Extracting Big Value From Big Data in Digital Media - An Executive Webcast with Aberdeen Group

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As the amount and variety of business data continues to grow at incredible rates, more organizations are beginning to pay attention to the potential business impact found in digital media. In fact, …

As the amount and variety of business data continues to grow at incredible rates, more organizations are beginning to pay attention to the potential business impact found in digital media. In fact, Aberdeen's research shows that 61% of organizations consider digital media to be a critical part of their Big Data initiatives. However, fewer than one in five of these organizations currently have the tools to efficiently manage this type of information. This means that leading digital media firms - including advertisers, marketing service providers, content publishers and more - are finding themselves in the middle of an incredible opportunity.

Much has been made of the solutions to efficiently manage the growing volume, increased variety, and faster velocity of business data, but for these firms it is just as important to consider how to use this data to deliver the most value - to deliver the right message to the right person at the right time... for the right price. This webinar will provide research findings on the state of Big Data, and a discussion of the tools, techniques and talent used to boost marketing effectiveness, optimize ad campaigns and drive strong customer acquisition and retention.

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  • 1. Extracting Big Value from Big Data in Digital Media An Executive Webcast with Aberdeen Group, June 2012 Nathaniel Rowe Krishnan Parasuraman Research Analyst CTO, Digital Media Enterprise Data Mgmt. Netezza and Big Data Solutions @kparasuraman1 © 2012 IBM Corporation
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  • 7. Digital Marketer’s Goals Key Challenges1 Single view of customer Customer information fragmented across channels – Online, Apps, Social, Mobile2 Increase Targeting Precision Behavior is a much better indicator of intent than demographics3 Improve Relevance Customers expect personalized services, have greater access to devices4 Drive up campaign profitability Audience attention is fragmented yet contention for eyeballs is increasing © 2012 IBM Corporation
  • 8. Digital Marketer’s Goals Solution Capabilities Clickstream Consolidation1 Single view of customer Transactions All in one Social Events place CRM Support calls Increase Targeting Precision Segmentation2 Clustering Scoring Feature Selection Associations3 Improve Relevance Personalized message Matching Matching algorithms Matrix computations Single Value Decomp.4 Drive up campaign profitability Optimization Forecasting Predictive algorithms Decision trees Linear Regression © 2012 IBM Corporation
  • 9. Digital Marketer’s Goals Solution Capabilities Clickstream Consolidation1 Single view of customer Transactions All in one Social Events place CRM Support calls Increase Targeting Precision Segmentation2 Clustering Scoring Big Data Feature Selection Associations3 Improve Relevance Platform Personalized message Matching Matching algorithms Matrix computations Single Value Decomp.4 Drive up campaign profitability Optimization Forecasting Predictive algorithms Decision trees Linear Regression © 2012 IBM Corporation
  • 10. Big Data Platform Requirements Analyze Extreme Volumes of Data Impressions Online, Offline, Social, Behavior, First Party & Cookies Third Party across multiple channels Online Registrations Purchase Transactions Analyze Wide Variety of Data In-Market Intent Structured – POS, 3rd Party, Transactions Unstructured – Social, Video, Blogs Influence Semi-Structured – Cookies, Impressions Sentiments BIG DATASocial Followers Analyze Data in Real Time Recommendations Likes PLATFORM Product Recommendations, Real Time offers, Targeted Ads in Real Time Psychographic surveys Geo-Demographic Discover & Experiment3rd Party Segments Ad-hoc analytics, data discovery & experimentation Offline Transactions Responses Governance Enforce data structure, integrity and control to ensure consistency © 2012 IBM Corporation
  • 11. IBM Netezza Big Data Impressions Cookies Appliance Online Registrations Purchase Transactions In-Market Intent • Purpose-built analytics engine • Integrated database, server and storage Influence Sentiments • Standard interfacesSocial Followers • Low total cost of ownership Recommendations Likes  Speed: 10-100x faster than traditional systems Psychographic surveys  Simplicity: Minimal administration and tuning Geo-Demographic3rd Party Segments  Scalability: Peta-scale user data capacity Offline Transactions  Smart: High-performance advanced analytics Responses © 2012 IBM Corporation
  • 12. Behavior Segmentation Use Case Product Life- style Sensitivity to Preference Preferred Markdown Channel Levels Engagement in Recency + Loyalty Program Frequency + Value Use of Private ?Response to Label Credit Media Card Use of Service Estimated Time Departments until Next Arrival Breadth of Return / Entities Shopped Exchange Predictive Behavior Customer Analytics Analytics IBM Netezza Unica Unica Customer Predictive Insight Insight © 2012 IBM Corporation
  • 13. Audience Campaign Yield Attribution Ad Sales Website Ad Targeting Optimization Analysis Optimization Analysis Analysis Optimization Netezza Powered Analytic Solutions Media Plans Execs, Analysts, Internal Data Customer Master Data Campaigns Quants, Staticians, Responses Data Miners List Pulls, Campaign Execution External Data Sources Competitive Site Performance Media Perf. 3rd Party Data Social Monitoring Video13 © 2012 IBM Corporation
  • 14. Merkle helps clients processhours worth of data inminutes with NetezzaNeed• Effectively transform petabytes of raw data into useful information that can influence marketing processes and predict customer preferences with accuracyBenefits• 25-90% revenue lift for one client through use of new analytic models• Regularly received a 70% reduction in processing time for complex marketing campaigns - decreasing time from hours to minutes• Up to 25% decrease in the cost of managing clients’ environments © 2012 IBM Corporation
  • 15. Question and Answer Round Table Nathaniel Rowe Krishnan Parasuraman Research Analyst CTO, Digital Media Enterprise Data Mgmt. Netezza and Big Data Solutions Nathaniel.Rowe@Aberdeen.com @kparasuraman Visit http://analyzingmedia.com to learn more about big data in digital media.15 © 2012 IBM Corporation