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Category: News

Enhance Your B2B Ads: Microsoft Adds LinkedIn Job Seniority Targeting
I recently discovered some exciting news from Microsoft Ads that could be a game-changer for advertisers like myself. They’ve expanded their LinkedIn targeting capabilities to include job seniority filters. This allows me to target audiences with more precision in both Search and Audience campaigns.

This new feature means that I can now target users based on their job seniority, a wonderful addition for those of us focusing on B2B marketing. Thanks to LinkedIn data, I can reach audiences at various levels of seniority.

What’s the scoop? According to Navah Hopkins, Microsoft Advertising has added job seniority targeting to its LinkedIn Profile targeting, allowing me to utilize it within Search and Audience campaigns.

This update provides me the ability to choose from 10 different seniority levels, ranging from CXO to Volunteer. This flexibility is available at both the campaign and ad group levels, making it easier to segment my audiences effectively.

Why is this vital for us? In the world of B2B marketing, it’s often challenging to separate decision-makers from operational staff in search campaigns. With this new job seniority targeting, I can better align my messaging and bidding strategies with the right audience segments, ultimately improving my campaign performance.

Understanding who is interacting with my ads is crucial, especially in organizations with long sales cycles or multiple stakeholders. It’s not just about conversions; it’s about knowing who is behind them.

A closer look: Unlike other platforms, Microsoft’s integration with LinkedIn provides a unique perspective of professional identity that allows me to better understand user interactions.

Not only can I apply these filters directly within my campaign settings, but I can also utilize them in observation mode to gather insights without limiting my reach.

How do I benefit?

Customize messaging by seniority: I can create targeted ad groups for different audience levels, like executives or individual contributors, tailoring my messaging to each group’s expectations.

An executive-focused strategy might highlight business growth, while campaigns targeting practitioners could focus on efficiency gains.

Analyze conversions by seniority: Observation mode helps me assess conversion performance across different seniority levels, answering questions crucial to my strategy:

Where are my conversions coming from? Are they decision-makers or influencers? Is my budget effectively spent? Which seniority levels bring in high-quality leads?

Enhance audience testing: This feature offers an extra layer of reporting, helping me make informed optimization and expansion decisions. If I’m importing from other platforms, this insight is invaluable for discovering performance patterns unique to Microsoft Ads.

Availability: This powerful tool is now accessible in select markets across the Americas, EMEA, and APAC regions, including countries like the United States, Canada, Brazil, and more.
- Americas: Argentina, Brazil, Canada, Chile, Colombia, and others.
- EMEA: Egypt, Nigeria, Saudi Arabia, and South Africa.
- APAC: Australia, India, Japan, among others.
The takeaway: Microsoft Ads continues to leverage its LinkedIn integration as a standout feature in B2B advertising. By aligning search intent with professional profiles, I gain deeper insights into not just what my audiences search for, but who the searchers are.

Inspired by this post on Search Engine Land.
June 16, 2026
Google Ads Adopts CPM Billing for Discover’s Demand Gen Campaigns

I recently came across some notable updates from Google Ads that could impact a number of advertisers like me. From July 15, Google is making a big shift in how it charges for Demand Gen campaigns on Discover, specifically those aimed at view-through conversions (VTC). Instead of the traditional cost-per-click (CPC) model, we’ll be billed on a cost-per-thousand impressions (CPM) basis.

What happened. Google Ads informed me, along with other advertisers, that this shift will directly affect campaigns using VTC optimization. If you’re like me and use this optimization, be prepared for the billing change. This only impacts campaigns with VTC enabled, so if you’re not using it, you’re in the clear.

Luckily, no action is required on my part for this transition to take place; it’s automatic.

Why we care. For those of us focused on efficiency in Demand Gen campaigns, this switch could mean we’ll need to closely monitor changes in spend, impressions, and reporting metrics since the basis for billing is changing from clicks to impressions.

This shift in billing might prompt some of us, who primarily look for click-driven performance, to reassess if VTC optimization aligns with our goals.

Why Google is making the change. According to Google, aligning billing with campaign objectives is key. View-through conversions rely heavily on ad impressions. Thus, billing on a CPM basis could more accurately reflect the actual value generated from these campaigns.

Moreover, Google believes this shift will enhance the system’s ability to optimize for VTC goals more effectively.

Opt-out option. If the new billing structure doesn’t suit you, there’s an opt-out. Disabling VTC optimization in campaign settings will prevent this change from affecting your campaigns.

The bottom line. With Google tying payments more closely to the behaviors Demand Gen campaigns are crafted to optimize, those of us leveraging VTC will now focus on impressions rather than clicks for billing and optimization on Discover.

First spotted. This update first came to my attention through Adsquire founder, Anthony Higman, who shared details on X.

Inspired by this post on Search Engine Land.

June 16, 2026
Discover Bing’s AI Reporting Revolution: Intents, Topics & More

Today, as I explore updates from Microsoft, I’m excited to share that Bing Webmaster Tools is rolling out a preview of its new AI performance report enhancements. These include insights like Intents, Topics, Citation Share, and Compare, and they’re being introduced globally. After witnessing Microsoft’s demo in April, it’s thrilling to know these features are finally accessible to us.

Reflecting on their past roll-outs, Bing officially launched its AI performance report earlier in February, a bold move ahead of Google’s similar feature which wasn’t available in Search Console until June. Google’s delayed release felt quite rushed to many of us.

New Insights: Krishna Madhavan from Microsoft describes these updates as built to give publishers a clearer understanding of why their content surfaces, the broader subject areas they’re gaining visibility in, and how their presence compares with other sources over time.

Intent: The Intents feature now classifies grounding queries into categories such as Informational, Commercial, Navigational, and more. This provides deeper insight into the intent behind user queries, moving beyond just triggering citations to understanding broader query contexts.

An example given was an e-commerce publisher finding visibility in comparison-focused experiences or an educational publisher learning their content is popular in research-oriented interactions. These insights can guide us in refining content structure and depth.

Topics: Topics group related queries into thematic clusters, offering us a more organized way to understand visibility, similar to modern AI’s reasoning across themes rather than isolated keywords.

For instance, queries like “solar panels” and “solar energy efficiency” can all be part of a larger topic cluster such as Solar Energy. This thematic organization helps us align our content with how AI systems engage with our content.

During this preview phase, some labels might remain broad, especially for niche domains, but meaningful patterns are already emerging.

Citations: Citation Share now displays the percentage of citation visibility your site enjoys compared to others. It’s a directional metric to help us understand our evolving visibility over time, without ranking or quality scores.

Compare: We can now compare citation changes over time. This feature overlays previous data onto current reports, helping us observe citation activity, which can be influenced by various factors like AI model updates, user demand shifts, and more.

Why This Matters: Although we’re still awaiting click and click-through rate data, these growing AI performance insights are invaluable. I’m hopeful that such detailed data will become available to us from Microsoft or even Google one day.

Inspired by this post on Search Engine Land.

June 16, 2026
Unlocking the Secrets of Google Discover Headline Formats
I recently delved into a fascinating study on Google Discover headline formats, looking at a staggering 3.4 million articles. The results were eye-opening and showed that a simple headline rewrite often doesn’t yield the expected lift.

You might have come across these bold statements before:
- Quote-led headlines outperform plain declarative ones by nearly 29%.
- Question headlines underperform both, sometimes by 24%.
- Format drives the result: Rewrite a statement as a quote, or add that magic word, and you should expect a real lift.
To put these claims to the test, I examined 1,674,518 English articles and 1,690,295 French articles from the 1492.vision Discover corpus. That’s quite a hefty sample size!

What I found was a deeper flaw than just numbers. It turns out that all three claims treat headline format as a leverage point for visibility. However, the data clearly shows that the impact of a headline’s format mainly reflects the publisher’s audience and the specific Discover surface used.

One striking analysis was Simpson’s paradox. An anomaly that, once noticed, appeared across the entire dataset.

Here’s what we’re really measuring:

Rather than clicks from Discover, our metric is hits per article: how often an article appears across the 1492.vision fleet. This serves as a proxy for visibility.

The dataset was limited to editorial articles, excluding platforms like YouTube because they have different headline norms. We’ll dive back into these at the end, as they bring more clarity than anything else.

Why is volume important? The crux of the argument depends on slicing this vast dataset by publisher, Discover surface, topic, and language while still keeping enough data in each segment for valid insights. This is where the real difference between numbers and insights, and between a genuine format effect and a statistical illusion, lies.

Here’s a sneak peek: when you pool all publishers together, a clear gradient appears with quote-led headlines leading the pack and statements trailing.

The frequently cited +29% is actually a conservative estimate for editorial pieces: quote-led headlines achieve a +37% lift in English and +48% in French. Even questions don’t lag behind as much as expected since they outperform statements to some extent (+7% EN, +16% FR).

Though claim 1 appears understated and claim 2 misguided at the aggregate level, these are the observations on which most headline advice leans. Let’s delve further to understand what the data is really revealing.

Let’s shift to the hidden aspects, starting with publishers. The raw comparison isn’t effectively between quotes and statements. It’s more about one set of publishers versus another because the publishers employing quotes often differ from those who don’t.

Some media, like celebrity-focused outlets, regional newspapers, and sites attuned to trending topics, gravitate towards quotes, and naturally earn more Discover hits compared to entities that prefer factual presentations.

This is a prime example of Simpson’s paradox: a strong trend at the aggregate level that fades or reverses when segmented into groups.

To focus on the format itself, publishers must each be their own baseline: comparing quotes with statements within the same publishing entities while controlling for audience and topic diversity.

So, the question is, how does each format fare on its own? Let me walk you through the rest of this journey as we unpack these layers.

Inspired by this post on Search Engine Land.
June 15, 2026
Understanding Google’s Stance on LLMS.txt and Search Rankings

I recently discovered that Google has updated its guidelines on optimizing for AI Search, and they’ve made it clear that LLMS.txt files on your site won’t impact your search rankings. It’s a relief to know that Google Search doesn’t actually utilize these files.

The portion of Google’s update that caught my attention explains that there’s no need to create new machine-readable files, such as AI text or Markdown files, to appear in Google Search, even with generative AI. Google will still discover, crawl, and index a variety of files, but these won’t receive special treatment.

Google also mentioned that maintaining LLMS.txt files for other services is perfectly fine and won’t influence your visibility in Google Search. In short, these files neither harm nor enhance your standing in search rankings.

For those interested, here is a valuable section screenshot along with more resources on the topic:

Meet llms.txt, a Proposed Standard for AI Website Content Crawling

Expressing why I care about this, there’s ongoing confusion around how Google handles such files. Remember, having them on your site won’t help but also won’t hurt your SEO efforts.

Inspired by this post on Search Engine Land.

June 15, 2026
Discover Google’s Latest Smart Bidding Innovations

I’m excited to share that Google has introduced new methods for advertisers to expand their campaigns while keeping a close grasp on efficiency targets. This expansion in Smart Bidding Exploration is sure to be a game-changer.

Google is unveiling a new series of updates designed to help advertisers discover fresh demand, take advantage of seasonal opportunities, and achieve more consistent campaign performance. I’ve always valued predictable outcomes in advertising, and these updates seem to focus exactly on that.

What’s new. The enhancements include a larger scope for Smart Bidding Exploration, the introduction of a new Promotion Mode beta, and updates to bidding target optimization specifically for campaigns with limited budgets.

Driving discovery. This enhancement allows me, as an advertiser, to set a return on ad spend (ROAS) tolerance, so my campaigns can capture additional conversion opportunities from search queries that currently might be overlooked.

From what I’ve seen, campaigns utilizing this feature experience about an 18% boost in unique converting search query categories and a 19% increase in overall conversions.

This capability is now extended to Performance Max campaigns without product feeds and is being tested in beta for Shopping ads within both Performance Max and Standard Shopping campaigns.

Peak period bidding. The new Promotion Mode empowers advertisers to adjust ROAS targets temporarily and increase the daily budget during peak periods like seasonal events, new product launches, and flash sales. I think this is a fantastic tool for maximizing high-demand opportunities.

What else is changing. Starting August 17, Google will update bidding target optimization for budget-constrained campaigns with the aim of delivering more consistent performance. This aligns better with our CPA and ROAS targets, which is reassuring for me as a campaign manager.

Notifications will begin rolling out in Google Ads on July 6, alerting advertisers about recommended campaign adjustments. I appreciate such timely updates that help me stay ahead in planning.

Why we care. These advancements allow Google’s AI bidding systems to explore incremental conversions beyond our current keyword and audience settings. This potential unlock of new demand could be pivotal in redefining campaign success for me.

The Promotion Mode stands out for retailers and seasonal advertisers by enabling temporary adjustments to ROAS targets and budgets during peak periods without needing a complete campaign overhaul. Additionally, the changes in bidding optimization aim at making performances more predictable in campaigns limited by budget.

The bottom line. Google’s recent bidding updates are designed to help advertisers, like me, find new conversion opportunities, react more assertively during peak demand times, and maintain consistent performance as campaigns scale.

Inspired by this post on Search Engine Land.

June 15, 2026
How Google’s New Ad Policy Impacts Advertiser Reach

I’ve recently discovered that Google is expanding its Limited ad serving policy across its Search platform. This change gives Google more control to restrict ad impressions from advertisers deemed unqualified or who might create confusion for users.

The implication of this update is significant. For newcomers, brands receiving negative feedback, or those not clearly presenting their identity in ads, the frequency of ad appearances could be affected.

What’s changing? As of this month, Google is rolling out an expanded policy affecting more search scenarios, which it plans to continue implementing through 2028.

This updated policy allows Google to limit ads on searches they believe might lead to poor user experiences.

How Google decides: User feedback is becoming crucial. Advertisers with frequent complaints about misleading content or practices could face limits on where their ads appear.

Additionally, if an ad makes it challenging to recognize who the advertiser is, Google might also impose restrictions.

Why we care: It’s not just about policy compliance anymore. Google is placing more emphasis on advertiser trust signals and branding clarity. Advertisers who don’t make their brand identity clear or have negative feedback histories might see reduced reach.

This shift underscores the importance of brand transparency in Search ads. Advertisers should reevaluate their ad copy and branding to ensure it’s evident who they are and their ad’s purpose.

What advertisers should do: To align with this update, advertisers are encouraged to enhance brand visibility in ads and landing pages, avoid overly generic messages, and clarify any brand affiliations.

Including a domain headline in the first position of responsive search ads can also help in making the advertiser’s identity more apparent.

The bottom line: Google’s updated policy prioritizes advertiser trustworthiness and clarity, potentially limiting visibility for those creating confusion with their identity or practices.

First spotted: Anthony Higman, Founder of Adsquire, first noticed this update. He expressed his concerns on LinkedIn.

Inspired by this post on Search Engine Land.

June 12, 2026
Master Google Analytics with New Source Grouping & Filters

I’m excited to share that Google Analytics is introducing significant updates aimed at streamlining our data analysis efforts. The introduction of cleaner source attribution and enhanced filtering controls is set to make evaluating cross-channel performance much simpler.
With these updates, I’m finding it easier to manage fragmented traffic source reports, enhance cross-channel performance analysis, and minimize noise in the analytics data we rely on.
What’s New. The new Source Group reporting dimension consolidates different traffic source variations into one cohesive category.
For example, instead of seeing scattered source names like “facebook,” “fb,” and others, all Facebook-related traffic can now be grouped under a single identifiable value.
At the same time, Google’s improvements to the Source Platform field ensure classifications align consistently across advertising channels, providing us with clearer data insights.
Why We Care. This cleaner source classification allows me to perform more accurate attribution analysis and cross-channel reporting. Instead of dealing with traffic fragmented by inconsistent labels, I can better understand which platforms truly drive conversions and where our budgets are yielding the best performance.
Including AI traffic sources like ChatGPT and Perplexity in this analysis offers a standardized way to measure these emerging channels alongside traditional ones. New hostname filters further refine data quality by making sure that only approved domain traffic enters our reporting.
The Big Picture. As we manage campaigns across multiple platforms, inconsistent source naming complicates attribution and budget analysis. This new reporting structure is a breath of fresh air, simplifying these comparisons and enhancing our strategic decision-making.
Between the Lines. This update extends source standardization beyond Google’s properties to platforms like TikTok, Pinterest, and Amazon, while also including support for emerging AI-driven traffic sources such as ChatGPT and Perplexity.
Also New. Google has added hostname filters in the Admin section, allowing us to exclude events from unapproved domains before reporting, enhancing data accuracy.
This feature helps prevent unwanted traffic from skewing our analysis, ensuring that our data remains precise and actionable.
What Advertisers Get. The updates provide standardized source reporting, retroactive access to historical source group data, cleaner attribution analysis, and more control over which domains contribute to reporting.
The Bottom Line. Google is equipping us with new tools to maintain reporting consistency, improve attribution analysis, and keep datasets cleaner as our traffic sources continue to diversify.

Inspired by this post on Search Engine Land.

June 12, 2026
Discover Microsoft’s Product Explorer for Enhanced Ad Performance

I’m excited to share Microsoft Ads’ latest tool—Product Explorer. It’s a remarkable addition that helps advertisers like us quickly spot catalog issues that might be hindering ad performance.

The introduction of Product Explorer represents Microsoft’s effort to create a central hub where advertisers can effortlessly monitor product catalog health and performance. Navah Hopkins, the Microsoft Product Liaison, highlighted its potential to revolutionize how we handle large product feeds.

Managing these expansive feeds often means struggling to pinpoint which items are ready to serve, which are capturing impressions, or which are missing vital data. Product Explorer steps in to make this task significantly more manageable.

What’s new? Now, I can explore my entire product catalog through a searchable interface. This tool allows for filtering by SKU, title, GTIN, and product ID, helping to quickly identify active products that are delivering performance results.

What it does. Product Explorer is designed to highlight eligibility issues and metadata gaps, along with other elements that might prevent products from serving. Plus, it offers recommended actions and the option to export filtered product lists for deeper analysis.

Why we care. As advertisers, having diagnostics and performance reporting combined in one interface means we can move more products into a servable state while identifying underperforming inventory more efficiently.

From searchable catalog reporting to gaining product-level performance insights covering the last 30 days, this tool offers issue detection and actionable recommendations to enhance feed quality.

The big picture. As retail advertising becomes more automated, focusing on feed quality is increasingly essential. Accurate visibility into catalog issues can significantly impact the reach and performance of our campaigns.

Availability. According to Navah Hopkins, the tool is live and ready for use in our accounts.

Inspired by this post on Search Engine Land.

June 12, 2026
Google’s DSA to AI Max Migration Postponed: More Time for Advertisers
As an advertiser using Google’s Dynamic Search Ads, I’ve got good news: Google has decided to delay the transition to AI Max by five months. This gives me more time to explore AI-powered options and manage the migration at my own pace.

The extended timeline is a relief, offering me the opportunity to test out new strategies and alternatives without the pressure of a sudden shift. Managing the transition away from one of Google’s most established campaign types on my own terms is crucial for continuity.

What’s changing: Google has pushed the auto-migration of DSA campaigns from September 2026 to February 2027. From June 15, I can even create new DSA campaigns again, offering flexibility during the transition period.

Catch up: For those not in the know, Dynamic Search Ads have been making way for newer, AI-driven campaign formats. These include AI Max for Search, broad match, and Smart Bidding.

With this delay, I have more time to assess how these AI-driven options perform compared to traditional methods. Preparing a solid migration plan before Google’s automatic upgrades can now be done thoughtfully and strategically.

Why we care: Google’s extension is quite significant, offering nearly six extra months to see how AI Max and other AI formats stack up. This valuable period allows me to conduct side-by-side tests, set performance benchmarks, and fine-tune migration strategies.

What advertisers should do: Google is prompting us to audit existing DSA campaigns, run experiments against AI Max for Search, and use tools for voluntary migration before February 2027.

Timeline:
- June 2026: DSA campaign creation is back.
- June 2026 – January 2027: Extended testing and voluntary migration period.
- January 2027: New DSA creation ceases.
- February 2027: Automatic migration kicks in for remaining campaigns.
The bottom line: Google is allowing advertisers more runway for transitioning from DSAs to AI-powered search campaigns, while still giving us access to creation and testing capabilities in the meantime.

Inspired by this post on Search Engine Land.

Timeline:
- June 2026: DSA campaign creation is back.
- June 2026 – January 2027: Extended testing and voluntary migration period.
- January 2027: New DSA creation ceases.
- February 2027: Automatic migration kicks in for remaining campaigns.
The bottom line: Google is allowing advertisers more runway for transitioning from DSAs to AI-powered search campaigns, while still giving us access to creation and testing capabilities in the meantime.

Inspired by this post on Search Engine Land.
June 12, 2026

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