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CTV/OTT viewership has been ballooning for the last few years. As of Q3 2020, streaming services have attracted 72% of U.S. internet users (appx. 215 million people) and in 2021, the volume of ad spending across CTV channels will increase to $11.36 billion. These facts make the CTV ad market, with its immense capitalization, an irresistible lure for both publishers and advertisers.
Today, digital TV is capable of running programmatic campaigns, which translate to targeted advertising on CTV/OTT. As a result, marketers are now looking at the issue of accurate calculations in this space. To perform efficient advertising campaigns, among other things, market players need data-driven reports and analysis to be able to estimate outputs and engage in strategic planning. We, at VlogBox, are on our way to power up CTV solutions with all necessary analytics tools for higher marketing results and hope to introduce the first adoptions quite soon. So let's go through the key aspects.
YouTube and Netflix have taken up pole positions on the ecosystem chart with bold market shares of 20% and 34% accordingly, making them the most-watched online video platforms in the U.S. as of Q2 2020 by Nielsen research.
According to an eMarketer study, it’s expected that YouTube is expected to generate $5.45 billion in ad revenue in total by 2022, increasing its market share of the U.S. CTV ad spend by up to 38.7%. A higher number of viewers are now watching YouTube content via big screens, while mobile device viewing rates have fallen from 49.0% in Q4 2019 to 40.9% in Q3 2020. And that’s no surprise - this consumer behavior is definitively explained by the pandemic.
Meanwhile, Emarketer indicates that ad revenues from advertising on YouTube are estimated at $4.04 billion as of 2020 (+17.8% YoY), and forecast to hit $6.87 billion by 2022. Therefore, the general trend of CTV consumption is ascending. If this trend continues, CTV viewership rates will soar.
Running profitable video ad campaigns, including on YouTube platform, requires an analytic approach. Currently, the industry already offers some metrics, measurement and attribution for brands and media owners.
Every advertising campaign needs definite measurements to help brands to estimate the efficiency of their marketing activities. One of the most common metrics here is ROAS (return on ad spend). With its help, advertisers can calculate how much money they stand to earn for every single dollar invested.
The ROAS formula provides general performance results, yet it can’t provide precise data per person – only per device user. For instance, one household can be CTV-plugged with one account, but this account might be used by every family member. Hence, an advertiser receives data concerning one TV set, while it’s actually being used by different people. This is a crucial fact, as in most cases family members come from different generations, and it takes customized marketing tactics to attract each cohort. At this point, achieving granular metrics is one of the critical roadblocks within the Addressed TV measurement challenge. Digital marketing experts forecast that artificial intelligence will serve to discover new audiences for programmatic advertising. The development of this technology is designed to bring the industry a new, more data-driven reporting and analytical approach.
Besides the ROAS metric, which allows marketers to understand if their ad campaign generates clicks and leads, there is also a ROI (return on investment) metric. The key difference between them is that ROAS can tell an advertiser if ads drive revenue, while ROI encompasses all operational costs and can predict whether the company can generate a profit from the money spent. Hence, brands would be wise to use both metrics to get a more detailed picture of their business results.
The growing trend in streaming video consumption has prompted marketers and publishers to look for a way to optimize their operational activities. Reporting data is essential in achieving that goal. But creating valid analytics for CTV campaigns is not that easy. The immaturity of standardized measurements and attribution within the technology can sometimes result in data distortion, which can lead to mistaken decisions.
To improve the situation, the IAB has offered to unite the industry and focus on technical standardization. Synergistic collaboration with standard-bearers like Coalition for Better Ads (CBA), Digital Advertising Alliance (DAA), Media Rating Council (MRC), Trustworthy Accountability Group (TAG), World Wide Web Consortium (W3C) and other industry behemoths intends to distribute a unified approach across the ad tech industry.
The problem of different metrics that different platforms use for their reports was recently described in a Netflix case study.
While there remains much work to be done regarding accurate data reporting on ATV, there are still some measurement solutions that media buyers and sellers have at their disposal:
Completion rates. This metric shows the timing of a video ad that ran in the video player of a concrete platform or website. Simply put, it’s data that allows marketers to see if their commercial (or, non-commercial) clip was played within a user’s browser, and see the timing details.
On one hand, this can help advertisers to understand if their ad is interesting and if people are engaged with the product/service being promoted. On the other hand, advertisers also want to know if the ad was actually seen by a prospect, or, it was just played without garnering attention. This is a problem that ad tech currently has no definitive answer for.
Conversion. This one is way more approachable. When impressions turn into a purchase, a marketer can see whether their video ad was successful. Advertising on CTV/OTT via comprehensive online video platforms allows brands to summarize the exact output of a video ad campaign. This metric embraces both online and offline purchasing.
If a user clicks on a link embedded into a video ad and goes to an online shop, that event is trackable – meaning that an advertiser can make a proper record for his sales report. At the same time, by using geofencing, brick-and-mortars businesses can lure prospects to shop shelves and accurately estimate the impact of ads by tallying up shop visitors. For marketing purposes, shop owners can then make questionnaires for customers, and ask how they became aware of the store.
Advertisers and publishers can also power up their reporting capacities by integrating CTV/OTT attribution and analytics software from external tech vendors. Such software allows seeing which ads work best, and can build a comprehensive picture of the entire customer journey by tracking events from the impression to purchase. Embracing extra analytics can help to uncover the precise details in a given funnel. Publishers can monitor app installs and new sign-ups, and receive insights that can ultimately increase their CPM rate. Attriboost, Kochava, AppsFlyer are just a few examples of this kind of software.
CTV advertising is also fueled by ACR (automatic content recognition technology). Similar to the audio fingerprinting approach that is used by Shazam, CTV applies video fingerprinting that allows marketers to see what kind of content a user watches, and to deliver their brand impression if it resonates with the company’s product or service.
For instance, if a user often watches travel shows, it’s quite reasonable for a travel agency to offer him some travel tours. In such a case the conversion rate is likely to be high. With such a targeted approach, it’s possible to measure sales via TV ads accurately. However, the problem here is that the user of ACR has to opt in, and a CTV/OTT device has to support such technology. This makes it a limited solution that only covers a part of the audience. But as time passes, ACR might become more ubiquitous, so sooner or later it should become another standard by default.
Despite the fact that TV marketers can use attribution solutions as well as ROAS and ROI metrics for statistics and reporting purposes, the ad tech industry still has to address the challenge of standardizing measurement and attribution. Collaboration between industry leaders and international organizations like the IAB and MRC are likely to drive the solution. Until then, advertisers and publishers need to pay close attention when choosing a business partner or tech vendor, as their preferred tools can affect the campaign’s overall results dramatically.