Targeted Marketing with Behavioral Segmentation

Situation

The world’s most diversified casino-entertainment provider struggled with inefficient customer targeting. Their existing model relied solely on average daily worth (ADW) from past trips, leading to poor ROI on player reinvestment and misallocation of their marketing budget.

Challenge

Key obstacles included:

• Limited customer insights, with ADW based only on historical spend.
• Inefficient budget allocation, resulting in reduced returns and mis-targeted rewards.
• High churn rates, stemming from an inability to engage customers effectively.

Approach

Mu Sigma revolutionized the client’s approach with a data-driven Segmentation, Targeting, and Positioning (STP) model:

• Redefined the concept of a “customer trip” to include visits across multiple properties in one trip.
• Developed a customer segmentation framework, categorizing customers by spending and engagement levels (High, Medium, Low).
• Built a predictive model to determine the likelihood of customers fitting into spending categories and introduced a reclassification algorithm for accuracy.
• Designed a scoring framework to forecast next-trip spending, incorporating trip frequency, demographic insights, and engagement metrics.
• Highlighted actionable positioning insights, emphasizing factors like hotel stays, amenities, and trip duration as critical spending influencers.

We enabled precise targeting and personalized offers, ensuring optimal engagement.

Impact

• 10% improvement in customer targeting, enhancing campaign efficiency.
• $20 million in additional revenue, generated through refined reinvestment strategies.
• $10 million in cost savings, achieved by eliminating ineffective reward programs.