Finding Your Audience An analytic study to understand the impact of audience targeting and content channels on digital advertising yield November, 2010 AdJuggler, Inc.
Finding Your Audience November, 2010 Executive Summary The last 2 to 3 years have produced a number of new players in the digital advertising landscape. The once network-dominated exchanges are being reconstituted as transparent, NASDAQ-like trading centers. New demand-side and supply-side platforms are taking over the role of distribution. And ad servers, like AdJuggler, are solidifying their positioning as the last mile by enabling real-time bidding into the exchange ecosystem, supporting an ever-growing set of media channels, and expanding work flow and analytic capabilities as a true enterprise marketing platform. We believe that data and transparency are the drivers of these changes: specifically, the ability of marketers to more effectively target specific audiences with a wide range of attitudes, demographics, and behaviors. Although direct marketers were the first to jump in, the migration to audiences is being further validated by global brands shifting significant spend to digital display namely video, rich media, and mobile - to drive brand engagement. As a long-time digital advertising platform to more than 200 publishers, ad networks, agencies, and marketers, AdJuggler conducted an in-depth analytic research study in Q2, 2010 to understand the varying yields across advertiser segments and publisher channels, the impact of relevant content on advertiser yield, and the incremental yield achieved by targeting audiences with specific demographic, attitudinal, and behavioral attributes. The data set for the study comprised more than 872 million impressions and 6,000 campaigns. We identified a number of new insights and substantiated certain intuitive beliefs shared across the industry. While we found that click-through-rates (CTR) varied significantly by advertiser segment and publisher category, these variances do not appear to be reflected in CPM rate sheets and actual campaign prices. And, while placing advertising on related content sites (e.g., credit cards on a financial advisory site) increased response as much as 40% in certain advertiser segments, the importance of content (what users are reading) only matters in certain segments. Perhaps most dramatic are the results from the audience targeting. After appending more than 150 anonymous variables to the sample s web visitors, the audience segments we produced were found to be highly predictive of yield and, the top two deciles of these audiences for specific advertiser segments improved CTR yields by 50% to 300%. AdJuggler believes that these findings have significant implications for marketers, networks, and publishers alike. Advertising is about the customer, as marketing strategists purport. Digital providers must jump headlong into the audience generation, linking into the exchanges, creating products and sales programs around audiences, and continuing to bolster content to attract the most valuable audiences. All for better marketer yield and publisher ecpm monetization. November, 2010 AdJuggler, Inc. Reproduction Prohibited 2
Audience vs. Content? One of the more significant shifts occurring in digital advertising is the migration of media distribution from content to audience. Much to the chagrin of major, branded content sites, the rise of audience targeting is based on two fundamental marketing tenets. Premise #1: Customers Trumps Content. The thinking goes like this. Publishers don t own their users. Users are individuals with unique preferences, attitudes, and behaviors that go beyond mere content consumption. Taken together, these collective attributes are the best predictors of brand engagement and purchase activity. Data providers like Blue Kai and Exelate aggregate these descriptors to create anonymous, targetable online segments, each with their own demonstrable advertising ecpm and ROI. Premise #2: It Doesn t Matter Where You Find The Right Customer. The second tenet, advanced primarily by demand side platforms (DSPs) and the digital exchanges, suggests that marketers don t need to pay premium CPMs to find target user segments. Instead, advertisers should purchase less expensive run-of-site (ROS) campaigns across a multitude of sites, finding target users regardless of the sites and pages they are visiting. Armed with user-tagging techniques (e.g., cookies), look-alike models, and third-party user data, advertisers only show impressions to users when they match the target audience description. In financial terms, the audience-centric approach can be good for marketers and publishers: more relevant users should translate to better advertiser ROI, even at higher CPMs. Finding a target user reading TMZ should generate the same brand impact and response as finding the same user on CNN, right? Television has worked this way for decades. Consider IBM s long-time advertising relationship with the professional golf tour, perhaps one of the best ways to get the attention of corporate executives. But, doesn t content have any impact on advertiser ROI? Is relevant content more relevant for digital advertising, in comparison to traditional media? Research Overview To address this debate, AdJuggler executed a controlled test on more than 6,000 digital ad campaigns executed across the AdJuggler platform to better understand the yield relationship between advertisers and publishers. We then appended a third-party consumer demographic database to the user records to understand the incremental impact of audience targeting. The test data comprised 872 million ad impressions with more than 10 million responses across more than 150 publishers and 4,200 advertisers. Responses included click-through-rate (CTR), lead rate (completing a contact form), and sales rate, based on a user progressing to a commerce-related page. November, 2010 AdJuggler, Inc. Reproduction Prohibited 3
For the third-party data append, we utilized Equifax s consumer lifestyle database (recently acquired by Alliance/Epsilon), enriching more than 37 million user impressions in our test, linked via an IP-zip code key based on Digital Element s geotargeting platform. The data append comprised more than 150 demographic, credit, lending, residential, and auto purchase variables, measured as a percent or average for the zip code (e.g., 7.4% of the zip code has purchased a Lexus in past 2 years). No personally identifiable information (PII) for individual users, individual advertisers, or individual publishers was captured, stored, or reported. The cause of incremental CTR or ROI was limited to the variables specified above and did not consider other valid drivers, such as ad creative, ad placement, ad size, or the ad offer itself. Additionally, to understand the unique yield of various advertiser and publisher segments, we categorized each digital ad into a standard segment taxonomy: One of eleven (11) advertising segments and 51 subsegments, and one of 22 publisher categories (a.k.a., channels). The Basics: Different Ads & Channels Produce Different Yields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ovember, 2010 AdJuggler, Inc. Reproduction Prohibited 4
Exhibit A highlights the variance in CTR yields for different advertiser segments and publisher categories. Although yield variances are expected, the difference from high to low performers is a factor of 8X and 30X, respectively. The question is whether the industry prices to these variances. The vast majority of publishers in the data set do not vary gross CPMs in line with the CTR variances shown in Exhibit A. Likewise, CPMs achieved from network traffic do not appear to vary nor align to the differences in advertiser CTRs. Content Matters - Sometimes We then sought to understand whether content what users are reading drives higher yield for advertisers operating in the same content category. For example, does a Dell advertisement truly outperform on technology sites, such as TechCrunch? Although we didn t store specific advertiser and publisher names, we did compare how CTRs for specific advertiser segments varied, based on the relevance of the publisher content. For this analysis, we examined four advertising segments: education, financial services, health care, and consumer packaged goods (CPG). &'*&% /89):;)/.%((+,)3'0)5<+$4=$)>"6+0&7+0)5+?@+(-7)!"#$%&'() *+%,-.)/%0+) &'*&% &')&% &')&% &'(&%!"#$% &'(&%!"#$% "+,-%./0,% 1+23% 4+567-% 8039%./0,% ":5;+6% <-=>% 1+23% 4+567-% &'*&% /12) &'*&% 34(%($4%,)5+064$+7) &')&% &')&% &'(&% &'(&%!"#$%!"#$% 1+23% <>=:7% <-=>%?+73% 4+567-%!"#$%$&'(')'''''*+,-.' <>=:7% 8039% "+,-%./0,% @+9A3% November, 2010 AdJuggler, Inc. Reproduction Prohibited 5
The results across the four sample advertising segments present different conclusions. In the health care and CPG segment, the CTRs were strongest on publishers with related content and those related content channels out-performed the segment average by 300% to 1000%. In the case of financial services and education ads, related content did not correlate as strongly to CTR performance. This may suggest that advertising on related content sites drives higher yields if the purchase requires greater research and consideration. Audience Matters More Consistently To understand the relative importance of audience targeting on CTR performance, the term audience needs to be better defined. In its most simple form, an audience is defined by a single variable: men (gender), teenagers (age), affluent (financial), etc. But, with the advent of direct marketing and the Internet, the definition of audience has become more sophisticated. Audiences Are Being Defined By A Growing Set Of Available Attributes Segments are based on demographics, as well attitudes, buying power, purchase behavior, web surfing habits, interests, etc. The Internet is rapidly enabling marketers to track this information empirically and in real-time. Audience Segments Aren t Relevant If They Don t Predict Market Response Audiences are described by multiple attributes, which, together, are predictive of a certain behavior or response to a particular offer or marketing stimulus. These collective attributes are aligned (i.e., collinear) to describe the audience. Segments Must Be Assignable For Targeting Marketers no longer tolerate conceptual audiences. The attributes utilized to describe an audience must together be scored and assigned to individuals. For digital advertising, these users are anonymous and linked by IP or cookie. Digital providers are further expanding these discrete audiences through sophisticated look-alike models that evaluate new individuals and allocate them into specific audience segments based on a partial set of attribute data. For this analysis, we found that, in general, the third-party consumer data set was strongly predictive of CTR meaning that targeting the right individuals with certain demographic, financial, or lifestyle values statistically demonstrated higher response. We utilized principle component analysis (PCA) to further define the groups of collinear variables (i.e., segments) that best predicted response (and which variables had no impact), and which segments responded most effectively to different advertiser segments. November, 2010 AdJuggler, Inc. Reproduction Prohibited 6
!"#$%&%"'()*+,-*.(/"*01*2%3&%"'*4%#/)%* 567'8&89:%*2%3&%"';*!"#$%&'$ ()*&+)$,-./*0)1$23$4)56758/9*):$!"#$%$&'(' Exhibit C summarizes the results for one advertising segment: automotive. It rank-orders (by decile) various audience segments based on their responsiveness to automobile advertisements. The chart shows that: All segments plotted are statistically predictive of auto ad response, but some respond better than others. The lift to CTR utilizing 1.0 as the historical baseline with no targeting is most significant in the first two deciles, yet continues to show improvement through 75% of the audiences. By isolating an audience that reflects the attributes of the top two decile audiences, marketers can achieve CTR lift of 50% to 300% above baseline. We found similar results for other advertising segments. The automotive segment experienced 80% lift, on average, across the top two deciles, compared to a 40% lift using publisher data only. The travel segment experienced 80% lift for the top two deciles, compared to 30% lift using publisher data only. And, the health care segment demonstrated 70% lift for its top two deciles of audience segments, compared to 20% using publisher data only. November, 2010 AdJuggler, Inc. Reproduction Prohibited 7
Implications For Marketers & Publishers Although there are limitations to the data and analysis utilized in this study, the findings provide a number of operational implications for both marketers and publishers. Price To Advertiser Segment At a minimum, publishers should recognize how CTRs vary by advertiser segment and how those advertisers may or may not get a bump from advertising on relevant content sites. This insight should inform pricing structures and direct CPM deals. Get On The Audience Bandwagon Advertisers are paying more for targeted audiences, translating to higher CPMs. Tactically, this means that advertisers should increasingly purchase specific audiences, and publishers and networks must be prepared to offer those same audiences. Unfortunately, many publishers still don t provide media kits that reflect those audiences and have not developed sales products built around those audiences (e.g., 32% of our inventory are frequent male shoppers ). Exchanges Are A Path To Audience Traffic Whereas early network and exchanges were built to trade non-transparent remnant traffic, the new and improved networks and exchanges are providing brand and price transparency making the exchanges a valid distribution models for even the most protected brand advertisers. Integrating to the exchanges can provide access to these higher-cpm audiences at increasing fill rates. SOV Is Dead For ROS Many publishers continue to sell direct advertising using a weighted share-of-voice approach. Although there are inefficiencies with this method, the ecpms for premium inventory are still attractive if an advertiser benefits from traffic spikes. For run-of-site/network deals, SOV structure may be leaving money on the table, as better performing audience campaign traffic, which utilizes real-time bidding (RTB) to evaluate the price for every individual user. Audience-Centric Content The above analysis suggests that audience targeting is more important, in many cases, than advertising on relevant content sites. That said, the CTR lifts for certain advertisements are substantial when placed on relevant content sites, reinforcing the importance for producing and distributing quality content. Even if the content does not materially improve related advertiser CTR performance, the content is still critical to attracting certain audiences, which, unto themselves, generate higher CPMs. November, 2010 AdJuggler, Inc. Reproduction Prohibited 8
About AdJuggler, Inc. AdJuggler develops and manages a leading SaaS-based digital ad serving and management software platform. AdJuggler s solutions comprises unique technology services for advertisers, agencies, publishers, and networks, as well as APIs, custom development services, content hosting, and ad operations support to tailor the service to your business needs. The AdJuggler platform reflects a commitment to provide the best technology with support for multi-exchange integration, real-time bidding, and the latest rich media, video, and mobile standards. AdJuggler boasts nearly 300 customers across all major global geographies. AdJuggler can be reached at 703-914-9700 or sales@adjuggler.com. November, 2010 AdJuggler, Inc. Reproduction Prohibited 9