Winter 2027 application instructions:

• Apply here: https://reg.kellogg.northwestern.edu/experientiallearning/‍ ‍

• Deadline: For Winter 2027, the application deadline is October 26, by end of day.

• If you are applying as a team, EACH team member must complete an individual application by the deadline.

Likely clients / projects for Winter 2027:

• Whirlpool Brazil: developing a channel strategy for its Latin American direct-to-consumer business, using daily pricing, sales, and margin data across 400 products, 20 online channels, and dozens of competitors to grow sales profitably.

• WNBA team (name withheld for now): turning a new, full-suite fan intelligence platform into actionable marketing insights, measuring which campaigns and channels drive ticket sales, engagement, and revenue.

• Chicago Sports Network: identifying how to attract new viewers and deepen engagement with existing ones as sports fans shift across broadcast, streaming, and digital platforms.

• Chicago Fire FC: building an AI roadmap that maps and prioritizes opportunities across marketing and the broader business, identifies where AI agents could automate internal workflows, benchmarks how peer clubs and leagues use AI, and lays out a practical playbook for pursuing the best opportunities.

• Northwestern Athletics: lay the analytical foundation for identifying factors that predict injury risk in student-athletes. Students will wrangle messy, unstructured data to support analysis, link it to injury, and test which data points show promise for predicting risk. This will be exploratory work on messy, unstructured data, and much of the project will be around wrangling it into useable form as a precursor to analysis of injury risk.

• Premium flooring leader (name withheld for now): uncovering where a category-defining garage flooring brand can grow next, analyzing sales and lead data to learn who buys, where, and through which channels.

How ACL works:

• If you are admitted to ACL, I will do my best to assign you to a project that you would really like. However, especially with sports clients, demand is often higher than supply. I recommend that you apply to ACL only if multiple projects sound interesting to you.

• Please note: “Analytical and AI consulting” isn’t just about statistical analysis and ML model-building around large datasets. Many companies already have data science teams for that. What they often lack, but truly value, are business-minded experts who can help them think differently about how to use data and AI. In some of the below projects, the real value (and often, the real fun) lies in uncovering new ways to solve business problems using existing data: reframing challenges, surfacing hidden opportunities, and shaping innovative use cases.

• Most ACL projects fall into one of the following categories:

  • Empirical analysis of a data set to generate recommendations - sometimes these projects might require building ML models and sophisticated model diagnostics, while others might involve simpler “insight generation.”

  • Helping clients map out how data can be useful to a particular goal, like “personalization for revenue generation.” These projects are a bit more about creating a strategy to use data to achieve a business goal, rather than conducting primary empirical work.

  • Helping clients map out how generative AI tools / LLMs can be used to achieve specific business goals. Given the early stage of industry’s use of gen AI, these projects tend to be more open-ended and require significant self-direction by the student team.