October 7, 2025
3 minutes
solve quota panic
optimize survey completion
predictive modeling
synthetic data
smarter sampling
In the world of online market research, even the best-designed studies can hit a wall: slow fieldwork progress, underperforming cells, and the dreaded “quota panic.” A global CPG brand came to DataDiggers facing precisely this issue. Midway through fieldwork for a multi-country concept test, several hard-to-reach demographic quotas were lagging severely behind, threatening the study’s timeline, budget, and stakeholder confidence.
Despite leveraging our MyVoice proprietary panels and extending reach via partner networks, we faced limitations in real-world availability for niche targets — including lower-income Gen Z consumers in rural Asia and senior decision-makers in mid-sized European B2B companies. Manual quota adjustments and rerouting weren’t closing the gap fast enough.
The client’s request was clear: “We can’t extend the fieldwork again. Is there a smarter way to hit these targets — fast — without sacrificing quality or representativeness?”
Enter Correlix, our advanced solution for bias correction, data augmentation, and simulation at scale. Designed to reflect real-world patterns without compromising privacy or quality, Correlix uses statistical and machine learning models to generate synthetic data that mirrors real respondent behaviors across thousands of dimensions.
Here’s how we used it:
1. Data Diagnostics First
We fed Correlix a live stream of real responses from completed quotas, identifying dropout patterns, response delays, and sample inefficiencies across key variables (region, age, income, device type, etc.).
2. Predictive Modeling for Completion Probability
Using a combination of regression trees and neural network classifiers, Correlix projected which quotas were at risk of under-delivery — before traditional quota logic would flag them. We now had an early warning system for quota panic.
3. Synthetic Sample Augmentation
For the most at-risk cells, Correlix generated high-integrity synthetic responses, statistically aligned with real sample characteristics and distribution. These were labeled transparently in the dataset and used exclusively for preliminary analysis and directional trends, never for KPI reporting.
4. Dynamic Survey Optimization
Finally, we used Correlix to simulate “what-if” adjustments to survey structure and routing — identifying the fastest, most likely paths to full quota completion without inflating cost or lowering quality. These scenarios guided the real-time rerouting of supply within Brainactive.
Thanks to Correlix’s predictive power, we went from reactive firefighting to proactive optimization — completing all quotas on time and under budget, with full transparency about the role of synthetic augmentation.
The client walked away not only with cleaner data but with a new model for smarter sampling and fieldwork risk management.
Since this project, the client has integrated Correlix into their early-stage feasibility checks, using it to simulate likely fieldwork outcomes before questionnaires go live. This shift toward predictive research operations is helping them plan smarter, reduce risk, and make faster decisions — even in the most complex, segmented markets.
Whether you’re running global trackers, early-stage concept tests, or high-stakes segmentation work, DataDiggers + Correlix gives you a new edge in sampling science.
Let’s talk about how Correlix can transform your fieldwork from chaos to confidence. Contact us today
