2. Turning Customer Behavior into Business Behaviors that Drive ROI

3. Agenda 1.Four Business Models + One 2.Four Stages of Customer Life Cycle 3.Predictive Analytics 4.Summary

4. Four Business Models Online Commerce Advertising Lead generation Customer Support

5. The Four Stages of the Customer Life Cycle Reach

6. “ Although you might have developed the best communications material on the market, if your Web site does not deliver on the promise made in this material you will experience large dropout volumes. Reach techniques must reflect the purpose and capability of Web sites -- because anything else misleads people as to the content of the site.” Hurol Inan in Measuring the Success of your Web site

7. KPI’s Recommended for Measuring Reach Overall traffic Volume Ratio of new to Returning Visitors Percentage of New Visitors Campaign Metrics Interested Visitor Share

8. The Four Stages of the Customer Life Cycle Reach Acquisition

9. KPI’s Recommended for Measuring Acquisition Average number of page views Page "stickiness" Response rates for all active campaigns The top three to five referring domains Average time spent on site

10. The Four Stages of the Customer Life Cycle Reach Acquisition Conversion

11. KPI’s Recommended for Measuring Conversion Conversion rates for any processes Campaign conversion rate for any active campaigns Cost-per-conversion for the campaigns Segment conversion rates

12. KPI’s Recommended for Measuring Conversion (Additional when selling on-line) Your site-wide conversion rate New and repeat site-wide customer conversion rates Percent of orders from new and returning customers Site-wide average order value Sales per visitor

13. The Four Stages of the Customer Life Cycle Reach Acquisition Conversion Retention

14. KPI’s Recommended for Measuring Retention The ratio of daily to monthly returning visitors Percent returning visitors Loyalty measurements for groups of returning visitors Activities of "retained" visitors

15. TURNING CUSTOMER INTERACTIONS INTO MONEY PREDICITVE ANALYTICS Using existing web analytics data and applying it toward anticipated future behaviors

16. Using Predictive Analytics to Achieve Greater ROI Smart Companies: Measure performance improvement Conduct business case models for IT investments, such as analytics

17. Defining Predictive Analytics And its Affect on ROI Aggregate knowledge is good, but individual knowledge is better. Predictive analytics help manage risk and identity fraud Building deeper engagement

18. Customer Data Customer Value Customer Attitudes and Preferences Increased Marketing Efficiency Increased Sales Efficiency Higher Contact Center Efficiency Increased Customer Satisfaction Increased Willingness to Recommend Increased Customer Loyalty The Continuous ROI Cycle The ROI Cycle leverages leanings‘ across the entire customer lifecycle providing a more complete picture of the ROI.

19. CASE STUDY T. ROWE PRICE Started analytics to keep up with competitors using online trading Analytics could not provide a complete picture of what the customer was worth to the Company, or what they would be worth in the future

20. IMPLEMENTATION Took existing data and parsed it into more actionable segments Combined this data with qualitative techniques that defined primary, secondary and tertiary personas Company now had enough data to accurately predict the value of newly defined segments

21. OUTCOME By understanding their current and future needs, we could predict what would be in both the customers’ and company's best Interest Predictive analytics has led to new approaches for a variety of customer segments

22. Establish Well-Defined Business Goals Define, Monitor and Continually Measure ROI Competing on Predictive Analytics

23. Getting Started with Your Predictive Analytics Program Three Questions To Ask Today... 1. What is my number one customer-based business goal? 2. What does my most valuable customer look like today and what will they look like tomorrow? 3. Who has the potential to be my most valuable customer?

24. Getting Started with Your Predictive Analytics Program Five Things To Do Tomorrow... 1.Create a customer persona. 2.Craft marketing campaigns that will grow the value of that persona. 3.Identify your analytics champion. 4.Rank five customer-based business goals. 5.Fine tune the definition of the numbers that will prove that they’ve been achieved.

25. The Business Imperative for Predictive Analytics Competing on predictive analytics has never been more urgent. Wide-ranging changes in nearly every aspect of business Makes customer behavior a critical “ need-to-know” application.

26. Four Business Models + 1 Intranet Analytics: Promoting Best Practices to Business Stakeholders An analytical understanding of how people use their intranet is the most important way business leaders can learn how to improve its return on this investment

27. Thank You