Research Archives - Wharton Customer Analytics

Interacting User-Generated Content Technologies: How Questions and Answers Affect Consumer Reviews

Wharton Customer Analytics Research Paper Series Interacting User-Generated Content Technologies: How Questions and Answers Affect Consumer Reviews This article studies the question and answer (Q&A) technology of electronic commerce platforms, an increasingly common form of user-generated content that allows consumers to publicly ask product-specific questions and receive responses, either from…Read More

Buying and Payment Habits: Using Grocery Data to Predict Credit Card Payments

Wharton Customer Analytics Research Paper Series Buying and Payment Habits: Using Grocery Data to Predict Credit Card Payments This study shows that individuals' habits in grocery shopping are incrementally useful in predicting their credit card payment behaviors and that such incremental predictive power can translate into incremental profits for firms.…Read More

Customers of A Feather Engage Together: Using K-Means Clustering to Maximize Retention

Wharton Customer Analytics Analytics Accelerator Case Study Customers of A Feather Engage Together: Using K-Means Clustering to Maximize Retention Objective NeuroFlow is a healthcare technology and analytics company enabling behavioral health access and engagement to improve outcomes, overall wellness, and costs of care. High user engagement rates set NeuroFlow apart…Read More

Understanding Large-Scale Dynamic Purchase Behavior

Wharton Customer Analytics Research Paper Series Understanding Large-Scale Dynamic Purchase Behavior In modern retail contexts, retailers sell products from vast product assortments to a large and heterogeneous customer base. Understanding purchase behavior in such a context is very important. Standard models cannot be used because of the high dimensionality of…Read More

How to Price Products for Non-Contractual Customers in a B2B Setting? Webinar

Wharton Customer Analytics Research Opportunities How to Price Products for Non-Contractual Customers in a B2B Setting? Sponsored by Download Slide DeckDisclaimerThe Research Opportunity webinars are posted here for a research-focused audience and should not be quoted, paraphrased or otherwise utilized without written permission of WCA. Any media inquiries or requests…Read More

How to Price Products for Non-Contractual Customers in a B2B Setting?

Wharton Customer Analytics Research Opportunities How to Price Products for Non-Contractual Customers in a B2B Setting? Sponsored by Wharton Customer Analytics is announcing a new collaborative research opportunity with Air Liquide, who is seeking researchers interested in developing innovative approaches to dynamically pricing products for different types of B2B customers. Customers in…Read More

Two Prices Diverge in the Wood

Wharton Customer Analytics Analytics Accelerator Case Study Two Prices Diverge in the Wood: Using Random Forest Modeling to Optimize Price Recommendations About Essity Essity is a global hygiene and health company, with its headquarters in Stockholm, Sweden. The products portfolio contains one-use products such as tissue paper, baby diapers, feminine…Read More

Demand Prediction for IoT Devices

Wharton Customer Analytics Analytics Accelerator Case Study Demand Prediction for IoT Devices About TE Connectivity TE Connectivity is a technology company that designs and manufactures connectivity and sensor products (IOT devices) for harsh environments in a variety of industries, such as automotive, industrial equipment, data communication systems, aerospace, defense, medical,…Read More

2020 EA Datathon

Wharton Customer Analytics Datathon Case Study Discovering New Customers and Game Usage via New Data Lenses About Electronic Arts Electronic Arts Inc. (EA) is a global leader in digital interactive entertainment. EA develops and delivers games, content, and online services for Internet-connected consoles, mobile devices, and personal computers. EA has…Read More

Identifying Key Customers and Industries through Customer Lifetime Value (CLV) Modeling and Regression Analysis

Wharton Customer Analytics Datathon Case Study Identifying Key Customers and Industries through Customer Lifetime Value (CLV) Modeling and Regression Analysis About the Datathon Twenty self-formed teams comprised of approx. 80 Penn/Wharton students were provided the same core set of Ryder System, Inc., customer data at the contract level to model…Read More