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Technology is pushing the boundaries of commerce like never before. Artificial intelligence (AI) is one of the primary driving technologies at the forefront of the commerce evolution, using advanced algorithms to revolutionize marketing and personalize customer experiences. As of 2024, AI adoption in e-commerce is skyrocketing, with 84% of brands already using it or gearing up to do so.
This article explores the AI revolution coming to commerce, focusing on what makes AI a driving force for e-commerce in particular, and the ways it’s reshaping how businesses engage with consumers.
Understanding the AI revolution in commerce
AI is quickly reshaping commerce as we know it by democratizing access to sophisticated tools once reserved for large corporations, breaking down functional silos within organizations, and integrating data from multiple sources to achieve deeper customer understanding. It’s paving the way for a future where every brand interaction is uniquely crafted for the individual, powered by AI systems that anticipate preferences proactively.
AI is a broad term that encompasses:
- Data mining: The gathering of current and historical data on which to base predictions
- Natural language processing (NLP): The interpretation of human language by computers
- Machine learning: The use of algorithms to learn from past experiences or examples to enhance data understanding
The capabilities of AI have significantly matured into powerful tools that can improve operational efficiency and boost sales, even for smaller businesses. They have also fundamentally changed how businesses interact with customers and handle operations. As AI continues to develop, it has the potential to provide even more seamless, personalized, and ethically informed commerce experiences and establish new benchmarks for engagement and efficiency in the marketplace.
Four benefits of the AI revolution coming to commerce
Major commerce players like Amazon have benefited from AI and related technologies for a while. Through machine learning, they’ve optimized logistics, curated their product selection, and improved the user experience. As this technology quickly expands, businesses have unlimited opportunities to see the same efficiency, growth, and customer satisfaction as Amazon. Here are four primary benefits of AI adoption in commerce.
1. Data-driven decision making
AI gives businesses powerful tools to analyze large amounts of data more quickly and accurately than a person. Through advanced algorithms and machine learning, AI can sift through historical sales data, customer behavior patterns, and market trends to uncover insights and suggest actions that might not be immediately obvious to human analysts. By transforming raw data into actionable insights, AI empowers businesses to make more informed decisions, reduce risks, and capitalize on opportunities.
As a real-world example, Foxconn, the largest electronics contract manufacturer worldwide, worked with Amazon Machine Learning Solutions Lab to implement AI-enhanced business analytics for more accurate forecasting. This move improved forecasting accuracy by 8%, saved $533,000 annually, reduced labor waste, and improved customer satisfaction through data-driven decisions.
2. A better customer experience
AI is set to make customer interactions smoother, faster, and more personalized by recommending products based on preferences and behaviors, making it easier for customers to find what they need.
When consumers visit an online store, AI also provides instantaneous help via a chatbot that knows their order history and preferences. These AI-powered assistants offer real-time help like a knowledgeable store clerk. They give the appearance of higher-touch support and can answer basic questions at any hour, provide personalized product recommendations, and even troubleshoot issues. Chatbots free up human customer service agents for more complicated matters, and these agents can then use AI to obtain relevant information and suggestions for the customer during an interaction.
3. Personalized marketing
Data-driven personalization of the customer journey has been shown to generate up to eight times the ROI, as data shows 71% of consumers now expect personalized brand interactions. Until AI came around, personalization at scale was complex to achieve. Now, gathering and processing data about a customer’s shopping experience is easier than ever based on lookalike customers and past behavior.
Many businesses have adopted AI to glean deeper insights into purchase history, web browsing, and social media interactions to drive better segmentation and targeting. With AI, advertisers can analyze behavioral and demographic data to suggest products someone is likely to love. Consumers can now browse many of their favorite online stores and see product recommendations that perfectly match their tastes and needs.
AI can also offer special discounts based on purchasing habits, and send personalized emails with products and content that interest customers to make their shopping experience more engaging and relevant. This personalization helps businesses forge stronger customer relationships.
Personalization across digital storefronts
Retail media involves placing advertisements within a retailer’s website, app, or other digital platform to help brands target consumers based on their behavior and preferences within that environment. Retail media networks (RMNs) expand this capability across multiple retail platforms to create seamless advertising opportunities throughout the customer journey. Integrating AI into RMNs can improve personalization across digital storefronts with personalized, relevant ads and custom offers in real time that improve the customer experience.
4. Operational efficiency
AI can also be beneficial on the back end, enabling more efficient resource allocation, pricing optimization, efficiency, and productivity.
Customers can be frustrated when they visit a store for a specific product only to find it out of stock or unavailable in a particular size. With AI, these situations can be prevented through algorithms that forecast demand for certain items. Retailers like Amazon and Walmart both use AI to predict demand, with Walmart even tracking inventory in real time so managers can restock items as soon as they run out.
AI can automate and streamline operational tasks to help businesses run smoother, faster, and more cost-effective operations. It can:
- Offload tedious data entry, scheduling, and order processing tasks for greater fulfillment accuracy.
- Analyze historical data and market trends, predicting demand to help businesses optimize inventory, reduce waste, track online and in-store sales, and prevent shortages.
- Forecast demand levels, transit times, and shipment delays to make better predictions about logistics and supply chains.
- Improve data quality using machine learning algorithms that find and correct product information errors, duplicates, and inconsistencies.
- Adjust prices based on competitor pricing, seasonal fluctuations, and market conditions to maximize profits.
- Pinpoint bottlenecks, identify issues before they escalate, and provide improvements for suggestions.
Future trends and predictions
If you want to stay ahead in e-commerce, it’s just as important to know what’s coming as it is to understand where things are today. Here are some of the trends expected to shape the rest of 2024 and beyond.
Conversational commerce
Conversational commerce allows real-time, two-way communication through AI-based text and voice assistants, social messaging apps, and chatbots. Generative AI advancements may soon enable more seamless, personalized interactions between customers and online retailers. This technology can improve customer engagement and satisfaction while providing helpful insights into preferences and behaviors for better personalization and targeting.
Delivery optimization
AI-driven delivery optimization uses AI to predict ideal routes for each individual delivery, boosting efficiency, reducing costs, promoting sustainability, and improving customer satisfaction throughout the delivery process.
Visual search
AI-driven visual search is quickly improving in accuracy, speed, and contextual understanding. Future developments may integrate seamlessly with augmented reality (AR) so shoppers can search for products by pointing their devices at physical objects. Social media and e-commerce platforms may soon incorporate visual search more prominently, allowing users to find products directly from images.
AI content creation
AI is already automating and optimizing aspects of content production:
- Algorithms can generate product descriptions, blog posts, and social media captions personalized to specific customer segments.
- AI tools also enable the creation of high-quality visuals and videos.
- NLP advancements ensure content is compelling and grammatically correct.
- AI-driven content strategies analyze consumer behavior and refine messaging to meet changing preferences and trends.
This automation speeds up content creation while freeing resources for strategic planning and customer interaction.
IoT integration
Integrating AI with Internet of Things (IoT) devices could help make the ecosystem more interconnected in the future. AI algorithms can use data from IoT devices like smart appliances, wearables, and sensors to gather real-time insights into consumer behavior, preferences, and product usage patterns. This data enables personalized marketing strategies, predictive maintenance for products, and optimized inventory management. AI-driven IoT data analytics can also streamline supply chain operations to reduce costs and inefficiencies.
Fraud detection and security
There will likely be an increased focus on the ethical use of AI and data privacy regulations to strengthen consumer trust and transparency. AI-powered systems will get better at detecting and preventing fraud in e-commerce transactions, which will heighten security measures for both businesses and consumers.
Chart the future of commerce with Experian
AI has changed how marketers approach e-commerce in 2024. With AI-driven analytics and predictive capabilities, marketers can extract deeper insights from extensive data sets to gain a clearer understanding of consumer behavior. This enables refined segmentation, precise targeting, and real-time customization of messages and content to fit individual preferences.
Beyond insights, AI automates routine tasks like ad placement, content creation, and customer service responses, freeing marketers to concentrate on strategic planning and creativity. Through machine learning, marketers can predict trends, optimize budgets, and fine-tune strategies faster and more accurately than ever. The time to embrace AI is now.
At Experian, we’re here to help you make more data-driven decisions, deliver more relevant content, and reach the right audience at the right time. Using AI in your commerce marketing strategy with our Consumer View and Consumer Sync solutions can help you stay competitive with effective, engaging campaigns.
Contact us to learn how we can empower your commerce advertising strategy today.
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The stakes are high when it comes to advertising during football’s biggest games as the cost of advertising continues to rise, with the average 30-second TV ad during the 2023-24 Sunday Night Football season priced at $882K. With record viewership at the College Football Playoff and the Super Bowl drawing in 123.7 million average viewers, the largest TV audience on record, it's no surprise that brands are willing to pay those prices since football games are prime time for reaching engaged audiences. In fact, an estimated 51% of viewers search for an ad they saw during the game, underscoring the potential of second-screen engagement to amplify campaign impact. Whether you advertise on TV during these games or not, brands are exploring how they can use football season to drive a deeper connection to their audience. To do this, brands need data driven strategies. In this blog post, we’ll reveal audience segments designed for you to craft tailored marketing strategies that resonate with football fans in the stands and on the couch. You can find the complete audience segment name in the appendix. Make a game-winning play with Experian Audiences With playoff season fast approaching, it’s the perfect time to go on the offensive and target football fans. Utilize Experian’s syndicated audiences to ensure your marketing messages resonate with fans when they're the most engaged. Experian’s 2,400+ syndicated audiences are available directly on over 30 leading television, social, programmatic advertising platforms, and directly within Audigent for activation within private marketplaces (PMPs). Reach consumers based on who they are, where they live, and their household makeup. Experian ranked #1 in accuracy by Truthset for key demographic attributes. Access to unique audiences through Experian’s Partner Audiences available on Experian’s data marketplace, within Audigent for activation in PMPs and directly on platforms like DirectTV, Dish, Magnite, OpenAP, and The Trade Desk. Four football audience categories to add to your advertising lineup Football fans come in all shapes, sizes, and viewing habits. From dedicated supporters to casual viewers, targeting the right audience can make or break your campaign. Here are four football audience categories you can target: Sports enthusiasts College football fans 21+ audiences TV viewers Let’s huddle up and break down the audience segments within each category. Whether it’s tailgating, tuning in, or cheering from the stands, these insights will get your campaign into the end zone. Sports enthusiasts Whether they’re following their favorite teams, attending games in person, or watching professional sports events on TV, football fans are deeply engaged, making them an ideal target for advertisers looking to score big. Here are five audiences to target: NFL Enthusiasts Football (FLA/Fair Lending Friendly)1 Sports Enthusiasts NFL Stadium Visitors Professionals Sports Event College football fans College football fans bring unmatched passion and loyalty, with bowl games during the 2023 season drawing on average of 4.6 million viewers across 40 total games—a 5% increase year-over-year. From students to alumni, these fans represent an invaluable opportunity for advertisers to connect with a deeply invested audience. Here are four audiences to target to connect with passionate college football fans: College Football Stadium Visitors College Football Bowls College Students College Sports Venues 21+ audiences With 84% of U.S adults reporting that they drink alcohol while watching football on TV, targeting 21+ audiences during game season is a winning play. Whether they’re cracking open a cold one at a tailgate, hosting a game-day party, or relaxing on the couch, these audiences represent a key audience for brands looking to tap into football culture. Here are four audiences that you can target this post season: Imported Light Beer Enthusiasts Domestic/Imported Beer High-end Spirit Drinkers Discretionary spend: Alcohol and wine $331 – $726 These audiences can help you serve up campaigns that pour directly into the heart of football fandom. TV viewers Football games attract some of the most engaged and diverse TV audiences, with 85% of sports fans preferring to watch live sports on TV rather than in-person. Notably, for the first time, viewers aged 18 to 49 spent the majority of their sports viewing time (54%) via streaming. This shift highlights the immense opportunity for advertisers to connect with highly attentive viewers tuned into every play. Here are seven audiences that you can use to create a game-winning strategy to reach engaged TV watching football fans: Cable Satellite or Streaming Network Subscribers Streaming Video: High Spenders Cord Cutters Cable and Streaming TV Service Subscribers Paid TV High Spenders Screen Size – Large Co-Watchers Whether they're catching the action on a large TV screen or streaming from their phone, these audiences will help you craft campaigns that deliver results with highly engaged viewers. Score big with Experian this postseason As some of football’s biggest games approach, it’s time to huddle up and connect with consumers who live for the thrill of the game. Whether they’re tuning in to cheer for their favorite teams, tailgating with friends, or enjoying the game-day experience from home, Experian Marketing Data provides the playbook to score big with targeting, enrichment, and activation. With Experian’s data-driven insights, you can turn every opportunity into a game-winning play! Need a custom audience? Reach out to our audience team and we can help you build and activate an Experian audience on the platform of your choice. Additionally, work with Experian’s network of data providers to build audiences and send to an Audigent PMP for activation. Connect with our audience team Connect with us You can activate our syndicated audiences on-the-shelf of most major platforms. For a full list of Experian’s syndicated audiences and activation destinations, download our syndicated audiences guide. Explore our other seasonal audiences that you can activate today. View now 1 “Fair Lending Friendly” indicates data fields that Experian has made available without use of certain demographic attributes that may increase the likelihood of discriminatory practices prohibited by the Fair Housing Act (“FHA”) and Equal Credit Opportunity Act (“ECOA”). These excluded attributes include, but may not be limited to, race, color, religion, national origin, sex, marital status, age, disability, handicap, family status, ancestry, sexual orientation, unfavorable military discharge, and gender. Experian’s provision of Fair Lending Friendly indicators does not constitute legal advice or otherwise assures your compliance with the FHA, ECOA, or any other applicable laws. Clients should seek legal advice with respect to your use of data in connection with lending decisions or application and compliance with applicable laws. Appendix Sports enthusiasts Lifestyle and Interests (Affinity) > Activities and Entertainment > NFL Enthusiasts Lifestyle and Interests (Affinity) > Sports and Recreation > Sports Enthusiast Mobile Location Models > Visits > NFL Stadium Visitors Lifestyle and Interests (Affinity) > Sports > Football (FLA / Fair Lending Friendly)2 Travel Intent > Activities > Professional Sports Event College sports fans Mobile Location Models > Visits > University Stadium College Football Visitor Lifestyle and Interests (Affinity) > Sports > College Football Bowls Mobile Location Models > Visits > College Students Mobile Location Models > Visits > College Sport Venues 21+ audiences Lifestyle and Interests (Affinity) > Activities and Entertainment > Imported Light Beer Enthusiasts Lifestyle and Interests (Affinity) > In-Market > Domestic/Imported Beer Lifestyle and Interests (Affinity) > Retail > High-end Spirit Drinkers Financial – Analytics IQ > Discretionary Spend > Alcohol and Wine: $331-$726 TV viewers Television (TV) > Household/Family Viewing > Cable Satellite or Streaming Network Subscribers Retail Shoppers: Purchase Based > Entertainment > Streaming/Video/Audio/CTV/Cable TV: Streaming Video: High Spenders Television (TV) > Household/Family Viewing > Cord Cutters Television (TV) > Household/Family Viewing > Cable and Streaming Service Subscribers Television (TV) > TV Enthusiasts > Paid TV High Spenders Television (TV) > Viewing Device Type > Screen Size – Large Television (TV) > Household/Family Viewing > Co-Watchers Latest posts

As marketers face growing fragmentation and signal loss, Experian has launched a powerful new solution: a data marketplace that brings addressability, interoperability, and identity resolution into one activation-ready platform. Download the overview to see how our data marketplace connects high-quality identity to scalable activation across all screens. Download the overview The data you need to reach real people across every channel Today’s marketers are trying to connect with real people, not just cookies, devices, or IDs, across more channels than ever. But with so many signals disappearing, that’s getting harder to do. That’s where Experian’s data marketplace comes in. Our data marketplace is built on our best-in-class identity graph, which includes 126 million U.S. households, 250 million individuals, and 4 billion+ active digital IDs. Experian connects the entire ecosystem — TV operators, programmers, supply-side platforms (SSPs), demand-side platforms (DSPs), and brands — with activation-ready audiences that drive measurable performance. Buyers can access data from retail, CPG, healthcare, B2B, location intelligence, and more. Because we start with verified offline data, our audiences are grounded in real-world accuracy, not just digital assumptions. That means when you activate through our marketplace, you can: Reach more of the right people Stay accurate at scale Keep addressability high even as the ecosystem shifts Whether you're running a campaign on CTV, mobile, or display, we help you show up in the right place, to the right person, at the right time. Related reading Four CTV advertising misconceptions marketers need to drop Tap into premium data from top partners like: Alliant, Attain, Circana, Dun & Bradstreet, and more. "Experian has been a longstanding partner of DISH Media, and we’re excited to be an early adopter of their marketplace which leverages the foundation of their identity solutions to ensure maximum cross-channel reach as we look to expand the breadth and depth of data we use for addressable TV."Kemal Bokhari, Head of Data, Measurement & Analytics Want a quick overview of Experian's data marketplace? Watch our video for a quick overview of how Experian's data marketplace works. Read the article here How it works: Benefits for buyers, sellers, and platforms Our data marketplace is built to support high-performance media strategies, helping partners activate and scale faster. Here’s how it delivers: Enhances addressability and match rates All audiences delivered from our 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. Simplifies audience planning and distribution for TV Operators TV operators can build custom audiences matched directly to their subscriber footprint and distribute them across all advanced TV channels (data-driven linear, addressable, digital, and CTV) for maximum impact. Reintroduces choice within the data marketplace ecosystem With the departure of Oracle’s advertising business, the optionality for buyers and sellers to connect with third-party data has become increasingly limited. With Experian's data marketplace, we’re excited to offer a new solution to the market that ensures data-driven targeting can continue to take place at scale. Reduces activation costs Experian’s data marketplace offers transparent, pass-through pricing with no additional access fees, enabling partners to maximize their earnings while reducing costs. Expands audience diversity and scale Platforms can access a broad range of audiences across top verticals from our partner audiences, which can be combined with 2,400+ Experian Audiences. This offers the flexibility, reach, and scale necessary to effectively execute advertising campaigns. “Circana and Experian have enjoyed a deep partnership for over a decade. We are exceedingly excited to extend our partnership and be an early adopter and launch partner of the Experian data marketplace. This additional capability will enable the ecosystem to more easily access Circana’s purchase-based CPG and General Merchandise (for example Consumer Electronics, Toys, Beauty, Apparel etc.) audience segments to drive performance outcomes across all media channels.”Patty Altman, President, Global Solutions Want to learn more about our data partners? Q&A with Attain Q&A with Circana Q&A with Webbula “Capturing the attention of target audiences across channels is critical for marketers navigating an increasingly connected digital world. We are excited to be an exclusive provider of B2B solutions within Experian’s marketplace, helping brands and media agencies to accelerate their reach, addressability and targeting capabilities across TV, mobile and connected TV channels.” Georgina Bankier, VP of Platform Partnerships How Yieldmo drove in-store traffic for an athletic retailer with Experian's data marketplace Yieldmo, a leading SSP known for its AI-powered creative formats and privacy-forward inventory, partnered with Experian to support an athletic retailer’s campaign focused on driving in-store traffic — particularly during key sales windows. By using Experian’s data marketplace, Yieldmo built a self-serve targeting strategy combining Experian Audiences and high-performing partner segments (e.g., Alliant, Circana, Webbula, and Sports Innovation Lab). They were able to: Quickly identify in-store and conquest segments Easily combine first- and third-party audiences Improve match rates and cross-channel addressability Deliver measurable foot traffic lift “Experian’s data marketplace fills a critical gap, letting us quickly search by brand, build smarter conquest segments, and activate audiences fast. The platform is flexible and the support is hands-on and reliable.”Abby Littlejohn, Director of Sales Planning The result? Faster setup, more tailored audiences, and stronger in-store outcomes all while reducing manual work. Download the full case study Learn more about our solutions for SSPs Ready to activate? Better connections start with Experian's data marketplace Experian’s data marketplace, easily accessible from our Audience Engine platform, brings unparalleled addressability, enabling our clients to reach more relevant consumers and increase revenue. Talk to our team if you’re interested in learning more about our new data marketplace or becoming an active buyer or seller, or download our overview to learn more. FAQs What is Experian’s data marketplace? Experian’s data marketplace is a centralized, activation-ready platform that allows TV operators, programmers, supply partners, and demand platforms to access and activate high-quality, privacy-compliant audiences across CTV, mobile, and display. It supports both first-party onboarding and third-party audience activation. Who is the Experian data marketplace designed for? The Experian data marketplace is built for TV operators, programmers, supply partners, and demand platforms looking to improve audience targeting, match rates, and addressability across fragmented digital environments. What types of audiences are available in the Experian data marketplace? The Experian data marketplace offers a mix of Experian proprietary audiences and third-party data partner segments across verticals like retail, CPG, B2B, healthcare, financial services, and location intelligence. Users can activate over 2,400+ Experian Audiences and premium partner segments from providers like Alliant, Attain, Circana, Dun & Bradstreet, Webbula, and more. How does Experian ensure addressability and match rate performance? Experian’s data marketplace is powered by our identity graphs which are rooted in verified offline data, spanning 126 million U.S. households, 250 million individuals, and over 4 billion active digital identifiers. This foundation ensures that audiences are accurate, actively targetable, and optimized for high match rates across CTV, mobile, and display platforms. Is Experian’s data marketplace privacy-compliant? Yes. All data in the Experian data marketplace is subject to Experian’s rigorous partner review process to ensure compliance with federal, state, and local consumer privacy regulations. Privacy and data stewardship are foundational to our data marketplace’s design. What makes Experian’s data marketplace different from other data marketplaces? Experian’s data marketplace stands out for its focus on audience accuracy, partner integration, privacy compliance, and deep identity expertise. Here’s how we’re different: – Accurate audience planning: Unlike many other marketplaces, Experian ensures that all identifiers tied to an audience are verified as active and targetable — improving match rates and reducing waste. – Seamless partner audience integration: In one platform, you can activate Experian Audiences alongside premium segments from our growing partner network — including Alliant, Attain, Circana, and more. – Privacy and compliance built in: Every partner and audience goes through Experian’s rigorous review process to meet federal, state, and local consumer privacy laws — so you can activate with confidence. – Trusted identity foundation: Experian’s identity graph is grounded in decades of offline data expertise, powering more reliable targeting and activation than marketplaces built solely on digital signals. Where can I learn more or get started? You can download the overview to explore the capabilities, or contact our team to become an active buyer or seller. The Experian data marketplace is available through Experian’s Audience Engine platform. Latest posts

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. Contact us Latest posts