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HPMC 2014 - The value of analytics - SAS
HPMC 2014 - The value of analytics - SAS
HPMC 2014 - The value of analytics - SAS
HPMC 2014 - The value of analytics - SAS
HPMC 2014 - The value of analytics - SAS
HPMC 2014 - The value of analytics - SAS
HPMC 2014 - The value of analytics - SAS
HPMC 2014 - The value of analytics - SAS
HPMC 2014 - The value of analytics - SAS
HPMC 2014 - The value of analytics - SAS
HPMC 2014 - The value of analytics - SAS
HPMC 2014 - The value of analytics - SAS
HPMC 2014 - The value of analytics - SAS
HPMC 2014 - The value of analytics - SAS
HPMC 2014 - The value of analytics - SAS
HPMC 2014 - The value of analytics - SAS
HPMC 2014 - The value of analytics - SAS
HPMC 2014 - The value of analytics - SAS
HPMC 2014 - The value of analytics - SAS
HPMC 2014 - The value of analytics - SAS
HPMC 2014 - The value of analytics - SAS
HPMC 2014 - The value of analytics - SAS
HPMC 2014 - The value of analytics - SAS
HPMC 2014 - The value of analytics - SAS
HPMC 2014 - The value of analytics - SAS
HPMC 2014 - The value of analytics - SAS
HPMC 2014 - The value of analytics - SAS
HPMC 2014 - The value of analytics - SAS
HPMC 2014 - The value of analytics - SAS
HPMC 2014 - The value of analytics - SAS
HPMC 2014 - The value of analytics - SAS
HPMC 2014 - The value of analytics - SAS
HPMC 2014 - The value of analytics - SAS
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HPMC 2014 - The value of analytics - SAS

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Presented during the High Performance Marketing Conference 2014, organized by Accenture on January 23rd, 2014.

Presented during the High Performance Marketing Conference 2014, organized by Accenture on January 23rd, 2014.

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  • 1. THE VALUE OF ANALYTICS IN THE WORLD OF THE DIGISUMER HPMC 2014 PETER WOODS C op yr i g h t © 2 0 1 4 , S A S I n s t i t u t e I n c . A l l r i g h t s r es er v e d .
  • 2. AGENDA THE VALUE OF ANALYTICS • • • C op yr i g h t © 2 0 1 4 , S A S I n s t i t u t e I n c . A l l r i g h t s r es er v e d . The business purpose of analytics The conditions to guarantee success How new technologies support analytics
  • 3. THE NEW CUSTOMER IS MORE DEMANDING AND LESS LOYAL THE CUSTOMER IS A CAT! The Customer is a cat. To conquer the heart of this new Customer type is one of the big challenges. C op yr i g h t © 2 0 1 4 , S A S I n s t i t u t e I n c . A l l r i g h t s r es er v e d .
  • 4. THE NEW CUSTOMER C op yr i g h t © 2 0 1 4 , S A S I n s t i t u t e I n c . A l l r i g h t s r es er v e d . ALL DOGS ARE CHASING THE SAME CAT!
  • 5. C op yr i g h t © 2 0 1 4 , S A S I n s t i t u t e I n c . A l l r i g h t s r es er v e d .
  • 6. WHY DO WE CARE? Act Orient Decide MARKET OPPORTUNITY Decide Orient Act Observe C op yr i g h t © 2 0 1 4 , S A S I n s t i t u t e I n c . A l l r i g h t s r es er v e d . YOUR COMPETITIVE ADVANTAGE
  • 7. WHAT ENABLES IT‘S PREDICTIVE ANALYTICS LOOKING INTO THE FUTURE THIS MAGIC? C op yr i g h t © 2 0 1 4 , S A S I n s t i t u t e I n c . A l l r i g h t s r es er v e d .
  • 8. WHERE IS ANALYTICS OF AS A GAME-CHANGER VALUE? Intelligence-driven Business Differentiation Intelligence-driven Business Innovation Intelligence-driven Business Transformation Increasing process effectiveness and customer relevance Innovating existing business model with new revenue streams Transforming the business entering in brand new markets Campaign Management Optimization Cross-sell to new business lines Creation of a new company C op yr i g h t © 2 0 1 4 , S A S I n s t i t u t e I n c . A l l r i g h t s r es er v e d .
  • 9. WHAT A GREAT IDEA! C op yr i g h t © 2 0 1 4 , S A S I n s t i t u t e I n c . A l l r i g h t s r es er v e d .
  • 10. C op yr i g h t © 2 0 1 4 , S A S I n s t i t u t e I n c . A l l r i g h t s r es er v e d .
  • 11. C op yr i g h t © 2 0 1 4 , S A S I n s t i t u t e I n c . A l l r i g h t s r es er v e d .
  • 12. C op yr i g h t © 2 0 1 4 , S A S I n s t i t u t e I n c . A l l r i g h t s r es er v e d .
  • 13. C op yr i g h t © 2 0 1 4 , S A S I n s t i t u t e I n c . A l l r i g h t s r es er v e d .
  • 14. SCIENCE C op yr i g h t © 2 0 1 4 , S A S I n s t i t u t e I n c . A l l r i g h t s r es er v e d . ART
  • 15. MARKETERS TODAY ARE DATA-DRIVEN Structured Rational needs Information, Transaction, Service SCIENCE Customer Experience Semistructured Emotional needs Unstructured #SASCI Belonging, Identity, Aspiration, Performance, Knowledge Sources: Work·Play·Experience I Forrester Blog--Kerry Bodine, April 2, 2014 | SAS C op yr i g h t © 2 0 1 4 , S A S I n s t i t u t e I n c . A l l r i g h t s r es er v e d . ART
  • 16. MARKETING CREATES UNDERSTANDING Forecasting Scenario analysis Dynamic time-lap analysis Decision tree analysis • • • Self-service Easy to use Analytics Work with more data C op yr i g h t © 2 0 1 4 , S A S I n s t i t u t e I n c . A l l r i g h t s r es er v e d . • • • Reporting and Dashboards Mobile BI Collaboration
  • 17. PICTURES MEET NUMBERS C op yr i g h t © 2 0 1 4 , S A S I n s t i t u t e I n c . A l l r i g h t s r es er v e d .
  • 18. YES, I WANT IT IS STRAIGHT FORWARD! ANALYTICS BUSINESS MANAGER Domain Expert Makes Decisions Evaluates Processes and ROI EVALUATE / MONITOR RESULTS IDENTIFY / FORMULATE PROBLEM DATA PREPARATION DEPLOY MODEL IT SYSTEMS / MANAGEMENT Model Validation Model Deployment Model Monitoring Data Preparation C op yr i g h t © 2 0 1 4 , S A S I n s t i t u t e I n c . A l l r i g h t s r es er v e d . BUSINESS ANALYST Data Exploration Data Visualization Report Creation DATA EXPLORATION DATA SCIENTIST / DATA MINER / STATISTICIAN VALIDATE MODEL TRANSFORM & SELECT BUILD MODEL Story Telling Exploratory Analysis Descriptive Segmentation Predictive Modeling
  • 19. THE MARKETER CAN BUILD THE CUSTOMER PROFILE Anonymous Behavior E-Mail Account Social Customer Behavior Customer Value (RFM) Customer Value Buying Behavior Segmentation Browsing Behavior Previous browsing activity Clustering Ability to look back Product linking (nearness) Predictive Insight (Churn/Opportunity) More effective targeting Lifecycle and Lifestyle marketing Frequency of visits Customer as partner/promoter Engagement Level Big Data Time Cookie 123 Sessions 1 2 … n C op yr i g h t © 2 0 1 4 , S A S I n s t i t u t e I n c . A l l r i g h t s r es er v e d . E-mail Peter.woods@sas.com User ID PW45361 Geo Online Segment 01 Browser Customer Segment DedicatedFan Customer Knowledge
  • 20. THRIVING IN THE BIG DATA ERA VOLUME DATA SIZE VARIETY VELOCITY VALUE TODAY C op yr i g h t © 2 0 1 4 , S A S I n s t i t u t e I n c . A l l r i g h t s r es er v e d . THE FUTURE
  • 21. WHAT IS THE IMPACT FROM BIG DATA ON CUSTOMER ANALYTICS? Operationalize Real-time In-database …. DEPLOY PREPARE DATA All Data Number of Variables New Events Unstructured Data ….. CUSTOMER ANALYTICS MODEL No. of Iterations Complex Models Retraining Ensembles …. C op yr i g h t © 2 0 1 4 , S A S I n s t i t u t e I n c . A l l r i g h t s r es er v e d . EXPLORE Fast Interactive Visual Analytical ….
  • 22. BIG DATA ANALYTICS?! Value creation Analytics High-Performance Analytics C op yr i g h t © 2 0 1 4 , S A S I n s t i t u t e I n c . A l l r i g h t s r es er v e d .
  • 23. THE ANALYTICS MOVE THE ANALYTICS TO THE (BIG) DATA LIFECYCLE EVALUATE / MONITOR RESULTS IDENTIFY / FORMULATE PROBLEM DATA PREPARATION DEPLOY MODEL DATA EXPLORATION VALIDATE MODEL TRANSFORM & SELECT BUILD MODEL C op yr i g h t © 2 0 1 4 , S A S I n s t i t u t e I n c . A l l r i g h t s r es er v e d .
  • 24. BIG DATA INTEGRATED USER EXPERIENCE ANALYTICS BUSINESS ANALYST STATISTICIAN DATA SCIENTIST /PROGRAMMER GUI Visual Analytics Data Preparation C op yr i g h t © 2 0 1 4 , S A S I n s t i t u t e I n c . A l l r i g h t s r es er v e d . Exploration/ Visualization GUI Visual Statistics Modeling Deployment
  • 25. LAST PIECE OF THE DATA QUALITY “DATA DELAYED IS DATA DENIED” PUZZLE: “…poor data quality costs U.S. businesses $600 billion annually” Market value C op yr i g h t © 2 0 1 4 , S A S I n s t i t u t e I n c . A l l r i g h t s r es er v e d . Pumped into the U.S. economy
  • 26. DATA QUALITY IMPACT: MANAGED DATA Predictive Modeling Process Limited and poor Data Low predictive effectiveness Model lift “low-average” Exhaustive and documented information High predictive effectiveness C op yr i g h t © 2 0 1 4 , S A S I n s t i t u t e I n c . A l l r i g h t s r es er v e d . Model lift “good-high”
  • 27. MANAGED ANALYTICAL DATA 1. Access the data from multiple systems: - Integrate - Enrich - Describe 2. Cleanse data - Analyse - Inform - Improve Growth path: Data governance, Master data management C op yr i g h t © 2 0 1 4 , S A S I n s t i t u t e I n c . A l l r i g h t s r es er v e d .
  • 28. BIG DATA ANALYTICS BUSINESS ANALYST STATISTICIAN DATA SCIENTIST /PROGRAMMER GUI Visual Analytics Data Preparation C op yr i g h t © 2 0 1 4 , S A S I n s t i t u t e I n c . A l l r i g h t s r es er v e d . Exploration/ Visualization GUI Visual Statistics Modeling Deployment
  • 29. BIG DATA ANALYTICS BUSINESS ANALYST STATISTICIAN DATA SCIENTIST /PROGRAMMER Quality Analytics Scoring GUI In-database processing Data Preparation C op yr i g h t © 2 0 1 4 , S A S I n s t i t u t e I n c . A l l r i g h t s r es er v e d . Visual Analytics Exploration/ Visualization GUI Visual Statistics Modeling Deployment
  • 30. SO WHERE DO WE READY YOURSELF TO CREATE VALUE STAND The business purpose of analytics >>> • Analytics to go beyond borders The conditions to guarantee success >>> • Managed data How new technologies support analytics >>> • Enabled on Hadoop, Cloud, real-time platforms C op yr i g h t © 2 0 1 4 , S A S I n s t i t u t e I n c . A l l r i g h t s r es er v e d .
  • 31. FUTURE VALUE OF ANALYTICS According to experts: - We are not able to crash a car anymore or burn diner - BUT Most importantly: All customer communication is personal!! C op yr i g h t © 2 0 1 4 , S A S I n s t i t u t e I n c . A l l r i g h t s r es er v e d .
  • 32. MORE INFORMATION Download the whitepaper: Four Tips to Mastering Multichannel Digital Marketing Attribution C op yr i g h t © 2 0 1 4 , S A S I n s t i t u t e I n c . A l l r i g h t s r es er v e d .
  • 33. THANK YOU PETER.WOODS@SAS.COM NL.LINKEDIN.COM/IN/PETERWOODS/ SELECTED MATERIALS COURTESY OF BRIAN VELLMURE BRIANVELLMURE.COM C op yr i g h t © 2 0 1 4 , S A S I n s t i t u t e I n c . A l l r i g h t s r es er v e d . sas.com

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