CTV viewership continues its upward trajectory, growing both in terms of number of viewers and time spent consuming content. According to a report by MNTN, CTV now accounts for 50% of all TV hours consumed, a jaw dropping 11.5 billion hours.
What’s more, half of all households with wifi now stream TV, according to comScore, which isn’t surprising given the number of options now available to consumers to watch their favorite shows at any time, day or night, that’s convenient to them, and on any device of their choosing. Those options include ad-supported video on demand (AVOD), free video on demand (FVOD), free ad supported television (FAST) and virtual multichannel video programming distributor (vMVPD).
It’s a truism in advertising: where consumers go, brands must follow. But are advertisers reaping the full benefit of digital advertising when they buy CTV inventory? The data says no, largely due to a lack of standardized measurement and verification.
A report from Xenoss succinctly highlights the lack of common identifiers, myriad measurement methodologies, and complex device identification as key challenges. Its authors discuss the need for ad platforms to pull data from multiple sources to give a complete picture of ad performance, and the challenges of cross-media measurement and data fragmentation.
Meanwhile, DoubleVerify reports that CTV advertisers confront multiple types of ad fraud, including bot traffic, fake apps and fake traffic, and urgently need sophisticated fraud detection mechanisms to combat ad fraud in the CTV environment.
This leads us to the most notable trend for 2024: CTV advertisers will demand assurance that their ads were delivered to real people, not bots, and were seen by the right consumer or household as promised.
Lack of Measurement Stymies CTV Advertising
There’s no denying that the TV advertising landscape is in the midst of a radical transformation. Notably, projections indicate that spending for streaming ads will exceed those of traditional linear TV by 2025. Within the next three years it will account for 68% of total TV ad spend.
For its part, spending on linear TV will decline from $61.31 billion in 2023 to $56.83 billion in 2027, according to Insider Intelligence. In that same time period, CTV ad spend will grow from $25.09 billion to $40.9 billion.
So what are the implications of this shift in focus? To begin, as more ad dollars flow into CTV, the more advertisers will be confronted with the challenges of measurement and the scourge of ad fraud. Without trusted and standard tools, how will they feel confident that the impressions they pay for were actually seen by real users?
This contrasts with linear TV, which had a standard mechanism for buying and measuring TV for 50 years: Nielsen’s panels and the gross rating point (GRP).
Say what you will about the efficacy of linear TV, at least it was standardized, and enabled marketers to compare performance across all publishers.
Three Vectors for Linear TV
The linear TV framework offers three vectors for audience audience targeting:
- Content: Marketers select shows based on content — sports, soap opera, news, etc., — which serves as a proxy for the viewers’ demographics. This, of course, is based on assumptions, such as “men watch sports” and “women watch soap operas.”
- Time of day: Dayparts help advertisers match products to consumers. For instance, breakfast cereal brands target consumers while they’re likely to be eating breakfast, and fast casual restaurants show their lunch specials at noon time.
- Geography: Where a consumer is located helps advertisers hone their targeting further. For instance, a tire company will show regular tires to markets in the south, and ads for snow tires for markets likely to experience winter weather.
Measurement was done through the GRP, which is a metric for gauging the effectiveness of linear television ads. GRP is calculated based on the percentage of the total potential TV viewership that the ad reaches. Specifically, one GRP represents the ad being seen by 1% of the entire potential TV audience.
Digital Expectations for a Critical Digital Channel
The linear model doesn’t translate well to CTV for multiple reasons. To begin, day parts are no longer relevant, as anyone can watch any content at any time. And without an IP address — data that isn’t transmitted in the programmatic bid stream — location is difficult to ascertain. This issue grows more severe as the surge in programmatic TV continues.
There is also the issue of the ad buyer’s expectations. CTV is a digital channel, and its inventory is traded by people who are steeped in the digital landscape. They are marketers who are accustomed to a plethora of attributes for targeting, measuring and optimizing campaigns. These advertisers, and their agencies, are well aware that they are hundred of variables that they should be able to leverage, but can’t, including
- IP location address, and all the insight that surrounds it, including locations down to the +4 ZIP code, home vs. business, mobile carrier, device type, among others.
- Time spent watching TV, when did they stop watching TV. While automated content recognition (ACR) data is fully opt-in and records both the content and ads played on a smart TV, CTV is consumed on many other device types — computers, tablets or phones — that don’t support it. This reality means there is a gaping hole in measurement. Additionally, ACR data doesn’t capture the location of the viewer, which is a critical data point for marketers.
- Precise audience segmentation based on demographics and psycho-demographics (e.g. users in these households who love fashion, or east coast moms who shop at Trader Joes). The city, neighborhood and block can contain a great many types of consumers, which is why digital advertisers place a premium on creating unique audience segments.
- Tracking and attribution. Advertisers are keen to track the outcomes of their ad spend. Of the users who saw their ads, how many visited the website or retail outlet? How many conversions or sales did the ad spend generate?
The State of CTV Measurement
CTV measurement has been a topic of concern for advertisers since the channel took off during pandemic-era lockdowns. In response, many CTV and measurement companies are starting to bring solutions to the market. The challenge is that these solutions vary from platform to platform, making it difficult for advertisers to compare performance across channels. They want standardization in measurement, and are increasingly vocal about that demand.
In some cases, the old way of measuring TV is being shoehorned into CTV. This is an extremely important point, because buyers say they don’t trust such methodologies. That lack of trust, in turn, is putting a damper on ad spend, preventing it from reaching its full potential.
How do we build trust in CTV measurement? We need to resolve the complexities in the current CTV landscape, which include:
- A lack of common identifiers. CTV measurement lacks common identifiers, making it difficult to track and measure ad performance across different platforms and devices.
- Data fragmentation. Advertisers have little visibility into where their CTV ad runs and who they reach, due to highly fragmented data. This, in turn, makes it difficult to measure and track campaign KPIs.
- Inconsistent measurement. Unlike the GRP, CTV is plagued with Inconsistent measurement practices. What’s more, advertisers don’t have transparency into how audiences are measured and how outcomes are attributed to ad spend.
- Opaque practices. Ad buyers often think they’re buying premium CTV inventory when, in fact, it can be less than premium or even fraudulent.
The bottom line is that CTV measurement today faces significant challenges for marketers who are accustomed to digital campaigns. At present, CTV can’t accurately determine whether the intended audience for an ad is indeed the one who views it. Panels, although valuable, do not paint a complete picture, as precise geolocation is lacking. If all panels were to disclose the geographical reach of their data (which is currently not a widespread practice), ad buyers would have a standardized understanding of their viewership, even if different panel measurement companies provide varying insights. Many ad buyers already rely on multiple measurement companies, and with access to location-based data, they can better comprehend the origins of their viewers and the demographic information provided by the panel company.
Until a standardized approach to television measurement comes to market, advertising will be stymied. That said, given the increasing importance of CTV in reaching and engaging consumers, 2024 will be a year when substantial innovation occurs.
State of Fraud in CTV
Ad fraud in CTV has been a significant concern for advertisers, as nefarious players deploy deceptive tactics, such as bots or fake CTV devices to simulate viewership in order to inflate video ad impressions. In some cases, these sophisticated schemes are the work of organized crime rings.
DoubleVerify’s Global Insights Report found that bot fraud on CTV surged 69% in 2022 compared with the year prior. The number of CTV fraud schemes and variants DV detected annually has tripled since 2020.
The billions of dollars that flow into CTV advertising is irresistible to fraudsters, many of whom have significant technical skills and resources at their disposal to ply their craft. As more dollars move into the CTV space, the greater the opportunity for fraud.
Residential IP proxy networks are another issue of concern for streaming TV providers. Consumers, crime rings and VPNs seeking to circumvent digital rights management (DRM) restrictions are leveraging residential IP proxy networks to circumvent geo-restrictions, a topic we’ve covered in the past. Quality teams need to get a handle on residential IP stuff in order to improve/home targeting.
Our prediction: 2024 will be a year of anti-fraud innovation in the CTV space.
CTV is a critically important channel, so we can expect to see more innovation in both measurement and fraud detection and mitigation. For this reason, experts in the industry are working hard to solve this challenge — Digital Element included. Stay tuned!