Though more structured than qualitative research, quantitative research presents its own set of challenges. Despite increasing pressure to do things faster and cheaper, researchers need to ensure that quality is not sacrificed.
The quality of data is paramount in quantitative research. The adage “garbage in, garbage out” has never been more relevant. From selecting an appropriate panel partner, to looking at how they treat their panelists, and the controls in place, researchers need to increasingly look at who is included in their surveys.
Appropriate sample sourcing, screening, sampling strategies, and survey structure, as well as proactively planning for any statistical analysis at the planning design stage, are all key to data accuracy for quality insights. Some of the ways we do this include adding control questions in the survey, monitoring for speeding and straightlining, and including an open-ended question in every survey, whether or not the data will be used, as a way to clean out those who are not engaged or are providing “garbage” responses.
These are all a part of Zeldis’ approach to quantitative research, ensuring optimal data quality from your research.
What’s NEW in Quant at Zeldis?
(Panel, List, or Client- provided Sample)
- Cluster Analysis
- Conjoint Techniques (Adaptive, menu-based, MaxDiff)
- Correspondence Analysis
- Discrete Choice
- Perceptual Mapping
- Price Elasticity (Van Westendorp, Gabor-Granger)
- TURF Analysis