Verizon’s marketing team needed to improve the efficiency and effectiveness of its direct marketing campaigns.

Traditional audience segmentation methods based on demographics and basic behavior were insufficient for:

• Predicting which customers were most likely to engage or convert
• Personalizing offers and messaging at scale
• Maximizing return on marketing spend across email, digital, and direct mail channels

Verizon required a more intelligent, data-driven approach to audience targeting.

CVM developed multiple machine learning models designed to optimize customer targeting across marketing campaigns.

Key components of the solution included:

• Predictive Modeling: Built models in Python that analyze historical engagement, purchase behaviors, demographics, and interaction history to predict future customer actions.
• Propensity Scoring: Assigned scores to each customer, indicating their likelihood to respond to specific types of marketing communications.
• Dynamic Audience Segmentation: Enabled Verizon to create highly targeted segments based on propensity scores and other behavioral indicators.
• Integration with Campaign Execution Systems: Provided marketing teams with tools to easily pull optimized target lists for specific campaigns, directly from the marketing database.

The models were designed for continuous retraining, improving over time as more engagement data was collected.

• Higher Engagement Rates: Targeted campaigns achieved significantly better open, click-through, and conversion rates compared to traditional segmentation approaches.
• Improved Marketing ROI: More efficient use of marketing budgets by focusing efforts on high-probability customers.
• Enhanced Personalization: Enabled Verizon to deliver more relevant messages to individual consumers, improving customer experience.
• Scalable Targeting Framework: The modeling approach can be adapted to future campaigns, new products, and emerging customer segments.

• Machine Learning Personalizes at Scale: Predictive models allow marketing teams to deliver the right message to the right person at the right time.
• Continuous Improvement is Key: Regular retraining and validation of models ensure targeting remains effective over time.
• Practical Deployment Matters: Successful AI solutions fit seamlessly into existing marketing workflows, enabling adoption without friction.