IncQuery Released Enhanced Quality Control System
The research platform update provides teams with customizable behavioral indicators to vet survey data quality.
Updated on Oct. 6, 2026 in Software
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IncQuery has launched an upgraded quality control system designed to help research teams identify suspicious responses. The software assigns data quality scores by monitoring respondent behavior through active time and page-click tracking.
Why it matters
These updates allow research teams to implement rigorous data vetting processes that can be transparently communicated to stakeholders. By using customizable signals, organizations can better tailor their assessment workflows to specific study needs.
The system evaluates survey respondents using behavioral and technical metrics, including active time and clicks per page. Users can adjust the weight of survey-specific flags to customize the automated quality assessment process.
The players
IncQuery
IncQuery is a technology company founded in 2016 that provides data quality control software for research teams.
The details
The platform flags suspicious activity for manual review, ensuring that automated vetting does not compromise data integrity. This system enables researchers to categorize and document their vetting methods more effectively when presenting results to clients.
Timeline
IncQuery was founded in 2016.
The platform enhancements were announced on October 06, 2026.
The Tech Race
This release follows the pattern of automated compliance and validation tools becoming standard in the research sector, as companies strive to align their internal software with the transparency requirements of the ISO 20252 market research quality standard. It replaces manual, time-intensive auditing processes with scalable, behavior-based machine learning systems.
Researchers and data analysts can immediately utilize the new customizable signals to reduce the time spent manually identifying fraudulent survey responses. This shift allows for faster project turnaround and provides clearer documentation when reporting data validity to clients.
The takeaway
Automated quality control is increasingly essential for maintaining trust in large-scale research datasets. Research teams should evaluate how these behavioral metrics can integrate into their existing vetting protocols to improve overall data accuracy.
Further reading
For more on industry standards in data vetting, visit the Software section.
More information
To review the updated features and system capabilities, see the IncQuery official product information.
Source note: This article includes information reported by The Manila times.
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