Luth Research Whitepaper Tracking Digital Ads: Facing Up to the Challenges 6/10/2014 Prepared By: Becky Wu, Ph.D. Sr. Executive Vice President Research Luth Research, Inc.
Digital advertising measurement technologies have evolved significantly in recent years. As the industry responsible for quantifying the value of advertising, we have advanced from earlier paradigms, including last-‐click attribution. However, the practice is not getting easier as the current ecosystems in which ad measurement research take place are laden with fragmented technological capabilities, non-‐standardized metrics, and varying privacy concerns. To begin solving these problems, the first step is to become crystal clear and cognizant about the leading challenges for the methods available today. Three areas warrant a more widely participated discussion. The foremost area is accuracy of tracking individuals associated with ad exposure and their ensuing activities. While it sounds easy, many popular tracking methods are unable to identify the individuals accurately. Cookie tracking is subject to cookie deletion and duplication. Digital fingerprinting, a newly emerging technique, takes device types, operating systems, IP addresses, and other device configuration attributes into consideration while turning these inputs into a statistical estimation to determine the same or different persons. These estimations are often subject to false matching due to switching between mobile network and Wi-‐Fi IP address assignment, which is a common event with Apple device configuration. The second area relates to the essential goal of advertising tracking – to gauge advertising’s full impact. While we have moved beyond the last-‐click mindset, we haven’t been able to have enough visibility into post-‐click/post-‐impression behaviors to do this job right. The most prevalent tracking mechanism, cookie tracking, has been used to determine ad exposure/impression, and post ad conversion if the conversion happens within a relatively short period of time following the exposure. This approach does not offer the ability to observe and capture the lion’s share of the individual’s digital activities that can be relevant to ad impact. An individual’s visits to websites of interest, searches, video views, and purchases related to the brand and its competitors are left out from this process. Adding to the mix of challenges is mobile tracking, which is increasingly critical to marketers. The mobile environment’s biggest drawback is its absence of standardization in abilities to track because it lacks the more established tracking mechanisms found in the PC digital world. Cookie tracking is not feasible with
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mobile apps. iOS has shifted from Universally Unique Identifier (UUID) to Advertising ID, which is created uniquely for each individual user. It can be reset by the user and Apple policy prohibits its integration with other data sources to mitigate privacy concerns. The Advertising ID is often employed to tie app downloads to individual users. On Android, advertisers can use Android Referrer to accomplish a similar goal. However, neither feature can adequately address the need to track in-‐app advertising, where ads are dynamically distributed across vast and diverse mobile apps. Heeding the above complex issues, Luth Research’s ZQ Intelligence™ digital behavior tracking technology presents an opportunity for fresh thinking in advertising measurement. At its very core, ZQ’s ad tracking technology consists of two components: 1) the ability to identify ad tags that are generated for ad creatives when they are being served, and 2) the ability to collect the user’s digital data across browsers, operating systems, and devices. Because each ad creative must have a unique ad tag in ad serving, detecting the ad tag is the surest way to accurately pinpoint if and where the ad is being shown to the user across publishers and ad networks. This detection mechanism is not effective without ZQ’s holistic digital behavior data collection. After a user has downloaded the tracking technology, ZQ captures granular http/https requests and responses from both PC and mobile devices. Specifically for mobile, ZQ enables unified data collection across iOS and Android, and across mobile web and mobile app. The ad tag identification is performed for the target ads within this digital data with tremendous depth and breadth. More importantly, ZQ makes it possible to directly correlate the individual’s ad tag exposure(s) with his/her other digital activities collected 24/7 and over time with user permission. Hence, post-‐click/post-‐impression attribution is no longer an unattainable ideal for ad measurement. Luth Research’s ZQ Intelligence offers a powerful alternative in tracking advertising impact. Its advantages lie in being platform agnostic, breaking down ecosystem fragmentation, precise ad detection, deep in-‐app ad visibility, and providing a single-‐source view of the entire consumer digital journey. Unprecedented challenges call for critical thinking and willingness for marketers to step outside of the traditional toolkits. With its distinct benefits, ZQ helps marketers unleash the true potential of digital marketing with clarity and accountability.