In 2012, we saw the incredible power of data to drive elections, and to help enable the next generation of hyper-efficient marketing. This year promises to fully demonstrate how big data, small data or just the right amount of data is driving online advertising success for brands and marketers. Right now is a great time for a gut check to reassess your strategy and audit how you’re managing the process. To help you along, here is an overview of how to look at your data management platform (DMP) and what you could (and should) be doing to make the most of your investment. We need to consider what the top agencies and brands are doing and follow their example. The leading players are leveraging data management platforms to address three specific purposes: 1) To enable marketers to integrate audience, contextual and geographic data across a company’s multiple touchpoints; 2) To enable a company to segment their audience and take immediate action on these segments; 3) To enable a company to discover new insights about their audience. Those who want to lead and not follow in the new techno-marketing era must ensure they are able to deliver on these abilities and they must ensure that their DMP is helping them get there. Integration To achieve the first purpose of integration requires a robust set of import capabilities from real-time pixels (also known as Tag Management) as well as batch files. Once the data is on-boarded, the system allows a marketer to transform the information, by bucketing transaction values from a shopping cart into a set of marketer-defined buckets. Transforming the incoming data enables downstream processes of segmentation and targeting to be faster and easier by standardizing the raw event data into more usable information. Segmentation and Action To achieve the second purpose, a DMP requires an easy-to-use interface for manually defining specific audience segments, such as combining third-party demographic information with first-party registration, activity and customer value information. These segments should be expandable through lookalike modeling to find similar audiences that are likely to behave in a similar manner to the “seed” audience segment. Many DMPs stop here. However, it is important to have real-time feedback to two additional criteria before generating the audience. First is the audience size. Marketers do not have the resources to craft specific campaigns to only a handful of consumers. Accordingly, a DMP should provide the feedback to the total addressable market that matches the segmentation rules both in terms of unique user counts and in terms of frequency of exposures at given price points. Even if a segment of users is large enough to warrant a campaign, a DMP should provide insight into the cost of reaching this audience with an increasing frequency of exposure. Stand-alone DMPs that do not have tight integrations into action-taking systems, such as Web site content management systems or ad-serving systems, are often unable to provide this feedback. Another important aspect of defining the audience segment, especially for digital channels, is the latency from creating the segment to being able to target this segment. Since the anonymous user identifiers used to target segments frequently change, to increase the latency between defining a segment and synching this information with an action-taking system would lead to a higher overstatement by the original forecast of available unique users. The lack of accurately understanding the number of unique users, the cost of reaching them in the desired context and the frequency are what we call premature “audience activation.” New Insights The third purpose of a DMP is to uncover new insights about a marketer’s audience segments. The DMP should provide easy access to understand what other attributes index most and least highly with the selected audience group. The platform should also recommend the best Web sites and content to reach that audience, as well as information about the best geographies to target. Furthermore, it should ensure that a marketer understands the cost implications of overlaying geographic, third-party attributes and contextual data with forecasting the cost of various advertisement placements. The online advertising ecosystem has never been more competitive. With consumers’ activity and attention increasingly fragmented across a variety of channels, such as video, mobile and social, it is of the utmost importance that marketers today have the technologies in place to ensure they fully understand this activity as they plan their segmentation and targeting strategies. Armed with a robust DMP, marketers are better able to locate, target and understand their desired audiences, ultimately increasing the effectiveness of their campaigns and improving ROI. By understanding and utilizing the capabilities provided by a complete DMP, marketers can ensure they are using the best planning and segmentation tools to achieve their goals.
I have previously argued that RTB is a disruptive innovation in advertising -- even going so far as to say that RTB represents the “Death of Advertising.” Many viewed the title and read my words as condemning the advertising industry. They were not. In retrospect I could see why the article could be perceived as “wishing” for the death of advertising, but I was simply making the point that RTB is a disruptive innovation. I would like to do my best to channel the esteemed Harvard Business School Professor Clayton M. Christensen and Michael Raynor, a director at Deloitte Consulting, to tease out my thesis. Let’s begin with the definition of disruption recently used by Christensen in a piece in the December issue of Harvard Business Review, as “less a single event than a process that plays out over time, sometimes quickly and completely, but other times slowly and incompletely.” This is an interesting notion of disruption, one that seems to fit where RTB currently finds itself. RTB is largely a display advertising innovation that has crept “upmarket” into mobile and video, and is beginning to show itself in some out-of-home formats as well. We have yet to see any significant RTB incursions outside of these formats, but my belief is that eventually all ad-server-generated advertising can potentially be delivered via RTB, and that all digital advertising (including television) will be ad served. To be clear, I do not believe that all advertising will be delivered via RTB, just as those who championed air cargo did not believe that cargo ships would cease to exist. Raynor has suggested that all disruptive innovations stem from technological or business model advantages that can scale as disruptive innovators moving upmarket in search of more demanding customers. Raynor illustrates this point using the hotel industry as an example, notably the differences between the cost, customers and comforts of Holiday Inn and The Four Seasons. In short, the Holiday Inn would not move upstream into the territory of the Four Seasons because it would be forced to adopt the same cost structures, and therefore suffer from shrunken profit margins. A disruptive innovator is one that can maintain its advantage while maintaining its performance. Christensen’s term for the ability of the innovator to move upstream while maintaining its advantage and improving its efficiency is the “extendable core,” well-discussed in the article referenced above. RTB provides several advantages over standard delivery of digital media but the question becomes, Can these advantages be sustained as RTB moves upstream? A common measuring stick for upstream advertising movement is the ability of a format to attract dollars from so called “brand” budgets, as opposed to budgets that are generally regarded as direct response campaigns. Observers of the advertising industry suggest that brand-advertising dollars have failed to move meaningfully into the digital format. So will RTB be able to move upstream and capture brand dollars? It is important to first consider the disadvantages that can be associated with RTB: 1) the cost to deploy RTB effectively is significant, both from a hardware and human resource capacity and 2) RTB deployed without prophylactic computing power can lead to corrupt behavior. In the first case RTB explodes the amount of data available to the parties in the transaction. This makes it more complex to use that amount of data effectively, be it for screening for brand safety, predicting outcomes, or optimizing for yield. The second disadvantage is exhibited by an overwhelming number of poorly placed media purchases on formats precisely designed to take advantage of the computing cost problem and poorly informed sales decisions. This leads to ill-advised yield decisions, such as selling exhausted user sessions for incremental revenue, or designing content to maximize page views. Getting back to the extendable core, I am a strong believer that RTB has benefits that far outweigh its disadvantages, and has the capacity to move upstream and capture additional dollars. I have previously suggested that RTB’s greatest strength is the deconstruction of the CPM and its ability to transform mass channels into direct communication, closing the gap between the consumer and the brand. This is made possible because RTB enables the media seller and buyer to present and evaluate each individual impression rather than the traditional CPM block. In this instance, each impression should represent the opportunity to address the media to a specific consumer, or to a better defined representation of the consumer based on the information that defines the user. This increase in information available to both buyer and seller can allow for a more efficient valuation and distribution of advertising impressions. The result is that the right consumers will see the right ads and brands will pay the right price. If you agree with my theory of RTB’s extendable core being the ability to convert mass channels to direct consumer communications, and that television advertising will someday be ad-served, you will also agree that the potential disadvantages of cost and expertise can be overcome, and RTB will allow advertisers to move upstream.
Wednesday OpenX Software will announce a partnership with device recognition platform company AdTruth to improve on its mobile ad inventory sold through OpenX Market, the company's real time bidding platform. The service becomes available in Q2 2013. The product allows advertisers to identify targeted audiences on mobile devices through a global real-time bidding exchange across the mobile Web and applications. It also opens possibilities for remarketing to target display ads with the knowledge of what consumers searched for on mobile devices. The same auction-based concepts around search engine marketing become available for display ad marketing on mobile. It gives search marketers the ability to quickly adapt to other marketing techniques that expand campaigns past search engine marketing. Aside from better return in investment, it also addresses a "privacy-by-design approach," which provides a layer of anonymity for consumers, according to James Lamberti, vice president and general manager at AdTruth. Lamberti said the technology, along with cookies, will enable programmatic buying, specifically giving marketers working with mobile campaigns tools like targeting and frequency caps. "There hasn't been a good approach to identification," Lamberti said. "The cookie isn't working well for technical reasons, and there are lots of issues for companies trying to use Android IDs or Apple IFAs."