Case Study: PepsiCo achieves store-level consumer insights with Microsoft Azure Machine Learning

PepsiCo uses Azure Machine Learning to identify consumer shopping trends and produce store-level actionable insights

PepsiCo, a global food and beverage company, needed a better way to balance consumer demand with inventory across thousands of U.S. stores. Using Microsoft Azure Machine Learning, the company moved its data into the Azure cloud to replace time-consuming spreadsheet- and document-based processes with a more predictive, store-level analytics approach.

Microsoft Azure implemented Azure Machine Learning and its MLOps capabilities to build the Store DNA solution, which generates prioritized product actions for field associates and helps PepsiCo predict what each store should stock. The pilot in North Texas showed more than 85% of recommendations were acted on and improved predictions by over 40%, while early estimates suggest 4,300 workdays a year can be shifted from routine tasks to higher-value work.

PepsiCo

Atul Jain

Advanced Analytics