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
It’s the holiday season! For some, this is the time of year for family, friends and reflection. For the other 97 percent* of us, it’s time to shop! America’s obsession with Black Friday, Cyber Monday and the rest of the holiday shopping season has never been stronger. Or weaker? Or something? All I know is that you should be skeptical of anything you see regarding the Thanksgiving weekend performance. And now, I will tell you about the Thanksgiving weekend performance We’re not discussing revenue in this post. Instead, we’ll dive into the weekend’s email subject lines – more specifically, how “percent off” deals affected email open rates. As everyone knows, Black Friday and Cyber Monday are the days for deals. Juicy “percent off” offers motivate customers to buy, buy, buy. But is the conventional wisdom, that “a deep discount will get people to engage with my brand,” actually right? A few weeks ago, my counterpart in the UK published an analysis of how percentage off discounts influence open rates. Taking the cue from Karl, I wanted to expand this analysis into the U.S. market, paying special attention to Thanksgiving weekend. To begin, I gathered data on a few thousand mailings from our largest retail clients. To determine the baseline expected open rates, I averaged each brand’s performance in the 6 weeks prior to Black Friday. I then analyzed all the mailings sent on Black Friday and Cyber Monday, dividing the subject lines based on the appearance of a percentage off offer. Interestingly, percentage off offers were less prominent than I expected: And when percentages off were present… their values were all over the place: Higher volume doesn’t lead to improved performance Conventional wisdom would suggest that advertising a discount more frequently would lead to better performing discounts. The data, however, doesn’t support that idea. When I looked at volume distribution and relative performance for each advertised discount, I found a relatively strong negative correlation of -0.63. So the more frequently a discount was advertised, the worse it tended to perform. We can see this visually in the chart below: On average, advertising discounts did not significantly improve open rates. What happened? The first thing to note here is the wide spread in the data – some percentage off discounts worked very well! Overall, though, shouting about a discount wasn’t what convinced customers to open emails during the holidays. But maybe it wasn’t just the percentage off discounts that faltered this season – perhaps all opens were down? As you can see in the histogram above – this wasn’t the case. The average mailing not touting a percentage off discount did ever so slightly better than the baseline average. Still, the spread of data is very wide, with a lot of variation in results. It could be that the dispersion of results was a product of each brand’s initial baseline; brands that normally had great engagement would see positive gains for percentage off discounts while brands with poor engagement would see little to negative lifts, or vice versa. But this hypothesis was also proven incorrect, as the relative starting place for each brand versus the discount performances had a correlation approaching zero. No matter which way I sliced it, the performance of discounted subject lines were more or less random. Ultimately, this last point is the most important. The subject line, for all its ubiquity and focus, is probably a lot less influential than we tend to believe. Sure, a subject line can be optimized, carefully crafted to invoke the greatest lift in response possible, but the baseline expected performance is influenced by a much larger conversation – the one between the brand and its customers. If the brand relationship has been cultivated and refined through intelligent interactions and sophisticated targeting, the open rate is likely going to be higher. If every marketing message simply shouts, DISCOUNT, DISCOUNT, DISCOUNT, and there is no larger value-add, engagement probably won’t be great. Advertising a discount in a subject line might really help get people involved – or it might not. So what is the future of the subject line? Are they worth the disproportionate time and energy that marketing organizations tend to spend on them? Or should we recognize that their importance is probably minimal? The truth is, it’s a little bit of both. Subject lines are important – they are the first impression and often the first interaction of the day with a customer. But their importance is likely inversely related to the strength of the brand (the “from” line, if you will). The stronger the relationship is, the less important the subject line becomes. Maybe that’s the ideal – a perfect “from” name, one that tells you more about what’s inside the message than a subject line ever could. *Not a real stat Connect with Jacob Davis, Senior Analyst, on Twitter: @davisj2007.
Before we get to the gift guides, here’s a brief update on the hottest products from the week including Cyber Monday. This week’s biggest movers and new additions to the list are a clear sign that Christmas is upon us. “Star Shower,” a laser light that bathes your house in festive lights without having to untangle cords, jumped to second place, up 49 rank points from the week prior. Likewise, the return of “Elf on the Shelf” to the hot products list coincides with his return to the homes of children nationwide. Otherwise, things seems to have stabilized with Fitbit showing no signs of falling from first place and Pie Face game being this year’s sensation. Toys Shopkins remains the toy to beat this season followed by Pie Face game, which remained in second place after skyrocketing interest during the week of Thanksgiving. Toys new to the top 10 this week include some old favorites like the Easy Bake Oven and Paw Patrol toys as well as the new entrant Glammin Salon Vanity. Keep checking back each week for the latest hot toys. This chart shows the 10 most searched for toys and games based on search clicks to Toys “R” Us – USA. Gift guide insight When it comes to buying presents for the holidays, some individuals are easy to shop for while others require a bit of inspiration. And when consumers need inspiration, consumers turn to the Web. Searches for “gifts for,” “gift guide” and “gift ideas” grow increasingly common as we get closer and closer to Christmas with peak search activity around this topic typically observed during the last full week before Christmas, which this year would be the week ending Saturday December 19th. Some of the most common gift recipients mentioned in gift guide-related searches are: “men,” “guys,” “her,” “mom,” “dad” and “girlfriend.” But shoppers are also frequently looking for suggestions on the perfect gift for someone very specific interests, such as “hunters,” “gamers” and “beer lovers” as well as specific types of gifts, like “tech” or “personalized.” The following gift guide insights, derived using our new AudienceView platform, were designed to highlight for you, as a marketer, the interests and preferences of key consumer segments so that you can more effectively tailor your campaigns to be more relevant and engaging. But if it also helps you, as a consumer, come up with the perfect gift for that hard-to-shop-for person in your life, then even better! Each gift guide contains a representative mix of search terms that were performed at above average rates by each audience segment during the four weeks ending November 28, 2015. They include a mix of product and retail brands and provide a good idea of the interests, style preferences and lifestyles of each audience. Learn more about how AudienceView can deliver unparalleled insights into your consumer audience so that you can deliver a better brand experience.
It’s October, and you know what that means; leaves are changing, sweaters are being pulled out of the closet, pumpkin-flavored items are taking over coffee shops. For many marketers, this is the most exciting (and stressful) part of the year. Holiday marketing is ramping up, and it will only increase in intensity as the weeks go on. Luckily, we’re hard at work here at Experian, analyzing data from past holiday seasons to bring you the insights you need to make your holiday marketing programs successful. We’ve examined search and email behavior to compile a list of the most important days to email and trends that will help you delight your customers from now until the New Year. You can access all of these insights in our Holiday 2015 Marketing Insights Calendar, which covers marketing trends from October through December. Holiday marketing tips for October With Halloween fast approaching at the end of the month (and Thanksgiving/Black Friday/Cyber Monday not far behind), marketers should use October to solidify their plan for the holiday season. Here are three things you can do to optimize your impact this month: 3 ways to optimize your holiday marketing programs in October Target reactivation campaigns to last year’s holiday-only shoppers to maximize active subscribers this season Perform a data cleanse and email verification to ensure message delivery. List health is key to a successful holiday season, and now is the time to double check. Consider offering Halloween-specific products for the little ones. Costumes for newborns and toddlers are on the rise, so don’t forget about the youngsters! Want more holiday marketing insights? Don’t miss our upcoming webinar, Check your list twice: Last-minute marketing strategies for the holiday season.