A leading energy services company needed to modernize its marketing function by predicting which customers were most likely to respond favorably to campaigns. Disparate data across multiple sub-brands made it difficult to build a unified view, leading to poor targeting and wasted spend on low-probability segments. 

 

Calfus enhanced a centralized Marketing Data Mart to unify Salesforce, MLS listings, and other systems into “golden records.” Leveraging Amazon Bedrock for generative AI-driven data enrichment and Amazon SageMaker for building and deploying predictive models, the solution combined advanced feature engineering with demographic insights to generate prioritized lists for prospects, winbacks, and active customers. Automated rules streamlined recurring campaigns, while flexible marketer tools supported direct mail, COD prospecting, and seasonal initiatives. 

 

The result was a smarter, more efficient marketing engine. With Bedrock powering richer customer insights and SageMaker enabling scalable, real-time predictions, teams gained a single view of customers, reduced manual effort, and improved targeting accuracy—delivering higher ROI. The client transformed campaign execution with automation and predictive intelligence, achieving stronger engagement and measurable business impact.