Scott Freeman, SEO Manager
Anthony Quagliata, Paid Search Manager

Google’s AI Overview feature has drawn quite a reaction from the world of organic and paid search experts, but is it an innovative step forward, or is it simply Google trying to stay afloat in the fast-evolving AI race? As this feature continues to roll out across search results, many wonder if it’s a game changer or just hype.

What Exactly Is Google’s AI Overview?

In a nutshell, the AI Overview feature generates a succinct summary based on AI’s understanding of your search query. Instead of having users click through multiple search results, they are presented with a synthesized snapshot of relevant information at the very top of their search, theoretically offering faster and more accurate answers. Google touts it as a way to enhance user experience, making search more intuitive and less time-consuming.

How Often Is the AI Overview Showing Up in Search?

Many are curious how often they’ll encounter these AI Overviews, and research shows they now appear in 3.9% of trending news searches — a relatively small, but growing percentage. The potential for expansion is huge, though, as the feature is still being tested and improved. For example, some reports show that Google AI Overview results have been showing up in 80% of searches for high-profile news events, signaling that the tech giant is serious about this AI integration.

How Does This Impact SEO?

The real elephant in the room is how this new feature affects SEO. Will it boost traffic to your site or steal it away? The answer is complicated and murky. On one side, AI Overviews give users faster answers, potentially leading to lower click-through rates (CTR) for organic results. Some SEO experts are already sounding alarms, saying AI summaries could reduce visibility for traditional SEO and that organic results may be less prioritized. Initial tests have shown the AI Overview could lead to organic traffic decreases anywhere from 18-64% for some websites, especially for informational-type queries.

On the other hand, some SEOs see this as an opportunity. For example, content optimization for AI-driven summaries might become the next big thing, with SEO professionals looking to adjust their tactics. If AI Overviews are prioritizing concise, well-structured content, there’s room to optimize accordingly and stay relevant. With detailed analytics reporting, SEOs can gather relevant information on user behavior and engagement within the search engine results page itself. With that insight, SEOs can begin to hone their strategies and use the AI Overview to their advantage. 

How Does This Impact Paid Search?

Google’s AI Overview has already impacted paid search results in ways that are hard to ignore. As consumers have begun exploring this feature, there has been a significant rise in search traffic on Google. However, much like organic, a decline in paid search click-through rate has been observed since most people need to click through to ad listings rather than explore the summary the AI Overview provides. 

Another notable finding is a year-over-year rise in CPC (cost per click) as click volume has declined for advertisers. While CPC increases can also be linked to increased ad prices for companies to meet targets, it is hard to imagine they will come back down as Google continues to alter where ads show around the AI Overview. Considering they’ve talked about returning top placements above the Overview, it likely signals that CPC will continue to rise. Also, as recent as the beginning of October 2024, ads were introduced into AI Overview for mobile users and will likely become an increasingly competitive placement for competitors. 

What’s Next for AI in Search?

So, is this indeed the future of search? Google is banking on AI, but whether the feature is here to stay depends on how it adapts to user behavior. With 57% of users reporting positive experiences with AI in search results, the technology seems to be resonating with many. But at the same time, only 23% of users say they fully trust AI-generated results, leaving a lot of room for growth — and skepticism.

At the end of the day, Google’s AI Overview feature has the potential to reshape how we search and how marketing professionals do their jobs, but it’s still too early to tell if it will revolutionize the experience or simply be a flash in the pan. As AI continues to evolve, monitoring how these changes impact SEO, paid search, user trust, and the broader digital landscape is crucial.

Erin Mullaney, Media Director

I recently participated in a lively discussion with buy-side and sell-side ad executives to dive into the latest thinking around targeting, measurement, and—of course—cookies. While these conversations can sometimes get technical, here are 4 straightforward takeaways for marketers navigating this landscape:

Remember the Root Concern

It’s not just about the third-party cookie as a method for collecting and using data on internet users, but about the act of data collection itself. The issue of unclear consent and privacy won’t disappear with the cookie, which makes building trust and transparency with consumers while still effectively advertising the real challenge. At its core, 1:1 deterministic targeting and tracking, regardless of the method, is what fuels privacy concerns. While there are many alternatives to third-party cookies, some are just fixes for targeting and measurement, while others aim to solve the underlying issue. The latter are likely to be more sustainable as privacy regulations evolve.

Wait, I Thought Google Said the Third-Party Cookie Wasn’t Going Away?

Google decided it wouldn’t proactively phase out cookies but would instead allow consumers to choose whether they want to be tracked. This mirrors Apple’s rollout of iOS 14.5 and App Tracking Transparency (ATT) in 2021, where users were prompted to decide if they wanted apps to track them. At that time, 96% of iOS users opted out. Today, that opt-in rate has climbed to about 24%, as people grow more accustomed to these types of prompts. While Google is putting the decision in the hands of consumers, if the prompt is as direct as Apple’s, we can expect most users to opt out. This means third-party cookie alternatives are still very much in demand. (Source: Adjust)

Exploring the Alternatives

At CP, we categorize targeting and measurement approaches into two groups: Hyper-Targeted and Privacy-First.

Hyper-Targeted solutions are the easiest alternatives to third-party cookies because they preserve 1:1 deterministic targeting and measurement, making them compatible with current ad tech. This group includes identifiers like IP addresses, device IDs, universal/alternative IDs, and data matching methods like identity graphs and cleanrooms. Measurement alternatives here include server-to-server tracking. Although these solutions are often considered “more accurate than third-party cookies,” they may still face future regulatory scrutiny, as they don’t fully address the root privacy concern. Even if the data is anonymized, it’s still being collected, leveraged, and in some cases, linked to personally identifiable information like names and emails.

Privacy-First alternatives, on the other hand, break away from 1:1 attribution. The key difference here is using “unattached” data in targeting, measurement, or both, to avoid tracking individual consumers across their entire journey. For targeting, this could mean probabilistic targeting via survey-based, contextual, or cohort methodology. On the measurement side, it could involve aggregated or modeled results, as well as brand lift studies, test & learns, and media mix modeling. These solutions, specifically on the targeting side, are less widely adopted and often perceived as less effective, but it’s critical to test them as the landscape continues to evolve. At CP, we’ve seen some promising early results with these alternatives, even outperforming hyper-targeted methods in certain cases. We believe AI will further improve the ability to leverage unattached data signals to drive results.

Where Does First-Party Data Fit Into All This?

The role of first-party data largely depends on your business model. Knowing your customer will always benefit your marketing efforts, but building a robust first-party data strategy requires transparency and incentivizing consumers to share their information. For some brands, there’s an immediate value exchange—like providing an email to unlock content behind a publisher paywall. For others, data is collected post-purchase, which is less helpful for prospecting. Ideally, you can use first-party data as a seed list to reach similar audiences, but privacy-first alternatives may also limit the effectiveness of lookalikes. Thinking strategically about how you collect and utilize first-party data is essential to determining its value for your business.

Conclusion

The ad industry’s focus has shifted from simply finding alternatives to third-party cookies to addressing the bigger picture: consumer privacy. While hyper-targeted solutions continue to dominate, privacy-first approaches are gaining traction, and their relevance will only grow as regulations tighten. As brands and advertisers, it’s crucial to stay ahead by testing a variety of strategies and ensuring that your approach to data is both transparent and adaptable to the evolving landscape. The future of targeting and measurement lies in balancing effectiveness with privacy, and those who can master this will be well-positioned for success.

Kim Mazejka, Senior Media Planner
Lee Junkin, Programmatic Media Supervisor

We recently attended StackAdapt’s StackDay conference in Chicago, where we had the opportunity to dive deeper into not only StackAdapt’s current and upcoming features, but also the programmatic landscape as a whole. Here are our top learnings and insights from the conference:

Programmatic ad spend is growing rapidly, driven by increased demand for connected TV, Retail Media Networks, and digital out-of-home.

• Connected TV (CTV) is growing at the same pace that Linear TV is declining. eMarketer predicts that by 2028, spend will be even between the two before CTV takes over in dominance. The downside is that there is a current ceiling on CTV inventory due to lighter ad loads and a larger share of ad free viewers, which will lead to an inventory shrinkage. 
• Retail Media Networks (RMNs) are growing at a faster rate than traditional search, which has seen its spend peak. StackAdapt is beginning to explore the integration of RMNs into their platform in order to create more seamless omnichannel integration. However, this will likely be a long roadmap as most RMNs are hesitant to join the open marketplace despite it being a large source of growth. 
• OOH is the only medium that is growing yearly, with digital out-of-home (DOOH) being the main driver. Running DOOH through a DSP can create a feedback loop to further fuel retargeting audiences and provide measurement opportunities to prove effectiveness of this once unmeasurable channel. 

Users will accept personalization in exchange for handing over their data. 

• Less than 1 in 5 users always accept cookies when given the choice, and only 26% of Apple users are opting into being tracked across sites when prompted. 
• Despite not wanting to opt in to tracking, 72% of consumers report they would only engage with a personalized ad. If they know that their purchase history information will be used for these personalized ads, they will approve being tracked. 
• This decrease in device data will likely lead to PMPs and programmatic direct buys increasing in popularity due to precise targeting abilities without this data. 

Choosing the right DSP can create omnichannel opportunities for better optimization and measurement. StackAdapt’s capabilities and recent evolutions include:

• Tools to estimate incremental reach of a CTV buy against a Linear campaign to reduce duplication of efforts and reach a higher percentage of your target audience. 
• ABM-specific reporting to measure B2B campaign performance by company, company size, seniority level, etc.
• Ability to build in brand lift studies straight into any campaign
• Optimize campaigns toward engagement metrics and vetted inventory to ensure ads are running in high attention spaces on premium inventory

With all of this information now in our arsenal, we sailed off into the Chicago sunset on a beautiful river cruise to cap off the trip! 

Katie Coughlin, Associate Media Director 

I recently had the opportunity to attend Digiday’s Retail Media Strategies conference in New York City, where leaders in the space dove into the rise of retail media, providing an exclusive look into its evolving role. While retail media has existed in various forms for quite some time, it has swiftly emerged as one of the most effective strategies for driving revenue and enabling brands to engage shoppers throughout their journey. 

In this blog, I’ll shed light on the importance of embracing a full-funnel approach to best position brands for success because the future of retail media is not just about quick wins – it’s about building lasting connections with consumers and creating value at every touchpoint.

Retail Media’s Expanding Role

Retail media is evolving from a low-funnel tool to a powerful, full-funnel ecosystem. No longer just banner ads buried on a retailer’s site, retail media now supports a brand’s entire customer journey – from initial awareness to post purchase engagement. This holistic strategy helps build a deeper connection with consumers at every stage, rather than focusing solely on immediate sales. By incorporating retail media throughout the funnel, brands can increase visibility and recognition from the outset. This broader exposure helps establish brand presence and credibility, making consumers more likely to consider the brand when they are ready to purchase. 

A full-funnel strategy also allows for a more personalized and seamless customer experience. Brands can tailor their messaging and offers based on where the customer is in their journey, leading to more relevant interactions and a higher likelihood of conversion. Finding opportunities to cut through the sea of sameness with placements and messaging that will resonate will ultimately differentiate the brand, capture attention more effectively, and foster a stronger connection with the customer.

This conference emphasized the need for brands to rethink and evolve their approach to retail media. While relying solely on retail media as a sales tactic can lead to short-term gains, it may not sustain growth in the long run. By shifting from a narrow low-funnel tool to a comprehensive full-funnel strategy, brands can position themselves for steady, sustainable growth by fostering customer relationships and retention over time.