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
Facebook has become a cultural phenomenon over the years and an object of affection for marketers to connect with its users. Experian Simmons has put together 10 consumer behavioral stats based on their National Consumer Study and New Media Study about the social networking site leading up to its Friday IPO launch: 39% of Facebook users say “this website gives me something to talk about.” Top 3 reasons Facebook users visit social networking sites: 86% to keep in touch with friends 72% for fun 66% to reconnect with/find people they’ve lost touch with 78% of Facebook users have shown support for a group or business on a social networking site. 34% of Facebook users have played games on a social networking site. Among those: 73% play social games (like Farmville, SIMS social, etc) 68% play casual games (like Bejeweled, etc) 73% play games on a social networking site once or more a day 28% of Facebook users with cell phones and 42% of Facebook users with a tablet computer have downloaded a social networking app for the device Adult residents of the following Designated Market Areas (DMAs) with 1,000,000 or more adult residents are the most likely to have visited Facebook in the last 7 days: ) Seattle-Tacoma, WA Austin, TX Salt Lake City, UT Portland, OR Washington, DC 15% of Facebook visitors follow a musical group on a social networking site, 14% follow a TV show, 11% follow a newspaper or news outlet and 4% follow a magazine. The average Facebook user is 39.3 years old. The average Facebook user claims an annual household income of $69,900 with annual household spending on discretionary goods and services of $15,500. Hispanic users of Facebook are 55% more likely than non-Hispanic users to say they like to follow their favorite brands or companies on social networking sites. Don’t miss 15 stats about Facebook, previously posted on the Experian Marketing services blog. . For more information like the data provided above please download the Experian Marketing Services 2012 Digital Marketer report.
Today, it costs more than $40 to send a five pound package from the U.S. to Canada or Mexico. The cost to Europe or South America is even more expensive. For U.S. companies operating on a global scale, such as retail specialists or ecommerce organizations, address accuracy is crucial. Organizations can’t afford undeliverable mail and packages due to a wrong address – the total cost would be unmanageable. Mistakes happen frequently, whether it is an error by the company or the customer. If a mistake is made, companies can’t ask the customer to cover delivery fees, leaving the organization with the bill. Retailers must also consider potential delays due to long distances and custom checks. Altogether, address errors result in a poor customer experience and a decrease in efficiency. Implementing international address verification will save money, time and improve the customer experience. By combining primary address data from national postal authorities with partner-supplied data, businesses can verify international addresses from countries all around the world.
On April 22nd, Americans and many of their terrestrial counterparts in countries around the world will celebrate Earth Day, a tradition that was started in the United States by Wisconsin Senator Gaylord Nelson in 1970. Much has changed on the planet since the first Earth Day, and even in recent years attitudes continue to evolve when it comes to our outlook towards the environment. In 2007, Experian Simmons created the GreenAware consumer segmentation, which classified respondents to the Simmons National Consumer Study between 2005 until 2007 into one of four mutually exclusive segments based on their consumer behaviors and attitudes toward the environment. Since then, Experian Simmons has continuously classified all adult respondents into the GreenAware segments providing our clients with valuable insights into the evolution of the environmental movement. The four GreenAware segments are: Behavioral Greens: This group of people thinks and acts green. They have negative attitudes towards products that pollute and incorporate green practices into their lives on a regular basis. Think Greens: This group of consumers think green, but don’t always act green. Potential Greens: This group neither behaves, nor thinks along particularly environmentally conscious lines and remains on the fence about key green issues. True Browns: They are not environmentally conscious, and may in fact have negative attitudes about environmental issues. Since 2005, we have observed a nearly constant increase in the percent of U.S. adults who are classified as Behavioral Greens, the “greenest” segment of the four. Today, 33% of adults are Behavioral Greens, up from 27% who were classified as such in 2005. Meantime, Think Greens have maintained an almost perfectly constant 21% share of the population. The size of the True Browns segment has also remained constant at between 14% and 15% of the total adult population. The Potential Green segment, however, has steadily declined in market share from 39% in 2005 to 31% today. La Vida Verde Hispanic Americans have traditionally been ahead of the curve when it comes to green thoughts and deeds and they’re only getting greener with time. Today, 39% of Hispanic adults are Behavioral Greens, up from 33% in 2007. Just 32% of non-Hispanic adults are Behavioral Greens today, up from 29% who fell into the greenest segment in 2007. Interestingly, among the True Browns segment there are virtually no Hispanics to be found, and, in fact, while the True Brown population is actually growing among non-Hispanics, Hispanics are increasingly moving to greener segments. Specifically, just 1.3% of Hispanics are True Browns today, down from 8% who registered as such in 2007. By comparison, 17% of non-Hispanics are True Browns today, up from 14% in 2007. Green Today, Greener Tomorrow? The illustration below shows the alignment of America’s largest metropolitan areas with the four GreenAware segments today and in 2007. We see that residents of the San Francisco-, New York- and Miami-areas are the most likely to be in alignment with the Behavioral Green mindset today. Denizens of Washington, D.C., Los Angeles, Chicago, Philadelphia and Boston tend to fit more closely with the Think Green set that has green attitudes and intentions, but not always the actions to back it up. But things are changing. In fact, since 2007, we’ve seen that as local minds change, some cities become aligned with a different, often greener, segment. Let’s look at Chicago, for instance. In 2007, Chicagoans’ environmental outlook was more reflective of a mix of Potential Greens and True Browns. Since then, local attitudes have changed so much that Chicago-area residents are now more aligned with Think Greens and Behavioral Greens. Likewise, Cleveland, which was clearly a True Brown town in 2007, now falls in step with the Potential Green segment. In five years’ time, who knows? Cleveland could be America’s next green leader. Not brown now towns Looking at markets large and small with the biggest drop in concentration of True Browns, we see that attitudes in inland markets located in Gulf States have become disproportionately less brown since the Deepwater Horizon oil spill in 2010. In fact, seven of the ten Designated Market Areas (DMA) that saw the biggest decline in the percentage of their population classified as True Browns between 2007 and 2011 are inland markets in states bordering the Gulf of Mexico. While the oil didn’t directly reach these markets, the attitude change did spread: For example, 3.2% of adults residing in the Columbus-Tupelo-West Point, Mississippi DMA today are classified as True Browns, down from 19.3% who were categorized as such in 2007. In Macon, Georgia, while not a Gulf State, a more impressive shift took place. In 2007, the Macon, Georgia DMA had the fourth highest percentage of its population classified as True Browns (20.1%) out of 209 DMAs. Today, only 5.8% of area residents are True Browns, which makes it the market with the 10th lowest concentrations of True Browns in the nation. Macon still has one of the lowest shares of residents who are Behavioral Greens in the nation, but what a difference a few years makes. While the towns directly in the path of the oil spill are not among those with the biggest relative decline in True Browns, area residents’ attitudes did take on a greener hue since the spill. Today, 8.4% of residents in Panama City are True Browns down from 17.3% in 2007. Likewise, only 9.8% of adults in both the Mobile-Pensacola and Biloxi Gulfport DMAs are True Browns down from 17.3% and 19.0%, respectively, who fell into the least green segment prior to the spill. Learn more about Experian Simmons consumer segmentation offerings