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
While the weather outside is frightfully hot this summer, it’s never too soon to start thinking about the holidays – and consumers are more likely to start their holiday shopping early this year. To get you ready for the 2022 holiday shopping season, we looked back at consumer shopping trends from 2019-2021. What did we learn and what trends do we expect to see this year? Let’s look back. A look back Over the last three years, average consumer spending has increased. Record 2021 holiday sales came amidst a wave of COVID-19 cases, rising inflation, labor shortages, and supply chain problems. Despite these challenges, consumers continued to let it snow when it came to spending during the holiday season. 2022 has been a year with its own economic roadblocks – the war in Ukraine, rising gas prices, and recession concerns. Yet 2021 was a banner year for holiday sales despite its obstacles, and we predict similar trends in the 2022 holiday shopping season. What trends do we expect to see for the most wonderful time of the year? 2022 predictions While consumer spending remains strong, changing economic conditions continue to shape shopper behavior. To develop our predictions for 2022 holiday shopper behavior, we focused on four key areas: When consumers shop Where consumers shop What consumers purchase Consumer media preferences Now, let's make our holiday campaign planning checklist and check it twice. When consumers shop Chestnuts roasting on an open fire. Jack Frost nipping at your nose. Those aren’t the only ways to know when the holiday season has begun. Shoppers tend to spread out their holiday purchases across multiple months and were more likely to start shopping earlier. To understand holiday retail sales trends from 2019-2021, we identified four shopper segments: Early Shoppers Traditional Shoppers Late Shoppers Random Shoppers What differences did we see between our four shopper segments? Early shoppers made almost half of their holiday purchases in October Random shoppers spread out their holiday purchases evenly across multiple months Late shoppers made almost half of their holiday purchases in December Traditional shoppers made almost half of their holiday purchases in November While December continues to dominate holiday sales, October has started to gain traction over the last three years, and November remains a core shopping month. Everybody knows a turkey and a mistletoe help to make the season bright but knowing when your consumers are most likely to shop will help deck your campaign planning halls. Jingle bell rock your way to holiday sales that shine bright with our tips to prepare for earlier shoppers: Offer targeted promotions earlier in the shopping season Target your ads based on the shopping habits of your customers throughout the season Where consumers shop There’s no place like home for the holidays but most consumers aren’t shopping from home. Despite the rise in online shopping, brick and mortar locations continue to dominate holiday sales. October is the most popular month to take a one-horse open sleigh to a store, and consumers gather around the fire to online shop in November and December. With most shoppers preferring to shop in-store, and e-commerce popularity growing, it’s critical to think about bridging the gap between your online and offline presence for the consumer. Are you offering multiple paths to purchase with solutions such as BOPIS (Buy Online, Pickup In-Store)? Go down in history like Rudolph with our tips to prepare for more in-store shopping: Focus on in-store shopping experience technology (self-checkout, VR, QR codes, scan to pay, etc.) Offer multiple paths to purchase to connect your online and physical presence through methods such as BOPIS (Buy Online, Pickup In-Store), BORIS (Buy Online, Return In-Store), and ROPO (Research Online, Purchase Offline), etc. What consumers purchase When it comes to holiday gifts, for some, only a hippopotamus will do. Compared to pre-pandemic, shoppers are spending more at apparel stores and mass retailers. Spending at specialty retailers, warehouse clubs, and on office, electronic, and games is almost the same across holiday and non-holiday shopping months. Time for toys and time for cheer may be year-round, but are there any correlations between where consumers shop (online vs. in-store) and what they purchase? Our data found that shoppers who bought from mass retailers were more likely to shop online, while shopping for apparel and warehouse clubs was done at a physical store location. Put this insight to the test by thinking through how you can target your consumer based on where they shop in-store and online. You just might find that hippopotamus at a brick and mortar mass retailer location! Consumer media preferences Do you see what I see? While we are seeing a shift to digital media channel preference, consumers still engage with traditional media channels like direct mail and the traditional newspaper. Successfully connecting with your customers involves capturing their attention through the right channel. We found that our four shopping groups prefer a mix of traditional and digital media channels. What does your media channel mix look like? Hark! The herald angels sing of ways to adapt to the change in holiday spend and media preferences: Align your activation efforts to digital, but don't forget about traditional channels Expand your targeting and activation focus beyond in-store vs. online Download our new 2024 report For a deeper dive into our predictions and actionable insights you can use to take your holiday campaign planning home for the holidays, download our new 2024 report. Experian data can help you refine your content and creative strategy to achieve maximum ROI for each campaign across all your channels. Download now
Fluctuation in consumers' behaviors and preferences during the pandemic has prompted a shift in the practices and patterns that we are accustomed to. Powerful market forces are emerging as society builds a new normal, forcing marketers to rethink their strategy, activation, and measurement. It is important for marketers to understand the forces that influence the industry, and to learn about alternative approaches that can be applied to help reach their goals. In our recent webinar, ‘How to Adjust to the New World of Advertising,’ Experian’s Chris Feo and guest speaker Tina Moffett, Principal Analyst at Forrester Research, lead an in-depth discussion of the market dynamics and developments guiding us to this new era of advertising. They talked about: The pandemic changing consumer behavior Emerging media channels Data deprecation The pandemic and increased media consumption The pandemic caused seismic shifts in consumer behaviors and business operations. Work from home became the norm, consumers made drastic changes in their routines, and businesses had to adjust to new operating models as local economies shrank and supply chains strained. As stay-at-home orders were put into effect, consumers increased their media consumption drastically as more time was spent at home in front of their devices. According to Forrester, by June 2020, 48% of US online adults subscribed to at least one streaming service, while 34% had signed up for multiple. Forrester contends that: Social and online video/OTT will grow fastest among other categories of ad spend Connected TV outpaces other video advertising channels 55% of consumers plan to continue watching movies at home rather than in theatres after the pandemic Data deprecation The ways that marketers can personalize content and measure the effectiveness of campaigns is changing with data deprecation. Consumer preferences, regulations, and technology providers are evolving the way advertisers understand consumers, causing changes to existing identity-based marketing strategies. According to Forrester, 66% of marketers are investing in first-party data collection strategies to adapt to these market forces. Marketers need to adjust Demand for a new advertising approach Changes in consumer behavior, evolving media consumption patterns, and data deprecation have marketers looking at new approaches to targeting and measurement. However, with the future uncertain in many of these areas, marketers need to test and experiment to determine which approach is best for them in particular use cases. Shifting to a new world of experimentation Advertisers need to start by assessing their current environment to determine where they have exposure today, which methods of identification they are using, and how those channels may be impacted by the market forces outlined earlier. From there, they need to start asking themselves how they can assess identity in the future or if there is another way to approach advertising in that specific channel. There are specific areas where marketers can look to make investments in terms of experimentation: Adoption of cleanrooms to support analytics and audience targeting Investment in first-party data to overcome the issue of data deprecation Shifting to a value-based, omni-channel advertising mindset to address customers’ needs Investment in data-savvy resources to manage media insights Adoption of consistent cross-platform advertising metrics and currencies to inform better planning If you missed our recent webinar ‘How to Adjust to the New World of Advertising,’ you can listen to the full discussion here.
Hashed Email is a privacy-safe digital identifier that can further enrich and expand the functionality and utility of The Tapad Graph with access to Tapad + Experian’s universe of email data. This provides maximum coverage for targeting and measurement when combined with household and individual IDs such as Cookies, MAIDs, CTV IDs, and IP Addresses. Gain back a clearer view Recent data from DMA shows that 51% of people have held the same email address for over 10 years. Email address data by its nature is authenticated and reliable due to its longevity. When leveraging Hashed Email as an extended functionality of The Tapad Graph, we are able to link on average 5 email addresses to each individual, reaching up to 90% of households across the US. Hashed Email expands the customer view by adding new email address identifiers into The Tapad Graph that associate with traditional digital IDs and cookie-less IDs emerging in the marketplace. Reduce fragmentation; and instead of viewing the emails as multiple customers, with Hashed Email they can be viewed as one user profile. When enabled, clients who wouldn’t traditionally have access to first-party customer emails are able to associate and link privacy-safe emails to individuals and their households. Brands and retailers can use Hashed Email to extend these linkages across offline purchases associated with each email; connecting traditional digital identifiers between walled gardens, activation in programmatic media buys, and addressable TV. With the holiday season quickly approaching, access to Hashed Emails will instantly increase scale, connectivity and improve measurement when efficiency, personalization and holistic attribution are pivotal to marketing strategies. Let’s visualize how quickly the customer journey can become fragmented when email addresses that belong to the same person are not associated. Mary has 3 email addresses that she frequently uses. One for social media accounts Email ID 1, one for shopping accounts Email ID 2, and another for work Email ID 3. Mary is a brand loyalist to a top national retailer and whenever there is a new season, there is a high likelihood that she will purchase the latest seasonal decor from that store. She recently did some holiday shopping in-store where she purchased nearly the whole holiday line. Email ID 2 was used to send her a receipt. However, Mary annoyingly receives the store's ads on Facebook for holiday decor that she had already purchased. This is because the retailer has not yet identified that Email ID 1 and Email ID 2 belong to the same consumer. If the retailer were to leverage Hashed Email, they would be able to identify that both email addresses used belong to Mary. This association connects her multiple email addresses together, enables her offline purchases to sync with her online activity, and helps to determine the most accurate ROAS. Hashed Email is a cookie-free added view into consumer behavior for control over messaging and for measurement. When leveraging it’s possible to report back across all channels and devices in a universal format to know when and how conversions are taking place. Don't leave valuable data on the table Hashed Email has use cases beyond reducing wasted media impressions. Hashed Email’s full capabilities extend to campaign measurement and attribution modeling. When utilizing The Tapad Graph combined with Hashed Email, know from the first touchpoint to the last where your customers are engaging. But more importantly, know where households and the individuals inside of those households are converting across all of their digital devices, by using traditional digital IDs, cookie-less IDs, and Hashed Email to associate, measure, and correlate online and offline purchases. Imagine what your campaigns could look like this holiday season if you expanded your graph with up to 5 additional IDs per household. This impact could be a game-changer to scale this holiday season. Hashed Email is a reliable cookie-less digital identifier that expands your customer universe that connects online and offline activity while improving the customer experience and reducing wasted media spend. Enabling Hashed Email for the holiday season is not an opportunity that should be passed on. Where do you sign up, you ask? 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!