Academic research fieldwork highlights how sampling strategy, mixed-mode design, and proactive quality controls help produce data that can withstand scrutiny and support confident decision-making.
AI can improve market research workflows, but its value depends on where it operates, because quality issues caught after fielding are often too late to fix.
Strong fraud detection can improve market research data quality, but technology alone cannot overcome weak sample strategy, recruitment bias, or poor audience composition.
Poor open ends, speeding, and duplicate responses are often symptoms of deeper issues, making a layered approach essential for improving market research data quality.
Multi-country brand tracking is one of the most operationally demanding programs in quantitative market research, and one of the most consequential.
A strong global research operations partner helps research teams scale capacity, protect data quality, and manage complex international studies with confidence.
The market research data quality problem is not just about bad respondents — it is rooted in how the industry operates.
Most Canadians expect housing prices to rise, though uncertainty and regional differences are shaping a more balanced outlook.
Rising fuel costs are changing how Canadians drive, spend, and plan their summer travel
AI usage in Canada is now part of everyday life for most people, with two thirds of Canadians using at least one AI-based tool or service.
