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Big Data Meets Social Analytics - IBM Connect 2012 (CN-CC13)
Big Data Meets Social Analytics - IBM Connect 2012 (CN-CC13)
Big Data Meets Social Analytics - IBM Connect 2012 (CN-CC13)
Big Data Meets Social Analytics - IBM Connect 2012 (CN-CC13)
Big Data Meets Social Analytics - IBM Connect 2012 (CN-CC13)
Big Data Meets Social Analytics - IBM Connect 2012 (CN-CC13)
Big Data Meets Social Analytics - IBM Connect 2012 (CN-CC13)
Big Data Meets Social Analytics - IBM Connect 2012 (CN-CC13)
Big Data Meets Social Analytics - IBM Connect 2012 (CN-CC13)
Big Data Meets Social Analytics - IBM Connect 2012 (CN-CC13)
Big Data Meets Social Analytics - IBM Connect 2012 (CN-CC13)
Big Data Meets Social Analytics - IBM Connect 2012 (CN-CC13)
Big Data Meets Social Analytics - IBM Connect 2012 (CN-CC13)
Big Data Meets Social Analytics - IBM Connect 2012 (CN-CC13)
Big Data Meets Social Analytics - IBM Connect 2012 (CN-CC13)
Big Data Meets Social Analytics - IBM Connect 2012 (CN-CC13)
Big Data Meets Social Analytics - IBM Connect 2012 (CN-CC13)
Big Data Meets Social Analytics - IBM Connect 2012 (CN-CC13)
Big Data Meets Social Analytics - IBM Connect 2012 (CN-CC13)
Big Data Meets Social Analytics - IBM Connect 2012 (CN-CC13)
Big Data Meets Social Analytics - IBM Connect 2012 (CN-CC13)
Big Data Meets Social Analytics - IBM Connect 2012 (CN-CC13)
Big Data Meets Social Analytics - IBM Connect 2012 (CN-CC13)
Big Data Meets Social Analytics - IBM Connect 2012 (CN-CC13)
Big Data Meets Social Analytics - IBM Connect 2012 (CN-CC13)
Big Data Meets Social Analytics - IBM Connect 2012 (CN-CC13)
Big Data Meets Social Analytics - IBM Connect 2012 (CN-CC13)
Big Data Meets Social Analytics - IBM Connect 2012 (CN-CC13)
Big Data Meets Social Analytics - IBM Connect 2012 (CN-CC13)
Big Data Meets Social Analytics - IBM Connect 2012 (CN-CC13)
Big Data Meets Social Analytics - IBM Connect 2012 (CN-CC13)
Big Data Meets Social Analytics - IBM Connect 2012 (CN-CC13)
Big Data Meets Social Analytics - IBM Connect 2012 (CN-CC13)
Big Data Meets Social Analytics - IBM Connect 2012 (CN-CC13)
Big Data Meets Social Analytics - IBM Connect 2012 (CN-CC13)
Big Data Meets Social Analytics - IBM Connect 2012 (CN-CC13)
Big Data Meets Social Analytics - IBM Connect 2012 (CN-CC13)
Big Data Meets Social Analytics - IBM Connect 2012 (CN-CC13)
Big Data Meets Social Analytics - IBM Connect 2012 (CN-CC13)
Big Data Meets Social Analytics - IBM Connect 2012 (CN-CC13)
Big Data Meets Social Analytics - IBM Connect 2012 (CN-CC13)
Big Data Meets Social Analytics - IBM Connect 2012 (CN-CC13)
Big Data Meets Social Analytics - IBM Connect 2012 (CN-CC13)
Big Data Meets Social Analytics - IBM Connect 2012 (CN-CC13)
Big Data Meets Social Analytics - IBM Connect 2012 (CN-CC13)
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Big Data Meets Social Analytics - IBM Connect 2012 (CN-CC13)

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Presentation at IBM Connect 2012 event in Orlando, Florida. For more contact me at @mheid or mheid@us.ibm.com

Presentation at IBM Connect 2012 event in Orlando, Florida. For more contact me at @mheid or mheid@us.ibm.com

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  • 1. INV307 - Big Data meets SocialAnalytics - Revolutionizing HowCompanies Address Customer NeedsAya Soffer | Director, Information Management &Analytics Research | IBMMark Heid | Program Director, Social Analytics |IBM© 2012 IBM Corporation
  • 2. Agenda■ Big Data – what is it, why now, why should I care?■ Social Analytics – challenges and opportunities■ Marketing in the era of Big Data and Social Analytics■ Social Analytics innovation in IBM Research■ IBM offerings and solutions 2 | © 2012 IBM Corporation
  • 3. An Explosion of Data 1.3 Billion RFID tags in 2005 30 Billion RFID tags in 4.6 Billion mobile phones worldwide 2010 Google processes 2 Billion Internet users in 2011 By 2013, annual internet traffic > 24 Petabytes of data will reach 667 Exabytes in a single day Facebook processes Twitter processes 10 Terabytes of data every 7 Terabytes of data every day day Hadron Collider at CERN For every session, NY Stock generates 40 Terabytes Exchange captures 1 Terabyte of data / sec of trade information 3 | © 2012 IBM Corporation
  • 4. Information Overload… But Lacking Insight Business leaders 44 1 in 3 make decisions based as much Data and on information they Content don’t trust, or don’t have Over Coming Decade x say they feel 56% overwhelmed by the amount of data their company manages say they need to 60% do a better job capturing and understanding 2020 information rapidly 35 zettabytes 2011 cited “BI & Analytics” 2009 1.8 zettabytes800,000 petabytes 83% as part of their visionary plans to enhance competitiveness 4 | © 2012 IBM Corporation4
  • 5. The “BIG Data” Challenge Extracting insight from an immense volume, Manage the complexity of multiple relational and non- variety and velocity of Variety relational data types and data, in context, beyond schemas what was previously possible. Streaming data and large Velocity volume data movement Scale from terabytes to Volume zettabytes 5 | © 2012 IBM Corporation5
  • 6. IBM’s Big Data Solution Bringing Together a Large Multi-channel customer Volume and Variety of Data to sentiment and experience analysis Find New Insights  Analyzing a variety of data Detect life-threatening at enormous volumes conditions at hospitals in  Insights on streaming data time to intervene  Large volume un-structured data analysis Predict weather patterns to plan optimal wind turbine usage, and optimize capital expenditure on asset placement Make risk decisions based on real-time transactional data IBM Big Data Platform  Variety Identify criminals and threats  Velocity from disparate video, audio,  Volume and data feeds 6 | © 2012 IBM Corporation6
  • 7. Merging the Traditional and Big Data Approaches Traditional Approach Big Data Approach Structured & Repeatable Analysis Iterative & Exploratory Analysis IT Business Users Delivers a platform to Determine what enable creative question to ask discovery IT Business Structures the Explores what data to answer questions could be that question asked Monthly sales reports Brand sentiment Profitability analysis Product strategy Customer surveys Maximum asset utilization 7 | © 2012 IBM Corporation7
  • 8. The intersection of social media and big data 8 | © 2012 IBM Corporation
  • 9. Agenda■ Big Data – what is it, why now, why should I care?■ Social Analytics – challenges and opportunities■ Marketing in the era of Big Data and Social Analytics■ Social Analytics innovation in IBM Research■ IBM offerings and solutions 9 | © 2012 IBM Corporation
  • 10. We have Many Challenges…and Opportunities Years to reach Tablet  Channels proliferate… 50M users: 2 Yrs Facebook  The Internet evolves… 3 Yrs Internet  The consumer is in control… 4 Yrs Network of pages Network of people TV  The rate of change accelerates… 13 Yrs Clearly organizations must evolve… 10 | © 2012 IBM Corporation10
  • 11. Social Analytics Has Extensive Potential August 28, 2011 by R "Ray" Wang, Constallation Research 11 | © 2012 IBM Corporation
  • 12. Customer Maturity Curve Quantify & Predict & Integrate Monitor & Engage Operationalize Integrate Transparently Business Outcomes  Predict & Improve  Seamless Integration of Outcomes With Internal, Extranet & Continuous Feedback Public Social Media  Identify & Measure ROI  Quantitatively Optimize Analysis & Action  Operationalize Insight  Systemic Governance Decisions Across  Identify & Track KPIs via Business Processes Functions  Qualitatively Improve  Quantitatively Improve  Limited Governance Marketing Decisions  Embedded Social Marketing Decisions  Open-up Social Media Analytics  Full Sentiment  “Targeted Crowd Marketing Channel  Geo-Spatial Analysis Sourcing”  Limited sentiment  Platform Analysis  Network & influencer  Predictive Modeling analysis  SaaS & On Premise Capabilities  Monitor & Engage  Limited back-end  Lightweight “Domain-  Partner / Ecosystem process integration Specific” Analytics Datasets  SaaS & On Premise  SaaS-Only  Complete Back-End Sourcing: ERP, HR, etc  Broad Public Social Media  3rd-Party DatasetsSources Sourcing (“Big Data”)  OEM-Level Sourcing of Data  Mainstream Social  Enterprise CRM & “Big Data” Media Transactional Data Organizational Maturity & Sophistication 12 | © 2012 IBM Corporation
  • 13. Understanding the Customer and Answering: “Why” High-value, dynamic approach - source of competitive differentiation Interaction data Attitudinal data - E-Mail / chat transcripts -Market Research How? - Call center notes - Web Click-streams Why? -Social Media - In person dialogues Descriptive data Behavioral data - Attributes - Orders Who? What? - Characteristics - Transactions - Self-declared info - Payment history - (Geo)demographics - Usage history “Traditional approach” 13 | © 2012 IBM Corporation
  • 14. Agenda■ Big Data – what is it, why now, why should I care?■ Social Analytics – challenges and opportunities■ Marketing in the era of Big Data and Social Analytics■ Social Analytics innovation in IBM Research■ IBM offerings and solutions 14 | © 2012 IBM Corporation
  • 15. Expanding marketing’s role, and contribution to the business + Transformative CMO Traditional CMO Agenda: + Understand the customer in real time, across the business Agenda: + Anticipate customer needs  Understand the market and the + Drive consistent, compelling interactions customer across all channels  Build awareness and demand + Steward the customer experience across  Steward the company’s brand all touch points + Monitor and harness customer evangelism  Drive brand strategy and + Accountable for business outcomes and execution return on investment 15 | © 2012 IBM Corporation15
  • 16. The vast majority of CMOs are underprepared to manage the impact of key changes in the marketing arena Underpreparedness Percent of CMOs reporting underpreparedness 50% Data explosion 71% Social media 68% Growth of channel and device choices 65% Shifting consumer demographics 63% Financial constraints 59% Decreasing brand loyalty 57% Growth market opportunities 56% ROI accountability 56% Customer collaboration and influence 56% Privacy considerations 55% Global outsourcing 54% Regulatory considerations 50% Corporate transparency 47% Source: Q8 How prepared are you to manage the impact of the top 5 market factors that will have the most impact on your marketing organization over the next 3 to 5 years? n=149 to 1141 (n = number of respondents who selected the factor as important) 16 | © 2012 IBM Corporation16
  • 17. Customers are the New Intellectual Property (Keep the promise) Customer Intimacy Decision Management Product Operational Leadership Excellence (Make the promise) (Deliver the promise) 17 | © 2012 IBM Corporation17
  • 18. We are seeing unprecedented upheaval in the consumer buying process In the past….there was a funnel • Many Brands - Consumers start buying process with a large number of brands in mind • Fewer Brands: These choices are narrowed down to a few • Final Choice: A decision is made between the few • Buy: A purchase is made… • Post Purchase: Consumers’ relationship with the brand is focused on the use of the product or service Today’s consumer buying process is far more dynamic and interactive….. 18 | © 2012 IBM Corporation * David C. Edelman, McKinsey, Dec 201018
  • 19. Increasingly, customer acquisition is more nuanced. Generating loyalty is the new marketing imperative Social Analytics is the key to success in Gain insights and increase positive this new environment sentiment in social conversations Accelerate re-purchase through propensity models Strengthen brand preference through advocacy 19 | © 2012 IBM Corporation * David C. Edelman, McKinsey, Dec 201019
  • 20. Looking ahead – The future must be intelligent marketing that understands the interrelations of all channels and media e web site, microsites, Owned blog, Facebook page, media etc display ads, PPC, Google sponsored content, etc. PR Paid Customer Earned Ads media media Google what your customers share and say about you on twitter, Facebook blogs and 20 | © 2012 IBM Corporation the internet20
  • 21. A Social Analytics Application: IBM Cognos Consumer Insight Create Relationships. Build Advocacy. Improve Loyalty. Grow Your BusinessEnhance YourReputationImprove Yourcustomer experience 21 | © 2012 IBM Corporation21
  • 22. Competitive analysis – Financial ServicesDrilldowns quickly uncovered a very different sponsorship investment strategy between Company sponsors many local event throughout the year, while competitor focuses one or two high visibility events 22 | © 2012 IBM Corporation
  • 23. Product brand analysis – Consumer ProductsSophisticated analytics revealed which beverage attributes are being leveraged by the competition 23 | © 2012 IBM Corporation
  • 24. Agenda■ Big Data – what is it, why now, why should I care?■ Social Analytics – challenges and opportunities■ Marketing in the era of Big Data and Social Analytics■ Social Analytics innovation in IBM Research ■ Customer analytics – 360 profile and lead generation (SMARC) ■ Spatio-temporal analytics for demand prediction (Microcosm) ■ Social Medical Discovery (SMD) ■ Voice of the Employee (SaND)■ IBM offerings and solutions 24 | © 2012 IBM Corporation
  • 25. SMARCSocial-media Micro-segmentation and Real-time CorrelationContinuously analyze social media data from a wide range of sources, to construct360-degree profiles of entities and leverage them in timely decision-making Value Proposition ─ Construct a comprehensive view of entities of interest (e.g., people, companies, products) ─ Identify actionable leads in real-time From ─ 10-100’s of TBs of social media data from sources such as Twitter, blogs, and forums Using ─ Scalable “Data-at-Rest” and “Data-in-Motion” analytics platform ─ Advanced analytics technologies (unstructured data analytics, real-time, and predictive analytics) 25 | © 2012 IBM Corporation
  • 26. SMARC Sample Application – Real Time Lead Generation Go for the Buying a Buying best, DP- DSLR Thrza gr8 deal DSLR 2000 today ! on ZX-550 @ today! the mall Prior Social Business Entity Extraction, Transactions Fact Discovery, Data Intent & Sentiment Influencers Intent 250M tweets/day Millions of tweets yield one company-specific fact Customer ready to buy a DSLR camera today, Michael’s online friends offer lots of advice possibly at a nearby mall Text Analytics used to extract intent from Social Media Married, Male, Spouse Wifey’s birthday tomorrow, looking for a killer dslr Birthdate, Gift Type, Intent to Purchase, Timeframe Sarcasm, Maybe I should buy her that purple Wishful Thinking Intent to Purchase, roadster, while I’m at it. ;-) lol Gift Type? Potential In NYC area this w/e, any good malls Locations and Region & City Location, nearby? Timeframe, Intent to Shop Activity Resultant fact base contains billions of facts, and is incrementally updated Fact segmentation or clustering is rapid enough to drive a business decision 26 | © 2012 IBM Corporation 26
  • 27. SMARC Lead Generation Dashboard Real-time product intents enriched with consumer attributesMicro-segmentation ofproduct intents byoccupation Real-time tracking by micro-segmentation Micro-segmentation of consumers by hobbies 27 | © 2012 IBM Corporation
  • 28. SMARC How Do We Create a User Profile? 28 | © 2012 IBM Corporation
  • 29. SMARC User Profiling Framework- Setting logging targeting Big Data Platform 29 | © 2012 IBM Corporation
  • 30. SMARC Going from Terms to Concepts Important Relevant Wikipedia Chosen terms Wikipedia titles/categories concepts articles1. Circuit2. Radio3. Electron4. Detector Circuits Integrated circuits Electronics5. Voltage Electronics6. Line Electronic music7. Chip Electronics8. Capacitor9. Input10. Signal Extract titles/Categories from Wikipedia pages Retrieve the most relevant pages Choose the most appropriate concepts 30 | © 2012 IBM Corporation
  • 31. MicrocosmSpatio-temporal Analytics for Demand Prediction■ What if you could find out immediately what’s happening in specific geographies or communities?■ Updated information ‘from the field’ can support decisions like: ─ Where should we send shipments? ─ What kind of promotions are needed? And where? ─ Which promotions were successful, which were not, and why?■ Although input is available for analysis from internal data sources like CRM, ERP, and more – it often involves delay■ How can you better understand what’s going on now? 31 | © 2012 IBM Corporation
  • 32. Microcosm Examples RecommendedLocation specific tweets ActionsUpbeat Charity event 09/08/11 in Redwoodcity. Dance and donate to local charities Local Events Annual Charity Event picking up very fast thisSylvieS Yes – I’m celebrating with dance year in Redwood city.and donate. Join us 09.08.11 in Redwood Ship more beverages toBuyTheWaySuperMarket Sponsors for the the local supermarketstreet party in Redwood City. Beer andpizza 4 all. 09.08.11. Local Promotion Cookies promotion very GoodHousekeeping Get $1 off Nestle cookies and milk with this coupon buy.x33/123/y8 popular in Sarasota. Redirect shipment from Care4Kids $1 off Nestle cookies when you St Petersburg to there. buy milk. HURRY buy.x33/123/y8 Carl Nestle’s giving $1 off milk and cookies! Get the coupon now buy.x33/123/y8 RestAssured I just wasted an evening having tasteless Thai food – no spice or flavor @LAfoodies Local Sentiment Negative sentiment about a Thai restaurant in LA.Zoe This restaurant is pathetic. Do not eat here Propose new spices ** This place looks good but the food is terrible. I assortment. ordered the chef’s special and was disappointed. 32 | © 2012 IBM Corporation
  • 33. Social MedicalSocial Medical Discovery ■ Social medical discovery ─ Analyzes medical and social relationships in the space of medical data ─ Searches over structured and unstructured information – Textual search – Faceted search, by age, medication name, genetic variation Patient ─ Ensures fast results, navigation, and exploration Patient Physician ■ Similar patients Patient Patient ─ Discovers similar patients that share similar medical conditions ─ Creates social communities of similar patients ■ Evidence-based medical recommendations ─ Recommends medication for symptoms ─ Recommends alternative treatments 33 | © 2012 IBM Corporation
  • 34. Social MedicalExample Use Case - Hemophilia Discover Lineage Find communities Has Genetic Has genetic symptom variation variation Hematuria Treated by Hemophilia Has Treated by disorder “Hemophila” Has Consumes disorder Drug Find physicians Consumes interaction Find adverse drugs Find Related Consumes patients Find medications 34 | © 2012 IBM Corporation
  • 35. SaND Voice of the Employee ■ 9 out of every 10 businesses using Web 2.0 technology are seeing measurable business benefits from its use (McKinsey). ■ 41 percent of respondents indicated that they have already implemented an enterprise social software solution (IDC)■ IBM as a leading example ■ Use Cases ─ Over 400K employee profiles ─ Recommending relevant content ─ Over 1M bookmarks with and people over 3M tags ─ Locating experts, influencers, and ─ Over 250K members in over central individuals 30K communities ─ Tracking trends and sentiment ─ Over 100K shared files and ─ Revealing information flow with 100K blog posts customers and partners ─ New event every 5 seconds in the activity streamMcKinsey Quarterly, "How companies are benefiting from Web 2.0: McKinsey Global Survey Results" 2009. IDC White Paper Sponsored by IBM, Becoming a Social Business: The IBM Story, Doc.#226706, January 2011. 35 | © 2012 IBM Corporation
  • 36. SaNDExample Use Case: Social Analytics for the Sales force■ Deliver accurate and highly relevant recommendations to help the sales organization most effectively close an opportunity: ─ Find experts – who is top seller, who knows key people from customer ─ Identify similar opportunities – sales opportunities, previous engagements with customer ─ Locating valuable assets that will maximize their chances of success ─ Business Intelligence - Trends regarding a given industry, competitive products ─ Example: Top 25 people related to large car manufacturer 36 | © 2012 IBM Corporation
  • 37. SaND SaND Streams – Sales Force Examples 37 | © 2012 IBM Corporation
  • 38. Agenda■ Big Data – what is it, why now, why should I care?■ Social Analytics – challenges and opportunities■ Marketing in the era of Big Data and Social Analytics■ Social Analytics innovation activities in IBM Research■ IBM offerings and solutions 38 | © 2012 IBM Corporation
  • 39. IBM’s Big Data Platform Marketing IBM Big Data Client and Partner IBM Unica Solutions Solutions Content Big Data Accelerators Analytics ECM Text Statistic Financial Geospatial Acoustic s Business Image/Video Mining Times Mathematic Analytics Series al Cognos & SPSS Connectors Applications Blueprints InforSphere Information Server Warehouse Appliance Big Data Enterprise Engines IBM Netezza Master Data InfoSphere InfoSphere Management Streams BigInsights InfoSphere MDM Data Warehouse Productivity Tools and Optimization InfoSphere Warehouse Workload Management Consumability and and Optimization Management Tools Database DB2 Open Source Foundation Components Data Growth Management Eclipse Oozie Hadoop HBase Pig Lucene Jaql InfoSphere Optim 39 | © 2012 IBM Corporation39
  • 40. IBM Cognos Consumer Insight Business Drivers Competitive Analysis Corporate Reputation Customer Care Campaign Effectiveness Product Insight Product Capabilities Source Areas COMPREHENSIVE SENTIMENT FACEBOOK ANALYSIS  Keyword Search  Dimensional Analysis BLOGS  Dimensional  Filtering Navigation  Voice  Drill Through to Content DISCUSSION FORUMS AFFINITY ANALYTICS EVOLVING TOPICS TWITTER  Relationship Tables  Relevant Topics NEWSGROUPS  Relationship Matrix  Associated Themes  Relationship Graph  Ranking and Volume MULTILINGUAL 40 | © 2012 IBM Corporation
  • 41. IBM Connections Profiles Home page Find the people you need See whats happening across your social network Communities Work with people who share common roles and expertise Social Analytics Discover who and what you don’t know Files via recommendations Post, share, and discover documents, presentations, images, and more Micro-blogging Wikis Reach out for help your social network Create web content together Activities Bookmarks Organize your work and tap your Save, share, and discover bookmarks professional network Forums Blogs Exchange ideas with, and benefit from Present your own ideas, and learn the expertise of others from others 41 | © 2012 IBM Corporation
  • 42. Questions? ? Aya Soffer Email: AYAS@il.ibm.com Twitter: @asoffer ? LinkedIn: Aya Soffer Mark Heid ? Email: Twitter: mheid@us.ibm.com @mheid LinkedIn: Mark Heid 42 | © 2012 IBM Corporation
  • 43. Additional Information Cognos Consumer Insight http://www-01.ibm.com/software/analytics/cognos/analytic-applications/consumer-insight/ Social Analytics – Overview Interview on YouTube http://www.youtube.com/watch?v=hjlwcXJaCWI 43 | © 2012 IBM Corporation
  • 44. 44 | © 2012 IBM Corporation44
  • 45. Legal disclaimer © IBM Corporation 2012. All Rights Reserved. The information contained in this publication is provided for informational purposes only. While efforts were made to verify the completeness and accuracy of the information contained in this publication, it is provided AS IS without warranty of any kind, express or implied. In addition, this information is based on IBM’s current product plans and strategy, which are subject to change by IBM without notice. IBM shall not be responsible for any damages arising out of the use of, or otherwise related to, this publication or any other materials. Nothing contained in this publication is intended to, nor shall have the effect of, creating any warranties or representations from IBM or its suppliers or licensors, or altering the terms and conditions of the applicable license agreement governing the use of IBM software. References in this presentation to IBM products, programs, or services do not imply that they will be available in all countries in which IBM operates. Product release dates and/or capabilities referenced in this presentation may change at any time at IBM’s sole discretion based on market opportunities or other factors, and are not intended to be a commitment to future product or feature availability in any way. Nothing contained in these materials is intended to, nor shall have the effect of, stating or implying that any activities undertaken by you will result in any specific sales, revenue growth or other results. If the text contains performance statistics or references to benchmarks, insert the following language; otherwise delete: Performance is based on measurements and projections using standard IBM benchmarks in a controlled environment. The actual throughput or performance that any user will experience will vary depending upon many factors, including considerations such as the amount of multiprogramming in the users job stream, the I/O configuration, the storage configuration, and the workload processed. Therefore, no assurance can be given that an individual user will achieve results similar to those stated here. If the text includes any customer examples, please confirm we have prior written approval from such customer and insert the following language; otherwise delete: All customer examples described are presented as illustrations of how those customers have used IBM products and the results they may have achieved. Actual environmental costs and performance characteristics may vary by customer. Please review text for proper trademark attribution of IBM products. At first use, each product name must be the full name and include appropriate trademark symbols (e.g., IBM Lotus® Sametime® Unyte™). 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