Quality
Check Mate.
Real-time fieldwork intelligence designed to protect data quality at every stage.
Monitor, detect and improve research data quality while fieldwork is still in progress.
Quality shouldn’t wait until fieldwork ends.
- Traditional Approach
Post-fieldwork quality control
Traditional quality checks happen after data collection is complete. By then, inconsistencies and low-quality interviews have already contaminated the database — requiring costly re-fieldwork or compromising analysis.
- Issues discovered only after all data is collected
- Re-fieldwork is expensive and time-consuming
- Compromised data affects analytical output
- No visibility during active collection
- Quality Check Mate
Proactive real-time monitoring
Every interview is automatically evaluated as it arrives. Issues are flagged, patterns are detected and teams can act immediately — while fieldwork is still in progress and corrections are still possible.
- Real-time alerts during active fieldwork
- Immediate corrective action before data is locked
- Clean, high-quality database from day one
- Full visibility for research teams and clients
From reactive checks to real-time intelligence.
Monitor
Continuous evaluation, automatically.
Every survey submitted during fieldwork is automatically captured and evaluated against a comprehensive set of quality indicators — with no manual intervention required.
Detect
Suspicious patterns surfaced immediately.
The scoring engine identifies abnormal completion times, GPS inconsistencies, straight-lining, duplicates and enumerator-level anomalies using multiple concurrent quality signals.
ACT
Correct before the data is locked.
Flag, review, filter or correct problematic interviews while fieldwork is still active. Redirect enumerators, exclude bad records and protect the integrity of the final dataset.
Every interview.
Every indicator.
An advanced scoring engine automatically evaluates 100% of collected surveys across six quality dimensions.
Interview Speed
Detect abnormal completion times and straight-lining behaviour patterns across the respondent pool.
GPS Verification
Monitor geographic consistency and flag interviews conducted outside designated survey zones.
Duplicate Detection
Identify suspicious response patterns and near-identical submissions that indicate fraudulent collection.
Logic & Coherence
Detect inconsistent, contradictory and gibberish responses that undermine the validity of collected data.
Enumerator Performance
Track interviewer-level behaviour and collection quality, and flag individuals requiring follow-up or retraining.
Custom Quality Indicators
Adapt quality controls to the specific requirements of each research project or methodology.
100%
Interviews evaluated
6+
Quality dimensions
Real-time
Monitoring cadence
Live
Client dashboards
Full visibility.
Zero waiting.
Dashboards are accessible to internal research teams and clients, delivering full transparency throughout the data collection process.
Built for confidence at every stage.
Real-time Quality Control
Monitor data quality continuously throughout active fieldwork — not after it concludes.
Automated Scoring
Every collected interview is evaluated automatically, with no manual review bottleneck.
Operational Efficiency
Reduce post-fieldwork data cleaning effort and improve team visibility across collection operations.
Client Transparency
Give clients direct access to live fieldwork insights, building trust through real, timely data.
Make every response count.
Developed by Integrate’s Tech & Analytics team, Quality Check Mate reflects our commitment to proactive, intelligent and transparent research data quality.