Data-Driven Marketing Seminar:
Data Mining for Direct Marketers

Data Driven Marketing

• Data Driven Marketing Framework
• Data Driven Marketing vs. Customer Relationship Management

Modeling and Statistics

• Business Applications
• Tactical vs. Strategic

Customer Lifetime Value

• Definition and applications
• How to use in decision making
• How to estimate and why it’s so hard to do so with spreadsheets
• As the key to successful data-driven marketing strategies
• Common problems in relating to customer acquisition costs

Testing: Better By Design

• Different methods
• How a testing program can reliably improve your results
• Choosing from A/B to Taguchi, from fractional factorials to optimal designs
• Using experimental design techniques to develop targeted strategies Ease of implementation versus economic returns

Networking Opportunity:
Lunch will be served each day to facilitate networking with your peers.

DAY 2
9:00 A.M. - 5:00 P.M.

Strategic Segmentation

• Strategic vs. tactical segmentation and when to use each
• 10 different segmentations from the exact same data
• Common segmentation myths
• Making the segments actionable
• New variables and approaches (e.g., impatience, innovativeness, technology preferences) that help you create and execute more effectively than in the past
• Using databases, technology, and interactivity to change the focus from the traditional approach of better models and larger surveys to smarter execution of a multichannel, technology-based, targeted strategy
• Leading marketers’ successful approaches

Offer Optimization

• Aligning products with customer needs
• Solving for maximum profits while satisfying business rules
• Challenges with getting it right
• Calibrating your models

Best Practices

• What are the most advanced companies doing?
• The difference between strategic and tactical segmentation and when to use each
• How to evaluate a segmentation study

Customer Database

• Foundation of data-driven strategies
• Capabilities required to support advanced techniques
• Speed and flexibility required to access and use the data
• A checklist of minimum and advanced database capabilities