The new platform capabilities include enhanced historical behavioural metrics at the respondent level in the platform’s Quality Tools feature, which includes survey frequency, completion rates, qualification rates and removal rates.

The metrics can be used alongside common fraud indicators to provide a more comprehensive view of individual behaviour. 

The Data Quality Co-op platform, which launched earlier this year, uses a shared infrastructure for measuring data integrity to help address data quality challenges, inconsistencies and disruptions.

Therefore, the platform aggregates, analyses and benchmarks data quality signals across studies, suppliers and time, according to the Data Quality Co-op. 

Users of the DQC platform can track Custom Groups, which provides insight into custom quality indicators, such as brand indicators or specific regions, to help teams to understand how supplier quality or removal rates impact long-term research programmes, like brand tracking or customer satisfaction. 

Other tools include supplier score carding and competitive benchmarking to give users standardised, side-by-side performance data across providers. These tools aim to support internal benchmarking and help identify the most effective partners for specific studies or programmes. 

Reporting capabilities now includes visualisations of failure patterns across an organisation to help users identify which quality checks are most impactful, which suppliers most often trigger specific flags, and where data loss is concentrated.

Bob Fawson, co-founder at the Data Quality Co-op, said: “The DQC platform continues to evolve in service of a more transparent, efficient and accountable insights ecosystem.

“This release makes it easier for our clients to efficiently provide the highest quality insights, whether assessing quality during a client engagement, or when deciding where to source first-party data.”