At A Glance
Identity resolution unifies fragmented IDs into complete customer profiles, helping companies understand their audiences and deliver personalized, privacy-compliant experiences in a cookie-light world. With Experian’s AI-powered identity resolution solution, marketers gain the scale, accuracy, and compliance to compete while making marketing more human.In this article…
Every marketer has seen it: a customer browses reviews on a laptop, adds items to a cart on mobile, then “disappears.” In reality, they just likely switched devices or logged in with a different email. Identity resolution connects these scattered signals into a single profile so you never lose sight of the customer journey.
Identity resolution is what helps you keep track of customers who bounce around.
Connecting scattered signals into a single customer profile can help you deliver seamless experiences, meet strengthening privacy standards, turn first-party data into measurable results, and fuel better customer analytics.
See our identity resolution solution in action
What is identity resolution?
Identity resolution is the process of pulling together the different identifiers a customer uses and connecting them to a single profile. Without it, you’re left with an incomplete picture of the customer — like a cart tied to one email, an app login tied to another device, or a loyalty swipe that never links back to the same person.

Common identifiers include:
- Cookies: Short-lived browser data
- Emails: Plain-text and hashed
- Device IDs: Mobile advertising IDs (MAIDs) or app-based identifiers
- Loyalty IDs: Program numbers that tie online and offline activity
- Hashed PII: Personally identifiable information (PII) encrypted for privacy
Ultimately, identity resolution can help you recognize the same customer wherever they engage.
Why does identity resolution matter now?
Marketers face incomplete views, data silos, privacy regulations, and shrinking visibility:
- Rising consumer expectations: People want seamless, personalized journeys across touchpoints.
- Privacy-first environment: Consumer privacy legislation (like the GDPR, CCPA, GLBA, FCRA, and new state laws) makes compliance non-negotiable.
- Signal loss: The decline of cookies, MAIDs, and walled gardens are pushing brands toward first-party data.
Experian utilizes AI and machine learning to fill these gaps, predict behaviors, and connect signals across devices — providing marketers with a clear, privacy-safe view of their customers, even when traditional identifiers are missing.
In this environment, identity resolution matters because it gives marketers a way to deliver seamless, personalized customer experiences and engage audiences effectively while respecting their privacy. It’s the basis for turning consented first-party data into measurable marketing outcomes without sacrificing trust.
Why is identity resolution critical in a privacy-first world?
Even as cookies linger, marketers have already shifted their strategies to rely on first-party data, where choice and transparency are the baseline expectation. At Experian, our long history as a regulated data steward makes us a uniquely capable and trusted partner for managing modern compliance expectations. Our identity resolution solutions maximize the value of permission-based data while meeting consumer demand for privacy, personalization, and control.
Struggling with scattered customer data? Experian makes identity resolution seamless
How does identity resolution help brands?
Identity resolution turns fragmented signals into unified profiles that drive personalization, efficiency, and compliance. Here’s how it creates measurable business impact.
Creates a unified customer view
One of the biggest advantages of identity resolution is the ability to integrate data from loyalty programs, point-of-sale (POS) systems, customer relationship management (CRM) platforms, web analytics, and offline sources into a single, comprehensive profile. Experian strengthens identity resolution with AI-driven clustering models that resolve household and individual identities across billions of signals with greater accuracy.

With a clearer picture of each customer, brands see higher match rates and larger addressable audiences, which translates to more substantial reach and better return on ad spend (ROAS).
Enables better personalization
Customers constantly switch devices, update their information, and change preferences. Experian makes it easier to keep pace with these changes through frequent data enrichment and near-real-time identity resolution via Activity Feed.
Combined with our long-standing use of AI and machine learning, this approach ensures shifting behaviors are captured quickly, enabling timely personalization, and more responsive engagement.

With less delay from data to action, the result is faster response times and higher conversion rates.
Improves the customer experience
Customers notice when brands deliver relevant ads and contextual content across every channel. Consistency matters! But consistency doesn’t just happen on its own; it comes from identity resolution, which keeps the customer journey connected.

As brands maintain continuity, they build trust, strengthen engagement, and increase customer lifetime value.
Drives better marketing ROI
Not every profile is valuable. Identity resolution helps marketers identify the highest-value audiences and reduce wasted spend.

That efficiency leads to lower CPA and a higher overall ROI across campaigns.
The power of modeling from a stronger foundation
When you have a unified customer view, your models are built on better data. That means you can find more people who look like your best customers, build more responsive audience segments, and target with greater accuracy. This foundation can lead to better spending, more relevant campaigns, and a higher ROI.
Maintains privacy compliance
With GLBA/FCRA-grade standards and consumer choice mechanisms like opt-outs and data correction, you can protect your brand while maintaining personalization — without compromising legal or ethical safeguards.

What are some identity resolution use cases and examples?
Every industry faces its own unique identity challenges, but identity resolution is the common thread that turns scattered data into connected experiences. Let’s break down how companies in different verticals are putting it to work (and the kinds of results they’re seeing).
Retail and e-commerce
Shoppers bounce between websites, carts, and checkout lines, leaving behind scattered signals in the process. In retail, identity resolution bridges the gap between online and in-store experiences by matching online carts with loyalty swipes or connecting connected TV (CTV) exposure to in-store sales. This means fewer silos, better targeting, and more personalized offers wherever people shop.

Our 2025 Digital trends and predictions report calls out that omnichannel experiences aren’t optional anymore. With CTV and social dominating spend, brands need identity resolution to cut through silos and build a complete view of customer behavior.
Financial services
In financial services, identity resolution makes it possible to deliver personalized, compliant offers like refinancing options for likely mortgage switchers or the right rewards card for frequent spenders.
Our partnership with FMCG Direct to create Consumer Financial Insights® and Financial Personalities® segments helps banks, insurers, and lenders understand behaviors — such as credit card use, deposit balances, and investment habits — without exposing sensitive details.
Read more below about how our financial audiences enable privacy-safe personalization.
Travel and hospitality
Travel decisions aren’t always planned out in advance. Many bookings happen spur-of-the-moment, which is why real-time identity resolution is so powerful; it keeps the journey seamless when travelers jump from phone to laptop to tablet and presents relevant offers right as decisions are being made.
Windstar Cruises put this information into action with Experian’s identity graph to connect digital interactions with actual bookings, which drove 6,500+ reservations and $20 million in revenue.
Media and TV
Viewers tend to hop around between linear TV, streaming apps, and social feeds. And without identity resolution, every screen looks like a different person. Marketers can accurately plan, activate, and measure campaigns by unifying viewing behaviors into one ID with Experian’s AI-powered identity graph.

Optimum Media tackled its multiscreen challenge by partnering with Experian for identity solutions. Layering our audience insights and our AI-driven Digital Graph onto their subscriber data, they were able to connect the dots across channels, reach the right households, and measure results instead of just impressions. In the end, they finally got a clear view of what works across every screen.
Curious how identity resolution can power your customer analytics? We can walk you through it.
Healthcare and pharma
Healthcare marketers can’t afford slip-ups with HIPAA regulations. Identity resolution makes it possible to engage the right patients and providers with de-identified audiences rather than third-party cookies.

At Experian, AI and machine learning have always been part of how we power identity resolution. In healthcare, that means using AI-enhanced modeling to connect de-identified clinical and claims data with lifestyle insights. The result is a more comprehensive picture of the patient journey that helps close care gaps, reduce wasted spending, and improve outcomes.
By working with partners like Komodo, PurpleLab, and Health Union, we make it possible to activate campaigns at scale that boost engagement and adherence while keeping patient privacy front and center:
- Komodo Health enriches our identity graph with insights from millions of de-identified patient journeys plus lifestyle data, giving brands a fuller view of where care gaps exist and how to close them.
- PurpleLab connects real-world clinical and claims data to Experian’s platform, letting advertisers activate HIPAA-compliant audiences across CTV, mobile, and social with the ability to measure real outcomes like prescription lift and provider engagement.
- Health Union contributes a data set built from 50 million+ patient IDs and 44 billion+ patient-reported data points. Combined with our identity and modeling capabilities, this expands match rates and unlocks up to 76% net-new reach, so campaigns reach patients and caregivers in critical health moments.
As a result, healthcare brands can launch campaigns that are privacy-first, highly targeted, and proven to drive meaningful impact.
Audio
People use audio while commuting, working out, and even folding laundry. It can be one of the hardest channels to track because of how frequently listeners switch between apps, stations, and devices.

Experian’s identity resolution partnerships with Audacy and DAX change the game:
- Audacy helps tie scattered listening into a single view, so advertisers can follow audiences across devices and keep ads relevant in the moment.
- DAX pairs Experian’s 2,400+ syndicated audiences with its audio network, enabling brands to target precisely and launch impactful campaigns at scale.
These partnerships turn audio into an accurate channel where ads feel personal, privacy-safe, and measurable.
Gaming
Gamers don’t stick to one platform. Player data gets scattered across mobile, console, and PC, so it’s tough to keep track of individuals. Experian helps stitch those signals together so publishers can finally see the whole picture, personalize gameplay, and keep players coming back.
With enriched profiles, publishers can deliver offers that resonate and unlock fresh revenue by packaging high-value gaming audiences for advertisers outside the industry.
Unity, a leading gaming platform, is tapping into Experian’s syndicated audiences to gain player insights and help advertisers reach gamers across mobile, web, and CTV. For global publishers, unifying player data with Experian has driven higher engagement and stronger ad ROI.
How should I evaluate identity resolution providers?
When choosing an identity resolution partner, look for:
- Data scale and quality: The value of identity resolution depends on how complete and accurate the underlying data is. The right provider should bring together a wide range of identifiers from online and offline sources, maintaining high accuracy so your customer profiles are broad and reliable.
- Match accuracy and recency: The best partners also refresh their data regularly and can blend deterministic (exact, one-to-one matches) with probabilistic (pattern-based matches) methods. That way, you get the accuracy of “this email is definitely that customer” with the reach of “this device likely belongs to the same person.”
- Privacy and compliance readiness: Compliance can’t be an afterthought. Your identity partner should be ready for GLBA, FCRA, GDPR, CCPA, and the latest state-level rules with built-in tools for opt-outs, corrections, and deletions.
- Integration flexibility: A good provider fits into your world, not the other way around. Look for pre-built integrations with your customer data platform (CDP), demand-side platform (DSP), or marketing tech (MarTech) stack so you can get up and running without the heavy IT lift.
- Data analytics capabilities: You need proof that identity resolution drives ROI. Look for closed-loop measurement that ties unified IDs directly to campaign performance, so you can see what’s working and optimize with confidence.
How Experian enables enterprise-grade identity resolution
Experian delivers identity resolution at the scale, accuracy, and compliance required by the world’s largest enterprises. Our solutions are:
- Built on trust: Backed by 40+ years as a regulated data steward and rated #1 in data accuracy by Truthset, so you can act with confidence.
- Powered by our proprietary AI-enhanced identity graph: Combining breadth, accuracy, and recency across four billion identifiers, continuously refined by machine learning for maximum accuracy.
- Seamlessly connected: Pre-built data integration with leading CDPs, DSPs, and MarTech platforms for faster time to value.
- Always up to date: Frequent enrichment and near-real-time identity resolution through Activity Feed for timely personalization and more responsive customer engagement.
- Privacy-first by design: Compliance with GLBA, FCRA, and emerging state regulations baked in at every step, supported by rigorous partner vetting.
The bottom line
Identity resolution turns fragmented signals into connected, measurable, and compliant experiences. From retail to gaming, brands using it see stronger personalization, engagement, and ROI.
With Experian, you get the data, trust, and responsible AI innovation to make identity resolution work across every channel. Our approach uses AI to connect identities, predict behaviors, and deliver personalization that balances privacy with performance. If you’re ready to turn fragmented data into growth, now’s the time to start.
The world’s leading brands trust us to power identity resolution at scale. See how we can do the same for you.
Identity resolution FAQs
Deterministic uses exact identifiers (like an email) for accuracy, while probabilistic uses signals and algorithms to expand reach. Best-in-class providers usually combine both.
Identity resolution helps with personalization by unifying scattered signals into one profile. It reduces wasted spend and increases match rates, which means bigger addressable audiences and higher ROAS.
Yes. With first-party data and hashed PII, brands can still maintain addressability and personalization.
Retail, finance, travel, media, gaming, and audio all use identity resolution to personalize, attribute sales, and improve efficiency.
A customer data platform unifies the data you already own. Meanwhile, we add depth, scale, and higher match rates by layering in our identity graph and data enrichment.
Yes. Experian is GLBA/FCRA compliant, GDPR/CCPA ready, and supports consumer opt-outs and corrections to ensure responsible personalization.
Latest posts

Contextual ad targeting paves the way for new opportunities Advertisers and marketers are always looking for ways to remain competitive in the current digital landscape. The challenge of signal loss continues to prompt marketers to rethink their current and future strategies. With many major browsers phasing out support for third-party cookies due to privacy and data security concerns, marketers will need to find new ways to identify and reach their target audience. Contextual ad targeting offers an innovative solution; a way to combine contextual signals with machine learning to engage with your consumers more deeply through highly targeted accuracy. Contextual advertising can help you reach your desired audiences amidst signal loss – but what exactly is contextual advertising, and how can it help optimize digital ad success? In a Q&A with our experts, Jason Andersen, Senior Director of Strategic Initiatives and Partner Solutions with Experian, and Alex Johnston, Principal Product Manager with Yieldmo, they explore: The challenges causing marketers to rethink their current strategies How contextual advertising addresses signal loss Why addressability is more important than ever Why good creative is still integral in digital marketing Tips for digital ad success By understanding what contextual advertising can offer, you’ll be on the path toward creating powerful, effective campaigns that will engage your target audiences. Check out Jason and Alex’s full conversation from our webinar, “Making the Most of Your Digital Ad Budget With Contextual Advertising and Audience Insights” by reading below. Or watch the full webinar recording now! Watch now Macro impacts affecting marketers How important is it for digital marketers to stay informed about the changes coming to third-party cookies, and what challenges do you see signal loss creating? Jason: Marketers must stay informed to succeed as the digital marketing landscape continuously evolves. Third-party cookies have already been eliminated from Firefox, Safari, and other browsers, while Chrome has held out. It's just a matter of time before Chrome eliminates them too. Being proactive now by predicting potential impacts will be essential for maintaining growth when the third-party cookie finally disappears. Alex: Jason, I think you nailed it. Third-party cookie loss is already a reality. As regulations like the General Data Protection Regulation (GDPR) and the California Consumer Privacy Act (CCPA) take effect, more than 50% of exchange traffic lacks associated identifiers. This means that marketers have to think differently about how they reach their audiences in an environment with fewer data points available for targeting purposes. It's no longer something to consider at some point down the line – it's here now! Also, as third-party cookies become more limited, reaching users online is becoming increasingly complex and competitive. Without access to as much data, the CPMs (cost per thousand impressions) that advertisers must pay are skyrocketing because everyone is trying to bid on those same valuable consumers. It's essential for businesses desiring success in digital advertising now more than ever before. Contextual ad targeting: A solution for signal loss How does contextual ad targeting help digital marketers find new ways to reach and engage with consumers? What can you share about some new strategies that have modernized marketing, such as machine learning and Artificial Intelligence (AI)? Jason: We're taking contextual marketing to the next level with advanced machine learning. We are unlocking new insights from data beyond what a single page can tell us about users. As third-party cookies go away, alternative identifiers are coming to market, like RampID and UID2. These are going to be particularly important for marketers to be able to utilize. As cookie syncing becomes outdated, marketers will have to look for alternative methods to reach their target audiences. It's essential to look beyond cookie-reliant solutions and use other options available regarding advertising. Alex: I think, as Jason alluded to, there's a renaissance in contextual advertising over the last couple of years. If I were to break this down, there are three core drivers: The loss of identity signals. It's forcing us to change, and we must look elsewhere and figure out how to reach our audiences differently. There have been considerable advances in our ability to store and operate across a set of contextual signals far more extensive than anything we've ever worked with in the past and in far more granular ways. That's a huge deal because when it comes to machine learning, the power and the impact of those machine learning models are entirely based on how extensive and granular the data set is that you can collect. Machine learning can pull together critical contextual signals and figure out which constellations, or which combinations of those signals, are most predictive and valuable to a given advertiser. We can tailor machine learning models to individual advertisers using all those signals and find patterns across those in ways that were previously impractical or unfeasible. The transformation is occurring because of our ability to capture much more granular data, operate across it, and then build models that work for advertisers. Addressability: Connect your campaigns to consumers How does advanced contextual targeting help marketers reach non-addressable audiences? Jason: Advanced contextual targeting allows us to take a set of known data (identity) and draw inferences from it with all the other signals we see across the bitstream. It's taking that small seed set of either, customers that transacted with you before that you have an identity for, or customers that match whom you're looking for. We can use that as a seed set to train these new contextual models. We can now look at making the unknown known or the unaddressable addressable. So, it's not addressable in an identity sense, it is addressable in a contextual or an advanced contextual sense that's made available to us, and we can derive great insight from it. One of the terms I like to use is contextual indexing. This is where we take a set of users we know something about. So, I may know the identity of a particular group of households, and I can look at how those households index against any of the rich data sets available to us in any data marketplace, for example, the data Yieldmo has. We can look at how that data indexes to those known users to find patterns in that data and then extrapolate from that. Now we can go out and find users surfing on any of the other sites that traditionally don't have that identifier for that user or don't at that moment in time and start to be able to advertise to them based on the contextually indexed data. Historically, we've done some contextual ad targeting based on geo-contextual, and this is when people wanted to do one to one marketing, and geo-contextual outperformed the one to one. But marketers weren't ready for alternatives to one to one yet. We want marketers to start testing these solutions. Advertisers must start trying them, learning how they work, and learn how to optimize them because they are based on a feedback loop, and they're only going to get better with feedback. Alex: Jason, you described that perfectly. I think the exciting opportunity for many people in the industry is figuring out how to reach your known audience in a non-addressable space, that is based on environmental and non-identity based signals, that helps your campaign perform. Your known audience are people that are already converting – those who like your products and services and are engaged with your ads. Machine learning advancements allow you to take your small sample audience and uncover those patterns in the non-addressable space. It's also worth noting that in this world in which we are using seed audiences, or you are using your performing audiences to build non-addressable counterpart targeting campaigns, having high-quality, privacy-resilient data sets becomes incredibly important. In many cases, companies like Experian, who have high quality, deep rich training data, are well positioned to support advertisers in building those extension audiences. As we see the industry evolve, we're going to see some significant changes in terms of the types of, and ways in which, companies offer data, and make that available to advertisers for training their models or supporting validation and measurement of those models. Jason: Addressable users, the new identity-based users, are critical to marketers' performance initiatives. They're essential to training the models we're building with contextual advertising. Together, addressable users and contextual advertising are a powerful combination. It's not just one in isolation. It's not just using advanced contextual, and it's not just using the new identifiers. It's using a combination to meet your performance needs. It's imperative to start thinking about how you can begin building your seed audiences. What can you start learning from, and how do you put contextual into play today? You are looking to build off a known set and build a more advanced model. These can be specialized models based on your data. You can hone in and create a customized model for your customer type, their profile, and how they transact. It's a greenfield opportunity, and we're super excited about the future of advanced contextual targeting. Turn great creative into measurable data points Why does good creative still play an integral part in digital advertising success? Jason: Good creative has always been meaningful. It's vital in getting people to click on your ad and transact. But it's becoming increasingly important in this new world that we're talking about, this advanced contextual world. The more signal that we can get coming into these models, the better. Good creative in the proper ad format that you can test and learn from is paramount. It comes back to that feedback loop. We can use that as another signal in this equation to develop and refine the right set of audiences for your targeting needs. Alex: If you imagine within the broader context of identity and signal loss, creative and ad format becomes incredibly powerful signals in understanding how different audiences interact with and engage with different creative. In the case of the formats that serve on the Yieldmo exchange, we're collecting data every 200 milliseconds around how individual users are engaging with those ads. Interaction data like the user scrolling back or the number of pixel seconds they stay on the screen, fills this critical gap between video completes and clicks. Clicks are sparse and down the funnel, and views and completes are up the funnel. All those attention and creative engagement type metrics occupy the sweet spot where they're super prevalent, and you can collect them and understand how different audiences engage with your ads. That data lets you build powerful models because they predict all kinds of other downstream actions. Throughout my career, I learned that designing or tailoring your creative to different audience groups is one of the best ways to improve performance. We ran many lift studies with analysis to understand how you can tailor creative customized for individual audiences. That capability and the ability to do that on an identity basis is starting to deteriorate. The ability to do that using a sample of data or using a smaller set of users, either where you're inferring characteristics or you're looking at the identity that does exist in a smaller group, becomes powerful for being able to customize your creative to tell the right story to the right audience. When you layer together all the interaction data collected at the creative level on top of all the contextual and environmental signals, you can build powerful models. Whether those are driving proxy metrics, or downstream outcomes, puts us in a powerful position to respond to the broader loss of identity that we've relied on for so many years. Our recommendations for marketers for 2023 and beyond Do you have recommendations for marketers building out their yearly strategies or a campaign strategy? Jason: Be proactive and start testing and learning these new solutions. I mentioned addressability and being in the right place at the right time. That's easier in today's third-party cookie world. But as traditional identity is further constricted, you will have these first-party solutions that will not be at scale, so you're less likely to find your user at the scale you want. It would be best if you thought about how to reach that user at the right place at the right time. They may not be seen from an identity basis. They might not be at the right place at the right time when you were delivering or trying to deliver an ad. But you increase your chance of reaching them by building these advanced contextual targeting audiences using this privacy-safe seed 'opted-in' user set; this is a way to cast that wider net and achieve targeted scale. Alex: Build your seed lists, test your formats with different audiences, and understand what's resonating with whom. Take advantage of some of the pretty remarkable advances in machine learning that are allowing us, really, for the first time to fully uncork the potential and the opportunity with contextual in a way that we've never done before. Jason: At the end of the day, it's making the unaddressable addressable. So, it's a complementary strategy; having that addressable piece will feed the models. But also, that addressable piece still needs to be identity-based, addressable still needs to be part of your overall marketing strategy, and you need to complement it with other strategies like advanced contextual targeting. The two of them together are super complimentary. They learn from each other, and it's a cyclical loop. Now is the time to take advantage and start testing and understanding how these solutions work. We can help you get started with contextual ad targeting Contextual advertising can help you stay ahead of the curve, identify your target audience, and continue to drive conversions despite signal loss. We've partnered with Yieldmo to help make sure that your marketing campaigns are reaching the right target audiences on the platforms that are most relevant. To get started with contextual ad targeting to reach the right audience at the right time and drive conversions, contact our marketing professionals. Let's get to work, together. Contact us today Find the right marketing mix in 2023 Check out our webinar, "Find the right marketing mix with rising consumer expectations." Guest speaker, Nikhil Lai, Senior Analyst from Forrester Research, joins Experian experts Erin Haselkorn, and Eden Wilbur. We discuss: New data on the complexity and uncertainty facing marketers Consumer trends for 2023 Recommendations on finding the right channel mix and the right consumers Watch now Get in touch About our experts Jason Andersen, Senior Director, Strategic Initiatives and Partner Solutions, ExperianJason Andersen heads Strategic Initiatives and Partner Enablement for Experian Marketing Services. He focuses on addressability and activation in digital marketing and working with partners to solve signal loss. Jason has worked in digital advertising for 15+ years, spanning roles from operations and product to strategy and partnerships. Alex Johnston, Principal Product Manager, YieldmoAlex Johnston is the Principal Product Manager at Yieldmo, overseeing the Machine Learning and Optimization products. Before joining Yieldmo, Alex spent 13 years at Google, where he led the Reach & Audience Planning and Measurement products, overseeing a 10X increase in revenue. During his time, he launched numerous ad products, including YouTube's Google Preferred offering. To learn more about Yieldmo, visit www.Yieldmo.com. Latest posts

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? Source: Google 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. Get in touch 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. Latest posts

Up next in our Ask the Expert series, Ben Rothke, Senior Information Security Manager, reviews two certifications that should be part of your information security strategy: Service Organization Control (SOC) 2 Type 2 and International Organization for Standardization (ISO) 27001. Tapad, a part of Experian, is 27001 and SOC 2 Type 2 compliant. Two information security certifications you can trust Seals from Good Housekeeping and Underwriters Laboratories give consumers confidence that they can trust the product that they’re buying. For IT solutions or service providers, what, or who can you turn to for that seal of approval? There are many equivalent third-party attestations you can use. But which should you trust? The International Organization for Standardization (ISO) 27001 The American Institute of Certified Public Accountants (AICPA) System and Organization Controls (SOC) International Organization for Standardization (ISO) 27001 is an international standard for information security from the ISO. ISO 27001 is globally acknowledged and sets requirements for controls, maintenance, and certification of an information security management system (ISMS). This international standard provides organizations with a framework to identify, manage and reduce risks related to the security of information System and Organization Controls (SOC) The SOC, as defined by the AICPA, is a set of audit reports. SOC reports, like 27001 certificates, are used by service organizations to give their customers the confidence they have adequate information security controls in place to protect the data that they handle. SOC 2 is an assessment of controls at a service organization regarding security, availability, processing integrity, confidentiality, and privacy. The purpose of the report is to provide extensive information and assurance to a broad range of users about the controls at a service organization that are relevant to the security, availability, and processing integrity of the systems that process user data, as well as the confidentiality and privacy of the information processed by these systems. Why ISO 27001 and SOC 2 are important The value of these third-party attestations is two-fold: Organizations can show they have passed an independent external audit Third-party attestations save organizations the time of having to do their own audits In addition to 27001 and SOC 2 Type 2 compliance, we are also certified with ISO 27017 and 27018, which are add-ons to 27001 that are specific to cloud computing. We take the security and privacy of our customers’ data as seriously as they do. Every cloud service provider (CSP) has a responsibility matrix that details what security and privacy tasks they are responsible for and which ones the customer is responsible for. Any cloud customer that needs to be made aware of what their security tasks are is putting themselves at risk. So, when you want to engage a CSP, ask them for their attestations. They worked hard for them and will be proud to share their compliance. We’re powered by decades of setting standards in marketing services At Experian, we’re a privacy-first business. We’re highly focused on respecting people, their data, and their privacy. We continue to show our dedication to information security by completing these security audits every year. The constant changes to data compliance regulations can be challenging to navigate, but you don’t have to do it alone. Contact us today. We will be your guide so you can ethically and confidently reach your customers. Contact us today Contact us today About our expert Ben Rothke, Senior Information Security Manager Ben Rothke, CISSP, CISA, is a Senior Information Security Manager at Tapad, a part of Experian. He has over 25 years of industry experience in information systems security and privacy. His areas of expertise are in risk management and mitigation, security and privacy regulatory issues, cryptography, and security policy development. Ben is the author of Computer Security – 20 Things Every Employee Should Know (McGraw-Hill), and writes security and privacy book reviews for the RSA Conference Blog and Security Management magazine. Latest posts