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.
Latest posts
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"The homepage surface is making a comeback in the publishing industry, proving its value in establishing a direct connection with readers. While we acknowledge the importance of technology partnerships for addressability and identity, our core competency as a publisher remains outstanding journalism that captures and engages great audiences." kevin gentzel, cco, newsweek Watch our Cannes panel for more on supply-side advertising We hosted a panel in Cannes that covered supply-side advertising. Check out the full recording below to hear what leaders from Audigent, Captify, Newsweek, Pubmatic, Truthset, and Experian had to say. Watch now Check out more Cannes content: Our key takeaways from Cannes Lions 2023 Insights from a first-time attendee Four new marketing strategies for 2023 Exploring the opportunities in streaming TV advertising The future of identity in cookieless advertising 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 today Latest posts
The digital advertising landscape has undergone a seismic shift in recent years. Privacy-conscious consumers, transformative regulations, and emerging technologies are converging to redefine how addressability — the ability to accurately reach a specific audience — functions in this new era. Addressability is a cornerstone of digital advertising, and its evolution presents both challenges and opportunities for publishers and advertisers alike. The need for enhancing addressability is driven by a complex set of factors. More consumers are opting out of data sharing or disabling cookie-tracking, leading to a drastic reduction in the reach of traditional programmatic advertising. Nearly 70 percent of consumers are now unreachable through these conventional methods, creating an 'addressability gap' that publishers and advertisers are eager to bridge. The landscape is further complicated by privacy regulations such as General Data Protection Regulation (GDPR) and California Consumer Privacy Act (CCPA), which mandate solutions that balance user privacy with advertisers' needs. Contributing to this intricate mix is the growing shift toward video and connected TV (CTV). These platforms have long operated in a cookie-less environment and are witnessing rising demand due to their engaging nature and broad reach. However, the attractiveness of these mediums to advertisers hinges on effective addressability, highlighting the urgent need for innovative audience identification and targeting methods. The emergence of data enablers and collaborative initiatives Data enablers like Experian are stepping up to meet this need. These companies are providing robust, privacy-compliant data resources to improve addressability. Experian's unique approach to identification, the Living Unit ID (LUID), is a key tool in bridging the current gap in reach. How Experian and Microsoft Advertising are redefining addressability We recently expanded our collaboration with Microsoft, to make our extensive data resources available through Microsoft Advertising’s data marketplace. This collaborative initiative represents a significant move, offering a compelling model of how data enablers and buy-side and sell-side platforms can work together to redefine addressability. The benefits of this arrangement extend to all stakeholders in the ecosystem. Advertisers using Microsoft Invest can now access Experian's audience data. This not only enhances the granularity of their audience targeting but also broadens the reach of their campaigns. Experian's identity spine also serves as a robust framework to extend the value and reach of advertisers' first-party data. For publishers, the accessibility of Experian data on Microsoft Advertising’s data marketplace opens the door to greater addressability in their inventory, enabling them to offer advertisers more addressable impressions. This then amplifies the value of their inventory, potentially increasing their overall yield. For advertisers, this integration facilitates access to highly relevant audiences while simplifying campaign setup and respecting user privacy. We can help you carve a new path toward addressability In the ever-evolving landscape of digital advertising, such collaborative efforts are becoming critical to ensure that advertising remains effective for brands, profitable for publishers, and respectful of consumer privacy. This model of cooperation and innovation is essential to navigate the challenges of a privacy-centric, cookie-less world and unlock the true potential of every media channel. With collaborative initiatives and innovative solutions, the industry is set to transform these challenges into opportunities, carving a new path toward addressability that respects privacy and delivers value for all stakeholders. Connect with us to learn more about how you can access our data in Microsoft Advertising’s data marketplace. To learn more about our partner Microsoft Advertising, visit their website. Contact us Latest posts
The cookieless future is here, and it's time to start thinking about how you will adapt your strategies to this new reality. In a cookieless world, you will need to find new ways to identify and track users across devices. This will require reliance on first-party data, contextual advertising, and alternative identifiers that respect user privacy. To shed light on this topic, we hosted a panel discussion at Cannes, featuring industry leaders from Cint, Direct Digital Holdings, the IAB, MiQ, Tatari, and Experian. In this blog post, we'll explore the future of identity in cookieless advertising. We'll discuss the challenges and opportunities that this new era presents, and we'll offer our tips for how to stay ahead of the curve. How cookieless advertising is evolving Programmatic advertising is experiencing multiple changes. Let's dive into three key things you should know. Cookie deprecation One significant change is cookie deprecation, which has implications for tracking and targeting. Additionally, understanding the concept of Return on Advertising Spend (ROAS) is becoming increasingly crucial. The demand and supply-side are coming closer together Demand-side platforms (DSPs) and supply-side platforms (SSPs) have traditionally been seen as two separate entities. DSPs are used by advertisers to buy ad space, while SSPs are used by publishers to sell ad space. However, in recent years, there has been a trend toward the two sides coming closer together. This is due to three key factors: The rise of header bidding Header bidding is a process where publishers sell their ad space to multiple buyers in a single auction. This allows publishers to get the best possible price for their ad space, and it also allows advertisers to target their ads more effectively. Cookie deprecation As third-party cookies are phased out, advertisers need to find new ways to track users, and they are turning to SSPs for help. SSPs can provide advertisers with data about users, such as their demographics and interests. This data can be used to target ads more effectively. The increasing importance of data Advertisers are increasingly looking for ways to target their ads more effectively, and they need data to do this. SSPs have access to a wealth of user data, and they're willing to share this data with advertisers. This is helping to bridge the gap between the two sides. The trend toward the demand-side and supply-side coming closer together is good news for advertisers and publishers. It means that they can work together to deliver more relevant ads to their users. Measuring and tracking diverse types of media The media measurement landscape is rapidly evolving to accommodate new types of media, such as digital out-of-home (DOOH). With ad inventory expanding comes the challenge of establishing identities and connecting them with what advertisers and agencies want to track. Measurement providers are now being asked to accurately capture instances when individuals are exposed to advertisements at a bus stop in New York City, for example, and tracking their journey and purchase decisions, such as buying a Pepsi. To navigate cookieless advertising and measurement, we must prioritize building a strong foundational identity framework. What you should focus on in a cookieless advertising era In a cookieless advertising era, you will need to focus on two key things: frequency capping and authentic identity. Frequency capping Frequency capping is a practice of limiting the number of times an ad is shown to a user. This is important in cookieless advertising because it helps to prevent users from being bombarded with ads. It also helps to ensure that ads are more effective, as users are less likely to ignore or click on ads that they have seen too many times. Frequency capping is often overhyped and yet overlooked. Instead of solely focusing on frequency, consider approaching it from an identity perspective. One solution could be to achieve a perfect balance between reaching a wider audience and avoiding excessive repetition. By increasing reach in every programmatic buy, you naturally mitigate frequency control concerns. Authentic identity The need for authentic identities in a digital and programmatic ecosystem is undeniable. While we explore ways to connect cookies, mobile ads, and other elements, it's crucial to remember who we are as real individuals. By using anonymized personal identifying information (PII) as a foundation, we can derive insights about households and individuals and set effective frequency caps across different channels. Don't solely focus on devices and behaviors in your cookieless advertising strategy and remember the true value of people and their identities. What’s next for cookieless advertising? The deprecation of third-party cookies is a major challenge for the digital advertising industry. Advertisers will need to find new ways to track users and target their ads. Here are three specific trends that we can expect to see in cookieless advertising. First-party data is moving in-house Many major media companies, equipped with valuable identifier and first-party data, are choosing to bring it in-house. They are focused on using their data internally rather than sharing it externally. "Many larger media companies are opting to bring their identifier and first-party data in-house, creating more walled gardens. It seems that companies are prioritizing data control within their own walls instead of sharing it externally."laura manning, svp, measurement, cint Fragmentation will continue The number of identifiers used to track people online is growing rapidly. In an average household, over a 60-day period, there are 22 different identifiers present. This number is only going to increase as we move away from cookies and toward other identifiers. This fragmentation makes it difficult to track people accurately and deliver targeted advertising. This means that we need new identity solutions that can help make sense of these new identifiers and provide a more accurate view of people. A portfolio of solutions will address signal loss Advertisers are taking a variety of approaches to cookieless advertising. A few of the solutions include: Working with alternative IDs. This refers to using alternative identifiers to cookies, such as mobile device IDs or email addresses. These identifiers can be used to track people across different websites and devices, even without cookies. Working with data index at a geo level. This refers to using data from a third-party provider to get a better understanding of people's location. This information can be used to target ads more effectively. Working with publisher first-party data that's been aggregated to a cohort level. This refers to using data that is collected directly from publishers, such as website traffic data or purchase history. This data can be used to create more personalized ads. Working with contextual solutions. This refers to using contextual data, such as the content of a website or the weather, to target ads. This can help to ensure that ads are relevant to the user's interests. "Cookie deprecation is often exaggerated, and alternate solutions are already emerging. As data moves closer to publishers and first-party data gains prominence, the industry will adapt to the changes."mark walker, ceo, direct digital holdings There is no one-size-fits-all solution for cookies, and you will need to be flexible and adopt a variety of different approaches. How will these solutions work together? You can take a waterfall approach to cookieless advertising. A waterfall approach is a process where advertisers bid on ad impressions in sequential order. The first advertiser to meet the minimum bid price wins the impression. In the context of cookieless advertising, a waterfall approach can be used to prioritize different targeting signals. For example, you might start by bidding on impressions that have a Ramp ID, then move on to impressions that have a geo-contextual signal, and finally bid on impressions that have no signal at all. This is a flexible approach that can be adapted to different needs and budgets. Watch our Cannes panel for more on cookieless advertising We hosted a panel in Cannes that covered the future of identity in cookieless advertising. Check out the full recording below to hear what leaders from Cint, Direct Digital Holdings, the IAB, MiQ, Tatari, and Experian had to say. Watch now Check out more Cannes content: Our key takeaways from Cannes Lions 2023 Insights from a first-time attendee Four new marketing strategies for 2023 Exploring the opportunities in streaming TV advertising Maximize ad targeting with supply-side advertising Follow us on LinkedIn or sign up for our email newsletter for more informative content on the latest industry insights and data-driven marketing. Get in touch Latest posts