CAPSTONE

Inside the Self-Checkout Mindset

MSBAi practicum project helps predict customer preferences

By Yasmine Iqbal

1. The Decision

When Jenna Weyant ’19 VSB, ’25 MS graduated with an undergraduate degree in Business Administration, she had acquired business analytics skills that she immediately applied to positions in human capital consulting before moving into a senior consultant people analytics role with Thermo Fisher Scientific, a biotechnology company. As she progressed in her career, she kept a close eye on new developments in her field, including transformative changes in artificial intelligence and generative AI chatbots.

“When I decided to pursue a master’s degree, I knew I wanted to build on my technical skill base and learn how to better use AI,” she says. “And I knew from my undergraduate work that Villanova was at the center of AI learning.”

2. The Project

For Weyant’s Capstone practicum project, she worked with three students under the direction of Nathan Coates ’16 MS, associate professor of practice and faculty director of what is now the Master of Science in Business Analytics and AI (MSBAi) program after a redesign of the MSBA program in fall 2025.

A market research firm had reached out for help in determining what types of customers would be interested in using self-checkout lanes. They had done a large survey of customer attitudes, and the students were tasked with gleaning insights from the data. Each student examined the data through a different lens, such as what time of day customers shopped, where they shopped and whether they were comfortable with technology. Weyant’s role was to use artificial intelligence tools to analyze demographic data to predict how likely it would be for a customer to use self-checkout.

3. The Insights

The project culminated in a 30-minute presentation to the client that offered some key insights and predictions. “For example, we found that the most likely customer to use self-checkout would be a married mother who has one or two kids and works full time,” Weyant says. “The second most likely would be a single man, aged 20 to 40 years old, with no children. We were able to give targeted recommendations for each persona we identified.”

“This was a tight-knit team that worked well together and really understood what the client was looking for,” Professor Coates says. “I tell students that I’d rather they go deep and narrow than broad and shallow, and that’s exactly what they did. It was phenomenal work.”

Weyant is now applying her skills as a value creation manager at the private equity firm Nordic Capital, where she is the “people expert,” helping to design compensation strategies, job architectures and operating models for the firm’s portfolio of companies. “It involves using AI in a responsible way to help companies hire employees and place them in roles where they are most likely to become high performers,” she says. “My MSBA degree gave me a solid foundation in understanding how AI and machine learning actually work. We know AI will reshape how we think about and get work done, but to me, we still always need to keep people at the center of that.”