model for Data Quality

Can You Trust Your Data - Dig Insights - 2026 Webinar Featured Images
This on-demand webinar is in partnership with:

Market research data quality is under strain. This webinar with Dig Insights and DQC explains how independent verification and ecosystem-level signals reduce risk.

Complete the form to watch the webinar recording

Webinar Signup Form (#4)

View full Event Terms

Market research data quality is harder to defend than it used to be. Professional survey takers can pass common checks, AI-assisted answers can read well without being genuine, and complex supply chains make it difficult to know where responses have come from.

In this session, Dig Insights and the Data Quality Co-op (DQC) set out a model that treats data quality as a systems problem, not a checklist. Dig describes steps taken inside its own research process, including designing mobile-first surveys to reduce disengagement, working with vetted sample partners, and applying advanced analytics and AI detection to find inconsistencies within individual datasets. Dig also discusses using multiple sources, including social conversation data, to add context and reduce reliance on a single survey.

DQC explains how independent verification can add a new layer of accountability. DQC uses platform-agnostic integrations, a persistent respondent identifier, and a respondent-level “data trust score” based on history and signals collected across the research ecosystem. The session also covers how shared quality signals can support supplier scorecarding, deduplication, reduced reconciliations, and more consistent quality management across internal platforms and external partners.

Key highlights

  • How shared quality signals can reduce reconciliations and support better supplier optimisation over time
  • Why professional survey takers, AI-generated responses, and fragmented supply chains increase risk for market research data quality
  • The limits of platform-level fraud detection when visibility is restricted to a single survey or supplier
  • Dig’s approach to quality, including mobile-first survey design, vetted sample partners, and study-specific machine learning checks
  • Using multiple independent sources, including social conversation data, to validate and contextualise survey findings
  • How DQC’s independent verification uses respondent history and cross-ecosystem signals to score trustworthiness

Speakers

Bob Fawson
Bob Fawson is Founder and CEO of Data Quality Co-Op (www.dataqualityco-op.com), the industry’s first independent first-party data quality clearinghouse.
FIND OUT MORE Bob Fawson
Kevin Hare
Kevin is a data-driven executive with 20 years of experience leveraging insights to drive decision making and strategy for some of the largest global brands.
FIND OUT MORE Kevin Hare

Learn More About Dig Insights and Data Quality Co-op (DQC)