Presented by Kate Tickner Date 12 th October 2012 Big Data Anwendungsfälle aus dem Bereich der digitalen Medien Using Big Data and Smarter Analytics to Increase Consumer Engagement
Dramatic forces affecting the media and entertainment industry require new approaches to maximize profitability and revenue. Rapid adoption of connected devices and social media Time and place for customer engagement has shifted Heightened customer expectations for new services, pricing, and packaging Exponential growth in data about customers, interactions and transactions Growing complexity in creation and distribution to new, multiple platforms Value chain migration and revenue model uncertainty 2
Today s changing business realities and expanding markets represent tremendous growth potential Integration and data capture Next generation analytics New consumption patterns New monetization opportunities 1 trillion 90 percent 50 percent $231 billion the internet of things will reach 1 trillion by 2015 of data growth is unstructured of consumers watch video daily or weekly on digital devices; internet advertising revenues are growing in revenue will be generated in the Connected Home by 2016 3 Source: 1) 2012 Mobility Predictions: A Year of Living Dangerously, Yankee Group, 2) The Expanding Digital Universe, IDC 3) 2011 US Consumer Survey, Yankee Group; Interactive Advertising Bureau, 4) Connected Home Report 2011-2016,Parks Associates.
Globally, a majority of mainstream consumers are now living connected. A snapshot of today s connected consumer Respondents aged 55 to 64: Respondents over 65: Respondents aged 18 to 64: 4 Source: IBM s 2011 Digital Consumer Survey, US, UK, Germany, Japan, and France.
M&E CMOs are eager to deploy tools and technologies to move to a more customer-centric focus. Plans to increase the use of technology Percent of CMOs selecting technologies Social media Customer analytics CRM Mobile applications Content management Tablet applications Single view of customer Collaboration tools Predictive analytics Reputation management Search engine optimization Campaign management 87% 83% 75% 81% 72% 79% 62% 62% 55% 66% 64% 59% 5 Source: 2011 IBM CMO Study, Media and Entertainment Point-of-view. Q22 Do you plan to decrease or increase the use of the following technologies over the next 3 to 5 years?
Merging the Traditional and Big Data Approaches Traditional Approach Structured & Repeatable Analysis Big Data Approach Iterative & Exploratory Analysis Business Users Determine what question to ask IT Delivers a platform to enable creative discovery IT Structures the data to answer that question Business Explores what questions could be asked Monthly sales reports Profitability analysis Customer surveys Brand sentiment Product strategy Maximum asset utilization 6 6
Media firms leverage Big Data analysis to deliver relevance Right message. Right person. Right time. Right price. 7 D I G I T A L M E D I A Page 7
Representative digital media customers Advertisers Marketing Service Providers Content Publishers Consumers 8 D I G I T A L M E D I A Page 8
Eurobuzz Live Social Network Analysis Application engages 2012 Eurovision Contest viewers for France TV - Users watching the broadcasted event were invited to send their comments by Tweets with specific hashtags, eg: #eurovision, #eurofrancetv - Tweets streams were computed by IBM Infosphere Streams using the Twitter Streaming API. - These tweets were then filtered, analyzed, aggregated to generate statistics such as popularity-rating on the 42 countries in competition. - Data visualization was processed by IBM partner Novius - This real-time analysis also highlighted other useful trends all along the event - The analyses outlined the success of the Winner (Sweden singer) 3 hours before the end of the event Winner: 2012 ConnectedTV Awards: Best WebApp 9
Polish media giant, Agora, realigned its online media strategy and supporting processes to capture online audience. Online readers grew by 45% Online advertising revenues increased 346% Business problem: With competition looming and its online market share slipping, the company needed to design and implement a new strategy for online media to capitalize on its strong local market presence. Solution: Conduct a comprehensive assessment of the company s business environment, and develop a series of strategic scenarios to identify marketing opportunities, detailed strategy recommendations and a roadmap for implementation. 10 We realized that our long-term success required us to align our strategy and resources to meet the challenges of the rapidly evolving global media market. IBM helped us frame these challenges, identify our strategic options and follow a clear roadmap to success. - Maciej Wicha, Director of News & Communities, Agora SA
A global media company, dedicated to health and wellness, measures online performance to grow readership and revenue. Increased page views 92% Improved click-through rates 45% Business problem: Content providers are constantly seeking to grow their audiences. That growth, however, is not always accompanied by corresponding increases in revenue growth. To succeed, content providers must find a way to monetize audience growth. Solution: Web analytics provide rich insight into online content performance, thereby enabling informed decisions that drive revenue growth. 11
Customer Stories Application Specific Solution Examples
Key Components Ref. Architecture Smarter Media and Entertainment 1. Behavioral Segmentation? Customer Analytics Unica Customer Insight Predictive Analytics Unica Predictive Insight Data Models 3 rd party integration partnerships lite ETL Ingestion best practices/ guidelines Predictive Audience Segmentation models Optimal Frequency Range computation Look-a-like segment creation Best practices to connect offline/online data 13
Key Components Ref. Architecture Smarter Media and Entertainment 2. Attribution Analysis $ $ $ Informix Timeseries Time Series computation algo. Run time extraction of data elements from Hadoop Attribution data model Attribution funnel dashboards Sessionization logic Smart consolidation across Big Insights and Informix 14
Key Components Ref. Architecture Federation Smarter Media and Entertainment 3. Social Data Analysis Social Data (unstructured text) Text Index Socially enriched audience data model UIMA framework for text extraction Correlation of text/unstructured and structured data Federated queries across structured and unstructured content 15
Key Components Ref. Architecture AdServers Exchanges Smarter Media and Entertainment 4. Real Time Ad Targeting Real time event detection and mediation Off-line scoring and execution of behavior models Real time scoring and profile management 3 rd party data sources; DMPs Event data models NoSQL and Relational Data sync logic Behavioral models DMP API based integration Data dedupe & enrichment Real time matching algorithm Exchange/ RTB Integration 16
Digital Media business results from IBM Big Data Solutions 300% to 2,000% conversion rate improvements with behavioral targeting loading clickstream data at 1 terabyte per hour 50%+ increases in campaign lift campaign goals achieved while reducing CPA from $170 to $80 25% conversion rate maintained with 33% lower CPA Launched ahead of schedule with a 92 percent reduction in operating costs Millions in increased ad revenue thru improved ad inventory forecasting, ad price optimization, and increased fill rate 17 2009 Netezza, Inc. All rights reserved Confidential D I G I T A L M E D I A Page 17
Increased Consumer Engagement: How do you provide differentiated experiences? Where do you want to begin? Business outcomes Increase customer intimacy, acquisition, and retention Website traffic increased Subscribers increased On-line revenue increased Advertising sales and effectiveness improved ROI across multiple platforms increased Insight into life-time value of a customer Transformational stages Value Customer Information Management Customer Experience Integration Customer and Marketing Insights Customer-Centric Go-to-Market Customer Experience Innovation Analyze patterns Optimize outcomes Manage data Maturity 18
IBM Connected Customer: Integrated Data Management Provides a 360 view of the customer and establishes the information platform for advanced customer analytics. Single or federated view of each customer CRM data Online interactions Social media conversations Enables you to Provide 360-degree view of customer to increase customer satisfaction and reduce churn Products and services Demographics Unstructured data Increase average revenue per user, subscriber, customer Lower operational costs with consolidated databases Increase ease of launching new products and services to micro-segmented customers 19
IBM Connected Customer: Customer Insight Reveals deep insight into the behavior of connected customers to enhance the value of media products and services for today s connected customers. Enterprise Data Unstructured Data/Natural Language Real-Time, Predictive, and Social Analytics Enables you to Deploy web and social network analytics as a source of valuable insight Perform deep analysis of audience sentiment and media behaviors Analyze conversations to optimize creative Measure audience response to drive CPMs and identify future ad sales targets Understand and anticipate customer behavior across all channels Develop micro-segment profiles and recognize what products attract each customer segment Offer real-time incentives to accelerate offer acceptance, improve cross-sell / up-sell, and reduce customer churn 20
IBM Connected Customer: Commerce and Portals Integrates and executes customer-centric commerce processes to improve operational efficiency and the customer buying experience. Enables you to Insight Strategy Realize insight-driven marketing to strengthen revenue streams Buy Service Market Sell Enable a personalized buying experience to deliver greater customer value Optimize order management and fulfillment to increase operational efficiency Transform partner integration and collaboration to expand marketplace presence Engagement 21
USC Annenburg Media Innovation http://www.ibmbigdatahub.com/video/uscannenberg-innovation-lab-uses-ibm-big-data-realtime-social-sentiment-analysis 22
Vielen Dank für Ihre Aufmerksamkeit Haben sie fragen?