In this update:
Paid Media
Updates by Casey Anderson, Paid Media Director
LinkedIn tools rolling out – great for B2B video
The new suite of video ads coming to LinkedIn will give B2B advertisers more placement options, much of it centering around reserving the type of visibility you want for your ad.
This will include first impression ads that use a full screen vertical video format where advertisers can reserve the first ad impression a user sees. Big announcements will benefit from this tactic.
Reserved ads are another potential winner for marketers that guarantee top feed placement for certain types of non-video ads: thought leader ads, single image ads and document ads.
CTV Expansion will include new upgrades across LinkedIn’s Connected TV capabilities. Paramount is joining as a premium streaming service, Innovid integration will be available to allow for faster uploads and asset management and new insights will be available to tap into larger audiences.
A video-first experience is growing in popularity among LinkedIn advertisers and users. This can be a great opportunity to break through noise.
Google’s Offerwall
Offerwall is a product targeted for publishers as an additional way to monetize their sites. Users can engage in a number of different ways in order to access more content:
- Rewarded ads require users to watch a video or view a display ad for access.
- Interest surveys allow users to answer short questions, which provides the advertiser with more user data.
- Custom choices allow advertisers to insert various ways/options for the user to engage with.
All of this is also combined with Google’s AI tools, to show the right Offerwall to the right visitor at the right time.
The intention here is to pre-qualify users and ensure more deliberate impressions to drive better outcomes. It also gives paid media another chance to team up with SEO to create an even more tailored experience.
SEO
Data from AI Mode is now being included in Google Search Console
After an initial bug, Google has allegedly made some changes so that search data (clicks, impressions, etc.) from AI Mode is now being included in Google Search Console. Hooray! Well, sort of.
Unfortunately, just like with AI Overviews, that data can’t be separated out and analyzed independently, making it considerably less useful. It would certainly be possible for Google to provide us with that information, and it’s equally likely that they’re withholding it intentionally. So while we’ll take all the insights they’ll give us, it highlights the need for digital marketers to review our deeply dependent relationship with granular data.
Sure, new tools are being created all the time to measure things like AI Overview citations and brand mentions in LLMs and we should definitely add them to our toolkit. But I believe we also need to get a little more comfortable painting our big picture with broader strokes, instead of the pointillism techniques that digital marketing has come to rely on.
Attribution is harder than ever, and these constantly evolving AI technologies are making it even more complicated to tell linear stories. But then again, were there ever any linear stories to begin with, or did all that data just make us think there were? We’re marketing to people at the end of the day, and people are complicated.
I’m not saying we don’t need data, we absolutely do. And we need to continue to seek to understand the technologies that people are using to solve their problems. But we also need to put as much effort (if not more) into understanding the people we’re marketing to as we do measuring and analyzing data. User value should be every bit as important as other KPIs.
If we’re stuck in the rhythm of measuring everything to the nth degree in order to make and feel good about our decisions then we might forget to ground our strategies in what’s best for people. Maybe a lack of specificity in AIMode keywords is what we needed to realign that focus.
– Update by Brett Woodward, Sr. SEO
Comparing traffic quality from organic search vs. AI
Last month, I included an article from Dan Taylor that compared website conversion rates for organic search traffic versus AI traffic. In the data he analyzed, organic generally performed better than LLM traffic. A few more data points below, telling a different story.
- Case Study: 6 Learnings About How Traffic from ChatGPT Converts, Seer Interactive – this case study is based on a single client, but found that ChatGPT traffic converted at about 9X the rate of Google organic. A sample size of one is not enough to say “how traffic from ChatGPT converts”, but it’s still a dramatic finding.
- The Average LLM Visitor is Worth 4.4x the Average Traditional Organic Search Visitor, SEMrush – this article doesn’t provide any detail on where the 4.4X number comes from, so hard to know how trustworthy it is.
- AI Visitors Visit Fewer Pages and Bounce More Often Than Traditional Search Visitors, ahrefs – does not cover conversion rates, but is the most comprehensive analysis of the bunch. Also kudos for providing details on the data used for the analysis.
How’s AI traffic performing on your website? Learn how to track AI traffic in Google Analytics with our step-by-step guide.
– Update by Nico Brooks, Head of Analytics
Google Is Rolling Out The June 2025 Core Algorithm Update
Google released their June 2025 Core Algorithm update on June 30th, with the expectation that it will take three weeks to complete the roll out. There is currently no indication that this update is addressing anything specific, so sites following best SEO practices for content and user experience should be fine. However, it’s never a guarantee that your site metrics won’t have fluctuations with any given core algorithm update, so monitor your analytics in July and look out for any spikes in impressions or clicks during the roll out time period.
Analytics
Find updates about marketing analytics in the Analytics Roundup by our Head of Analytics, Nico Brooks. This month, he shares what’s on the GA4 roadmap (including cost importing, now available), resources for understanding enhanced conversions, click identifiers, and Google Search Console data in BigQuery, and big ideas about the future of analytics.
