TD Ameritrade Client Experience

Authors

Jared Yost, University of Nebraska-LincolnFollow
Allison Inman, University of Nebraska-LincolnFollow
Catherine Krueger, University of Nebraska-LincolnFollow
Jessica Smith, University of Nebraska-LincolnFollow
Peter Wen, University of Nebraska-LincolnFollow
Jacob Sampson, University of Nebraska-LincolnFollow

Date of this Version

5-2020

Document Type

Thesis

Citation

Yost, Jared, et al., TD Ameritrade Client Experience. Undergraduate Honors Thesis. University of Nebraska-Lincoln. 2020.

Comments

Copyright Allison Inman, Catherine Krueger, Jacob Sampson, Jessica Smith, Peter Wen, Jared Yost 2020

Abstract

We aim to help TD Ameritrade utilize text-based client survey responses to identify ways to better TD Ameritrade’s customer experience, increasing customer satisfaction and retention. In order to do this, we created a machine learning algorithm to classify each survey as positive, negative, or neutral. After each survey is classified, we are able to manipulate the data in various ways to provide insight into current customer sentiment and display areas which are doing well along with those that need improvement.