Who We Are

We partner with our clients to uncover, test, and scale analytical insights that can drive decision-making across industries and functions. By leveraging existing data resources to launch analytical pilots at no cost to our sponsoring organizations, we offer our clients a risk-free opportunity to capture value using the latest analytical innovations from the Wharton Customer Analytics Initiative.

Together, we will help you to solve complex business challenges across your organization; crowd-source and pilot analytical initiatives; gain access to top-tier analytics expertise through our partnership with Wharton’s high-caliber faculty at the WCAI; build strong relationships with Wharton students and faculty; and test the work product of potential recruits in a low-risk environment.


Our Approach

We believe there is no "one size fits all" approach to analytics; we tailor our program to match the specific challenge at hand.

Define hypothesis

Engagement Leaders (EL) connect with stakeholders to identify objectives, explore data resources, develop hypotheses, and develop project plan

Develop models [4-6 Weeks]

Teams test hypotheses, maintaining regular contact with clients and reviewing models with faculty and PhDs on an ongoing basis

Summary + Recommendations [1 Week]

Teams present key insights and quick-win opportunities, placing special emphasis on actionable next steps that will enable clients to immediately capture value using the team’s findings

Past Projects

Global Research Non-Profit

We performed customer sentiment analysis to help a global research think-tank better connect with their core audience and donor base.

San Francisco Giants

We developed a predictive engine to improve ticket sales forecasting by more than 30%.


We enabled a national retail chain to drastically improve their retail location strategy by using classification analytics to identify best practices.

EA Games

We drove player engagement and retention by predicting online behaviors using customer-level data.


We identified drivers of employee attrition and provided recommendations to improve corporate diversity.


We leveraged performance data to unlock career path insights and kickstart the SEC’s People Analytics practice.

Citi Ventures

We collaborated with Citi’s MD of Data Science to predict sovereign default using machine learning.


We developed a scoring system that can measure and improve customer engagement for a digital equity trading platform.

Vistar Media

We created a revenue forecasting model for a large digital advertiser by predicting media owner behavior.

SRP Systems

We used machine learning to optimize and adapt a demand prediction model.

Swift Capital

We analyzed responses to various marketing channels to uncover the most effective combination that maximizes engagement.




What we do

Each semester, we send 4-6 teams of MBAs, graduate students, and undergraduates from across the Penn community to work with clients in various industries across the globe. Our consultants are rigorously screened by WCAI and Wharton Analytics Fellows leadership during a highly selective application process, and we carefully tailor each team to ensure that our sponsoring organizations have access to the right mix of experiences, leadership skills, and technical abilities needed to solve their unique challenge. Each Fellow receives deep analytical training in SQL, R, Python, Tableau, and other technologies (dependent on client needs), and our tightly-knit teams are led by experienced MBAs and/or trained consultants to champion our hypothesis-driven approach and expedite the analysis process.


Getting Started

To ensure that we will be able to deliver quality, actionable insights in a relatively short period of time, we ask for three commitments from our clients:

  • Lend us 1-2 hours at the front and back-end of every engagement to
    a) define hypotheses and b) present final insights and recommendations
  • Identify a key point-of-contact that can answer questions and validate findings during the engagement (dependent on availability)
  • Provide a usable dataset and/or database connection as well as any required compliance documentation