Driver Analysis

Also known as: Key Driver Analysis, Importance-Performance Analysis, KDA

Statistical analysis identifying and quantifying which factors most impact a key metric like overall satisfaction, NPS, or preference.

Driver Analysis is an analytical technique that identifies and quantifies which attributes or factors have the greatest statistical impact on a key business metric—overall satisfaction, NPS, purchase intent, or brand preference—with the goal of prioritizing improvement actions.

Most common techniques: Linear/Logistic Regression with variable importance (standardized beta coefficients or Shapley values), Importance-Performance Analysis (IP Analysis) that crosses statistical importance with current performance perception to identify priority action areas, and Random Forest with feature importance.

Driver Analysis answers critical questions: What most impacts my customers' NPS? Where should I invest to most effectively improve satisfaction? Which product attributes most differentiate purchase intent?

Atlantia includes Driver Analysis as a standard component in its Brand Trackers and satisfaction studies.