In 2022, Google began changing the availability of the information available in User-Agent strings across their Chromium browsers. The change is to use the set of HTTP request header fields called Client Hints. Through this process, a server can request, and if approved by the client, receive information that would have been previously freely available in the User-Agent string. This change is likely to have an impact on publishers across the open web that may use User-Agent information today.
To explain what this change means, how it will impact the AdTech industry, and what you can do to prepare, we spoke with Nate West, our Director of Product.
What is the difference between User-Agents and Client Hints?
A User-Agent (UA) is a string, or line of text, that identifies information about a web server’s browser and operating system. For example, it can indicate if a device is on Safari on a Mac or Chrome on Windows.
Here is an example UA string from a Mac laptop running Chrome:
To limit the passive fingerprinting of users, Google is reducing components of the UA strings in their Chromium browsers and introducing Client Hints. When there is a trusted relationship between first-party domain owners and third-party servers, Client Hints can be used to share the same data.
This transition began in early 2022 with bigger expected changes beginning in February 2023. You can see in the above example, Chrome/109.0.0.0, where browser version information is already no longer available from the UA string on this desktop Chrome browser.
How can you use User-Agent device attributes today?
UA string information can be used for a variety of reasons. It is a component in web servers that has been available for decades. In the AdTech space, it can be used in various ad targeting use cases. It can be used by publishers to better understand their audience. The shift to limit access and information shared is to prevent nefarious usage of the data.
What are the benefits of Client Hints?
By using Client Hints, a domain owner, or publisher, can manage access to data activity that occurs on their web properties. Having that control may be advantageous. The format of the information shared is also cleaner than parsing a string from User-Agents. Although, given that Client Hints are not the norm across all browsers, a long-term solution may be needed to manage UA strings and Client Hints.
An advantage of capturing and sharing Client Hint information is to be prepared and understand if there is any impact to your systems and processes. This will help with the currently planned transition by Google, but also should the full UA string become further restricted.
Who will be impacted by this change?
Publishers across the open web should lean in to understand this change and any potential impact to them. The programmatic ecosystem supporting real-time bidding (RTB) needs to continue pushing for adoption of OpenRTB 2.6, which supports the passing of client hint information in place of data from UA strings.
What is Google’s timeline for implementing Client Hints?
Do businesses have to implement Client Hints? What happens if they don’t?
Not capturing and sharing with trusted partners can impact capabilities in place today. Given Chromium browsers account for a sizable portion of web traffic, the impact will vary for each publisher and tech company in the ecosystem. I would assess how UA strings are in use today, where you may have security concerns or not, and look to get more information on how to maintain data sharing with trusted partners.
We can help you adopt Client Hints
Reach out to our Customer Success team at tapadcustomersuccess@experian.com to explore the best options to handle the User-Agent changes and implement Client Hints. As leaders in the AdTech space, we’re here to help you successfully make this transition. Together we can review the options available to put you and your team on the best path forward.
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About our expert
Nate West, Director of Product
Nate West joined Experian in 2022 as the Director of Product for our identity graph. Nate focuses on making sure our partners maintain and grow identity resolution solutions today in an ever-changing future state. He has over a decade of experience working for media organizations and AdTech platforms.
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In our Ask the Expert series, we interview leaders from our partner organizations who are helping lead their brands to new heights in AdTech. Today’s interview is with Samantha Zhang, Senior Data Scientist, and Jim Meyer, General Manager of the DASH TV Universe Study at the Advertising Research Foundation (ARF). DASH is an annual tracking study conducted by the ARF to define and better understand TV audience behavior and household dynamics. What does DASH measure, and how does it help the industry understand TV consumption today? By capturing hundreds of individual- and household-level data points from each respondent in a rigorous and nationally projectable sample, DASH creates a comprehensive picture of U.S. consumer TV “infrastructure” – how America watches. Core elements in DASHElements that create context in DASHTV setsLocation | brand | smartness | service modes | sources DemographicsConnected devices Game consoles |video players | streaming devicesYesterday viewing Daypart | TV/device genre | Out-of-home viewingMobile devicesOwners | sharing usersShoppingOnline and in-store | Exposure to major RMNsInternet serviceModes | ISPs | connectivity by device Streaming audio Streaming TVSVOD/AVOD tiers and sharing | FAST Email accounts and apps Live TV Modes of access | including casting from devices Social media For example, DASH gathers: Data on every TV set, including brand, room location, age, “smartness,” and connection devices and modes Household connectivity and video service data, even in homes with no TV set Internet Service Providers (ISP) and TV service usage, including Multichannel Video Programming Distributors (MVPDs), virtual vMVPDs, streamers (ad-supported and premium), and Free Ad-Supported Television (FAST) channels Person-level ownership and usage of video-capable mobile devices, including smartphones, tablets, and laptops Measures of viewing and co-viewing across dayparts, devices, and services Additional modules covering shopping and retail media networks, streaming audio, social media, email, and apps Broad coverage and granularity make DASH a uniquely robust source of truth for practitioners across the industry, including measurement experts and ad programming strategists. DASH also reports regularly (and publicly) on key industry dynamics. DASH identified a growing segment of device-only viewers – now nearly 9 million households that watch TV, but do not own a TV set – and highlighted the implications of that trend for traditional ratings systems based only on households with TV sets. Households (HHs – million)2025 HHs (M) U.S. penetrationChange vs. 2024 (M)Total US134.8100%+2.7Connected TV (CTV)114.685%+2.1TV (Set)124.292.2%+1.1Device-only8.86.6%+1.6TV-Accessible133.198.7%+2.7 DASH called out the rise in app-based pay TV and proposed a new connection framework that better represents the modern TV world, in which linear and streaming overlap. DASH also defines the universes of households reachable with advertising. This graphic, for example, shows how all ad-supported linear and streaming properties in aggregate define the true scale of TV advertising. While 35 million households (and growing) are reachable only with streaming ads and 13 million (and falling) only with linear ads, most households are reachable with both, underscoring the importance of understanding the “overlap.” Who uses DASH data, and what decisions does it help inform? There are three primary users of DASH, each with its own use cases: Measurement providers, including Nielsen, use DASH to calibrate viewership data, turn household data into persons data (and vice versa) and estimate potential reached audiences–what the providers call media-related universe estimate (MRUEs)–for the calculation of ratings. Not surprisingly, measurement companies were the first to see the value that an independent TV universe study could provide. Media companies, including major broadcasters and streamers, use DASH to add context and color to their ad sales presentations – and to track the measurement providers, whose ratings play a major role in valuing ad inventory. AdTech companies, including Experian, use DASH to create high-value audience segments for activation. The recent accreditation of DASH by the Media Rating Council (MRC) and adoption by Nielsen as an input to its TV ratings have generated interest from a broad range of companies. We are actively pursuing new licensees and partners to make DASH more useful within, and even outside, the TV ecosystem. What does MRC accreditation signify, and why is it meaningful for DASH? MRC accreditation means DASH passed a rigorous audit conducted by Ernst & Young over many months, which validated our methodology, controls, and data quality. MRC accreditation establishes that DASH is an industry-standard dataset. While the service provider normally announces its own accreditation, the MRC took the unusual step of issuing its own release on DASH, announcing the accreditation of DASH for TV universe estimation and endorsing the study for broader, cross-media use. How does Experian use DASH data to build audiences? The segments combine specific TV usage habits and behaviors from DASH with Experian data on demographics, spending, and other contextual inputs to create a fuller view of consumer viewing behavior. They are designed to be valuable to advertisers in many categories and planning contexts – and to be customizable to fit advertisers’ media targets. The segments can be used to: Apply or suppress audiences to improve target coverage across a campaign Better align media and creative Reach elusive but high-value viewers, such as Ad Avoiders Drive valuable consumer behavior Achieve specific advertising objectives What are some practical use cases for DASH-based audiences? Here are some practical use cases for four different kinds of DASH segments in five different advertiser categories. Travel Co-WatchersA couples-only resort uses TV Co-Watching Households without Children to strengthen target reach and ad memory recallA big theme park destination uses TV Co-Watching Households with Children to reach families in moments of togetherness Home Entertainment TV Owners and Brand LoyalistsA premium TV manufacturer uses the overlap of Multi Brand TV Owners and Single Brand TV Loyalist Households to market its newest TV model to its most loyal consumers. Fast Food Screen Size ViewersA fast food chain with a high-impact new brand campaign uses Large Screen TV Viewers to better align the media and creativeThat same fast food chain uses Small-Screen TV Viewers to drive store traffic by increasing exposure of its retail campaign among on-the-go viewers Financial Services Cord Cutters A personal cost management app and a cash-back credit card target Streaming-First Cord Cutter Households to reach young, tech-savvy, cost-conscious consumers Thanks for the interview. Where can readers learn more about DASH? We started work on DASH seven years ago, and it’s been fun to watch it “grow up.” Our partnership with Experian is a big step toward putting DASH to work for advertisers and agencies. To learn more, visit our site at https://theARF.org/DASH or contact us at DASH@theARF.org. Contact us About our experts Samantha Zhang, Senior Data Scientist at ARF Samantha Zhang is a Senior Data Scientist at the Advertising Research Foundation working on the DASH TV Universe Study, with additional research spanning areas including attention measurement, digital privacy, and artificial intelligence. Jim Meyer, General Manager, DASH, at ARF Jim Meyer is general manager and co-founder of the ARF DASH TV Universe Study and managing partner of Golden Square, LLC, which advises media and research technology companies on growth strategy and development. Latest posts
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