2024 marked a significant year. AI became integral to our workflows, commerce and retail media networks soared, and Google did not deprecate cookies. Amidst these changes, ID bridging emerged as a hot topic, raising questions around identity reliability and transparency, which necessitated industry-wide standards. We believe the latest IAB OpenRTB specifications, produced in conjunction with supply and demand-side partners, set up the advertising industry for more transparent and effective practices.
So, what exactly is ID bridging?
As signals, like third-party cookies, fade, ID bridging emerged as a way for the supply-side to offer addressability to the demand-side. ID bridging is the supply-side practice of connecting the dots between available signals, that were generated in a way that is not the expected default behavior, to understand a user’s identity and communicate it to prospective buyers. It enables the supply-side to extend user identification beyond the scope of one browser or device.
Imagine you visit a popular sports website on your laptop using Chrome. Later, you use the same device to visit the same sports website, but this time, on Safari. By using identity resolution tools, a supply-side partner can infer that both visits are likely from the same user and communicate with them as such.
ID bridging is not inherently a bad thing. However, the practice has sparked debate, as buyers want full transparency into the use of a deterministic identifier versus an inferred one. This complicates measurement and frequency capping for the demand-side. Before OpenRTB 2.6, ID bridging led to misattribution as the demand-side could not attribute ad exposures, which had been served to a bridged ID, to a conversion, which had an ID different from the ad exposure.
OpenRTB 2.6 sets us up for a more transparent future
In 2010, the IAB, along with supply and demand-side partners, formed a consortium known as the Real-Time Bidding Project for companies interested in an open protocol for the automated trading of digital media. The OpenRTB specifications they produced became that protocol, adapting with the evolution of the industry.
The latest evolution, OpenRTB 2.6, sets out standards that strive to ensure transparency in real-time bidding, mandating how the supply-side should use certain fields to more transparently provide data when inferring users’ identities.
What’s new in OpenRTB 2.6?
Here are the technical specifications for the industry to be more transparent when inferring users’ identities:
- Primary ID field: This existing field now can only contain the “buyeruid,” an identifier mutually recognized and agreed upon by both buyer and seller for a given environment. For web environments, the default is a cookie ID, while for app activity, it is a mobile advertising ID (MAID), passed directly from an application downloaded on a device. This approach ensures demand-side partners understand the ID’s source.
- Enhanced identifier (EID) field: The EID field, designated for alternative IDs, now accommodates all other IDs. The EID field now has additional parameters that provide buyers transparency into how the ID was created and sourced, which you can see in the visual below:
Using the above framework, a publisher who wants to send a cross-environment identifier that likely belongs to the same user would declare the ID as “mm=5,” while listing the potential third-party identity resolution partner under the “matcher” field, which the visual below depicts. This additional metadata gives the demand-side the insights they need to evaluate the reliability of each ID.
“These updates to OpenRTB add essential clarity about where user and device IDs come from, helping buyers see exactly how an ID was created and who put it into the bidstream. It’s a big step toward greater transparency and trust in the ecosystem. We’re excited to see companies already adopting these updates and can’t wait to see the industry fully embrace them by 2025.”
Hillary Slattery, Sr. Director, Programmatic, Product Management, IAB Tech Lab
Experian will continue supporting transparency
As authenticated signals decrease due to cookie deprecation and other consumer privacy measures, we will continue to see a rise in inferred identifiers. Experian’s industry-leading Digital Graph has long supported both authenticated and inferred identifiers, providing the ecosystem with connections that are accurate, scalable, and addressable. Experian will continue to support the industry with its identity resolution products and is supportive of the IAB’s efforts to bring transparency to the industry around the usage of identity signals.
Supply and demand-side benefits of adopting the new parameters in OpenRTB 2.6
- Partner collaboration: Clarity between what can be in the Primary ID field versus the EID field provides clear standards and transparency between buyers and sellers.
- Identity resolution: The supply side has an industry-approved way to bring in inferred IDs while the demand side can evaluate these IDs, expanding addressability.
- Reducing risk: With accurate metadata available in the EID field, demand-side partners can evaluate who is doing the match and make informed decisions on whether they want to act on that ID.
Next steps for the supply and demand-sides to consider
For supply-side and demand-side partners looking to utilize OpenRTB 2.6 to its full potential, here are some recommended steps:
For the supply-side:
- Follow IAB Specs and provide feedback: Ensure you understand and are following transparent practices. Ask questions on how to correctly implement the specifications.
- Vet identity partners: Choose partners who deliver the most trusted and accurate identifiers in the market.
- Be proactive: Have conversations with your partners to discuss how you plan to follow the latest specs, which identity partners you work with, and explain how you plan to provide additional signals to help buyers make better decisions.
We are beginning to see SSPs adopt this new protocol, including Sonobi and Yieldmo.
“The OpenRTB 2.6 specifications are a critical step forward in ensuring transparency and trust in programmatic advertising. By aligning with these standards, we empower our partners with the tools needed to navigate a cookieless future and drive measurable results.”
Michael Connolly, CEO, Sonobi
These additions to the OpenRTB protocol further imbue bidding transactions with transparency which will foster greater trust between partners. Moreover, the data now available is not only actionable, but auditable should a problem arise. Buyers can choose, or not, to trust an identifier based on the inserter, the provider and the method used to derive the ID. While debates within the IAB Tech Lab were spirited at times, they ultimately drove a collaborative process that shaped a solution designed to work effectively across the ecosystem.”
Mark McEachran, SVP of Product Management, Yieldmo
For the demand side:
- Evaluation: Use the EID metadata to assess all the IDs in the EID field, looking closely at the identity vendors’ reliability. Select partners who meet high standards of data clarity and accuracy.
- Collaboration: Establish open communication with supply-side partners and tech partners to ensure they follow the best practices in line with OpenRTB 2.6 guidelines and that there’s a shared understanding of the mutually agreed upon identifiers.
- Provide feedback: As OpenRTB 2.6 adoption grows, consistent feedback from demand-side partners will help the IAB refine these standards.
Moving forward with reliable data and data transparency
As the AdTech industry moves toward a cookieless reality, OpenRTB 2.6 signifies a substantial step toward a sustainable, transparent programmatic ecosystem. With proactive adoption by supply- and demand-side partners, the future of programmatic advertising will be driven by trust and transparency.
Experian, our partners, and our clients know the benefits of our Digital Graph and its support of both authenticated and inferred signals. We believe that if the supply-side abides by the OpenRTB 2.6 specifications and the demand-side uses and analyzes this data, the programmatic exchange will operate more fairly and deliver more reach.
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In a perfect world, we’d all have a single, go-to grocery store that carried everything on our shopping list – fresh produce, gourmet coffee beans, rare spices, and maybe even that special-grade olive oil, right alongside our wholesale bulk purchases at unbeatable prices. It would be convenient and efficient, and it’d save a lot of driving around town. The changing data marketplace: From one-stop shop to specialized selection For a long time, data buyers enjoyed something similar in their world: a small set of large-scale data marketplaces that offered a wide array of audiences, making it easy to load up on whatever you needed in one place. Not only are there fewer places to pick everything up, but new factors like privacy and signal deprecation are placing a spotlight on quality and addressability. Just as our dinner plans are growing more ambitious insofar as we want health, flavor, value, and convenience all in one place – so are our data strategies. Instead of a single steak-and-potatoes meal, today’s data marketplace operators might be cooking up a complex menu of campaigns. As a result, data buyers are beginning to shop around. Some still rely on large-scale marketplaces for familiar staples, but now they have reasons to explore other options. Some are turning to providers known for offering top-tier, transparently sourced segments. Others are focusing on specialty providers that excel in one area. A more selective approach to data buying In this environment, choosing where to “shop” for data is becoming more deliberate and selective. Data buyers aren’t just thinking about broad scale; they’re looking to prioritize quality, durability, data privacy, and differentiation. They need to place higher value on data marketplaces that can maintain audience addressability over time, despite signal loss. Sometimes, that means accepting a smaller assortment in exchange for tighter vetting and more reliable targeting. Other times it means mixing and matching – stopping by one marketplace for premium segments and another for cost-friendly, wide-reaching data sets. Either way, they can benefit from having more choices. Experian’s marketplace: A trusted source for high-quality data Experian’s vetted and curated blend of data partners and vertically-aligned audiences offers a trusted specialty store for data buyers. Experian’s marketplace, powered by identity graphs that include 126 million households, 250 million individuals, and 4 billion active digital IDs, enables partner audiences to be easily activated and maintain high addressability across display, mobile, and connected TV (CTV) channels. In particular, Experian’s marketplace provides: Enhanced addressability and match rates All audiences delivered from the marketplace benefit from our best-in-class offline and digital identity graphs, which ensure addressability across all channels like display, mobile, and CTV. Unlike other data marketplaces, Experian ensures all identifiers associated with an audience have been active and are targetable, improving the accuracy of audience planning. Audience diversity and scale Access a broad range of audiences across top verticals from our partner audiences, which can be combined with one another and with 2,400+ Experian Audiences. The ability to join audiences across data providers ensures that buyers can build the perfect audience for the campaign. Trusted compliance and oversight With decades of experience, Experian is a trusted expert in data compliance. Our rigorous data partner review ensures available audiences comply with all federal, state, and local consumer privacy regulations. The future of data marketplaces: Precision and flexibility matter The evolution of data marketplaces reflects the industry's shifting priorities. Data buyers seek specificity, reliability, and adaptability to align with their diverse campaign needs. The best data strategy, much like the best grocery run, isn’t about grabbing everything in one place – it’s about carefully selecting the right ingredients to create the perfect recipe for success. This shift underscores the importance of flexibility and precision as data buyers navigate a landscape shaped by privacy regulations, signal loss, and evolving consumer expectations. As data marketplaces adapt to meet these demands, they are redefining what it means to deliver value. Experian’s marketplace enables buyers to strike the perfect balance between reach and quality by offering enhanced match rates, precise audience planning, and seamless distribution. In this new era, data buyers have the tools and options to craft campaigns that are impactful and aligned with the increasingly selective and privacy-conscious digital landscape. The key is recognizing that today’s data strategy is about utilizing the strengths of many to create a cohesive and effective whole. If you're interested in learning more about Experian's marketplace or becoming an active buyer or seller in our marketplace, please contact us. Contact us Latest posts
Conventional TV advertising campaigns have historically relied on general audience metrics like impressions and ratings to measure outcomes. These metrics can help marketers understand how many people have seen an ad, but they don’t reveal its real-world impact, which leaves a gap between ad exposure and results. Outcome-based TV measurement bridges this gap and helps marketers tie ad spending directly to their business goals. Instead of counting eyeballs alone, TV measurement zeroes in on what viewers do after seeing an ad — whether signing up for a service, visiting your website, or purchasing a product. TV ad measurement helps marketers adjust campaigns based on clear, trackable outcomes rather than guesswork. Let’s talk about how marketers can get started with outcome-based TV measurement and start experiencing tangible results. Why outcome-based TV measurement matters Outcome-based measurement indicates a massive shift in how marketers evaluate TV advertising success. As a principal analyst at Forrester explained, the industry is about to “move into a whole different world" where multiple metrics are tailored to advertisers’ unique goals, such as sales, store traffic, or web engagement. This shift is driven by improved tools for tracking TV outcomes, which help justify spending and clarify ROI. With TV measurement, you can see how your campaigns impact aspects of your marketing like sales and engagement. Aligning TV ad spend with business goals Every business has distinct objectives. Outcome-based measurement ties your marketing efforts to business goals and enables smarter decisions, campaign optimization, and ROI improvements. Whether you're a B2C brand wanting immediate sales or a B2B organization looking to drive website traffic, this method provides the insights needed for strategic decision-making. Marketers can deliver the most value by adjusting TV ad spending to maximize desired results: Sales goals: Identify which ads and platforms directly influence purchases to ensure TV ad spend contributes to revenue growth. Customer engagement: Link actions like website visits or app downloads to TV campaigns and refine messaging to deepen audience connections. Desired outcomes: Align ad spend with goals like consumer awareness or repeat purchases to allocate resources effectively for measurable success. Reducing wasted spend on ineffective channels Outcome-based TV measurement allows you to pinpoint which networks, times, or programs drive the most engagement and conversion. When you know your underperforming channels, you can reallocate budgets to those with a higher ROI and avoid waste. Core metrics in outcome-based TV measurement The effective implementation of outcome-based measurement requires advanced TV advertising analytics and tracking metrics that shed light on TV ad performance. Incremental lift This metric measures the increase in desired actions and business results — like purchases or site visits — that can be attributed directly to a TV campaign. Incremental lift quantifies your campaign’s impact and separates organic activity from the results your ads have driven. Let’s say a meal kit service experiences a 20% lift in subscriptions within a single week of running TV ads compared to a week without ads. They’d want to be able to isolate the impact of their ad from their organic growth so they can determine if the growth is actually a result of the TV ads or another effort. Attribution and conversions Attribution links TV ad exposure to specific customer actions, such as newsletter sign-ups and product purchases. Conversion data helps marketers understand the whole customer journey to optimize messaging, targeting, and channel mix to improve conversion rates. A retailer that knows 50% of TV ad viewers visit its e-commerce site within 36 hours of exposure could use that information to adjust the timing of its retargeting and align with site visit spikes. Audience segmentation for targeted measurement Outcome-based measurement breaks down performance across target demographics and allows for granular audience segmentation so TV ads resonate with the right audiences. For example, if a luxury brand saw better TV ad performance with high-earning Millennials, they’d want to refine their campaign messaging based on this group’s habits and preferences. Customer journey tracking Knowing how viewers move from awareness to conversion is critical. Outcome-based TV measurement helps you track the customer journey by pinpointing touchpoints where engagement happens and tying these to your TV campaigns. If a fitness brand found that TV campaigns drive app downloads, it could combine app analytics and TV exposure data to find out when most of their conversions happen after ad exposure and create follow-up messaging for that window of time. Integrating these insights with other marketing channels allows you to fine-tune your messaging, channel mix, and audience targeting to drive better outcomes and deliver more personalized customer experiences. Lifetime value (LTV) Beyond immediate conversions, outcome-based TV ad measurement helps brands identify which TV campaigns attract high-value customers with long-term revenue potential. If a financial institution ran a TV ad campaign centered on its new credit card, for instance, it could use LTV to track new cardholders and determine whether ads occurring during financial news airtime produced customers with higher average annual spend compared to other segments. How outcome-based TV measurement works Outcome-based measurement is a data-driven process that involves collecting, analyzing, and applying insights to improve TV ad performance. 1. Collect data When someone sees your TV ad, they might take action, like downloading your app or buying something. Outcome-based TV measurement begins by tracking these actions and gathering data from various sources, such as: TV viewership CRM Digital engagement Purchase behavior Cross-platform interactions And more Data integration with digital platforms Combining TV data with insights from platforms like social media or website analytics creates a more unified view of campaign performance. This integration powers easier retargeting and better alignment between digital and TV advertising strategies. Some marketers enhance this integration further using artificial intelligence (AI) to streamline data coordination and ensure campaigns are optimized for effectiveness and ROI. 2. Connect the dots Next, marketers need to find out which actions were influenced by TV ads. It’s important to ask questions like these as you work to connect the dots: Did website traffic spike right after the ad aired? Did the ad viewers match the people who signed up for the service or made a purchase? You can link TV exposure to real-world behaviors with tools and identifiers like hashed emails, device IDs, surveys, and privacy-safe data-matching techniques. 3. Analyze the data Then, the data needs to be analyzed for patterns like these: Which TV ads or time slots drove the most engagement? Did certain customer groups respond better than others? Was there a noticeable lift in sales or signups after the ad campaign? This step can help you uncover what’s working and what’s not. Role of advanced analytics and machine learning The data analysis required in this process can be overwhelming, time-consuming, and risky without the right tools. Fortunately, advanced analytics and fast, effective artificial intelligence tools can process large amounts of data from digital platforms, TV viewership, and customer interactions in less time to reveal accurate, actionable insights and patterns. They can also predict which audiences, messages, and channels will be most profitable so campaigns can adapt in real time, whether by reallocating spend to higher-performing channels or refining audience targeting. 4. Turn insights into action Once you have your data-derived insights, you can tweak your campaign in a number of ways, whether you decide to: Adjust your ads: If one message works better than another, lean into it. Refine your targeting: Focus on the audience segments most likely to act. Optimize your spend: Invest in channels or times that deliver the best return. For example, if you see that ads during prime time lead to more purchases than morning slots, you can shift your budget accordingly. This type of knowledge can be used to continuously improve your campaigns. Each time you run a new ad, you measure again, building on past insights to make your outcome-based TV advertising even smarter. Applications of outcome-based TV measurement Outcome-based TV measurement has wide-ranging applications across industries. Here’s how it’s helping businesses link TV ad exposure to real-world actions and optimize campaigns for better results. E-commerce and retail: Retailers can track how TV ads influence purchases and use those insights to refine their assets and target specific customer groups. A clothing retailer may track how well a TV ad boosts online traffic and in-store purchases. For instance, if a seasonal sale commercial correlates with a spike in website visits or mobile app downloads, the brand can refine its ad placement to focus on the most responsive demographics. Automotive: Automakers use outcome-based TV measurement insights to determine how ads drive dealership visits, test drives, or inquiries. A car manufacturer could analyze whether TV spots featuring a new vehicle increase traffic to its dealership locator or car configuration tool online. Healthcare: Pharmaceutical companies could assess whether TV spots lead to increased prescription fills, or a health provider could test how ads promoting flu shots result in appointment bookings through its website or app. If any messages resonate more with families, the provider can create similar campaigns for the future. How Experian enhances outcome-based TV measurement Experian has recently partnered with EDO, an outcomes-based measurement provider, to offer more granular TV measurement across platforms. Our identity resolution and matching capabilities enhance EDO’s IdentitySpine™ solution with rich consumer data, including age, gender, and household income, all in a privacy-centric way. Integrating these demographic attributes is helping advertisers achieve more precise audience insights and connect their first-party data to actionable outcomes. As a result of this collaboration, brands, agencies, and networks can optimize their TV campaigns by identifying which ads drive the most decisive engagement among specific audience segments. We’re improving accuracy, targeting, and more so advertisers can maximize the performance of their CTV strategies. Get in touch with Experian’s TV experts If you’re ready to take your data-driven TV advertising strategies to the next level, connect with our team. We combine advanced data and identity solutions as well as strong industry collaborations to help brands optimize their TV campaigns. Whether you're navigating traditional or advanced TV formats, our expertise ensures your efforts deliver maximum impact. Connect with us today to drive engagement, connect with audiences, and achieve better ROI. Let’s transform the way you measure success on TV. Reach out to our TV experts Contact us Latest posts
Advertising today is more complex than ever. Consumers demand personalized, relevant experiences from brands, making it increasingly challenging to meet expectations without external support. Businesses must work with publishers, retailers, and platforms to thrive, using these partnerships for data insights that refine their strategies and fuel growth. We spoke with industry leaders from Ampersand, AppsFlyer, Audigent, Comcast Advertising, Fox, ID5, and Snowflake to gather insights on how strategic collaboration can expand audience reach, improve targeting precision, and drive measurable advertising success. 1. Expand your reach with strategic collaborations Gone are the days when brands relied solely on third-party data. By linking their first-party insights with equally valuable data from partners, brands develop a far more comprehensive understanding of their audiences. This collaborative approach creates richer audience profiles, improves targeting, and enhances campaign performance. Partnerships also create opportunities for operational efficiencies. For instance, brands that share data and expertise with collaborators can expand their audience reach without overhauling existing systems. These collaborations allow marketers to work smarter, turning shared knowledge into strategic wins. "Partnerships are everything. We can't fulfill our goals on the sale side, marketers can't fulfill their goals of finding their audience where they need to reach them and with the right level of outcomes without partnering together. Why? Because each of them has their own line of sight to the data that they have access to and the data that they know best."Justin Rosen, Ampersand 2. Identify the right partnership model Choosing the right partnership model is key to achieving your business objectives. For some, pairing first-party data with publishers' insights creates better targeting. For others, aligning with complementary brands allows them to engage shared audiences. For large-scale efforts, agencies can unify collaboration frameworks, making onboarding and activation seamless. Meanwhile, emerging categories like FinTech, hospitality, and commerce media provide brands new avenues for impactful partnerships. Evaluating these options thoroughly will ensure your collaboration aligns with long-term marketing goals. "With first-party data being really the central point of signal today, we see more and more of our advertisers identifying partnerships with maybe potentially historical competitors or partners they would've never considered."Tami Harrigan, AppsFlyer 3. Utilize the power of pooled insights Combining various data sources, like CRM records, browsing behavior, and shopping receipts, creates an in-depth view of your customers. By understanding what motivates consumers at every stage of their journey, brands can better tailor messaging and funnel marketing spend to where it matters most. This approach also enables data-driven agility. Real-time insights help brands make informed adjustments, whether it’s shifting strategies mid-campaign or identifying new growth opportunities. When brands share data responsibly, the results are campaigns that resonate and deliver measurable improvements. "A lot of advertisers have gotten smarter about their data than they were just two, three years ago. They’re now doing that segmentation on their side with their data and bringing that to Fox and saying, ‘Look, match this segment against your entire user base.’ In order to do that, we can work with providers like Experian, or with data clean rooms to really bring that data and do a direct match without going through a third party."Darren Sherriff, Fox 4. Adopt the right tools and technology The right tools empower a collaborative data ecosystem. Solutions like data clean rooms ensure privacy-first data matching and measurement. Identity frameworks, such as Unified ID 2.0 (UID2) or ID5, enable secure data alignment across platforms, simplifying audience targeting while safeguarding sensitive information. Shared dashboards are another crucial tool, providing all collaborators with clear, co-owned performance metrics. Yet, while technology is an enabler, success ultimately depends on how well tools align with each partner’s goals and build trust within the collaboration. “You have to make it accessible to non-technical personas and you have to have the ability to have it stood up and pay dividends in a short amount of time. The other thing is interoperability. We very much think as an industry we need to have interoperability with clean rooms, ones that operate on different frameworks.” David Wells, Snowflake 5. Overcome barriers to collaboration Collaboration often faces obstacles, like differing goals, fragmented data, or resource gaps. Brands can tackle these issues by aligning stakeholders on clear KPIs, standardizing data-sharing practices, and selecting tools that integrate smoothly with existing systems. Breaking down barriers early fosters fluid cooperation and improves outcomes for everyone involved. When goals, tools, and resources are in sync, these partnerships deliver lasting value and stronger results. “The key is to bring together data assets and work collaboratively to address fragmentation. The way to solve that is with more interoperability and connect the data in very privacy-safe ways, offering more opportunity to reach high fidelity audiences and incorporate better measurement methodologies.”Carmela Fournier, Comcast Advertising The path to growth through partnership Those who prioritize collaboration will outrun the competition and drive sustainable growth through smarter, more connected advertising. By choosing the right models, using powerful technology, and addressing potential obstacles, brands can co-create campaigns that resonate deeply with their audiences. Connect with our experts Latest posts