{"slug":"air-miles-brings-brands-closer-to-customers-with-databricks","url":"https://findausecase.com/use-cases/air-miles-brings-brands-closer-to-customers-with-databricks","title":"AIR MILES brings brands closer to customers with Databricks","description":"AIR MILES (LoyaltyOne) migrated its loyalty program data to the Databricks Data + AI Platform to unify billions of collector and retail partner records, building over 250 ML models for personalized marketing, revenue forecasting and fraud detection. This cut pipeline development time from 3-4 months to 2 days, delivered 100 million personalized offers per month, increased product sales 4x through personalized campaigns, and doubled collector response rates using reinforcement learning models.","company":"AIR MILES / LoyaltyOne","industry":"Retail","aiCapabilities":["Recommendation & Personalization","Predictive Analytics"],"technology":["Agent Bricks","Databricks SQL"],"deployment":"Public Cloud","problemStatement":"AIR MILES had an opportunity to foster stronger touch points with each of its loyal customers to improve retention and customer lifetime value. To achieve this, they needed to modernize their lagging legacy infrastructure, which struggled to provide a holistic view of their customers, preventing the company from making more intimate connections. The company's data scientists couldn't access data older than 5 years, and pipeline development alone took 3 to 4 months.","solutionApproach":"With the Databricks Data + AI Platform, AIR MILES is tapping into their data across all facets of their business. The data science team is now able to quickly build, test and deploy machine learning (ML) models to deliver various use cases: the marketing team uses ML to better understand web traffic performance, the finance team more accurately forecasts revenue, customer care improves support through ML-powered dashboards, and the fraud department detects patterns and outlier behavior to ensure promotional offers are redeemed as intended.","businessValue":"Data pipeline development that used to take 3 to 4 months now takes just 2 days with Databricks. Using its product recommendation models, AIR MILES has been able to increase product sales 4x through personalized email marketing campaigns, and with reinforcement learning models has increased collector response rates to promotional offers by 2x. Through the delivery of 100 million personalized offers per month, they have driven $600 million in redemption value, contributing to $70 billion in AIR MILES sales across their network.","evidence":{"band":"high"},"sourceUrl":"https://www.databricks.com/customers/air-miles","dates":{"publishedAt":"2026-09-27T05:49:09.205Z","publishedAtSource":"pipeline","updatedAt":"2026-09-27T05:49:09.205Z"},"license":"Open for reading and citing with a link to https://findausecase.com/use-cases/air-miles-brings-brands-closer-to-customers-with-databricks. Bulk republication requires permission."}