Case Studies and White Papers

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Analytics Accelerator Case Studies

Customers of A Feather Engage Together

Students were asked to build a statistical model for NeuroFlow, SaaS healthcare technology and analytics company. The goal was to identify users at high risk of churn, which would help inform product design, promotional offerings, etc. to proactively engage and retain these users.

Sweet Solutions to Advertising Questions

Ferrero is the third top-selling chocolate confection manufacturer in the world. The company has ambitious growth plans to be achieved through innovation, category expansion, and M&A. Their student team was asked to develop a marketing mix model(s) to better balance resources to power brands and product innovations.

Demand Prediction for IoT Devices

TE Connectivity is a technology company that designs and manufactures connectivity and sensor products for harsh environments in a variety of industries. Their student team was asked to develop a model to predict sales and revenues for this sensor manufacturer.

About the Analytics Accelerator

Every fall and spring semester, Wharton Customer Analytics hosts the Analytics Accelerator, an experiential learning program that pairs students with a company to solve a real-world business problem using the company’s actual datasets and the latest techniques including machine learning and AI.

Companies

Students

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Datathon Case Studies

Discovering New Customers and Game Usage via New Data Lenses

Student teams had one week to analyze user data from Origin Access, EA’s all-you-can-play subscription service, including their activity on the games included in the subscription catalogue and individually purchased games.

Driving Revenue Through Guest-To-Host Conversion

Students were asked to increase revenue for Evite by addressing one or more of the core drivers of growth. The winning team’s solution would be deployed on the Evite platform to make real-time decisions and to drive measurable improvement to an aspect of Evite’s user experience or lifecycle.

Identifying Key Customers through CLV Modeling and Regression Analysis

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 the most valuable customers and industry segments to their business.

About Datathons

Spanning up to one week, several self-formed, multidisciplinary Penn and Wharton student teams compete to present the most innovative machine learning and strategic solutions to a company’s business needs.

Companies

Students