What?! Causal Drivers from Cross-Sectional Survey Data. How? (LiNGAM)
How often do we as researchers want to attribute causality to what we know is just correlational? It can be so easy to mix up correlation with causation! And in our industry we do driver analyses so often. The mix-up is easy: for example, ice cream sales and drownings both increase during summer, but it […]
Extending the Value of Attitudinal Segmentation Through Data Fusion and Lookalike Modeling
Most discussions around data fusion and lookalike modeling start with improving predictive accuracy—better features, better models, better performance. At AT, we approach the problem differently. Our work begins with attitudinal segmentation. These segments capture how people think, what motivates them, and why they behave the way they do. In practice, this type of segmentation delivers […]
MaxDiff vs Conjoint: When and Why to Use Each Method
Across the last year, I have had many opportunities to help my clients not only choose between MaxDiff and Conjoint but to understand why its the best choice. This way my clients are equipped to have a productive conversation with their clients and be an expert in that conversation. Several times, MaxDiff has been the […]