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As Google deprecates third-party cookies on Chrome, advertisers will know less about their audiences and will be less able to use last-click attribution to track performance. As a result, they’ll need new metrics to understand whether their campaigns are generating results and, critically, how to attribute those results. 

  

On-page attention metrics will play a key role in making up for audience signal loss. They’ll also allow advertisers to improve upon last-click attribution, which fails to account for the often multiple touchpoints that lead to a conversion. 


With attention metrics, advertisers are able to compare the content quality of the media properties they invest in against conversions. And they are finding a correlation between high-quality pages, impressions generated by page, and conversions. 


Here’s more on how attention scores such as Adelaide’s AU work and how advertisers can drive higher performance with Advanced Contextual. 


How Adelaide measures attention with AU


Attention metrics such as Adelaide’s AU rate the media quality of ad slots. To calculate a given placement’s AU rating, Adelaide uses a machine learning algorithm to assess the surrounding design on the page and how it affects customer engagement and KPI performance.


The higher a placement’s AU score, the more likely it will drive awareness, purchase intent, and ROI. For example, a large ad slot in the center of a premium publisher’s news article that doesn’t have that many other ads will generate a higher AU rating than a tiny ad slot in the corner of a blog homepage.


In addition to helping advertisers identify prime targets, measurements like AU will be critical for screening out subpar advertisement placements like made-for-advertising (MFA) sites, which drive low-quality engagement and, accordingly, score low on attention. 


Why advertisers get high attention metrics with Advanced Contextual’s engine


Advanced Contextual’s engine supports attention metrics so advertisers can assess the relationship between media quality — which contextual intelligence helps evaluate — and their KPIs. Advertisers find they secure inventory with high attention metrics with Advanced Contextual’s engine. How does Advanced Contextual’s engine deliver this high-quality, high-attention inventory? In a word: curation. 


Advanced Contextual’s engine homes in on premium ad slots in high-quality advertising environments. To do this, it screens out homepages (like nytimes.com), channel fronts (like health.nytimes.com), and MFA sites because these sites often make for low-impact engagements. 


By maintaining this level of curation, Advanced Contextual’s engine enables advertisers to only target granular, individual pages of content that are the most likely to drive quality customer interactions and scale their performance. 


With the combination of attention metrics’ benefits and a superior, data-driven understanding of content, advertisers will be able to take on a post-cookie world and resonate with their ideal audiences in a way that’s transparent, scaleable, and performant. 


To learn more about how Advanced Contextual is driving results for advertisers, reach out today or check out our results page.   

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Google is finally deprecating third-party cookies on Chrome in 2024. As a result, advertisers will lose a lot of cross-site data to evaluate the effectiveness of their advertising campaigns. Other metrics will help fill in the gaps. Since brands will increasingly rely on contextual signals, on-page metrics will be more relevant to campaign performance.


While KPIs will always be the ultimate arbiter of campaign success, metrics such as time on page, page clutter, page load time, attention scores, and click rate can all help advertisers assess whether their campaigns are running on worthwhile media properties and how likely they are to generate returns. They will also help in the critical area of attribution, which will have to evolve in the aftermath of Chrome cookie deletion.


Here’s what you need to know about each of those on-page metrics.


Time on page


Analyzing time on page allows an advertiser to see how long visitors spend viewing a page or screen (or a certain set of pages or screens) where its campaigns run. Brands often find engagement with content to be a strong predictor of KPI achievement. The more time spent with a page, the more likely viewers are finding an ad relevant. 


Measuring efficacy with time on page will be critical for successful attribution post-cookie. Assessing time on page enables brands to compare their KPIs and engagement targets against page topics and session lengths. That way, brands ensure they’re reaching their highest-intent audiences.   


Page clutter


Tracking page clutter (or ad density) enables advertisers to assess how much space ads take up on a given page. Page clutter is calculated by taking the sum of the heights of all ads on a page and dividing it by the total height of a page’s main content. 


The Coalition for Better Ads recommends 30% as the maximum page clutter. Any higher than that means the ads on a page are intrusive. By prioritizing media properties that stay below the 30% threshold, advertisers choose inventory with better user experiences for audiences and that's more likely to generate favorable reactions. 


Page load time


Page load time is the amount of time it takes for a browser to show a full page in a window. The longer a media property’s page load time, the less likely users are engaging with the page and seeing an ad — let alone going down the conversion pipeline. 


Attention score


Assessing page attention scores, such as Adelaide’s AU, enables advertisers to predict how well ad space on media properties is capturing attention and driving subsequent return on investment. 


In the case of Adelaide — which analyzes samples of pages to extrapolate how well other pages with similar design (the number of ad slots, the page layout) are performing — a page with a higher AU score indicates a greater likelihood that that page is driving high-quality engagement. 


Click rate 


Click rates allow advertisers to gauge how well their keywords and ads are performing. Click rate is calculated by dividing the number of times an ad is clicked by the number of times the ad is shown. (For example, 15 clicks out of 1,000 impressions would translate to a 1.5% click rate.)


Higher click rates suggest that an advertiser’s campaign is reaching high-intent audiences. What’s more, advertisers often find a correlation between higher click rates and higher conversions. 


Page activity measurements help brands gain a deep understanding of how well the content they run on drives programmatic performance. As the cookie makes its exit, context will be the one, ubiquitous signal that brands can depend on — and measurements informed by context and page activity will ensure brands perform and hit KPIs. 

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2024 presents unprecedented challenges for advertisers in the form of third-party cookie deprecation. The way agencies have helped brands optimize and measure advertising for years is finally disappearing. So, agencies need new methodologies to deliver results for clients — whose expectations won’t dip as a result of technological change.


Enter contextual advertising. By leveraging contextual signals — what people read and watch, not who they are — brands and agencies can achieve efficient marketing performance without third-party IDs.


But this isn’t your father’s contextual advertising. It’s not just putting Nike ads on articles about running. Here are five capabilities you should look for from contextual advertising and intelligence in 2024.


1. Increased signal across verticals

Contextual intelligence should help brands and agencies build audience and inventory models in place of the audience targeting and measurement the third-party cookie facilitated. To ensure the strongest contextual signal possible for those models, we’re rapidly increasing the list of sites our platform analyzes so that agencies can tap into as many verticals and audiences as possible. 


2. Brand suitability

While they may facilitate cheap reach, made-for-advertising (MFA) sites — which are stuffed with ads and low-quality content — fail to generate meaningful engagement and risk harming your brand by association. That’s why our contextual platform leverages a data-driven formula to rule out MFA sites so brands’ ad dollars only go toward premium, brand-suitable advertising opportunities. 


3. Multi-layered targeting

With contextual advertising, agencies can gain deep understandings of their audiences. In addition to identifying topics a brand’s target customers are interested in, Advanced Contextual’s platform analyzes the tone, mindsets, and sentiment (among other psychographics) of the text and video audiences are consuming. So, you target audiences who won’t just be interested in your message but receptive to it.


4. Look-alike audiences 

With the third-party cookie’s phase-out and resulting ID deprecation, how can agencies leverage look-alike audiences to reach a broad array of prospects beyond the small set of customers they’ve already identified? By using our contextual engine, agencies can understand which pages and topics resonate with their ideal customers and precisely target an accurate cohort of IDs. Advanced Contextual takes the segment data agencies already have and extrapolates from it to generate lists of high-value targets and pages. Agencies can take these lists to walled garden look-alike models, reaching their audience on both social and the open web.


5. Page-level targeting 

The basic form of context works like this: enter a bunch of keywords into a walled garden or DSP interface, and they’ll target those words across their inventory. But this approach doesn’t consider the various connotations those words may have, and can lead an airline’s vacation ads to show up on news coverage about refugees escaping war or natural disasters. 


Enter programmatic contextual. Advanced Contextual’s platform avoids keyword ambiguity by checking the surrounding environment of content to ensure the content is truly relevant to the brand’s message. That way, agencies only bid programmatically on desirable inventory. Your travel ads don’t end up next to upsetting news stories; they target the hospitality content where you’re most likely to convert prospects. 


Scale marketing performance in the new cookieless ecosystem


With third-party cookies finally going away, agencies need new privacy-safe ways to help brands reach their audiences cost-effectively at scale. Advanced Contextual exists to solve that problem. And we’re already solving it for dozens of agencies, which are using AC to find scalable and performant audiences on both social platforms and the open web.


By precisely targeting your highest-intent customers on the open web and social in a way that protects consumer privacy, agencies will be able to deliver results for their clients using contextual advertising — no matter the latest change from Google or Apple. 

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