Case Study: Walgreens Boots Alliance achieves faster, more scalable customer targeting with Microsoft Corporation’s Azure Machine Learning service

Walgreens Boots Alliance finds the sweet spot for reaching customers with Azure Machine Learning service

Walgreens Boots Alliance, a major retail pharmacy and healthcare company, needed a faster, more scalable way to turn millions of daily loyalty and purchase transactions from its Boots Advantage Card program into propensity models for targeted promotions. Its existing machine learning approach was too resource-intensive, so the company turned to Microsoft Corporation and Azure Machine Learning service, along with Azure SQL Database, to improve customer targeting and support brand partners more effectively.

Microsoft Corporation helped Walgreens Boots Alliance build automated machine learning pipelines on Azure to train models faster and scale compute on demand. The result was a major boost in speed and productivity: models that once took days could be trained in minutes, resource provisioning became quicker and lower cost, and promotion performance improved with more relevant offers. Walgreens Boots Alliance is now expanding the Microsoft solution to other areas of the business, including logistics, customer surveys, and support centers.

Walgreens Boots Alliance

Dean Riddlesden

Senior Data Scientist, Global Analytics