The Transformative Potential of Programmatic Buying

Transcription

1 The Transformative Potential of Programmatic Buying 4A s White Paper Section 1: Business Transformation Data management platforms (DMPs) and programmatic are transforming the core of the media business through innovation in ad tech as well as disruption of the standard economic model. This transformation has been gradual, with significant acceleration in two critical directions. The first is in the construction of systems that generate new forms of business intelligence based on audience data, and the second is the way in which media buying is transacted between publisher and advertiser. These trends are converging on a new media economic model based around the programmatic value chain and its ability to provide linkages with actual product offerings, revenues and technical innovation. Key elements of that valuechain include: (a) audience data, (b) technology and trading, (c) content and publishing, (d) newly enabled media channels and (e) sales data for closed-loop measurement and return on investment calculation. Audience data s transformative potential is in the aggregation of vast amounts of media intelligence generated by audience interests, intents and actions across paid, owned and earned channels. Linking audience behaviors with first-party customer data provides a truly universal view of both today s consumers and potential future consumers. Programmatic trading platforms allow business to reach audiences at scale and, therefore, create unique business value for the both the demand and the supply side of the equation. Content publishers are providing access to quality audiences, pushing programmatic content across devices, and programmatically enabling more interactive channels, including the emerging Internet of Things. Finally, analytic solution providers are creating unique value propositions by creating attribution solutions, measurement frameworks and in-depth understanding of the consumer journey. 1 It is important to understand that programmatic and data management platforms sit at the core of the current business transformation. Such a momentous shift, requiring a change in both technological implementation and business model, means that this transformation is and remains very much a work in progress. Programmatic s clearly accelerating trend lines, however, are a clear indication of its place at the core of media buying systems of the future. In other words, agencies and advertisers are starting to understand clearly the potential impact such a shift can have on their businesses. There are also risks inherent to trying to harness the fire hose of data generated by marketing activities in the digital world. Massive amounts of data can create a deluge that can cause confusion and lead to incorrect or insignificant findings if not managed properly. The ideal state of total data capture can cause serious operational issues when combined with non-agile technology, which can lead to wasted 1 (Edelman, van Bommel, & Ungerman, June 2014) McKinsey Report. 1

2 man-hours and render systems functionally paralyzed. Resource management around time, space and behavior for systems deployment is key to balance upside with investment. Section 2: Overview A recent emarketer report, US Programmatic Ad Spend Tops $10 Billion This Year, to Double by 2016, 2 is the latest in a series of indicators that programmatic technology is transforming traditional media economics. This paper seeks to deliver the media agency perspective of this transformation and discuss the importance of data management within audience buying platforms. Three objectives inform the content of this paper: (1) To provide a holistic understanding of programmatic buying techniques and how media agencies should position themselves within the changing landscape. (2) To advise on how, when and why programmatic technologies and data management systems should be used to optimize and deliver on an advertiser s goals and objectives. (3) To explore the current and future state of advertising, including technological evolution, cultural and technical obstacles in the marketplace, new channel emergence, changing consumer perceptions of how their data is used, complexities of a fragmented environment, and workflow impact for planning, tracking, media delivery and measurement. Programmatic adoption is being driven by a number of causes. 3 The following sections will elaborate on five areas of discussion: (a) Data Management Platforms, as we understand them today, (b) Programmatic media concepts, general and specific, as pertaining to agencies, (c) Audience Data and their differentiating elements, (d) DMP & Programmatic interplay, (e) Forward-looking recommendations on how to proceed in the programmatic future. 2 emarketer Editorial, 2014, refer to Figure 1 on next page. 3 Refer to Figure 2 on next page. 2

3 Figure 2:Primary sources of programmatic buying Figure 1: US Programmatic Ad Spend Section 3: Data Management Platforms First, a simple definition. A data management platform (DMP) is a consolidated data warehouse, with data capture capabilities (via tagging) and fast, possibly real-time access, analysis and syndication integrations of valuable data to optimize the media decision-making process. For advertisers, a clientside DMP can incorporate some or all parts of their advertising and marketing data, some or all customer information, and additional third-party audience information, however, it lacks the valuable addition of having the broader cross-fertilization of data than an agency can offer. While this view of the DMP is typical within the industry from a marketer s point of view, agencies view the DMP as a unified source for delivering and optimizing messages to target audiences and measuring digital campaign effectiveness through relevant marketer business KPIs. DMP, as a result, can also be a source for gathering and building new intelligence as opposed to aggregating existing intelligence. 4 An agency DMP also affords the ability to connect online to offline data sets as well as tie digital campaign exposure to customer behavior, all of which opens new methods to analyze campaign efficacy. Despite the potential for intelligence creation, 5 DMP adoption at the agency level has not yet reached its full potential. Some of the hurdles for both agency and client DMPs include the need for significant investment, management of a complex technology layer, log-level data query complexities, access to 4 Bidel, Boosting First-Party Data Effectiveness with DMPs, Data Intelligence: The term can be defined as using data to make better decisions that would not be otherwise possible. 3

4 audience information and privacy concerns. Additionally, stand-alone DMPs and vendors that provide such access and service are positioning themselves to provide audience targeting and optimization directly to marketers or media platforms. That said, proprietary technology platforms, bilateral data exchanges, 6 and first-party agreements can pose some restrictions for stand-alone DMPs to optimize audience targeting. Lack of integration or absence of various sets of audience data, measurement solutions and programmatic media sources via demand-side platforms (DSPs) can constrain the optimal performance of any advertiser s campaigns. 7 The key value-add to the DMP data ecosystem is first-party data generated by an audience s interaction with an advertiser s paid, owned and earned media activity. Audience segments and insights derived from such data inputs are the ability to: Boost media performance in terms of achieving efficiency and precision in reaching KPI goals. Sociodemographic, behavioral, interest and intent attributes of users within the first-party environment can help optimize media and target audiences with relevant messages. Elusive offline customer engagement and sales data can also open the door to new, more relevant business KPIs. Create unique economic opportunities by integrating the various data exhausts 8 given off by marketing activity to better understand customer lifetime value, long-term brand engagement and potential cross-selling opportunities. A fundamental aspect of any DMP is its ability to enable segment-level targeting as a part of an audience buy, summarized neatly as the ability to reach the right audience in the right place at the right time with the right message. Audience buying has been almost universally adopted by the industry and incorporated into almost every media plan, execution and optimization. To validate the use of these tactics, a good DMP must empower agencies and marketers to act on these audiences effectively with measurable outcomes. The challenge is that most DMPs, agencies and marketers are still defining what those successful outcomes look like, particularly towards finding the right audience, most often defined as the most valuable component. Part of the challenge of leveraging/operationalizing a unified DMP stems from the fact that rights to audience data are in a state of fragmentation across an ecosystem of intelligent systems. 9 For example: Advertisers own the DMP instance with known customer profiles, communication channels and lifetime values. Measurement companies own audience demographics. 6 Bilateral data exchanges: Data exchange agreements (deals, prices, inventory, API) made between two parties, with specific terms and conditions. 7 emarketer published a comprehensive industry view highlighting the use of DMP-derived audience data to inform media buying. (Fisher, Using Big Data to Power Marketing Performance, 2013). 8 Data Exhausts: Broadly defined as technology, application processing and integrations between data providers and owners. 9 Refer to Figure 3 on next page. 4

5 Agency holding companies own reachable audiences by media channel. Analytics companies own audience behaviors online and offline outside the purview of the advertisers and agencies. Media platforms own social, mobile and location data. Figure 3: First-party and Third-party data are crucial for audience targeting The challenge of fully leveraging the unification of these disparate datasets is one that can only be solved by developing necessary data exchanges, promoting participation in the data value-chain, justifying investment costs, proving out return on investment for data systems and alleviating privacyrelated legal and regulatory issues around consumer protection. Efficiency of a client-owned DMP will depend on three factors: (a) agile technology stack, (b) media planning and execution capabilities and (c) resource planning. While it is possible for such a DMP to develop robust solutions around all data components listed earlier, 10 the second and third factors are better suited for the agencies and holding companies. Media planning, buying and execution in an Omni channel environment are what agencies can offer to complement a client DMP. For a long time, agencies and their holding companies have gained tremendous efficiency in the marketplace for allocating resources, channel and talents. The most optimized way a client can understand the value of a client-side DMP is to combine the three factors holistically and identify the proper mix to execute any marketing and advertising campaign. Perhaps the most critical challenge with regard to adopting and deploying a unified DMP is the decision process around how and where to invest, adopt and maintain the (most) appropriate technology stack. Global agency holding companies are gradually moving towards building unified tech stacks to fulfill 10 Refer to Figure 3. 5

6 advertiser demand for holistic media measurement and insights tools at an aggregate level to justify media investment. The notion of audience target, time, place and message is still a work in progress, particularly in terms of measurement and effectiveness. While programmatic targeting capabilities have improved substantially over the course of the past two years, the measurement of channel effectiveness, proper attribution and holistic optimization are not fully developed. Section 4: Programmatic Landscape Programmatic has been the advertising industry s most discussed, documented and presented catchphrase. Originally describing a technological process, programmatic has evolved into a state-ofbusiness that has attracted immense investment, development and media spend. The programmatic advertising ecosystem is a global thing, involving many advertisers, agencies, partners and vendors engaging to bring unique value to the media landscape. 11 Again, a simple definition. Programmatic advertising is an automated, technology-driven method of buying, selling or fulfilling advertising. Although most commonly associated with digital display, it can also be used to procure search, , streaming radio and even TV inventory. 12 For the purposes of this paper, the current section focuses on understanding programmatic within the context of data management and touches on the following concepts: A fragmented addressable environment devices, channels and touch points pertaining to programmatic delivery of media Programmatic buying and selling exchanges, Deal IDs and programmatic fundamentals relating to common standards and protocols for executing media meeting the demand and supply Platforms and systems capturing, storing, ingesting and analyzing data sourced from social behaviors (e.g., Facebook, Twitter), demographics and household data (e.g., Experian, Acxiom), purchase data (e.g., Kantar Shopcom, Cardlytics), and client inputs (e.g., site analytics, CRM databases) Programmatic marketplace models inventory, scale, reach and audience quality of open marketplaces, programmatic networks, private marketplaces and programmatic direct relationships. Programmatic is necessary for core DMP services to activate audiences effectively. In a fragmented media ecosystem, the DMP can enable unified insight into a user s journey based on exposure, actions and connected behavior. This can only happen, however, if the DMP and programmatic technology are part of the technology piping. The DMP is a vast reservoir of user data that must be connected to both data and media streams to facilitate delivery of value. 11 Refer to Figure Fisher, 2014 Programmatic Advertising Forecast,

7 The Deal ID is an important evolution within the programmatic ecosystem. 13 Forrester defines the Deal ID as a real-time bidding (RTB) parameter that captures the post-negotiation details of an ad program within a private marketplace environment, including: pricing, pacing and frequency capping, priority, placement, targeting, and custom elements. It is an automated key that communicates these details and allows the transaction to take place. Deal ID standards are still a work in progress, requiring refinement and agreement between suppliers (publishers and supply side platforms) and demand generators (advertisers, agencies and DSPs). Currently, Deal IDs are concerned with setting commercial rules for access to inventory. Future rules will have to better align based on key values to the demand side such as the delivery of specific audiences against only viewable inventory in real time. A programmatic platform that uses agile technology, proprietary knowledge and access to unique audience intelligence to enrich a robust qualified user pool stands to succeed. Recent surveys among the C-suite indicate that many of them lack full understanding of the value of programmatic for digital media buys mainly due to complexity, lack of transparency and the need for a constellation of technology providers with acronyms like DSP, SSP, DMP, etc. 14 The challenge is understandable. However, advertisers are increasingly shifting towards programmatic, knowing the future of media will rely on programmatic. It is clear that the sheer complexity of digital media buying process and access to qualified audiences across different platforms requires automation A good primer on Deal ID is Bidel, Brief: Embrace Deal ID Now to Support Direct Sales and Programmatic Growth, Nail, Media Buying s Evolution Challenges Marketers, See Figure 4 on next page. 7

8 Figure 4:Programmatic Share of Digital Media Spend Traditionally, programmatic has been associated with real-time buying (RTB), which itself is viewed exclusively as the access of remnant inventory through open exchanges. These limited and incorrect views are being rectified as more robust marketplaces such as private deals, premium markets, closed auctions, proprietary exchange platforms and transparent, accountable quality audiences have become the primary features of the ecosystem. The past four years have seen programmatic evolving to address some of the core functionalities of the media industries: Ad networks are able to solve publisher fragmentation issues and provide new sales channel, but proliferation of numerous networks and buying and selling between networks leads to issues of duplications of reach and overtargeting Ad exchanges, to a degree, can resolve the ad network proliferation, but have issues with quality audience and room to allow for differentiation among buyers 8

9 DSPs and SSPs solve differentiation issues and allow buyers and sellers to start creating their own inventory access, targeting rules and reporting Specialty DSPs and SSPs (video, native) solve lack-of-format specific capabilities but create another layer of technical complexities for market participants to integrate o DSPs and SSPs have allowed any market participant to replicate pieces of an exchange or ad network o Common issues of solving fragmentation, inventory transparency, safety, etc., still exist but point to solutions, and industry groups are slowly addressing them Some challenges remain within the programmatic, but one particular issue needs immediate focus. It is the seamless ability of programmatic to provide information needed for the buyers and sellers to forecast for planning efficiency. Programmatic is fast evolving to include other channels such as addressable TV, many forms of digital video delivery, digital print and out of home and, most importantly, any form and format of mobile. While technology plays a key role for programmatic to fully transform the landscape, it is not far from being inevitable, all for the same reasons we have just discussed. Section 5: DMP & Programmatic Linkage Meaningful access to Omni-Channel data is critical for a good DMP, particularly broadcast data. Currently, it is challenging to map such multichannel user paths within user-level DMP analysis, a practice that has been the dominion of channel-level econometric modeling. Data siloing 16 due to technical roadblocks, commercial restrictions and privacy issues has been the primary obstacle in creating a user-level data store that could solve the overarching marketing mix. Alternatives have been developed, but these are mostly ad hoc solutions with a high degree of fuzziness. For example, most holding companies put a statistically based data-spine at the center of a modified ad-tech stack to solve media optimization and broader channel attribution and marketing mix strategies. In theory, programmatic and DMP can be necessary and sufficient for good reasons and be a valuable investment to advertisers, agencies and publishers. The reality, as it stands today, is not close to what I perceive to be optimal. While I try to highlight the ingredients for media and advertising to glean value and efficiency by combining programmatic and DMP, the same set of ingredients commercial, opportunities, data silos and privacy due to the nature of the current state of business, poses a hurdle to reconcile towards a unified platform. 16 Data Silo: A common term defining data assets that reside in isolated environments due to reasons pertaining but not limited to privacy, institutional legality, legacy platforms and systems and high cost of adoption. 9

10 Section 6: Conclusions If data is the new oil of the digital economy, then it is incumbent upon the industry to build the necessary infrastructure to both extract it as well as turn it into a valuable source of marketing energy. In the case of extraction, the role and control of the DMP in any advertiser s business must be defined and implemented clearly to make the media dollars of yesterday go farther today. A universal view of the consumer and their behaviors across online channels as well as in the real world is within sight. Advertisers and their agencies must align and work with technology providers to make this a reality. In a broad sense, the more relevant and high-quality data added to the DMP and the more connections the DMP has to other systems, the more valuable the DMP becomes. In the case of marketing transformation, programmatic will continue to be the engine of change that makes this consumer data actionable. Advertisers and their agencies must align with technology providers here, as well, to promote greater visibility into the new infrastructure being created. Accountability, trust, quality and value are four key pillars on which the foundation of a programmatic future must be laid. List of Figures Figure 1: US Programmatic Ad Spend 3 Figure 2: Primary sources of programmatic buying 3 Figure 3: First-party and Third-party data are crucial for audience targeting 5 Figure 4: Programmatic Share of Digital Media Spend 7 10

11 Works Cited Bidel, S. (2013, January 10). Boosting First-Party Data Effectiveness with DMPs. Forrester Research. Bidel, S. (2014, November 11). Brief: Embrace Deal ID Now to Support Direct Sales and Programmatic Growth. Forrester Research. Bidel, S., & Joyce, R. (2014, December 29). Maximizing Media ROI with a Customer-Centric Approach. Forrester Reports. Chango & Brand Innovation. (2014, Dec). Programmatic Pulse. New York, NY, USA. Edelman, D., van Bommel, E., & Ungerman, K. (June 2014). Digitizing the Consumer Decision Journey. New York: McKinsey & Company. emarketer Editorial. (2014, October 16). US Programmatic Ad Spend Tops $10 Billion This Year, to Double by emarketer. Fisher, L. T. (2012, December). The State of Cross-Platform Ad Measurement. emarketer. Fisher, L. T. (2013, May). Using Big Data to Power Marketing Performance. emarketer. Fisher, L. T. (2014, October) Programmatic Advertising Forecast. emarketer. Greene, M. (2011, January 11). Audience Data Management: A Must-Have for Publishers. Forrester Research. Joyce, R. (2014, December 2). The Future of Digital Media Buying. Forrester Reports. Kihn, M. (2015, January 6). Collision Course: Ad and Marketing Tech. Retrieved from Ad Exchanger: Merlivat, S. (2014, October 14). North American Online Display Advertising Forecast, 2014 to Forrester. Nail, J. (2013, October 10). DMPs Deliver Value to Early Adopters in a Nascent Market. Forrester Research. Nail, J. (2014, February 18). How Software Is Eating Video Ads and, Soon TV. Forrester Research. Nail, J. (2014, May 22). Media Buying s Evolution Challenges Marketers. Forrester. Norman, R. (2014). Buying by Numbers. Atticus, O'Connell, J., & Greene, M. (2012, September 7). The Future of Digital Media Buying. Forrester. O'Connell, J., & Overby, C. S. (2012, December 6). Scale Success with Programmatic Multichannel Media. Forrester. Orsini, P. (2014, September). The Biggest Ad Spenders Look to Automate Buys, but on Their Terms. emarketer. Schlickum, C. (2014). Media is More Than a Commodity. Atticus, Skinner, R. (2014, November 24). Content Marketers Share Data with Other Brands to Close the Loop from Interest to Sales. Forrester Research. 11

12 Sridharan, S. (2012, May 15). It s Time to Bridge the Audience Data Management Divide. Forrester Research. Zwillenberg, P., Field, D., Rich, N., Rogers, K., & Cohen, S. (2014). Adding Data, Boosting Impact: Improving Engagement and Performance in Digital Advertising. Boston, MA: Boston Consulting Group. 12