Measurement and Attribution in CTV: 2022 Trends

Industry InsightsMeasurement and Attribution in CTV: 2021 Trends
Table of contents

    In the third quarter of 2020, over 200 million people were using streaming services – that’s just in the US, representing more than 70% of the entire country’s population. Another milestone was reached just a couple of months later, when the total ad spend volume across the CTV environment reached over $11.3 billion. This makes an already attractive field for publishers and advertisers even more lucrative.

    Now, with all the benefits brought by programmatic advertising, marketers are able to set up highly targeted and easily manageable campaigns. One of the main tools that ensure strategic planning are data-driven reports and analytics. VlogBox is a platform that gathers all these tools in one place – from powerful marketing features to deep analytics. Let’s take a closer look at them!

    YouTube and Netflix are the main CTV drivers

    YouTube and Netflix are leading the charge in the Advanced TV environment. These OTT (over-the-top) services hold 20% and 34% of the entire market respectively, judging by the number of daily viewers in the US provided by Nielsen.

    YouTube will evidently generate almost $5.5 billion in ad revenue by the year 2022 according to eMarketer, boosting its total CTV ad spend share to almost 40%. Remarkably, ‘big-screen’ YouTubing is getting bigger, while the leader, mobile, has fallen by nearly 10% of the total share (from 49% in 2019 to 40.9% in 2020). This shift in consumer behavior resulted mainly from COVID lockdowns and may likely remain this way for a while longer.

    YouTube ad campaign efficiency obviously relies on an analytic approach, and the industry already provides metrics, stats, reports, and other details necessary to that end.

    KPIs for CTV advertisement

    Some decades ago, marketing campaigns could take weeks and months before advertisers saw a noticeable return on their money. Nowadays, brands can estimate the efficiency of their activities with just  a couple of clicks. CTV advertising is a prime example of that responsiveness.

    One of the main metrics to highlight is the return on ad spend (ROAS). Even though it can’t deliver precise data for each viewer, ROAS provides a hint on how campaigns perform in general. The thing is, CTV is the type of ad medium that is typically used by multiple people. A single account is used by parents, kids, and sometimes even by older family generations. This means that we can still measure the metrics for one account or household, but it takes a slightly different approach to distinguish individual users.

    Other than ROAS, marketers might also use the return on investment (ROI) metric. The latter can illustrate how much pure revenue ads ultimately bring, though it requires much more time to report. ROI counts all operational expenses and answers the main question: whether those ads have generated additional revenue, or not.. Normally, brands will use both metrics to get a more extensive picture of their business operations.

    Concerns of CTV measurement and attribution

    The growth the CTV industry has experienced has inevitably pushed both publishers and advertisers to seek reliable ways to optimize their operations, which requires precise reporting. However, there are some complications when it comes to gathering statistics, as obtaining CTV campaign analytics is not always straightforward.

    Basic measurement and attribution techniques lack precision and sometimes can cause data distortion. In order to solve this issue, the IAB proposed adopting a unified technical standardization across the industry. This resulted in a transformation of the conventional ad tech approach among organizations like the World Wide Web Consortium, the Digital Advertising Alliance, the Coalition for Better Ads, and the Trustworthy Accountability Group.

    Obviously, there are still significant problems to deal with, but the industry is collectively working to resolve them. For instance, generally accepted measurement metrics have been established to be used by media buyers in their reporting. Here’s a list of the most popular metrics:

    Completion rates. Completion rate shows the percentage of completed video ads, i.e. the number of people who watched the ad entirely. This information helps marketers to understand if a given ad is engaging enough, gain insights into general ad-watching behavior, and develop a better video advertising strategy. The problem with this particular metric is that it’s almost impossible to distinguish if those impressions were actually seen and interacted with, or just played with no actual attention paid by the viewer.

    Conversion. Ad impressions are meant to drive sales. And when a brand notices significant sales growth, you can often tell that an ad investment was worth it. As a result, conversion is the metric for summarizing the outputs of a given ad campaign for both offline and online purchasing. When a user commits an action, say, one follows a link in an ad, marketers can track this event and based on that information, draw accurate conclusions. For example, using geofencing, shop owners can estimate the correlation between ad interactions and physical store visits.

    There are also software solutions that can automatically analyze data and power up CTV/OTT reporting capabilities. With these tools at hand, marketers can clearly see which ads perform better and which need modifications. In addition, software can track activities from the initial impression to the final purchase, and draw customer journey maps. This can help build more effective marketing funnels. Attriboost, AppsFlyer, and Kochava are among the best examples of CTV ad measurement software.

    Another promising CTV ad feature is automatic content recognition (ACR). This technology uses machine learning algorithms to analyze video content, and is able to identify differing attributes of that content. Not only does this allow marketers to know exactly what kind of content viewers are watching, but it can also implement interactive buying capabilities. Some brands use ACR to promote and sell their products directly through video players. The technology can recognize an object in a video, for example a jacket, and can offer the viewers a call-to-action to purchase the same jacket online. ACR technology opens up vast targeting capabilities for marketers, as knowing what kind of content viewers are into can provide us with information on what ads are most likely to be effective.

    Conclusions

    Connected TV marketers can use various CTV measurement techniques like ROAS and ROI to collect statistics on their marketing activities, and can base their reports on relevant and precise data. However, there are still issues to address. For instance, standardizing metrics is a collective ad tech responsibility to ensure an easy-to-use and easy-to-measure environment. But before we enter the bright future of advertising, we need to know exactly how to measure CTV ads with the tools available to us now. This requires extra attention from media buyers and publishers when cooperating with tech vendors, since their marketing tools and metrics will impact ad performance and reporting differently.