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Big Data, Bigger Campaigns: Using IBM’s Unica and Netezza Platforms to Increase Marketing ROI
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Big Data, Bigger Campaigns: Using IBM’s Unica and Netezza Platforms to Increase Marketing ROI

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Is your organization challenged by the explosion of data and increasing expectations for results? Unica Campaign Management and IBM Netezza appliances can provide capabilities to address and......

Is your organization challenged by the explosion of data and increasing expectations for results? Unica Campaign Management and IBM Netezza appliances can provide capabilities to address and overcome them. This presentation offers customer case histories and performance studies that provide insights in today's world where digital and traditional channels are increasingly intertwined.

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  • IBM IOD 2011 09/12/12 Prensenter name here.ppt 09/12/12 13:52
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  • 1. Big Data, Bigger CampaignsUsing IBM’s Unica & Netezza Platformsto Increase Marketing ROI
  • 2. Agenda1) Observations on “the empowered customer” and “big data”2) IBM Netezza & IBM Unica in the age of big data: good on their own, great together © 2012 IBM Corporation
  • 3. • IBM’s statements regarding its plans, directions, and intent are subject to change or withdrawal without notice at IBM’s sole discretion.• Information regarding potential future products is intended to outline our general product direction and it should not be relied on in making a purchasing decision.• The information mentioned regarding potential future products is not a commitment, promise, or legal obligation to deliver any material, code or functionality. Information about potential future products may not be incorporated into any contract. The development, release, and timing of any future features or functionality described for our products remains at our sole discretion. 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. © 2012 IBM Corporation
  • 4. The age of the “empowered customer” 86% 78% use multiple of consumers channels trust peer 61% recommendations 4 in 10 trust friends’ Smart phone reviews more users search for than experts’ an item in a store 75% 44% do not of companies believe use crowd companies sourcing from tell the truth customers in ads 58% 4-5x are more price- conscious today than they were a 80% 8% more than average is spent by multi- year ago of CEOs think of their channel buyers they deliver a customers superior agree customer4 experience
  • 5. Empowered marketers need a “system ofengagement” Analyze Decide marketing data to find on the best actionable insights marketing action Collect Deliver data that augments engaging messageseach customer profile and capture reactionsheavily impacted Manage by big data marketing processes and measure results © 2012 IBM Corporation
  • 6. Support calls Platform Capabilit Transactions Clickstream Marketeer’s objectives Events CRM1 Single view of customer Matrix computations Feature Selection Single Value Decomp.Associations Clustering Matching algorithms Scoring2 Increased Targeting Precision Personalized message Consolidation3 Improved Relevance4 Higher campaign profitability Segmentation Forecasting Optimization Predictive algorithms Decision trees Linear Regression D I G I T A L M E D I A | Page 6 Matching
  • 7. Support calls Platform Capabilit Transactions Clickstream Marketeer’s objectives Events CRM1 Single view of customer Matrix computations Feature Selection Single Value Decomp.Associations Clustering Matching algorithms Scoring2 Increased Targeting Precision Big Data Personalized message Consolidation3 Improved Relevance4 Higher campaign profitability Complex Analytics Segmentation Forecasting Optimization Predictive algorithms Decision trees Linear Regression D I G I T A L M E D I A | Page 7 Matching
  • 8. Digital Media firms leverage Big Data analysis todeliver relevance and discover insights Right message. Right person. Right time. Right price. © 2012 IBM Corporation
  • 9. The Information to Audiences White Paper• IBM & Acxiom Sponsored Research – Research conducted by Winterberry Group – In association with the Interactive Advertising Bureau (IAB) – Interviewed 175 advertising and marketing thought leaders – Findings published at http://bit.ly/x5g1dW – Infographic on AnalyzingMedia.com at http://bit.ly/HYJUwb © 2012 IBM Corporation
  • 10. To What Extent Do You Believe The Following Solutions Will Be Focal Points of Your Future Data-Driven Marketing Activity? Not likely to be a Likely to be a focus of our future significant focus of our data utilization future data utilizationSource: Winterberry Group survey © 2012 IBM Corporation
  • 11. To What Extent Do You Believe The Following Solutions Will Be Focal Pointsof Your Future Data-Driven Marketing Activity? 1. Audience 1. Audience 1. Audience 2. Content 2. Content 2. Content 3. Channel 3. Channel 3. Channel 4. Yield 4. Yield Not likely to be a Likely to be a focus of our future significant focus of our data utilization future data utilizationSource: Winterberry Group survey © 2012 IBM Corporation
  • 12. 1. Solution: Audience Optimization(Ad Targeting) Business Effectiveness: Identifying customers Benefit and likely prospects through the integration of first- and third-party data sources Customer Low: Despite technology advances, Maturity Level uncertainty around the optimal approach to structured integration of data Core E-commerce Marketers, Digital Beneficiaries Advertisers, DSP, SSP, DMP, Lead Generation Portals, Publishers IBM Big Data Customers Long-Term High: The ability to define high- Opportunity potential audiences and facilitate Potential multichannel communication represents a fundamentally new way of marketing High Impact 1. Behavioral Segmentation Use Cases 2. Real-Time Ad Targeting 3. Social Data Analytics © 2012 IBM Corporation
  • 13. 2. Solution: Content Optimization(Website Analytics) Business Effectiveness/ Efficiency: Enabling Benefit “right message, at the right time, via the right content” targeting; drive content monetization via personalized, relevant and engaging content Customer Low: Content optimization is limited to Maturity Level usage analysis via SaaS based web analytics tools; disconnected experience Core E-commerce Marketers, Lead Beneficiaries Generation Portals, Publishers IBM Big Data Customers Long-Term High: The ability to analyze granular Opportunity level click-stream data and integrate Potential that information with actionable systems presents an opportunity to unlock greater business value than traditional SaaS based tools High Impact 1. Path analysis Use Cases 2. A/B Testing 3. Rich Media Engagement © 2012 IBM Corporation
  • 14. 3. Use Case: Yield Optimization Business Efficiency: Maximizing the value of Benefit available advertising inventory by identifying and “selling” high-value audiences across individual publisher properties Customer Low: Though technological advances are Maturity Level rapidly allowing audiences to be “sold” across distinct online media platforms, the use case demands true cross-channel yield optimization Core Publishers, SSP IBM Big Data Customers Beneficiaries Long-Term High: For a publisher community struggling Opportunity to effectively monetize content, the Potential identification and optimization of audience- centric inventory has the potential to deliver substantial revenue opportunities High Impact Use 1. Ad Inventory Yield Optimization Cases 2. Price optimization 3. Ad Inventory forecasting © 2012 IBM Corporation
  • 15. 4. Solution: Channel Optimization(Attribution Analysis) Business Efficiency/Effectiveness: Enabling the Benefit economical, value-oriented purchase of advertising media; understanding value of channels higher up in the funnel Customer Intermediate: Attribution is primarily Maturity Level driven by “last-click”; ability to harness and analyze data across different touch points in the funnel, across channels, is lacking Core Marketers (via Demand-Side Platforms), Beneficiaries CRM providers, Digital Agencies/Trading IBM Big Data Customers Desks Long-Term High: Meaningful media-buying Opportunity efficiencies are already accruing to Potential sophisticated users; coordinated use of channels and the targeted messaging/offer will deepen value High Impact 1. Media Mix Modeling Use Cases 2. Conversion funnel analysis 3. Search Engine Optimization © 2012 IBM Corporation
  • 16. To What Extent is Your Company Realizing Value From the Following Data Sources? We (or our clients) are We (or our clients) are realizing no value from realizing significant from these data sources these data sourcesSource: Winterberry Group survey © 2012 IBM Corporation
  • 17. Big data challenges Netezza and Unica customersask for help with• Regular data warehouses • Ordinary approaches to are challenged with dealing marketing don’t enable with big data marketers to scale  Nearly 70% of data  Too much IT effort to design warehouses experience database campaigns performance-constrained  Cannot scale to the number of issues monthly campaigns needed  Too much IT cost and DBA  Cannot be agile with creating effort to maintain ad hoc campaigns performance  Too difficult to make  Many of these ‘large’ marketing relevant, i.e. conventional data targeted messages to past and warehouses are simply current behavior of each holding pens. individual © 2012 IBM Corporation
  • 18. How Netezza and Unica help – on their ownIBM Netezza Appliance IBM Unica • Purpose-built analytics Marketing Interaction Optimization engine using integrated solution database, server & • Scalable: Deliver 30x as storage many marketing programs • Scalable: Low total cost • Fast: Reduce prep time for of ownership campaigns to 25 - 50% • Speed: 10-100x faster • Empowering: Put marketers than traditional systems in control & minimize IT • Simplicity: Minimal needs administration and tuning • Smart: Increase marketing • Smart: High-performance relevancy and success advanced analytics © 2012 IBM Corporation
  • 19. How Netezza and Unica help – together Common pairing over the years: Unica Campaign + Netezza Marketing interactions • Are executed as defined by 1 marketers 2 3 2 • Are refined with self-learning algorithms • Can also be refined by importing analytical output from IBM Netezza and Business Analytics solutionsMarketing data mart is key for Unica1. Stores customer + marketing data,2. Enables scalable performance because Unica can have queries executed inside the database to leverage database speed 19 © 2012 IBM Corporation
  • 20. Customer example:Large US department store retailer • IBM Netezza benefits – Campaign execution time faster by 300% – Complex campaigns accelerated by 600% – No longer dependent on vendor help to manage • IBM Unica benefits – Able to execute 40x times as many marketing programs as before – New marketing team members can easily be on-boarded and pick up“Very little to do for optimization. I have seen existing marketing nothing as easy as Netezza and Unica” programs - Marketing IT Manager: © 2012 IBM Corporation
  • 21. Customer example: Marketing Service Provider“The IBM Netezza data warehouse appliance helps us deal with the volume and captureclick stream transactions at the lowest level and aggregate it into a single customer view. Combined with IBM Unica® campaign management software, we can now help the brands quickly understand customer preferences and communicate the relevant messages in both online and offline campaigns.” -Russ Pearlman, Chief Information and Technology Officer, Merkle• Joint benefits at Merkle: • Regularly received a 70 percent reduction in processing time for complex marketing campaigns—decreasing time from hours to minutes • 25-90 percent revenue lift for one client through use of new analytic models • 50 percent decrease in end-to-end run time for marketing campaign execution—from sample to test to final version © 2012 IBM Corporation
  • 22. How Netezza and Unica help – togetherNew offering: Unica Interaction History (on Netezza) & Attribution ModelerCross-channel Interaction History Attribution Modeler • Provides singular Leverages statistical method to give database of marketing (partial) credit to “stimuli” based on: audience interactions • Combinations of promotions and channels their response data •Provides structured data model for cross- • Power law or polynomial channel attribution and distribution algorithms to reporting measure relationship •Supports customer interaction data via • Expectation-Maximization (E-M) IBM EMM and non- algorithm to iteratively tune IBM platforms model parameters (future) • Store Interaction • Enable complex statistical queries forIBM Netezza Appliance History = “Big Data” attribution with high speed on “Big Data” Benefit: With these capabilities, attribution is allocated more rationally than traditional methods allow © 2012 IBM Corporation
  • 23. Benefits of using Netezza and Unica together• Faster identification of key opportunities in customer data• Be quick-to-market with ad hoc campaigns to capture hot opportunities• Be agile with experimenting and optimizing campaigns• Faster execution of marketing campaigns• Ability to benefit from full, detailed customer data in designing campaigns• Less time spent on data management issues, more time for marketing © 2012 IBM Corporation
  • 24. Typical business results reported by EMM users More effective marketing: More efficient marketing: Improved customer value, More campaigns with the same loyalty & retention resources 5-15% increase is typical 2-5x increase is typical Higher online marketing ROI Reduced cycle time for 15x-25x increase is typical marketing efforts 40%-80% reduction is typical Higher campaign ROI Reduced marketing costs 15-30% increase is typical 20-40% reduction is typical Increased response rates Lower customer acquisition 10-50% increase is typical costs 25%-75% reduction is typical Increased order value Other business metrics 15-20% increase is typical revenue, profit, others vary by industry (assets under management, ARPU, #products owned, etc.)24 © 2012 IBM Corporation
  • 25. We appreciate your feedback. Please don’tforget to fill out your evaluation• Go to summitsmartsite.com from your mobile device or log on to SmartSite at any Kiosk at the event:• Select the Survey icon• Complete the surveys for the sessions you attended• Submit your feedbackThank you for joining us! © 2012 IBM Corporation
  • 26. Copyright and Trademarks © IBM Corporation 2012. All Rights Reserved. IBM, the IBM logo, ibm.com are trademarks or registered trademarks of International Business Machines Corp., registered in many jurisdictions worldwide.Other product and service names might be trademarks of IBM or other companies. A current list of IBM trademarks is available on the Web at “Copyright and trademark information” at www.ibm.com/legal/copytrade.shtml. © 2012 IBM Corporation