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
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
Identified in The 2021 Digital Advertising Trends Report published by Postclick, marketers are striving to improve and enhance their segmentation and targeting strategies in their digital ad campaigns. Carlos Lopez, SVP of Brand Planning at Digitas Health predicted that in 2021, the challenge will be to overcome the death of third-party cookies and still deliver a personalized advertising experience. It’s fair to say that his prediction will still be impacting marketers past 2021 with the delay of cookie deprecation. These goals along with the constantly changing digital landscape paint a challenging picture for even the most advanced marketers. Marketers can be prepared for the next era of digital marketing by finding the right mix of partners that offer privacy-safe, cookie-free solutions. Smart marketers will employ these solutions and compare these results with data from cookies. The Tapad + Experian Take The Tapad Graph enables brands, agencies, and ad tech platforms to identify and target individuals and households across their digital touchpoints. With this data, they can personalize messages across devices, measure and optimize throughout the customer journey, and then report back on conversions at the individual and household levels. Tapad, now part of Experian, leverages a machine learning algorithm that determines these connections at scale by using probabilistic models with authenticated, privacy-safe, real-time data. There are a myriad of cookieless IDs emerging in the marketplace, and it’s not likely going to be a one size fits all situation. In order to be prepared for the next era of digital marketing, marketers should diversify ID partners and be proactive with testing while the cookie is still around to benchmark against. With Switchboard, a module within The Tapad Graph, we’ve been able to develop connections between traditional digital identifiers (IP Addresses, MAIDs, CTV IDs) and the new wave of cookieless IDs (UID2.0, Panorama ID, ID5 ID) that will be utilized in the future. Here’s an example of what The Tapad Graph and Switchboard looks like at the Household level with various traditional digital identifiers and cookieless IDs. Get started with The Tapad Graph For personalized consultation on the value and benefits of The Tapad Graph for your business, email Sales@tapad.com today!
Marketers are under more pressure than ever before to prove ROI and efficiency of marketing activities in relation to business performance. On top of that, there are new privacy regulations and uncertainty around what new technologies will have to be implemented in order to replace the granular level targeting and measurement the industry historically has used third-party cookies for. It’s clear marketers are going to need the right tech stack and partners to continue to prove their team’s efficacy. We recently partnered with Forrester Consulting to evaluate the current state of customer data-driven marketing and surveyed over 300 global marketing decision makers at the brand and agency levels. We found that marketing is facing increased demands today, insights from the study include: Consumers expect brands to deliver engaging experiences across highly fragmented journeys. Seventy-two percent of decision-makers reported that customers demand more relevant, personalized experiences at the time and place of their choosing. Marketing runs on data, but the rules governing customer data usage are changing quickly. More than 70% of study participants stated that consumer data is the lifeblood of their marketing strategies, fueling the personalized, omnichannel experiences customers demand. These demands paint a challenging picture. Just as marketers are poised (and tasked) with delivering greater value to their organizations and customers, the ground rules are changing and threatening their ability to deliver. Indeed, 62% of respondents said that the forces of data deprecation will have either a “Significant” (40%) or “Critical” (21%) impact on their marketing strategies over the next two years. Effective identity resolution can help brands prepare for data deprecation challenges Marketers face a daunting landscape, but they can leverage the data, technology, and processes that comprise identity resolution to address business objectives, combat ecosystem complexity, and future-proof customer engagement efforts. By utilizing identity resolution, marketers will be able to match and connect multiple identifiers across devices and touchpoints. This allows for a cohesive, omnichannel view that enables brands to continue to deliver personalized and contextually relevant messages throughout the customer journey and without the use of cookies. The identity graph is the underlying infrastructure that defines connections between the numerous, fluid, and disparate identifiers created during moments of consumer engagement, turning disparate signals into addressable and actionable steps. These connections enable brands to bolster their ability to gain deeper customer insights and power audience building, attribution, and connected measurement. Identity resolution encompasses a wide range of capabilities that support an equally diverse set of marketing use cases. These include the targeting, personalization, and measurement of both known and pseudonymous audiences in the offline and digital worlds, which enables marketers to improve customer data management, drive more effective personalization, and gain insights and efficiencies through measurement across touchpoints. By taking the time to vet the privacy procedures and data collection processes of identity solutions you can reduce your regulatory risk and maintain customer trust. In an open-ended survey response, a marketer shared, “We’ve found that users are willing to volunteer data when they understand what it’s being used for and are asked for clear consent.” Finding the right partners to help navigate the changes The scramble to find an alternative to third-party cookies has slowed down since Google announced they will be delaying their cookie removal until late 2023. However, this gives marketers a unique opportunity to take advantage of the additional time and feel more prepared and confident in their solutions. With the delay, marketers can now test ID solutions and compare apples to apples with data from the third-party cookie while it’s still active and addressable. Test and find a solution that works now, so there are no surprises once cookies have finally made their way out the door in 2023. At Tapad, a part of Experian, we’ve developed a solution that provides agnostic interoperability for the myriad of cookieless identifiers emerging in the market. As a new module in the Tapad Graph, Switchboard will connect traditional digital identifiers to cookieless IDs to support the entire ad ecosystem with privacy-safe future-proof identity resolution. Get started with The Tapad Graph For personalized consultation on the value and benefits of The Tapad Graph for your business, email Sales@tapad.com today!
Identity is being constrained, forcing the industry to rethink the way it has operated for 27 years. Industry, regulatory, technology and data trends are leading to a fundamental shift in the way that data is permissioned, accessed, and used for marketing purposes. How the industry defines digital identity moving forward, consumer trust and transparency need to be at the forefront. We, as an industry, have the opportunity to build a more effective advertising framework that puts consumers and data privacy at its core, a framework that won’t rely on a single prevailing identifier. That approach requires all of us to be upfront and transparent about our data practices and usage and make it easy for consumers to opt-out of the use of their information for advertising and marketing solicitations. We, at Experian, also believe that there are a lot of ways to improve the experience for consumers, who are becoming more aware and apprehensive of giving away their data. We believe we can ease the minds of consumers and work within these new constraints by offering better controls and practices around the ways data is shared and utilized. There will be new approaches that come to the market as well that include modeled, non-identifiable information, cohorts, contextual