Integrated Marketing Analytics & Data-Driven Intelligence

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Integrated Marketing Analytics & Data-Driven Intelligence

  1. 1. Integrated Marketing Analytics & Data-Driven Intelligence
  2. 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. 3. Module 1: Big Data, Visualization, and Answering the Question: Why?
  4. 4. Agenda I. The opportunity of information overload and analytics II. Analytically-injected data visualization III. Predictive modeling, forecasting, and applications for segmentation IV. Mobilizing business insights
  5. 5. Video (Time: 0:00 – 7:30) http://youtu.be/5Zg-C8AAIGg
  6. 6. “The Greatest Value Of A Picture Is When It Forces Us To Notice What We Never Expected To See.” John W. Tukey, Exploratory Data Analysis 1977
  7. 7. Interactive Living Creatures http://www.informationisbeautiful.net/visualizations/worlds-biggest-data- breaches-hacks/
  8. 8. Everything Is Relative http://guns.periscopic.com
  9. 9. Mapping http://www.richblockspoorblocks.com/
  10. 10. WHY IS DATA VISUALIZATION SO HOT RIGHT NOW? 1. Liberate Data 2. Empower People 3. Design for People Perspective:
  11. 11. The Need For Data-Driven Marketing http://adobe.ly/OZJfSi
  12. 12. Advanced Analytics(Data Miners, Statisticians, etc.) Web & Digital Analytics (Digital Ninjas, Web Analysts, etc.) 1. Mature analytic methods & practices 2. Powerful databases & tools 3. Low (growing) experience with digital data 1. BI-centric analytic methods & practices 2. Lack powerful tools for multi-channel analytics 3. Low (growing) awareness of advanced analytics TWO ANALYTIC WORLDS COLLIDING… …AND COMMUNICATION IS KEY
  13. 13. Advanced Data Visualization (ADV) “Enterprises find advanced data visualization (ADV) platforms to be essential tools that enable them to monitor business, find patterns, and take action to avoid threats and snatch opportunities.”
  14. 14. Why Is ADV Critical? Firms need to use data visualization because information workers: 1. Cannot see a patternwithout data visualization 2. Cannot fit all of the necessary data points onto a single screen 3. Cannot effectively show deep and broad data sets on a single screen
  15. 15. How Has Data Visualization Changed? 1. Dynamic data content 2. Visual querying 3. Multiple-dimension, linked visualization 4. Animation 5. User personalization 6. Business-actionable alerts
  16. 16. Business Actionable Alert
  17. 17. THE INTERSECTION OF DATA VISUALIZATION AND BIG DATA…
  18. 18. Video (Time: 0:00 – 1:20) http://youtu.be/ntWphJvCTqk
  19. 19. Video (Time: 0:00 – 1:18) http://youtu.be/ipxRA7ira4c
  20. 20. Where Do We Begin? “There is no better place to start than data, since it is the fuel needed to make insightful decisionsthat can drive your business forward.” OtherEDW SocialCRM Digital Mobile Integrated Data Management DataSources Data Quality Data Integration Data Model Data Governance
  21. 21. Big Data Challenges Many organizations are concerned that the amount of amassed data is becoming so large that it is difficult to find the most valuable pieces of information 1. What if your data volume gets so large and varied you don't know how to deal with it? 2. Do you store all your data? 3. Do you analyze it all? 4. How can you find out which data points are really important? 5. How can you use it to your best advantage?
  22. 22. One Possible Consideration… Marketers increasingly want to merge their own customer data with that of third parties to better segment audiences. That's why the Data Management Platform (DMP)has been a hot segment…
  23. 23. DMPs – Current State 1. Today’s leading DMPs are ingesting a wide range of owned and licensed data streams for insights and segmentation and are pushing data into a growing number of external targeting platforms, helping marketers deliver more relevant and consistent marketing communications. 2. DMPs still need to build out mobile tracking and targeting 3. DMPs still need to tighten integrations with existing marketing automation platforms and offline systems.
  24. 24. Another Consideration: “DIY” A number of recent technology advancements are enabling organizations to make the most of big data and big data analytics: 1. Cheap, abundant storage and server processing capacity. 2. Fasterprocessors. 3. Affordable large-memory capabilities, such as Hadoop. 4. New storage and processing technologies designed specifically for large data volumes, including unstructured data. 5. Parallel processing, clustering, MPP, virtualization, large grid environments, high connectivity and high throughputs. 6. Cloud computing and other flexible resource allocation arrangements.
  25. 25. Video (Time: 0:00 – 4:48) http://youtu.be/d5OXF-0B6JM
  26. 26. Data Management & Analytics “Being able to derive insights from data is the key to making smarter, fact-based decisions that will translate into profitable revenue growth.” OtherEDW SocialCRM Digital Mobile DataSources Data Management Analytics Data Quality Data Integration Data Model Data Governance Analytic Segmentation Predictive Modeling Analytic Data Visualization Forecasting
  27. 27. * Gartner’s research shows only 13% of companies make extensive use of predictive capabilities. * “What would you prefer – a report that shows customers you lost, or a model that shows who is about to churn and how to keep them?” Be Proactive: More Difficult, But More Value http://www.gartner.com/technology/su mmits/la/business-intelligence/
  28. 28. EA Case Study Video (Time: 0:00 – 9:00) http://youtu.be/ZK_PXlbvOfM
  29. 29. Discover relevant themes and relationships in social media, call notes and email for deeper insights and improved business management Understand and find relationships in data to make accurate predictions about the future Leveraging historical time series data to drive better insight into decision-making for the future Make appropriate business decisions by understanding dynamics and utilize resources the best way FORECASTING DATA MINING TEXT ANALYTICS OPTIMIZATION FOUNDATION ANALYTICS ADVANCED ANALYTICS INFORMATION MANAGEMENT
  30. 30. DATA VS. ANALYTIC VISUALIZATION IS THERE A DIFFERENCE? DATA VISUALIZATION ANALYTIC VISUALIZATION EXPLORATION DISCOVERY
  31. 31. Forrester Big Data Predictive Analytics Solutions Wave Q1-2013 Forrester Advanced Data Visualization Solutions Wave Q3-2012
  32. 32. Social Media, Foursquare, & Visualization NYC vs. Tokyo http://vimeo.com/62289901
  33. 33. Questions?
  34. 34. Saturday Afternoon Preview Omni Channel Orchestration &Interaction 1. Operationalizing digital data capture and integration 2. Data-driven, multichannel outboundmarketing 3. Real-time inbound marketing and dynamic analytics 4. Creating adaptive customer experiences

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