Capital One Services, LLC

Robert Edward Cezeaux

Rohit Sarin

Weiyan Sun

Elizabeth Claire Maue

Alex Baird

Ryan Tomlinson

Chengjun Zhu

Jose Martinez

Based on the interaction data and response data, an interaction monitoring platform may determine a first known sentiment and a second known sentiment, identify a first pattern and a second pattern in the interaction data, and generate a first pattern-level sentiment and a second pattern-level sentiment based on the known sentiments and the identified patterns. A binary indicator may indicate which identified patterns are exhibited in a subset of the interaction data. The platform may train a gradient boosting model using known sentiment as a target variable and using binary indicators and pattern-level sentiments as input data. The platform may predict a sentiment corresponding to a subset of interaction data with unknown sentiment that exhibits one or more of the first pattern or the second pattern based on a binary indicator and the trained gradient boosting model.

Pattern-level sentiment prediction

A device obtains historical interaction data concerning a plurality of user interactions, where a user interaction of the plurality of user interactions includes one or more touchpoint sets, obtains historical response data concerning a plurality of user responses, where a user response of the plurality of user responses corresponds to a user interaction, and processes the historical interaction data and the historical response data using a modelling pipeline to determine an association between user interaction score and a touchpoint set. The device determines information concerning a current user interaction, processes the information concerning the current user interaction using the modelling pipeline to determine a current user interaction score and ranking of one or more touchpoint sets of the current user interaction, and causes, based on the current user interaction score and the ranking of the one or more touchpoint sets, at least one action to be performed.

Performing an action based on user interaction data

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McLean, VA, United States of America

Robert Edward Cezeaux