CTV viewership continues its upward trajectory, growing both in terms of number of viewers and time CTV viewership continues its upward trajectory, growing both in terms of number of viewers and time spent consuming content.
According to the latest Comscore State of Streaming data, CTV usage continues its rapid ascent — by 2025, 96.4 million U.S. households were streaming content on connected TV devices, with total streaming time reaching 13.9 billion hours. This 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 2026: 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 “kids watch cartoons” and “adults watch the news.”
- Time of day: Day parts 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.
Then vs. Now
While linear TV relied on content, time of day, and geography as proxies for audience targeting, modern CTV advertisers expect deterministic and real-time signals. They want to understand not just what content was viewed, but where the viewer was located, what device was used, and whether the impression was valid. This shift in expectations highlights the growing gap between legacy TV buying models and digitally driven CTV strategies.
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 while IP address signals have historically supported location targeting in digital advertising, they are often inconsistent, obfuscated, or missing in programmatic CTV bid streams — making location 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. This absence of reliable geographic signals in the programmatic CTV ecosystem has created what many advertisers refer to as a “location gap,” where ads can be served without consistent insight into where or to whom they were actually delivered. Simply put, the location gap occurs when ads are delivered without consistent or dependable insight into where — or to whom — they were actually served.
While some platforms can derive household identity and enhanced geographic signals through authenticated logins and cross-device graphs, these capabilities are not universally available. Across the broader programmatic CTV ecosystem, such signals remain fragmented and inconsistent, allowing the location gap to persist.
As a result, advertisers and their agencies know there are hundreds of data variables they should be able to use for targeting, measurement, and optimization but often cannot, 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. ACR is opt-in and powerful on smart TVs, but coverage is uneven across device types. Data availability varies by provider and location often isn’t consistently available in a usable form.
- 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’s rapid acceleration during the pandemic years. In response, CTV platforms, verification providers, and measurement companies have continued to introduce new approaches — though challenges around consistency, transparency, and standardization remain.
For digital advertisers, CTV measurement feels opaque because it lacks the transparency, consistency, and interoperability they expect from other digital channels. Performance data is fragmented across platforms, measurement methodologies vary widely, and buyers often have limited visibility into how audiences are defined or impressions are validated. This disconnect makes it difficult to compare CTV performance to channels like display, search, or social.
In some cases, the old way of measuring TV is being shoehorned into CTV. This is an 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, advertisers 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 often 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, 2026 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.
In 2024, bot fraud made up 65% of all fraud in CTV environments; a share significantly higher than in other digital channels.
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 greater visibility into residential IP proxy networks to safeguard premium CTV inventory and support accurate household targeting. These networks can obscure fraudulent activity, undermining advertiser trust and complicating efforts to validate real audiences.. When fraudulent traffic is masked behind residential IP proxy networks, it can contaminate premium CTV inventory, reduce advertiser confidence, and make it harder to distinguish legitimate household viewers from automated or coordinated fraud schemes.
This leads to a defining trend for CTV advertising in 2026.
Solving challenges related to location accuracy, fraud detection, and audience validation requires high-quality IP intelligence that can operate at scale across fragmented CTV environments.
What Comes Next for CTV Advertising
As CTV matures, the conversation is shifting from rapid growth to long-term sustainability. Advertisers are no longer evaluating the channel solely on reach or scale, but on whether it can deliver the same level of accountability they expect from other digital media investments.
The next phase of CTV advertising will be shaped by how effectively the ecosystem addresses structural blind spots — particularly around geographic validation, impression legitimacy, and cross-platform comparability. Solutions that bring greater clarity to these areas will help reduce friction between buyers and sellers and support more confident budget allocation.
Rather than relying on legacy TV constructs, the industry is moving toward data-driven approaches that better reflect how streaming content is consumed and monetized. As this shift continues, trusted data foundations and verification capabilities will play an increasingly important role in establishing consistency and rebuilding confidence across the CTV supply chain.
The Data Backbone Advertisers Can Trust
This evolution is already underway, and the progress made in 2026 will define how CTV is measured, valued, and trusted moving forward. Digital Element helps make that progress possible by delivering the data foundation the CTV ecosystem depends on.
Through consistent geographic validation, household and device context where available, and advanced detection of VPNs, proxies, and residential proxy traffic, our Digital Element products bring greater accuracy and accountability to programmatic CTV. Combined with supply-path transparency and alignment with verification standards, these capabilities enable advertisers to measure performance with confidence, validate delivery, and build trust at scale.
Contact us to learn more about our range of Digital Element CTV advertising intelligence platforms.
