Download as PDF, PPTX
Uploaded byAccenture the Netherlands
HPMC 2014 - The value of analytics - SAS
The document discusses the value of analytics for businesses in the digital era. It covers: 1) The business purpose of analytics is to go beyond borders and understand customers better. 2) To guarantee success with analytics requires managed data quality. 3) New technologies like Hadoop, cloud platforms, and real-time systems enable more effective analytics.
More Related Content
Similar to HPMC 2014 - The value of analytics - SAS
More from Accenture the Netherlands
HPMC 2014 - The value of analytics - SAS
- 1. THE VALUE OFANALYTICS 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 OFANALYTICS • • • 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 ISMORE 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 Cop 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 yri 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 WECARE? 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 PREDICTIVEANALYTICS 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 OFAS 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! Cop 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 yri 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 yri 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 yri 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 yri 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 yri 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 AREDATA-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 ForecastingScenario 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 Cop 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 ITIS 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 CANBUILD 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 THEBIG 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 THEIMPACT 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-PerformanceAnalytics 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 THEANALYTICS 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 USEREXPERIENCE 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 OFTHE 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: MANAGEDDATA 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 BUSINESSANALYST 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 BUSINESSANALYST 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 DOWE 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 OFANALYTICS 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: FourTips 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 MATERIALSCOURTESY 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