DIY Driver Analysis

Learn how to do a state-of-the-art driver analysis in 30mins.

Discover how to uncover which attributes in your data have the biggest impact on behavior.

By the end of the webinar, you will know how to

  • Prepare your data
  • Deal with outliers and multicollinearity
  • Know which techniques to use and when (e.g., Shapley, Kruskal, OLS, robust standard errors).
  • Create quad maps to show the results.

Driver analysis is used to quantify the importance of the drivers of satisfaction, NPS, or brand preference. It’s an application of regression, where the outcome is a measure of the performance of one or more brands, and the predictors are measurements of the performance of the brand.

Finding the Story in your Survey Data
First session 19 May 2022

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