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Zuben AI & Polaris - 2018

Profile Analysis and Transition Prediction of High Performance Off-Road Vehicle Dealerships


Zuben AI is a data science consultancy whose current client, Polaris Industries, desires to better understand quality and performance drivers for their Off Road Vehicle (ORV) dealership network. This project aims to recommend influential actions Polaris can take to improve dealership performance, while providing students an opportunity to experience vendor-client dynamics and relationship management. Students working on this project will have access to historical dealer volumes and are encouraged to utilize outside sources like FRED (ALFRED) to augment their analysis. Additionally, students will have access to Zuben’s “Data Science Portal” (DSP) with the ability to run Python and/or R on robust hardware.

Project Goals

  • Create Dealership Performance Clusters
    • Desired Output: Classification of Dealership ID to Cluster ID
  • Develop Cluster Transition Models
    • Desired Output: Probability for Dealer moving from Cluster A to B, A to C, etc.