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IAB/Winterberry Group Member Webinar: "From Information to Audiences--The Emerging Marketing Data Use Cases"
IAB/Winterberry Group Member Webinar: "From Information to Audiences--The Emerging Marketing Data Use Cases"
IAB/Winterberry Group Member Webinar: "From Information to Audiences--The Emerging Marketing Data Use Cases"
IAB/Winterberry Group Member Webinar: "From Information to Audiences--The Emerging Marketing Data Use Cases"
IAB/Winterberry Group Member Webinar: "From Information to Audiences--The Emerging Marketing Data Use Cases"
IAB/Winterberry Group Member Webinar: "From Information to Audiences--The Emerging Marketing Data Use Cases"
IAB/Winterberry Group Member Webinar: "From Information to Audiences--The Emerging Marketing Data Use Cases"
IAB/Winterberry Group Member Webinar: "From Information to Audiences--The Emerging Marketing Data Use Cases"
IAB/Winterberry Group Member Webinar: "From Information to Audiences--The Emerging Marketing Data Use Cases"
IAB/Winterberry Group Member Webinar: "From Information to Audiences--The Emerging Marketing Data Use Cases"
IAB/Winterberry Group Member Webinar: "From Information to Audiences--The Emerging Marketing Data Use Cases"
IAB/Winterberry Group Member Webinar: "From Information to Audiences--The Emerging Marketing Data Use Cases"
IAB/Winterberry Group Member Webinar: "From Information to Audiences--The Emerging Marketing Data Use Cases"
IAB/Winterberry Group Member Webinar: "From Information to Audiences--The Emerging Marketing Data Use Cases"
IAB/Winterberry Group Member Webinar: "From Information to Audiences--The Emerging Marketing Data Use Cases"
IAB/Winterberry Group Member Webinar: "From Information to Audiences--The Emerging Marketing Data Use Cases"
IAB/Winterberry Group Member Webinar: "From Information to Audiences--The Emerging Marketing Data Use Cases"
IAB/Winterberry Group Member Webinar: "From Information to Audiences--The Emerging Marketing Data Use Cases"
IAB/Winterberry Group Member Webinar: "From Information to Audiences--The Emerging Marketing Data Use Cases"
IAB/Winterberry Group Member Webinar: "From Information to Audiences--The Emerging Marketing Data Use Cases"
IAB/Winterberry Group Member Webinar: "From Information to Audiences--The Emerging Marketing Data Use Cases"
IAB/Winterberry Group Member Webinar: "From Information to Audiences--The Emerging Marketing Data Use Cases"
IAB/Winterberry Group Member Webinar: "From Information to Audiences--The Emerging Marketing Data Use Cases"
IAB/Winterberry Group Member Webinar: "From Information to Audiences--The Emerging Marketing Data Use Cases"
IAB/Winterberry Group Member Webinar: "From Information to Audiences--The Emerging Marketing Data Use Cases"
IAB/Winterberry Group Member Webinar: "From Information to Audiences--The Emerging Marketing Data Use Cases"
IAB/Winterberry Group Member Webinar: "From Information to Audiences--The Emerging Marketing Data Use Cases"
IAB/Winterberry Group Member Webinar: "From Information to Audiences--The Emerging Marketing Data Use Cases"
IAB/Winterberry Group Member Webinar: "From Information to Audiences--The Emerging Marketing Data Use Cases"
IAB/Winterberry Group Member Webinar: "From Information to Audiences--The Emerging Marketing Data Use Cases"
IAB/Winterberry Group Member Webinar: "From Information to Audiences--The Emerging Marketing Data Use Cases"
IAB/Winterberry Group Member Webinar: "From Information to Audiences--The Emerging Marketing Data Use Cases"
IAB/Winterberry Group Member Webinar: "From Information to Audiences--The Emerging Marketing Data Use Cases"
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IAB/Winterberry Group Member Webinar: "From Information to Audiences--The Emerging Marketing Data Use Cases"

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  • -- The span of marketing “use cases” is broad, and the only way to really understand what’s working and what’s not was to poll the entire data ecosystem -- We set out to learn a few things: How mature is your deployment of each of these “use cases” (however you might define them)? How much value are you receiving from your efforts? To what extent do you expect that each of these will be part of your mainstream advertising/marketing strategy in the future?
  • -- In kicking off our efforts, we turned to a very senior-level panel of marketing data decision-makers -- Included in-person, telephone and online surveys with 176 senior decision makers… spanning advertisers/marketers, publishers, agencies, marketing service providers, technology developers and other folks who are using data or involved in the compilation and processing of information
  • -- We started, as you might imagine, by asking our panelists to assess a very wide range of potential use cases AS THEY’RE DEPLOYED TODAY—essentially, tell us how intensely they’ve been focusing on almost every use case we had been hearing about -- What you see here, simply, is that there is pretty substantial interest in a wide range of use cases. If we assume that every instance that scored “3” or higher is rising in interest, then at least 10 major data applications are growing in demand, with at least half of those attracting substantial resources
  • -- Next: we asked the same panelists to take a look into the future and guess which use cases they expected would grow in importance -- For the most part, the lineup of “priority” use cases remained the same… with one exception. Panelists said OFFER OPTIMIZATION would grow substantially in importance… -- And when you think about it, that use case—which really speaks to advertisers’ ability to imbue their online ads with very specific, targeted, relevant content on offers that are personalized to the consumer or cohorts of consumer—really does speak to the great potential of online advertising: the ability to target not just on the basis of MEDIA…. or PRODUCT…. or even “AUDIENCE”… but at the granular intersection of all three of those -- It’s worth drilling down more deeply into the “big four” use cases we identified
  • -- The first use case is something of a hybrid of the ad and offer targeting cases we asked about, and is very much at the heart of the innovation efforts in the online marketing world today -- All about identifying actionable audiences from disparate data sets, including first- and third-party resources -- Ultimately, the goal is to reach and ENGAGE these audiences (and MICROaudiences, really) across media, using online behaviors as the baseline -- The challenge, though, is in identifying and maintaining a steady dialogue… given limitations with respect to tracking and specific user identification. Does an IP address always constitute a specific “audience” member? How do we track these audiences across “traditional” media? -- These are significant challenges. And even though great investment and effort is going into this use case today, it’s why maturity remains very low
  • -- The second use case is closely related to the first one, but adds an element of audience DECISION-MAKING to the mix -- Channel optimization is all about developing strategies that seek to deploy the “right media, at the right time… to the right audience,” irrespective of the actual message -- Part of this is and ought to be dictated by the user (through preferences). And part of this resides in true marketing “science,” through predictive preference modeling -- But on both counts, the industry is still immature. Preference centers are common in email marketing, for example… and beginning to gain in prominence on the display side (especially moreso now that the industry and government are coalescing around a series of standards that provide for consumer choice over their “trackability”), but true MULTICHANNEL optimization is a long ways off -- The potential, though, is very high. And it will require deep data integration (and a lot of historical attribution/performance data) in order for this to grow
  • -- The third use case is the only one specific to PUBLISHERS, rather than advertisers… and it speaks to the integration of data to drive the value of individual media units, essentially allowing publishers to set optimal pricing for their ad units in alignment with the potential of the audiences beneath them -- The real value here is in being able to show true value for an ad unit, which has been elusive for centuries. (John Wanamaker’s: “I know half of my advertising is wasted…”) -- A brewing debate here continues. Between data and technology constituencies who see this as driving substantial efficiencies to the way that ads are sold… to current-state ad sales teams who see this as a threat to their ability to package large ad units for sale -- This is a case where the potential is likely high, but a substantial educational and re-engineering effort will be needed to align the interests of buyers and sellers
  • -- The final “big picture” use case is really the flip-side of yield optimization… and that’s the buying of media on the basis of likely AUDIENCE through efficient, targeted media platforms -- This is the one case where maturity levels have finally grown to an “intermediate” point… and that’s because, in simple terms, buying “targeted” media has been happening in one form or another for many years. What has emerged over just the past few, though, has been a new array of technologies (like RTB and demand-side platforms) that essentially allow for the automation of very manual, time-consuming purchase decisions -- The great potential here is in continuing to improve the quality/effectiveness of ad TARGETING… and in exporting these tools to a variety of other media to deliver seamlessness across the advertising effort -- At the heart of that, as in the case with the other use cases, is identifying which data elements really add value…
  • -- And when we asked panelists, it wasn’t surprising to see that FIRST-PARTY resources deliver the most value. Especially those that provide very tailored detail into target audiences and their past purchase behaviors and likely needs/wants as expressed through the social graph -- The challenge for the industry will reside in deriving value from the vast array of THIRD-PARTY resources which are in tremendous supply and we know can add substantial value if integrated appropriately into a holistic analysis
  • -- That thinking was expressed, too, when we asked what’s driving greater investment in data: the need to make better use of proprietary data, and the need to export those insights across a range of other media applications -- Ironically, that “multichannel integration” point could just as well speak to the potential impact of third-party data
  • -- Foremost among priorities, though, is the need for data to be accurate, recent and insightful. Specific priorities here will vary substantially across vertical markets, though. What’s “recent” or “insightful” for an auto campaign, for example, will vary substantially for a campaign for CPG products… the lifetime value of the customer, timing of the message, and depth of supporting detail all differing in potential impact
  • -- Ultimately, though, progress on all of the above fronts will require a new effort to make data a centerpiece of the multichannel advertising strategy
  • Fade from silos to 4 different pillars holding up marketing infrastructure
  • Fade from silos to 4 different pillars holding up marketing infrastructure
  • Transcript

    • 1. From Information to Audiences:The Emerging Marketing Data Use CasesJonathan Margulies March 1, 2012Managing Director
    • 2. Thanks to Our Sponsors!
    • 3. Winterberry Group: Helping Advertising, Marketing, Media andInformation Companies Grow Value Strategic Consulting • Corporate Strategy Development • Market Intelligence • Marketing Process Optimization • M&A Transaction Diligence Support • Investment Banking Services, through
    • 4. Our AgendaFrom Information to AudiencesWhat inspired the research?What role is data playing indigital advertising today?How should we be thinkingabout our “data strategy” forthe future?
    • 5. In the Beginning, There Were Subscriber Files… Name: Addre ss: H. Catalogus(0-~1980 A.D.)
    • 6. … Which Begat Demographic “Selects,” Data Cards and the First TrueCommercial Data Models… NAME ADDRESS PHONE GENDER AGE INCOME H. Catalogus H. Mailinglistus (-~1980 A.D.) (~1980s)
    • 7. … Which Begat Modeling, Cluster Segmentation, Cooperative Databasesand—With the Arrival of the Internet—E-mail Data… H. Catalogus H. Mailinglistus (-~1980 A.D.) (~1980s)
    • 8. … Which, In Concert with the Growth of “CRM,” Gave Rise toSophisticated Database Management, CDI and MDM Infrastructures…“Customer File”: Contact Info, Persistent Identifiers CRM, Demographics “Prospect File”: Demographics, Credit Scores Interactions Logs Transactional / Loyalty Records “Single Source of the Truth” Public Records Self-Reported “Intent” Data Mr. John Q. Customer One Response Rate Way H. Analyticus Boston, MA 01234 (~1990-2000s)
    • 9. But “Evolution” Isn’t Always Painless; The Emergence of Digital ChannelsHas Brought With It a Deluge of New Data Sources Direct Mail Call Centers Catalogs Retail Transactions Print Publications Broadcast Outlets Email
    • 10. And Those Various Channels Generate—and Rely Upon—a Range ofInformation Types Transactional added from Psychographic and behavioral purchase records, cooperative compiled from surveys, analytical databases models Offline Social compiled from Providers social sites, blogs, Geo- Social Sites / sharing sites, Demographic Offline Online compiled from Compilers Providers ? publishers, Online Data Types: databases and • Registrationsother third parties • Cookies (Flash) / browsing activities Publisher Portals / • Social networks Online • Online purchase data s Compilers • In-market purchase intent Artwork Source: David Harbaugh, Harvard Business Review
    • 11. … And So “Traditional” Database Infrastructures Are Being Asked to Support Vast New Streams of Unstructured Information ? Behavioral (Clickstream) Intent (Opt-In/Registered and Inferred) Web Analytics (Geo-/ Technographic)“Customer File”: Contact Info and Demographics “Prospect File”: CRM Demographics, Credit Scores Transactional / Loyalty Records Public Records H. Digitalus Self-Reported “Intent” Data (~2009-Today)
    • 12. But The Integration of “Traditional” and “Digital” Data Poses a Set ofUnique Challenges, Owing To Discrepancies Between… Known Names/Addresses… “Batch” Processing… m er n Q. Custo Way Mr. Joh onse Rate esp One R , M A 01234 n Bosto … and Anonymous IP Addresses … and Real-Time Deployment Campaign-Driven Execution… Single-Channel Focus… … and Continuous Targeting … and Integrated Marketing
    • 13. Today, The “Use Cases” for Marketing Data Differ Substantially AcrossAddressable Media
    • 14. Our AgendaFrom Information to AudiencesWhat inspired the research?What role is data playing indigital advertising today?How should we be thinkingabout our “data strategy” forthe future?
    • 15. Our Panel: Senior Thought Leaders Across the Data Ecosystem “Which Best Describes Your Job Role / Function?”N=176Source: Winterberry Group survey
    • 16. “To What Extent Are the Following Use Cases Focal Points of Your CURRENT Data-Driven Marketing Activity?” Not a focus of our A significant focus ofSource: Winterberry Group survey current data utilization our current data utilization
    • 17. “To What Extent Do You Believe The Following Use Cases Will Be Focal Points of Your FUTURE Data-Driven Marketing Activity?” Not likely to be a focus Likely to be a significantSource: Winterberry Group survey of our future data focus of our future data utilization utilization
    • 18. Use Case: Audience OptimizationIdentifying customers and likely Fundamental Effectiveness: Identifying customersprospects through the integration of Advertising and likely prospects through therich (though disparate) data sources; Benefit integration of first- and third-party datamanaging cross-channel marketing sourcesexecution with the goal of engagingthose audiences strategically—and in Maturity Level Low: Despite technology advances,accordance with consumers’ preferred uncertainty around the optimaladvertising media. approach to structured integration of data Core E-commerce Marketers, Digital Beneficiaries Advertisers, Lead Generation Portals, Publishers (for traffic acquisition) Long-Term High: The ability to define high- Potential potential audiences and facilitate multichannel communication represents a fundamentally new way of marketing
    • 19. Use Case: Channel Optimization Fundamental Effectiveness/ Efficiency: Enabling “right Advertising message, at the right time, via the rightEnabling “right message, at the right Benefit media” targeting; expanding the role oftime, via the right media” targeting;expanding the role of consumers in consumers in choosingchoosing optimal/preferred optimal/preferred communicationscommunications media. media Maturity Level Low: Traditional marketing efforts are channel-specific; “channel agnostic” internal alignment that most marketers have not yet undertaken Core E-commerce Marketers, Digital Beneficiaries Advertisers, Lead Generation Portals, Publishers (for traffic acquisition) Long-Term High: Media-agnostic communication Potential strategies will enhance consumer engagement (through dialogue and purchase behavior)
    • 20. Use Case: Advertising Yield Optimization Fundamental Efficiency: Maximizing the value of Advertising available advertising inventory byMaximizing the value of available Benefit identifying and “selling” high-valueadvertising inventory by identifying and“selling” high-value audiences across audiences across individual publisherindividual publisher properties and properties and delivery mediadelivery media. Maturity Level Low: Though technological advances are rapidly allowing audiences to be “sold” across distinct online media platforms, the use case demands true cross-channel yield optimization Core Publishers Beneficiaries Long-Term High: For a publisher community Potential struggling to effectively monetize content, the identification and optimization of audience-centric inventory has the potential to deliver substantial revenue opportunities
    • 21. Use Case: Targeted Media Buying Fundamental Efficiency/Effectiveness: Enabling the Advertising economical, value-oriented purchase ofEnabling the economical, value- Benefit advertising media; delivering targetedoriented purchase of advertisingmedia; delivering targeted messages to messages to audiences across a diverse,audiences across a diverse, actionable actionable range of channelsrange of channels. Maturity Level Intermediate: “Real-time bidding” (RTB) tools have matured substantially over the past few years, and are in common use by enterprise marketers across verticals Core Marketers (via Demand-Side Platforms), Beneficiaries Digital Agencies/Trading Desks Long-Term High: Meaningful media-buying Potential efficiencies are already accruing to sophisticated users; coordinated use of these applications and the targeted messaging/offer tools will deepen value
    • 22. “To What Extent is Your Company (Or Your Clients) Realizing Value From the Following Data Sources?“ We (or our clients) are We (or our clients) areSource: Winterberry Group survey realizing no value from realizing significant from these data sources these data sources
    • 23. “To What Extent Do You Believe Each of the Following Are Driving Deeper Interest/Investment in Marketing Data?” Not a focus of our A significant focus ofSource: Winterberry Group survey current data utilization our current data utilization
    • 24. “To What Extent Do You See the Following Attributes Driving the Underlying Usefulness of a Marketing Dataset?” Not at all important in Critically important driving the value of a in driving the valueSource: Winterberry Group survey data set of a data set
    • 25. “To What Extent Do You Believe Each of the Following Are Inhibiting Interest/Investment in Marketing Data?” Not inhibiting interest / Substantially inhibitingSource: Winterberry Group survey investment in interest / investment in marketing data marketing data
    • 26. Our AgendaFrom Information to AudiencesWhat inspired the research?What role is data playing indigital advertising today?How should we be thinkingabout our “data strategy” forthe future?
    • 27. The Complexity of Today’s Advertising and Marketing Programs HasDriven Many to Re-Examine their Internal Operating Silos What’s at stake? Holistic Marketing • Data Process Management • Strategic Resources/Authority • Creative Assets Effective People • Investment Capital • Knowledge/Expertise Management Brand Mktg. Digital Direct Mktg. LoBs Sales Fin. Int’l Mktg. IT
    • 28. Requirement: Improved Operating Structures Holistic Marketing Efficient, Effective Process Management Ad./Mktg. Execution Strategic Effective People Management Utilization Process People Technology of the Design Mgmt. Deploy. Supply Chain
    • 29. Requirement: Rules-Driven Integration of Disparate Data Sets Anonymization First-Party Aggregation Third-Party
    • 30. Requirement: A Strong Network of Data-Centric Technology and Service PartnersReal-Time Media Buying Asset ManagementAd Serving Scheduling/RoutingDistributed Mktg. Mgmt. Ad OperationsBudgeting Business Rules Mgmt.Creative Production Creative OptimizationYield Management Data ProcessingAd Verification Web AnalyticsCampaign Management
    • 31. Requirement: Marketing Data Governance PII vs. Non-PII External & Self-Regulation Transparency Marketing Use Guidelines
    • 32. “To What Extent Do the Following Reflect Your Long-Term (2013 and Beyond) Priorities for Improving the Usefulness of Marketing Data?” Improving attribution across channels 4.1 Integrating across different data collection… 3.9 Improving access to granular audience… 3.9 Identifying dedicated data staff and building… 3.9 Improving automation abilities 3.9 Improving data hygiene and quality assurance 3.7 Linking data inputs (and the appropriate rules… 3.7 Extracting greater value from the use of data… 3.7 Simplifying the processes by which third-party… 3.6 Reducing latency / processing data more rapidly 3.5 Storing / warehousing data more efficiently 3.4 Clarifying regulatory barriers to data utilization 3.3 1 2 3 4 5 Not a priority for us Very important priority forSource: Winterberry Group survey (or our clients) in the us (or our clients) in the long term long term
    • 33. Thanks to Our Sponsors and Contributors!Jonathan MarguliesManaging Directorjmargulies@winterberrygroup.com(212) 842-6031www.winterberrygroup.com/ourinsightswww.iab.net/marketingdatause

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