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!
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.
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
Get in touch
About our experts
Jason Andersen, Senior Director, Strategic Initiatives and Partner Solutions, Experian
Jason 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, Yieldmo
Alex 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.
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Every year, the Experian team attends the Consumer Electronics Show (CES) in Las Vegas, to immerse ourselves in the world's most significant consumer tech showcase and stay at the forefront of the latest technological advancements and innovations that shape the AdTech industry. This year's event was a vibrant melting pot of innovation and vision, from streamers taking a bigger bite of the advertising pie to the emergence of AI-powered solutions and drone delivery services. Amidst these advancements, the dynamic interplay of technology, media, and advertising raised important questions, especially in the context of evolving regulations and cookie deprecation. During CES, we captured insights from various thought leaders, and in the coming months, we'll be sharing these valuable perspectives with you. Watch the video below for full insights coming from our content studio onsite during the event. Or, keep reading for a recap on four key trends from CES and what they mean for your business in 2024! “My first CES was a major success. You could feel the buzz in the air as new ideas and partnerships were being created within and across industries. The intersection of the different players within retail media, connected TV, retail technology, the demand and supply-side, and agencies all in an ever-changing world of regulation and privacy begs for a solution that can maximize a successful outcome for all.”anne passon, sr director, sales, retail & cpg 1. Audience targeting: How first- and third-party data work together A central theme at CES was the importance of audience targeting, highlighting the crucial role of first-party data. However, it’s clear that to maximize its potential, this data needs to be augmented with sophisticated identity solutions and enriched with third-party insights, all while navigating the complexities of privacy regulations. This integrated approach is vital to understanding audiences and for creating more effective marketing strategies that comply with privacy regulations. 2. Standardizing metrics in retail media networks The challenges around retail media networks, particularly in terms of standardizing metrics like incremental return on ad spend (iROAS), were a hot topic at CES. This complexity around this topic underscores the need for neutral, expert third parties to help bring clarity and consensus, aiding businesses in navigating this multifaceted domain. 3. The challenge of switching data solutions Discussions covered the broader challenges associated with transitioning to new data solutions. For businesses, this involves a critical assessment of the benefits versus the costs and complexities of adopting new platforms or systems. This decision-making process is increasingly significant as data strategies become integral to marketing success. 4. Identity solutions in a cookieless future With the industry moving toward a cookieless future, the spotlight at CES was on the importance of robust identity solutions. Understanding the functionality and necessity of various universal IDs is essential to minimize data loss and maintain effective targeting. Investing in flexible and adaptable identity solutions like the Experian Graph is essential to maintain effective targeting and audience engagement in this new landscape. Announcements and advertising innovations at CES 2024 CES was a stage for significant announcements and innovative marketing initiatives: Criteo and Albertsons announced their collaboration in retail media. Instacart's partnership with Google for enhanced shopping ads and AI shopping carts. NBCUniversal's advancements in streamlining programmatic advertising. Brands like Netflix, LG, Freewheel, and Amazon Ads also captured attention with their creative marketing strategies, ranging from unique collaborations to themed promotions and captivating events. These insights from CES provide a glimpse into the future of technology, media, and advertising. They highlight the need for adaptability, innovation, and informed decision-making in these dynamic industries, especially in the context of privacy regulations. Stay tuned for our series of posts where we'll dive deeper into these topics, sharing exclusive insights from industry thought leaders. Follow us on LinkedIn or sign up for our email newsletter for more informative content on the latest industry insights and data-driven marketing. Contact us Latest posts
In this article…A history of ad-supported TVThe resurgence of ad-supported TV models Free ad-supported streaming vs paid ad-supported TV What FAST popularity means for marketersThe future of ad-supported TV In the early days, streaming services were presented to viewers as convenient alternatives to cable that allowed you to get content whenever you wanted it — without ads. But as standalone streaming platforms have grown in number and prominence, often charging high monthly costs for subscription-based content and continually hiking their rates, many are warming back up to the idea of ads if it means lower monthly fees. Cue free ad-supported TV (FAST) streaming services: free video content with no paid subscription requirement. These services generate revenue through advertising and deliver content with periodic commercial breaks to support their free model. This option has become popular as viewers have sought out cost-effective alternatives to traditional scheduled television. Free streaming TV platforms such as the Roku Channel, Tubi, and Pluto TV are growing, with one in three U.S. viewers subscribing to free ad-supported TV streaming services. If premium streaming platforms keep raising their monthly costs, we can predict that FAST will continue to grow. In this article, we’ll talk about the current state of the ad-supported TV climate, including the opportunities and challenges it poses for marketers. A history of ad-supported TV Historical context is crucial to understanding the current climate of ad-supported TV and its implications for your marketing. Before the rise of cable TV, television was free for viewers, with advertisers covering the costs. The first TV commercial, a 10-second spot for the Bulova Watch Company, aired in 1941 during a baseball game and cost the company $9. This ad kickstarted the era in which advertisements funded the TV model, which quickly surpassed radio in popularity and led to an explosion of content. From 1956 to 1988, commercials became embedded in culture, giving rise to marketing icons like Ronald McDonald and memorable campaigns like Nike's “Just Do It.” From 1989 to 2006, the world saw the rise of online entertainment and advertising with the invention of the World Wide Web — and subsequently, online video broadcasting and advertising emerged. But between 2007 and 2014, over-the-top (OTT) broadcasting and connected television (CTV) innovation disrupted traditional broadcasting, with ad-supported streaming gaining greater prominence. Platforms like Netflix and Hulu allowed viewers new freedom from the confines of scheduled programming. By 2022, CTV advertising thrived thanks to programmatic advertising, which allowed businesses to reach targeted audiences with relevant campaigns. Ad-supported streaming became widespread as platforms like Netflix and Disney+ incorporated advertising into their models. Free ad-supported TV (FAST) emerged as a form of advanced television that displaced traditional cable and satellite TV. Recent years have witnessed a notable shift back to ad-supported streaming television due to the proliferation of streaming services, subscription fatigue, and the desire for cost-effective content consumption. Looking ahead to the future, TV advertising is expected to continue growing with the potential to be influenced by innovations like virtual reality and artificial intelligence. Why did the popularity fade? Ad-supported TV waned in popularity due to the introduction of cable TV and subscription-based models. Cable TV offered ad-free content for a subscription fee, which reduced the appeal of traditional ad-supported broadcasts. Uninterrupted content became a critical selling point for cable providers, but it created fragmentation for advertisers and made it more challenging for them to reach their target audience. With cable and, later, satellite TV dominating the market, advertisers had to adapt their strategies. The decline in the popularity of ad-supported TV led to a decreased reliance on traditional advertising methods, and marketers began exploring alternative avenues to connect with consumers effectively. The recent resurgence of ad-supported TV, particularly in streaming services, indicates a shift in viewer preferences. You can utilize targeted advertising cost-effectively, as viewers prefer free, ad-supported content over subscription-based models. The resurgence of ad-supported TV models The resurgence of ad-supported TV models can be partly attributed to the COVID-19 pandemic and changing viewer preferences. In 2020, stay-at-home measures led to a surge in media consumption, and people turned to streaming for entertainment. This shift provided a unique opportunity for ad-supported models to regain popularity. But as viewers explored various streaming options, subscription fatigue set in. Paid streaming proliferation increased costs, and people began reconsidering spending on multiple subscriptions. The pandemic triggered a fundamental shift in TV consumption and caused viewers to favor ad-supported streaming models that offered free content with occasional commercial breaks. In fact, LG Ad Solutions research revealed that 80% of American TV viewers use free ad-supported streaming services — and 63% express a preference for this model. This finding challenges assumptions made during the initial stages of the pandemic, where subscription-based consumption seemed dominant. The study suggests that as subscription fees accumulated, viewers sought more content without increasing costs, driving a preference for ad-supported streaming. Furthermore, the landscape of ad-supported TV saw notable entries from major streaming platforms: HBO launched its ad-supported model in June 2021. Netflix and Disney+ introduced their ad-supported tiers in late 2022. Amazon announced in September 2023 that they would be launching their ad-supported service in 2024. These developments emphasize the industry's recognition of the demand for ad-supported content and further contribute to the prominence and endurance of this model. Most popular platforms A report from Samba TV showed that one in three U.S. viewers subscribes to free ad-supported TV streaming services, such as Pluto TV, Tubi, or the Roku Channel. The report highlights Amazon's Freevee as a standout due to its high viewership growth in the first half of 2023 compared to competitors. Here are some details to note about Freevee and its major competitors: Freevee (Amazon Prime) With a focus on bringing diverse content to its audience, including thousands of premium TV shows and movies, Freevee has positioned itself as a go-to destination for those looking for quality programming without subscription fees. In early 2022, Freevee had 65 million monthly active users, and their ad prices, similar to competitor costs, range between $13 and $24 per day — around $400 and $720 per month, respectively. Pluto TV (Paramount) As a pioneer in the FAST streaming space, Pluto TV, now under Paramount, boasts a diverse range of 250+ channels. According to Statista data from November 2022, 8% of Americans watched TV on Pluto on a daily basis, with men watching more often than women. You can strategically engage with Pluto TV's varied audience for around $999 a month, with advertising costs influenced by factors like viewership and channel prominence. Tubi (Fox) Surpassing many competitors in viewership, Tubi, owned by Fox, offers an extensive collection of free content (200,000 movies and TV episodes) and enjoys 74 million active monthly users. Tubi has experienced the fastest growth among young, diverse audiences and has produced or acquired 200 titles that almost 54 million viewers have watched. You can market to viewers on Tubi for $10 to $45 daily or $300 to $1,350 monthly. The Roku Channel With over 350 channels and premium original content, The Roku Channel has become an important player in the FAST space. Approximately 38% of streaming hours in U.S. households are spent on the Roku Channel. With Roku Ads Manager, you can get started with only $500. New players The FAST industry is seeing an influx of new players all the time, which is contributing to the industry's growth and innovation. As traditional subscription-based models adapt to include ad-supported tiers, the competition in the ad streaming sphere has intensified, prompting both established and emerging platforms to explore the FAST model. Statista reports that the number of users in the FAST market is expected to reach 1.1 billion by 2028! The recent entry of industry giants like Netflix into the ad-supported realm has set the stage for significant shifts. When Netflix announced and launched its ad-supported tier in late 2022, the industry experienced a notable spike in CPMs (cost per mille/cost per thousand impressions). This reflected the initial scarcity of users on this tier. As more subscribers embraced the ad-supported offering, CPMs decreased. Subscription video-on-demand (SVOD) platforms, including Disney+, are also incorporating ad-supported tiers into their models to cater to viewers' preferences for cost-effective streaming options. Industry reports illustrate a decrease in CPMs as more users engage with ad-supported tiers, which creates a vibrant, competitive environment for advertisers like you. Free ad-supported streaming vs paid ad-supported TV The affordability of free ad-supported streaming services is attractive for viewers seeking cost-effective alternatives to traditional cable or non-ad-supported streaming platforms. Platforms like Pluto TV and Tubi provide viewers with a wealth of content without the financial commitment of a subscription. Free ad-supported streaming services like these have gained traction for their cost-effectiveness. In contrast, paid ad-supported TV models present a unique proposition — pay for the service and enjoy reduced subscription costs by opting for an ad-supported plan. These models provide users with a middle ground between subscription-based and free ad-supported streaming. The future popularity of free ad-supported streaming versus paid ad-supported streaming is likely to be influenced by a combination of viewer preferences, content strategies, ad experiences, and broader industry dynamics. As both models evolve, streaming services will continue to experiment and adapt to meet the diverse needs of their audiences. What FAST popularity means for marketers The shift towards FAST aligns with changing viewer preferences. This makes things easier for your marketing, as you can: Engage a broader audience: Without the barriers of subscription fees, and the ability to place ads in front of diverse demographics, you can customize campaigns for specific audiences and ensure your messages resonate with viewer interests. Convey your message to a captive audience: The rise of FAST also implies an increased viewership of commercials, as these services typically feature ad-supported models with limited options for viewers to skip or fast-forward through ads, creating a more captive and engaged audience. Expand your brand exposure: The cost-effectiveness of ad-supported models provides a valuable avenue for brand exposure without the hefty price tags associated with traditional TV advertising. As a marketer, it’s essential for you to understand the dynamics of ad-supported TV platforms so you can recognize unique advertising formats, optimize campaign frequency to prevent ad fatigue, and embrace the potential for localization and personalization. As advertising evolves with the growing popularity of FAST, you have an opportunity to stay ahead of the curve, craft compelling campaigns, and maximize your reach at a time when ad-supported streaming is at the forefront of entertainment. The future of ad-supported TV The re-emergence of ad-supported TV, along with recent innovations, indicates that the future of this model is bright. Teevee Corporation, a hardware startup led by the co-founder of Pluto TV, is an excellent example. It is set to unveil a groundbreaking ad-supported physical television that won’t cost consumers a single cent — as long as they’re okay with a second integrated screen that displays ads while they watch the main screen. This TV is distinct from streaming services and uses automatic content recognition (ACR) for contextually relevant ad delivery. Teevee's approach introduces a new dimension to viewer engagement that combines traditional broadcasting with targeted advertising. Major streaming platforms are actively contributing to the evolution of ad-supported TV as well. Amazon made the strategic move to bring Amazon Original titles and additional ad-supported channels to Freevee to demonstrate its commitment to the ad-supported market. The platform introduced 23 new ad-supported TV channels from major entertainment players such as Warner Bros. Discovery and MGM. As a result, Amazon's Freevee experienced tremendous growth in viewership in the first half of 2023, up 11% year-over-year. These recent advances illustrate what the future of streaming with ad-supported TV may look like moving forward, where hardware innovation meets strategic content integration, and major platforms compete to enhance their ad-supported offerings. How Experian can help Although the FAST industry is rapidly evolving, Experian stands at the forefront with powerful data-driven solutions that empower you to take advantage of this valuable marketing opportunity. Consumer Sync is a robust identity solution that empowers advertisers by facilitating collaboration and offering insights that contribute to more effective and targeted FAST campaigns. Audience segmentation, attribution, and campaign optimization play vital roles in FAST advertising. Our Consumer View solution provides industry-leading data solutions for audience segmentation, which allows marketers to predict buying behaviors and deliver personalized experiences. Connect with Experian's TV experts As you explore the possibilities of ad-supported TV, Experian offers the expertise and solutions you need to elevate your marketing strategies. Connect with our TV experts today to gain a deeper consumer understanding, refine your targeting, and ensure the success of your campaigns. Connect with our TV experts today Latest posts
Experian continues to lead in data accuracy according to Truthset's latest analysis Advertisers, technology partners, and agencies are all chasing accurate data to power their marketing strategies. But not all data is created equal. Truthset’s latest findings confirm Experian's leadership in third-party data accuracy, giving brands and agencies confidence in every decision they make. Accurate data is the foundation for predictive insight, real-time intelligence, and AI-powered personalization. Experian’s AI-driven solutions help marketers move from data to action, delivering more relevant messages with less waste. Truthset's independent study found that up to 51% of ad targeting data is inaccurate, with accuracy rates ranging between 32% and 69% across providers. This reinforces the importance of validated, trusted data from partners like Experian. The data quality challenge Inaccurate data can lead to: Wasted ad spend Without accurate data at the start, marketers can’t reach the right audiences, resulting in wasted impressions. Privacy and compliance risks In an increasingly privacy-centric world, advertisers need to be especially mindful of accurate targeting to avoid putting their brand reputation at risk. Poor campaign performance Low-quality data skews metrics and attribution models, making it difficult to measure campaign success and optimize spend. Low-quality data can come in different forms, like inconsistent or outdated information – think demographics (age, gender) and interests (dog versus cat lover), or simply the wrong relationship can be made between data sets. Data records can be incomplete or duplicative, and data segments could be misclassified or inaccurate. 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Experian's AI-powered capabilities, including predictive models, transform clean, validated data into meaningful engagement strategies that balance performance with privacy. Independent validation from Truthset ensures that Experian’s data remains among the most accurate in the ecosystem. "As cookies and mobile ad identifiers continue to phase out, consented, durable identifiers (hashed email, postal addresses) are going to serve as the foundation for identity solutions of the future. And the only way to ensure you are transacting on the highest quality identity and demography data is to actively validate the data you rely on with a third party.” Chip Russo, President at Truthset Experian's commitment to data accuracy Since joining the Truthset Data Collective in 2023, Experian continues to be the industry leader in data accuracy. Truthset's latest Q2 2025 analysis reaffirms our leadership in data accuracy: Experian is the #1 data provider of largest volume of high-accuracy hashed emails (HEMs) Experian ranks #1 in accuracy for eight marketing data attributes, including but not limited to Age, Geography, Presence of Children, and Education Experian ranks #1 or #2 for 22 of the 24 attributes, and #3 for the two others (out of 12 companies being analyzed) Experian consistently has the largest number of HEMs that are 90% or more likely to be accurate “As a member of the Truthset Data Collective, Experian received top ranks across a variety of categories for its data. The entire digital advertising world runs on data, but focusing on data accuracy is going to drive the next phase of innovation for the industry, enhancing ROI for advertisers, CPMs for publishers, and relevant experiences for consumers.” Chip Russo, President at Truthset As Truthset's recent study highlights, the data matched between hashed emails and postal addresses is crucial, underpinning everything from targeted ads to TV audience measurement. Highly accurate HEMs linked to high-quality demographic data should be the foundation of any marketing plan. Advertisers are able to overcome the complexities of identity resolution by tying online and offline touchpoints together to deliver a consistent message across channels. Real-time relevance, powered by ethical AIExperian combines validated identity data with intelligent technology to deliver marketing that works for people and brands. Companies are striving to eliminate marketing waste and provide consumers with personalized marketing and the advertising industry can have confidence that Experian’s marketing data has been externally validated as being highly accurate. The accuracy of our data will power better marketing initiatives, like insights, targeting, identity, and measurement. Whether you're optimizing for reach, relevance, or ROI, AI is changing how marketing works. Experian’s human-centered, privacy-first AI makes it easier to adapt, act faster, and connect with consumers in ways that are more meaningful. Let's start a conversation about how we can fully realize the potential of data-driven advertising together. Contact us today FAQs What is Truthset, and why does their validation matter? Truthset is an independent data validation company that reviews and ranks data providers based on accuracy. Their ratings help advertisers understand which data sources they can trust. Experian ranks #1 in data accuracy according to Truthset. How does Experian’s performance compare to others in Truthset’s study? Experian ranks #1 for accuracy in multiple categories, including Age, Geography, and Presence of Children, and holds the largest number of hashed emails that are 90% or more likely to be accurate. Why is data accuracy so important for marketers? Accurate data is important for marketers because it leads to more efficient targeting, reduced ad waste, and better campaign performance. It also reduces compliance risk by helping advertisers engage responsibly. Experian's data is ranked #1 in data accuracy according to Truthset. How does Experian use AI responsibly? Experian’s privacy-first, AI-driven models clean, enrich, and validate data while respecting consent and ethical standards. How can advertisers get started with Experian's data? Connect with the Experian team to learn how our validated data and AI-powered solutions can strengthen your targeting, insights, and ROI. Latest posts