Integrated Marketing Analytics & Data-Driven Intelligence: Module 4
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  • 1. Integrated Marketing Analytics & Data-Driven Intelligence
  • 2. • Bruce Swann • Manager, CI / Integrated Marketing, SAS • Scott Briggs • Principal Solutions Architect, Customer Intelligence, SAS • Suneel Grover • Sr. Solutions Architect, Integrated Marketing Analytics, SAS • Adjunct Professor, The George Washington University (GWU)
  • 3. Module 4: Emerging Analytical Approaches for Integrated Marketing
  • 4. Agenda I. High-performance marketing optimization II. Social media analytics and real-time actions III. Social network analytics and community influence
  • 5. HIGH-PERFORMANCE MARKETING OPTIMIZATION
  • 6. Customer Offer A Offer B Offer C 1 100 120 90 2 50 70 75 3 60 75 65 4 55 80 75 5 75 60 50 6 75 65 60 7 80 70 75 8 65 60 60 9 80 110 75 Objective Maximize projected profit Constraints 1 offer per customer 3 customers per offer Campaign Prioritization Campaign Prioritization = $655 A Simple Example
  • 7. Customer Offer A Offer B Offer C 1 100 120 90 2 50 70 75 3 60 75 65 4 55 80 75 5 75 60 50 6 75 65 60 7 80 70 75 8 65 60 60 9 80 110 75 Objective Maximize projected profit Constraints 1 offer per customer 3 customers per offer Campaign Prioritization = $655 Customer Prioritization = $715 Customer Prioritization A Simple Example
  • 8. Customer Offer A Offer B Offer C 1 100 120 90 2 50 70 75 3 60 75 65 4 55 80 75 5 75 60 50 6 75 65 60 7 80 70 75 8 65 60 60 9 80 110 75 Objective Maximize projected profit Constraints 1 offer per customer 3 customers per offer Campaign Prioritization = $655 Customer Prioritization = $715 Campaign Optimization = $745 Campaign Optimization A Simple Example
  • 9. • Financial Services – Cross-sell and up-sell in retail banking: savings accounts, home equity loans, credit cards, lines of credit, etc. – Insurance policy offers – Deciding credit line increases – Deciding what APR to offer on balance transfer offers • Telecom – Complex cell phone or calling plan offers – Bundled service offers – Cross channel offers with different costs of execution • Others – Loyalty offers (Hotels, Casinos) – Personalized coupons (Retail) Use Cases
  • 10. SOCIAL MEDIA ANALYTICS AND REAL-TIME ACTIONS
  • 11. The Opportunity 1. Know how many visits, leads, and customers each individual social channel is generating… 2. Improve the customer experience… 3. Leverage social networks and communities…
  • 12. Social Intelligence
  • 13. Listening Data Mining Correlation & Forecasting Text Mining Natural Language Processing Taxonomies Influence & Engagement Sentiment Analysis Categorization Portals CRM Collect Clean Integrate Organize Accessible by All Analytics, Classify, Seg ment, Sentiment, Natur al Language Processing iPad apps Dataset Export Web Data Survey Data Call Logs Text Analytics
  • 14. Social Media Analytics Online Conversations Brand & Market Tracking PR & Reputation Tracking Customer Feedback Mgmt Online Media Analysis •WHAT are consumers saying about your brand? About the competition? •WHO is creating content about your brand…Journalists? Bloggers? Forum members? •WHO among these authors is a threat to reputation? An opportunity for advocacy? •WHERE are consumers talking? • Is volume trending up or down? •WHICH sites matter most? • WHICHsites are more positive? Negative? • WHATaspects of your business drive satisfaction and loyalty? • WHAT questions and unmet needs emerge? • HOW do perceptions differ across the various channels through which customers give you feedback?
  • 15. The Business Need How can I ensure it’s accurate and relevant to my business? How do I cut out the noise and get to the true insights and action? How can I customize it to understand my business, my brands and competitors? How does social media fit with my other business intelligence? How can social data augment what I already know? How can it help me get a clearer picture of my business as it changes? How do I use social media to drive my business forward? Where does it fit within my business strategy? Where can I focus for the best returns? How can I use it to get a competitive edge? How do I monetize it?
  • 16. Engage 1. CRM 2. Outbound/Inbound Marketing 3. Integrated Marketing
  • 17. Engage
  • 18. Engage Increase Engagement Across Email, Then All Channels Website Visitor Analysis Targeted Email Collection Content 1 2 3 Sign-up Incentive Loyalty Program Email and/or Mobile Capture Call-to- Action
  • 19. Engage Optimized Performance Return-trip Propensity Model Targeted Cross-sell Messaging 1 2 3 2xEmail Open Rate 72% Increase in Conversion Rate Targeted Email Offer Push to Conversion Post to Social Targeted Message • Email & Mobile activity • Online behavioral data • Survey results • Social profile • Customer service events
  • 20. Engage 0% 10% 20% 30% 0 1 2 3 4 5 6 7+ PercentofTotalFile # of Social Networks Social Participation Seg 1 Seg 2 Social Network Engages Social | Email Influencers Create Friend-centric Message 1 2 3 0% 10% 20% 30% 40% 0 1 2-3 4-10 11-19 20+ PercentofTotalFile # of Friends Social Reach Seg 1 Seg 2 32% 28% 40% 0% 5% 10% 15% 20% 25% 30% 35% 40% 45% Inactive Opener Clicker Email Activity Segments - 20+ Friends
  • 21. Engage Enable customer care agents monitoring social media to communicate with consumers in order to… Address the consumer’s service issues and questions Mitigate or respond to negative comments or threats Reinforce a customer’s positive sentiment • Broadcast comments to other customers • Reward with offers Facilitate customer consideration process • e.g. consumer comparing hotel options for a vacation
  • 22. Engage
  • 23. SOCIAL NETWORK ANALYTICS AND COMMUNITY INFLUENCE
  • 24. Social Network Analysis ‘A social network is a social structure made up of individuals, which are connected by one or more specific types of interdependency, such as friendship, kinship, common interest, financial exchange‘ etc.
  • 25. Social Network Analysis • Attract outside influencers in the expectation that their community will follow. • Incent inside influencers to pull in off-network followers. Acquisition • Target cross/up sell offers to inside influencers. • Cross promote products within communities. Cross/Up Sell • Reduce churn by holding on to influencers. • Decrease virality effect of followers. Retention
  • 26. Social Network Analysis Data feeds: ETL to data environment 1 Data Management: Cleanse, parse, categorize, and standardize social media data around “Vail Customers” 2 HUB Epic Mix Social Media Chatter (e.g. Twitter, Facebook) 3 4 Executive Insights: Explore results in Visual Analytics 5
  • 27. Social Network Analysis Social Media Analytics Data Batch ETL HUB Outbound Inbound Customer DB (or EDW) Non-matched/Possible matched Social/Customer data Mastered data with Social Info Appended Matched customer Info (is this possible?)
  • 28. Community Influence Social Media Analytics Extract Data Available Fuzzy Match Processing Facebook Twitter MDM
  • 29. Community Influence Sarah Casino Visitor Sarah’s Social Network • Semi-frequent Visitor • High Value • Large Friend Network • Content Creator and Contributor • Active Social Elements • Encourages Sharing • Friend-centric Targeted Email Campaign to Sarah Sarah Engages • Engages with Email • Forwards to Friends • Posts Content • Network Engages and Converts • Individuals begin to contribute content (blogs, reviews, etc.) Sarah’s Network Engages
  • 30. Community Influence  Virality is the effect of influencers on followers.  In particular, what is the increased likelihood of churn within a community once an influencer churns.  Virality churn lift is the churn rate delta of followers. Influencer churn Follower churn
  • 31. Social Profile Social Audience Profile •Number of Friends •Social Membership •Number of Profiles •Last Activity Date •Social Tenure Map your constituent audience to social profiles Use email address as match key Match constituent to social behavior Access publicly available social data Build Social Audience Profile Assess social engagement levels
  • 32. Social Profile 0% 10% 20% 30% 0 1 2 3 4 5 6 7+ PercentofTotalFile # of Social Networks Social Participation Seg 1 Seg 2 Social Network Engages Social | Email Engagers Create Friend-centric Message 1 2 3 0% 10% 20% 30% 40% 0 1 2-3 4-10 11-19 20+ PercentofTotalFile # of Friends Social Reach Seg 1 Seg 2 32% 28% 40% 0% 5% 10% 15% 20% 25% 30% 35% 40% 45% Inactive Opener Clicker Email Activity Segments - 20+ Friends Mobile PurchaseWebsiteEmail Search SocialDisplay Ad M D PE S W O
  • 33. Case Study • Major US-based wireless carrier with 30+ million customers. • 89 million individuals within the overall population. • Average community size is roughly 18. • 5% of all subscribers are influencers. • Followers’ churn rate increased by 25% when influencers churned. • 30% model lift when SNA was used. • Campaign take rate among followers doubledwhen influencers took.
  • 34. Questions?