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A Guide for Marketers

Addressing Four Key Issues for Successful Programmatic Ad Buying

IN THIS REPORT

3 Part One: Big Data Analytics in Action

5 Part Two: Retargeting Smart Retargeting

7 Part Three: Cross-Device Tracking Device Usage Patterns

8 Part Four: Fraud Bots and Viewability

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ne great promise of digital advertising is that marketers will finally be able

to demonstrate and measure the success of their marketing techniques. So far, that outcome has proven somewhat elusive, but new technologies and smart marketing strategies are start-ing to bring marketers closer to the goal.

It's no secret that track-ing customers and measuring “reach” can be tricky, even online. Despite the huge amount of available information about web traffic, a great many factors—from fraud to mobile impres-sions to retargeting—complicate marketers' efforts to get the results they want from their ad

Custom

2 PROGRAMMATIC AD BUYING MIT TECHNOLOGY REVIEW CUSTOM + DIGILANTINTRODUCTION

campaigns. But addressing the potential pitfalls can make a mar-keter much more effective. This paper is designed to provide a primer for marketers on some of the most important issues that con-front today's digital advertising landscape.

To a great degree, digital adver-tisers can track precisely who their customers and prospects are. They can also determine the routes by which these customers and pros-pects arrived at their sites, and, by extension, what led each customer to buy or subscribe or register. This knowledge will enable market-ers to pay only for the advertising and marketing efforts that lead to the result they desire, improve the their return on investment (ROI), and effectively target future ads to reach the most likely buyers. Marketers are clearly recognizing the power and efficiency of digital advertising: U.S. spending for Internet advertising hit an all- time high of nearly $43 billion in 2013, up 17 percent from 2012, according to a PricewaterhouseCoo-pers report prepared for the Interac-

tive Advertising Bureau (IAB). But advertisers and marketers

long ago realized that digital marketing is a lot more complex than just paying for clicks or impressions. Brand impressions created a month or more before a purchase may have been crucial to the buyer's decision. An ad that popped up on a cellphone while the customer was playing Candy Crush in a doctor’s waiting room might have also played a role. The target customer may have reached the site three times by different routes, cementing the purchase plan, before finally arriving there by yet another route and actually making the purchase.

Although marketers believe that digital advertising can influence cus-tomer decisions at every stage of the purchasing funnel, they have trouble determining the value of each sepa-rate interaction. For instance, a cus-tomer may have made her decision while viewing ads on her cellphone, but waited until she was on her desk-top at work to make the purchase.

In the past decade, a vast ecosystem of technologies and

companies has emerged to help marketers understand more pre-cisely who their customers and potential customers are. Techniques that employ “big data” analytics are helping to identify new customers and increase sales. Companies that effectively use big data for marketing improve their ROI by 15 to 20 percent, according to research by the McKinsey & Com-pany consulting firm. Now new technologies are being developed to ensure that ads are placed where they will yield the greatest ROI. The industry is also addressing the issue of online advertising fraud through better policing, self-regulation, and improved technology.

This report aims to review the complex process of measuring digital advertising outcomes and to examine the solutions that the industry has developed—and con-tinues to develop—to improve the process. We will look at four key programmatic factors in the cor-rect measurement of advertising effectiveness: big data, retargeting, cross-device tracking, and fraud.

In the past decade, a vast ecosystem of technologies and companies has emerged to help marketers understand more precisely who their customers and potential customers are."

Part One: Big Data

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3 PROGRAMMATIC AD BUYING MIT TECHNOLOGY REVIEW CUSTOM + DIGILANTPART 1: BIG DATA

Big DataPart One

Online marketing can provide far more accurate and detailed information about the steps leading up to a sale than more traditional marketing approaches do. However, to really take advantage of all this detail, marketers need to use tech-nology to analyze it. Big data predictive analytics provides marketers a far bet-ter way than raw data does to determine what steps lead to actions, allowing them to target both new and existing customers more effectively.

When a visitor comes to a website for the first time, the site can install a track-ing "cookie" that will log the user’s future Internet activities. Internet browsers track user activity and make it available to marketers, and as a result, marketers can tell what the buyer did online before finally making the purchase. However, tracking cookies are benign and designed only to use your information, along with the data of millions of other anonymous users, for marketing analysis.

Until recently, only direct-mail cam-paigns and infomercials came close to showing marketers comparably clear con-nections between a marketing effort and a purchase. Even now, with all the benefits of ad technology, online tracking is only a piece of a larger strategy.

According to Google Analytics research, a buyer interacts with a brand, on average, 4.3 times over a two-day period before taking action. Google research also found that the average U.S. shopper consults 10.4 new and traditional media sources before making an in-store or online purchase. Other researchers say that for major purchases, particularly automobiles, buyers start researching nine months before they sign the papers. Still, even after online interaction or view-ing of a product, many consumers still make the actual purchase offline.

Trying to figure out the most cost-effi-cient way to reach the consumer at key points in the purchase journey is the task of the marketer. And big data goes far beyond the tried-and-true online targets of search and retargeting.

Big Data Analytics● Digital advertising creates vast amounts of data—data about customer touch points, behavior, and purchases in both the online and the offline worlds. The problem is knowing what to do with what Forrester Research describes as the rapidly escalating "volume, velocity and variety" of information—in other words, big data. ● Marketers rely on data analytics companies, which employ teams of math-ematicians with doctorates to create algo-rithms that segment web users and figure out which segments to target. Entirely new companies have sprung up to tackle this problem. They include big-data firms such as BlueKai (recently acquired by Oracle) and eXelate, as well as ad-technology firms such as ChoiceStream, DataXu, Digilant, MediaMath and Turn.

In addition, marketers are gravitating quickly to big data and predictive analyt-ics to boost their returns from the $102 billion spent worldwide on digital mar-keting in 2012 (according to McKinsey & Company research). More than 40 percent of marketers increased data-driven spending in the first quarter of 2014, according to the Quarterly Busi-ness Review report produced by the Direct Marketing Association and Win-terberry Group.

Analytics in Action● Digital advertising and marketing gen-erate billions of points of data. The chal-lenge is in determining which data points are useful and then combining them to amplify their impact. ● Marketing data providers first create user profiles by analyzing data from a random sample of millions of users. They analyze the websites those users visit, the search terms they use, and the purchases they have made, all while “anonymizing” their identity by assigning user IDs. Then they use this data to segment users further into several thousand categories.

For instance, website visits using search terms such as "football" and "fan-tasy" probably come from armchair sports fans, who might want team-logo merchan-dise and beer. Terms like "shoulder pads" and "uniforms" might indicate coaches or parents, who would be interested in equipment and sports drinks. Segmenta-tion like this is much more precise than the traditional audience metrics used by television or website ad salespeople, who use a publisher's site or a TV show as a stand-in for its audience, rather than dif-ferentiating between the characteristics of different football fans. By relying on content over behavior, their segments might identify sports program watchers, but without differentiating armchair fans from active athlete.

After identifying segments, marketers then go on to analyze the traffic on their own websites to see which of the segments visits them, and which segments actually make purchases. Information from these user clusters provides a basis for identi-fying similar users in the broader online population who may not yet be aware of their brand.

Marketers also closely analyze pur-chasers’ activities on the websites. One segment of older buyers might

4 PROGRAMMATIC AD BUYING MIT TECHNOLOGY REVIEW CUSTOM + DIGILANTPART 1: BIG DATA

gravitate to a detailed product page when they are seeking information about new automobiles. But the “soccer moms” seg-ment might navigate to a section about implementing parental controls.

Using insights about the existing cus-tomer segments, marketers can create ads and marketing campaigns to appeal to potential buyers in that segment. According to McKinsey & Company, the approach of profiling users based on their web histories and customizing digital ads in response has proven to be 250 percent more effective than average web display advertising.

Analytics and Programmatic Ad Buying● Big data also informs ad buying. Using the data for profitable segments, market-ers, ad-technology providers and agencies create algorithms that serve targeted ads more efficiently to the right people on the right sites. ● Digital marketers can identify and even create private networks of select web sites where certain ads can be placed to get the best results. Marketing providers can use web crawlers to scan all the material on a client’s website and related marketing col-lateral, white papers, and blogs. Then they create an index of keywords on web pages and match that index to millions of web-sites where they can place relevant ads.

Serving ads on pages with appropri-ate content, tightly correlated to a client’s products and services, ensures more rele-vant advertising that gets better responses and feeds new users into the purchase funnel. Among the companies doing this kind of buying are Digilant and Sizmek (Peer39), along with platform providers or agencies such as Conversant, Xaxis and GSI Commerce (eBay).

Contextual advertising technology can clarify the meaning of the content of a web site far more accurately than sim-ple keyword searches can. For example, if a user has been researching pickup

trucks, it might serve him ads on sites that mention the Toyota Tundra (or trucks in general), but not ones about the Arc-tic tundra. Traditionally, advertisers have relied on publishers to describe the con-tent and audience for their websites, but those descriptions aren’t always accurate.

Trading desks and programmatic companies often negotiate deals with publishers that give them first crack at inventory; these are known as private exchanges. Private-exchange clients spec-ify sites on which they want to appear. Cli-ents get premium access and better brand affinity than they would for direct deals with publishers, and achieve a more customized audience than they would get with only real-time bidding (RTB) at the lowest cost per thousand impres-sions (CPM). Additionally, by securing longer-term, volume-based agreements, clients can secure lower rates than direct agreements. For instance, a grocery chain might want a campaign to appear on every major food and recipe site accessed by consumers located in regions served by their stores.

Including Offline Marketing Information: Attribution ● Every month, quantitative modeling companies such as Visual IQ, Convertro (owned by AOL), and Adometry (owned by Google) process billions of market-ing touch points for their clients. Other companies in this space include Data-logix, LiveRamp (owned by Acxiom), and Oracle (which owns BlueKai). This anal-ysis started with online data, but today these companies can incorporate data of varying quality from television ads, direct mail campaigns, print campaigns, and point-of-sale loyalty cards. In the best case they can correlate factors like direct-mail-ing addresses with IP addresses. That's

important, because companies want to see whether online efforts augment or replace costly direct mail.

Attribution of sales is also aided by big-data analytics. Marketers say the data tells them which ads influenced sales and point to the best places to spend their future budgets. They can identify the most fertile segments and channels and judge how many times a prospect should see an ad before it becomes counterproductive. Analysts can produce reports overnight after big events like the Super Bowl, tell-ing marketers how effective their ads were and where to spend money to amplify their effect.

Weaknesses ● Big-data algorithms are only as good as the data they have to work with, and measurements in many channels are imperfect. (This is particularly true in the increasingly important mobile mar-keting space).

Marketers still have a difficult time tracking the impact of “earned” media, such as CEO interviews or product reviews. Hiring a big-data provider is expensive, and so it's an option usually reserved for larger companies. The results of predictive analytics are often some-thing of a black box, and may be difficult to explain to corporate CEOs and CFOs and even to some traditional marketers.

Best Practices

n Use analytics to segment your audience precisely.

n Target segments of the broader population that match your audience segments.

n Use analytics to find the best websites to place your ads.

n Develop models to evaluate your return from all advertising channels, and continue to optimize your programs.

Part Two: Retargeting

5 PROGRAMMATIC AD BUYING MIT TECHNOLOGY REVIEW CUSTOM + DIGILANTPART 2: RETARGETING

60% Percentage of U.S. cosumers who

have used a mobile device exclusively for deciding on a purchase.

Of course, customers don't purchase every time they visit a website. As noted pre-viously, Google research shows that the average customer interacts with a brand at least four times before buying. Those interactions may take place over several days, and in some instances—such as car purchases—even many months.

Still, people who have visited a web-site are far more likely to actually make a purchase than any other audience. That means marketers need to try to keep their information “top-of-mind” until users take action. They can accomplish that with incentives, such as free shipping or a discount, to lure back a shopper who has left.

Retargeting technology allows mar-keters to reach out to those users. This is accomplished using a small, invisible piece of code called a pixel, which places anony-mous tracking cookies on the browser of each visitor to a website. The cookie allows advertisers to identify users when they are no longer on the company's website and serve ads up to them. Retargeting provid-ers then see the potential customer again and target ads for products from the origi-nal advertiser. (However, it's important to note that tracking pixels aren't enabled in most mobile browsers or for mobile apps.)

Risks of Retargeting● Retargeting can be extremely effective. However, like any form of marketing, it needs to be done strategically.● Many users are annoyed when they see an ad on a website promoting something from another website that they visited several days earlier. Others get irritated

RetargetingPart Two

by seeing the same ad for low-interest loans just because they read a particular article on credit-card debt. Major retar-geting-technology platforms can establish frequency caps that prevent serving too many ads to the same person. Often, how-ever these platforms cannot tell whether the user has already made the purchase in a store as a result of an ad served by another retargeting provider, and waste their ad placements.

Smart Retargeting ● ChoiceStream, a programmatic ad platform, says that customer surveys and other research indicate that traditional retargeting works with only about 2 per-cent of site visitors. Still, it often makes sense to retarget the same customers with different offers. After all, someone who looked for a hotel in Houston is probably someone who is traveling to Texas, so it makes sense to serve that person other relevant ads for businesses in that area.

Ad platforms have developed pro-grams for advertisers that use knowledge about a customer’s previous page views and clicks to perform predictive target-ing (which involves targeting based on customer behavior) and affinity target-ing, (which involves targeting based on customer interest in similar products).

Examples of predictive targeting might be providing urban apartment dwellers in their mid-20s to mid-30s with ads for suburban real estate, or reach-ing out to music fans in the same age group with ads for upcoming local perfor-mances. Affinity targeting could involve serving someone who had been looking

at spring dresses with an ad for sandals, or someone who had been perusing sites that sell high-performance bicycles with ads for helmets.

Blocking Ads and Cookies● Retargeting on desktops and laptops is largely dependent on users deciding not to block tracking cookies. In a 2013 survey, Forrester Research found that more than 27 percent of computer users were using software such as AdBlock for blocking some ads and tracking cook-ies. But relatively few people block all cookies, and even those who block track-ing may still get ads—just ones that are less relevant.

Evaluating Retarget Clicks● Conducted correctly, retargeting is more effective than any online targeting or audience segmentation strategy.

In fact, it’s so much more effective that it can lead to misallocation of resources. Especially when marketers are making their decisions based on “last click” or “last impression,” they will tend to over-value the retargeters’ work. Actually, the most valuable advertising was likely done before the customer first visited the web-site, because it accomplished the heavy lifting of making the customer aware of the product. X

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Because of retargeting’s effectiveness, many ad tech providers are likely to boost their numbers by retargeting whenever possible. That makes it hard for market-ers to tell whether their digital partners are really generating new business—or whether they're just getting the same consumers who would have shopped on their site anyway. One strategy to control this problem is for the marketer to autho-rize just one or two retargeting partners. In addition, attribution for a retargeter should be given far less credit than the credit given to a campaign that brings in a new customer. It's important to under-stand that retargeting is limited in scale to people who actually visited the website.

Mobile Retargeting● Researchers say that customers are increasingly comfortable with both browsing and buying on smartphones and other mobile devices. ● Up to 60 percent of consumers surveyed have used a mobile device exclusively for deciding on a purchase, according to a survey of 6,000 mobile users in the xAd and Telemetrics 2014 Mobile Path-to-Purchase report. Forty percent of those surveyed called mobile the most impor-tant source for gathering purchase-related information, while 29 percent called mobile their most important shopping tool, period.

Some users worry about security on smartphones in particular, and, of course, typing credit-card numbers and delivery addresses on small devices can be cumber-some. For that reason, buyers who are, say,

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riding a commuter bus may make a pur-chase decision while in transit, but post-pone making the actual purchase until they get to a keyboard. And mobile users often have short attention spans. Incom-ing text messages and phone calls fre-quently interrupt potential buyers, and they may change screens and forget what they were looking for.

Mobile retargeting is difficult because Apple’s Safari browser on its smartphones and tablets turns tracking cookies off by default. Apple provides something called Identifier for Advertisers (IDFA), but Apple controls it, and the publisher who created the app cannot let advertisers follow the user around. Google has also launched its own Advertising ID with sim-ilar restrictions.

In-app marketing raises another level

of difficulty for marketers trying to under-stand customers’ online activity. A hotel seeker who uses Priceline’s app on his tab-let generates no cookie that would help other travel companies target him.

Companies such as ActionX, Con-versant, Digilant and TapCommerce use IDFA and other technologies to perform retargeting on mobile devices.

Best Practices

n Establish a retargeting campaign that employs different metrics from other campaigns, so the results are not given too much weight.

n Develop special offers to close deals with users who abandoned their carts or left a website.

n Combine creative messages and target-ing to upsell and cross-sell.

n Limit the number of retargeting partners to one or two providers.

Part Three: Cross-Device Tracking

Conducted correctly, retargeting is more effective than any online targeting or audience segmentation strategy."

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7 PROGRAMMATIC AD BUYING MIT TECHNOLOGY REVIEW CUSTOM + DIGILANTPART 3: CROSS-DEVICE TRACKING

Cross-Device Tracking

Part Three

Advertisers know that the same per-son who sees an ad on a smartphone may end up buying the item from eith- er a work desktop or a home lap- top. Currently, marketers don’t have an easy way to know when that has happened.

Apple’s Safari browser on its smart-phones and tablets turns tracking cookies off by default. That means it's even harder to know whether a web surfer is interested in a product. Still, marketers need to reach customers where they are—and, increas-ingly, customers are on mobile devices. Moreover, mobile-ad inventory is gen-erally cheaper than desktop inventory, making it possible to achieve a strong ROI.

Device Usage Patterns● Business people have traditionally used desktops and, more recently, lap-tops. Growing numbers of them now use tablets for business, and almost everyone uses smartphones. Home-use patterns are changing.

Many families share a desktop attached to a printer and connect their personal devices, including tablets and smartphones, to a wireless net-work, according to research by Gartner Inc. Family members may access the web and see ads on different devi- ces while watching TV, preparing dinner, or even sitting in the back yard. Sometimes they use devices sequent-

ially, sometimes they use them simulta-neously.

When it comes to cross-device target-ing, marketers' goal is to spot a user who is indicating the intent to buy, and then serve an appropriate ad on the next device he or she uses. Buying intent may be dif-ficult to determine on phones, however. Even a click that takes a user to a website that is being promoted might result from clumsy thumbs rather than real desire to visit the website.

Social Media Targeting● Users of major social media sites, especially Facebook, use the same iden-tity on all their devices so that they can see their news feeds and keep in con- tact with their friends. Because such sites are closed ecosystems, the pro-cess of cross-device targeting is some-what less complex. That means that when someone is playing “Words with Friends” on Facebook, the social network knows that this i s the same person who has been planning a camping trip with friends, and can serve up ads for rain gear, tents, and backpacks.

Twitter, Instagram, and other popular mobile apps offer similar cross-platform capabilities. Google's cross-device sync for its Chrome browser makes it pos-sible to retarget ads to the same person, assuming that the person is logged onto Chrome on each different device.

Mobile Cookies● Mobile users’ cookies are enabled in order to stay signed in to mobile apps or email services. Ad technology providers can then retarget the user on the hand-set by syncing cookies from the desktop. Google Display Network can retarget users of mobile devices that are signed into Google web services. But mobile cookies are far from universal, and smart-phone users who simply use apps are dif-ficult for advertisers to target when they jump from one app to another.

Statistical Analysis● Employing analytics to guess that a smartphone user is the same as a desktop user is becoming increasingly popular. Though not a perfect science, this enables marketers to determine which user prob-ably belongs to which device, without rais-ing the privacy questions that tracking cookies do. ● With analytics, no personally iden-tifiable information is used, and this approach sidesteps the potential gate-keeper roles of Google and Apple with their advertiser IDs.

Statistical analysis looks at factors such as location data, Wi-Fi networks used, websites visited regularly, and the time of day that users make particu-lar connections. Even without a device identifier or an installed cookie, some companies—for instance ActionX and BlueCava—say they can deliver relevant ads to the right devices through a method called probabilistic identification. They can do this at the same time as users are working on their devices. Drawbridge and Adelphic Mobile also have techniques for finding users on multiple devices.

Deterministic identification is more accurate. Companies like Facebook and Live-Ramp can track users without

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using any personally identifiable informa-tion (PII) by recognizing when a person has logged on to a site from different devices using the same name and password. It's worth considering, however, that deter-ministic identification relies on consis- tent logins across all devices and can be subject to "sample skew"—for instance, by using Google single sign-on prod- ucts, marketers run the risk of ignoring Yahoo users. Ad technology provid-ers can combine data from clients who send them information about their use of apps on mobile devices (without PII) using ad ID information. That can allow providers to track who has placed an item in a shopping cart without a pur-chase and remind the customer, even when on another device, to complete the purchase, possibly offering an incentive such as free shipping.

Best Practices

n Develop a relationship with companies that have strategies for tracking and retargeting from mobile to desktop to home.

n Set a threshold of accuracy when using analytics to decide on ad buys.

n Leverage applications such as Facebook to target users across devices.

FraudPart Four

One of the unpleasant realities of online advertising is that a lot of the traffic being paid for doesn’t actually exist. It is fraudu-lent traffic, created by people who make money from machine-generated impres-sions and clicks.

In February 2014, the IAB trade group estimated that 36 percent of all web traf-fic sold to advertisers is fake. Such traffic is generated by computers that have been infected by viruses and instructed to visit websites—usually without the computer owners’ knowledge. Solve Media, a New York City-based online advertising and security company, estimates that fake ad traffic will cost marketers $11.6 billion this year, up 22 percent from last year. That’s a significant chunk of the nearly $43 billion Internet advertising market identified in the PricewaterhouseCoopers/IAB report.

The problem is that fighting fraud also costs money—and meanwhile, fraud methodology is constantly evolv-ing. Fraud-detection firms generally base their charges on the number of impressions they monitor. When a fraud-detection firm is employed by an ad network, blocked fraudulent impress- ions result in lower charges to advertisers.

Fraud has short-term benefits for almost everyone--except the advertiser. It makes publishers’ sites look more heavily trafficked. It makes ads appear as though they’re seen by more peo-ple. Sometimes multiple ads are served on the same page on top of each other, increasing inventory: that makes marketers think their cam-paigns are doing well–when, in fact, no humans actually viewed their ads. Ad networks that get paid per impression served can claim more unique impres-sions. The large volume of ads lowers prices in programmatic buys.

Types of Fraud Bot fraudPublishers pay third parties to deliver traf-fic to their websites. The publishers assume that it is real traffic: but, the third party may be using Internet bots to visit the page and create page views, which the publisher reports to the ad networks. Robot retargetingA retargeting fraudster can create a bot that follows predictable steps on a website; for instance, the bot may click on specified pages of an automaker's website to gener-ate a payment to the retargeting company. Ad injectionFraudsters can create browser extensions that insert ads into high-value legiti-mate websites. These ads are listed on ad exchanges, but all the revenue from them goes to the insertion creator. CMS hackingMany content management system (CMSs) users use the ID “admin” and sim-ple passwords that can be hacked. Once inside a publisher’s website, hackers can set up their own pages and list them on ad exchanges to buyers who think they are purchasing premium domains. YouTube resalesGoogle prohibits third-party resale of You-Tube ads, but low-priced YouTube inven-tory often hits the market, and much of it is phony. While Google says it has resolved this issue (and offered full refunds), the practice still exists on other exchanges. Impression stacking fraud Ads can be “stacked” behind vid-

$11.6 billion

The estimated amount that fake ad traffic will cost marketers this year.

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eos or automatically refreshed: these pro-cesses create additional impressions even though the person viewing the video never sees these ads.

Viewability ● Even when a marketer knows an ad was on a page that a consumer viewed, there’s little certainty that the consumer actually saw the ad. The user may have only scanned the top of the page, miss-ing the ad further down the page, or may have immediately scrolled down the page, missing the banner at the top. Or the visitor may have jumped immediately to another page. Finally, ad servers may rotate a number of ads rapidly —- some-times too fast for comfortable viewing.

Marketers wrestle with similar prob-lems in all media. Magazine buyers don’t always get to the back of the book. News-paper readers may skip entire sections. Radio listeners switch stations. TV watch-

ers leave the room when ads appear.Digital media buyers want to be sure

that when they pay for impressions, they are buying impressions that viewers can and do actually see.

StandardsThe IAB defines a viewable impression as one where at least 50 percent of an ad appears for one full second. Such a measure is particularly important for digital video. In March 2014, the indus-try’s Media Rating Council issued new guidelines making viewable impressions the standard units for ad sales, replacing served impressions.

BenefitsGoogle, which started selling viewability in 2013—and which guarantees that cus-tomers won’t pay for unviewed impres-sions—reported that such ads were much more successful for advertisers than ads that didn’t meet the standard. Not sur-prisingly, a viewable ad is up to 21 times more likely to be clicked. An ad that is

rated viewable for more than four seconds is nearly twice as likely to be clicked as an average ad.

Viewability measures can be a big ben-efit for publishers. Google says that view-able ads retain their value even when they are “below the fold,” coming into view only after a user scrolls down. Google says view-able below-the-fold ads get clicks at the same rate as those above. One reason may be that a viewer who scrolls down is highly engaged with the content on the page.

Determining ViewabilityA number of ad-technology companies have developed methods to assess view-ability and deploy them on behalf of advertisers, publishers, and ad networks. The Media Rating Council, as part of its accreditation work, certifies the effective-ness of technology that has proven capa-ble of determining viewability.

All the technologies rely in large part on sampling and statistical analysis.

Such analyses reveal significant dif-ferences in viewability from site to site. DoubleVerify reports that in its managed campaigns ads delivered by real-time bid-ding are 48 percent viewable, while those sold through ad networks are 55 percent viewable, and those sold directly by pub-lishers are 64 percent viewable.

DoubleVerify installs a pixel in a given ad and then deploys web crawlers to see how long the ad is viewable. Google’s Adometry installs a tag in each ad to help it assess viewability.

Integral Ad Science (formerly AdSafe) uses predictive analytics to rate the view-ability of campaigns; the company reports that 40 percent of ads are in view through programmatic buying, and 50 percent are in view when purchased directly from publishers.

Private Networks● One reason ad fraud is so common in the online world is the lack of direct connection between the advertisers and content publishers. Thanks to

10 PROGRAMMATIC AD BUYING MIT TECHNOLOGY REVIEW CUSTOM + DIGILANTPART 4: FRAUD

advertising networks and RTB, market-ers can maximize impression numbers at low cost: but it is difficult to police where those impressions appear.

Some ad tech companies are starting to create private networks for large cli-ents, which aggregate inventory from cer-tain high quality publishers. Under these individualized contracts, the ad tech com-panies can sell inventory through RTB, but with much higher levels of control and transparency for the advertiser. Prices to advertisers are higher than through public networks, but often cheaper than negotiating deals directly with individual sites. Because advertisers are dealing with well-known publishers, the likelihood of fraud is much lower, while viewability is higher. The impact on CPMs may be more varied: significantly higher on some sites, and lower on others.

Technology Solutions● A number of companies have devel-oped technology to spot fraudulent traf-fic and block the websites from which it originates.

●Google recently acquired Spider.io, a small British company that has detected a number of bot techniques used for fraudu-lent advertising. Spider.io exposed the ad network ClickIce as an entity specially designed to sell fake impressions, at the same time it claimed to represent thou-sands of small websites.

Integral Ad Science offers real-time detection and blocking of fraudulent web traffic using semantic filters, analysis of links between websites, image analysis, and human scoring, as well as databases of fraudulent websites.

Benjamin Edelman, a Harvard Busi-ness School associate professor of busi-ness administration, also runs a business that detects fraudulent traffic. He has about 40 clients, and his 150 computers, which run 24 hours a day in nine 9 coun-tries, find malicious software that deliv-ers fake traffic. Edelman received a huge amount of attention earlier this year when

he made a blog post accusing the Inter-net ad sales company Blinkx of inflating its sales with fake traffic. Blinkx stock fell about 37 percent in the wake of his claims (which Blinkx has denied).

Business Practice Solutions● Industry groups are now taking action.The Network Advertising Initiative, a non-profit trade group, has established codes of conduct for website operators. The IAB has established a working group, the Traf-fic of Good Intent task force, which is working to establish guidelines for sup-pressing illegitimate traffic. The IAB task force has developed recommended best practices that advertisers can adopt to reduce the risk of traffic fraud.

Campaigns need to have clear success indicators, ones that aren’t easy for bots to achieve. Relying on clicks, views, and cookie attribution is an invitation to fraud, but purchases, registration forms, or ver-ifiable survey results all show human interaction. Bots have even been uncov-ered entering zip codes on store locator pages, though, so advertisers should con-sider specific and possibly even somewhat complicated key performance indicators (KPIs) so the bots can’t optimize results using high-volume, low-price, fraudulent impressions. Optimizing for the lowest cost per impression raises the risk of bot fraud.

Vendors and ad networks that empha-size fraud detection and prevention should get advertisers’ business.

Publishers that want to provide real inventory should use technology to detect nonhuman traffic. Before they buy traffic, they should examine the sellers’ practices for screening their suppliers. Unusually large volumes of traffic or poorly perform-ing ad placements should be investigated for potential fraud and the source blocked.

RTB providers and networks should monitor websites and screen out sites with substantial traffic that suddenly emerge

from nowhere. Audience overlap among unrelated websites—camping and high-heel shoes, for example—can be a red flag. Ad buyers blacklist certain sites that they know are frequently fraudulent.

Working with ad technology firms that have experience blocking ad fraud can help advertisers reduce the problem. The industry has also taken steps to com-bat fraudulent activity. The IAB recently announced its revised Quality Assurance Guidelines and now offers certification for ad-tech companies that take steps to prevent fraudulent activity.

Best Practices

n Be aware of various types of fraud.n Understand conversion metrics; investi-

gate if they look unusual.

n Question ad networks and RTB provid-ers about how they police against fraud.

n Ask publishers whether they purchase traffic and how they audit their suppliers.

n Consider using private networks for a larger portion of your ad budget.

n Be skeptical of low CPMs for highly popular domains from third parties.

Conclusion

Connecting the Dots● Digital advertising is the fastest grow-ing ad medium in history. That’s because marketers need to reach potential cus-tomers, and customers are spending more time online. Desktop use may be flatten-ing out but smartphone and tablet use is exploding.

Last year, for the first time, total digital advertising revenues surpassed broadcast TV ad revenues, according to the IAB’s Online Ad Revenue report.

The biggest category of online adver-tising remains paid search — advertising connected to search engines— but mar-keters are also spending heavily on ban-ners and other display advertising as well as video and mobile advertising.

11 PROGRAMMATIC AD BUYING MIT TECHNOLOGY REVIEW CUSTOM + DIGILANTACKNOWLEDGMENTS

They need those kinds of campaigns to build brands and create demand for their products beyond their existing customers.

Big data provides a way to analyze existing customer activity and identify similar audiences that can be targeted. Targeting can substantially increase time-liness of advertising and responsiveness to it. Big data also makes it possible to plan marketing campaigns aimed at particular types of buyers and to serve customized creative content to more users in the sales funnel.

Big data even provides a way for mar-keters to recognize a user across devices,

allowing marketers a more holistic view of their customers.

Nevertheless, the digital world doesn’t give marketers perfect knowledge. It’s important to understand the limits that digital marketers face and to plan cam-paigns around them. Properly under-standing what programmatic buying partners and networks can do to incre- ase online conversions and to protect against fraudulent activity, will enable marketers to better allocate their budgets to drive results. Awareness of the ways that advertisers can be misled about their campaigns

can provide guidelines for smarter plan-ning and buying: by knowing what can go wrong, advertisers can ask the right questions so that things go right.

According to a recent eMarketer study, U.S. adults currently spend 47 per-cent of their viewing time with digital media, exceeding the 36 percent of their time spent with television. Marketers have to be where the people are. Working with companies and consultants that truly understand the technology can help them develop customized programmatic adver-tising strategies that create new opportu-nities to reach their customers.

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