Yoast SEO now works with Elementor’s new atomic editor

Elementor recently introduced a new way to build pages, called the atomic editor. If you’d switched to it, you may have noticed something annoying: Yoast SEO couldn’t see your content. Your text length, keyphrase checks, and readability results came back empty, even on a page full of content.

We’ve fixed that. Yoast SEO now reads your content straight from Elementor’s atomic editor, so every check works the way you’d expect: text length, keyphrase density, images, links, and more. Keyphrase highlighting works too. Click the eye icon on any check, and you’ll see your keyphrase marked in your text, right there in the editor.

If you’re still using Elementor’s classic editor, nothing changes for you. Everything keeps working as it did before.

What you need to do

Update your Yoast plugins to the latest version. That’s it. Your existing content gets picked up automatically the next time you open a page.

The post Yoast SEO now works with Elementor’s new atomic editor appeared first on Yoast.

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Web Design and Development San Diego

Search Central Deep Dive Europe 2026: Apparently we’re going to Barcelona

We’re excited to officially announce the next stop for
Search Central Live Deep Dive Europe 2026! Mark your calendars: based directly on
your feedback, we’re headed to
Barcelona, Spain, from September 30 to October 2, 2026.

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The June 2026 SEO Update by Yoast recap

Each month, we host the SEO update by Yoast covering the latest in search and AI. In this edition, Carolyn Shelby and Alex Moss discussed Google’s evolving stance on AI-driven search, publisher controls in the UK, and how to navigate visibility in an era where traditional SEO tactics are being reconsidered.

Watch the full recap on YouTube to dive deeper into these topics, hear some examples, and hear the answer to audience questions.

Remembering Bruce Clay

In this month’s SEO Update, we honor Bruce Clay, who recently passed away. He was a pioneer in SEO whose work shaped the industry. His mentorship and leadership left a lasting impact on professionals worldwide.

Google warns against manipulating brand mentions for AI

Google issued a clear warning: stop manipulating brand mentions to game AI systems. This includes tactics such as paying for unrelated brand citations, think dog food brands mentioned on sports betting sites, to artificially inflate perceived authority.

Why it matters: 

Google’s message is simple: if your brand mentions are irrelevant or forced, they won’t help your authority. Worse, they might backfire as AI systems get better at detecting manipulation. Focus on earning genuine mentions from relevant sources instead.

Actionable takeaway: 

  • Avoid paid or spammy brand mentions. 
  • Build authority through contextually relevant citations. 
  • If your mentions feel unnatural, they probably are. 

UK forces Google to give publishers control over AI use

The UK’s Competition and Markets Authority (CMA) struck a deal with Google, requiring the company to let publishers block their content from being used in AI features, without hurting their standard search rankings.

Why it matters: 

Publishers can now opt out of AI training data, but there’s a catch. If you block Google’s AI from using your content, you might lose citations in AI overviews, even if you rank well in traditional search. Users will instead see synthesized answers from other sources.

Actionable takeaway: 

  • If your content is truly unique and proprietary, blocking AI access might make sense, but only if you have a monetization strategy beyond search traffic. 
  • For most sites, allowing AI access is better for visibility. Ensure your content is structured and crawlable so AI systems can cite you accurately.
  • If you block AI access, provide a teaser, like Amazon’s “Look Inside” feature, to encourage clicks. 

New AI visibility insights in Google Search Console and Bing Webmaster Tools

Both Google and Bing rolled out new reporting features to help you understand how your content appears in AI-driven search. 

Google Search Console grounding queries

Google now shows grounding queries, the specific searches where your content was cited by AI. This helps you see which topics are driving AI visibility.

Why it matters: 

Grounding queries indicate that AI systems are using your content to generate answers. If you’re not seeing citations, your content might not be structured or visible enough for AI to reference.

Actionable takeaway: 

  • Check Search Console weekly for grounding queries. 
  • Focus on visible, structured content, so avoid hiding key info in accordions or tabs.
  • Use this data to refine your content strategy, so double down on what’s working or fix what’s not.

Bing Webmaster Tools: AI performance reports

Bing’s new reports include intents, topics, citation share, and performance comparisons for AI-driven search. This gives you a clearer picture of how your content performs in Bing’s AI experiences, like Copilot.

Why it matters: 

Bing’s AI integrations, such as Copilot in Windows, reach millions of business users. Ignoring Bing means missing out on a growing segment of AI-driven traffic.

Actionable takeaway: 

  • Set up Bing Webmaster Tools if you haven’t already.
  • Compare Bing’s data with Google’s to spot gaps or opportunities. 
  • Use LLMs like ChatGPT or Claude to analyze exports from both tools for deeper insights.

Google’s new publisher profiles and business data integrations

Google introduced publisher profiles and enhanced business data integrations, giving creators and businesses more control over how their content appears in search.

Why it matters: 

These tools help you fill out your knowledge graph, which improves visibility across Google’s ecosystem, including Gemini. Think of it as Google+ for publishers, but with a focus on entity authority rather than social networking.

Actionable takeaway: 

  • Create or update your publisher profile in Google Search Console.
  • Ensure your Google Business Profile is complete and accurate.
  • Use structured data to connect entities such as authors, brands, and products to your content.

Google updates SEO guidance: Don’t blindly trust AI or SEO tools

Google’s latest guidance warns against blindly following AI-generated SEO advice or third-party tool recommendations. The example? An AI suggested changing “consultant” to “advisor” for a site, only for the site to start competing with financial advisors instead of its actual audience.

Why it matters: 

AI and SEO tools can misinterpret context. Always verify recommendations before implementing them.

Actionable takeaway: 

  • Trust but verify, so use AI and tools for ideas, but apply critical thinking. 
  • Check multiple sources, so compare Google’s data with Bing’s, or use tools like Semrush/Ahrefs for cross-referencing.
  • Prioritize human judgment, because if a recommendation feels off, it probably is.

Schema.org usage stats reveal underutilized opportunities

Schema.org released data showing that 95% of websites use only 12 of the 958 available schema types. Meanwhile, fewer than 1,000 sites use 485+ schema types.

Why it matters: 

Schema helps search engines understand your content, but most sites aren’t leveraging its full potential. Using more schema types can improve visibility in AI-driven search and rich results.

Actionable takeaway: 

  • Audit your current schema usage to identify any missed opportunities.
  • Explore less common schema types, like FAQPage, HowTo, or Event to stand out.
  • Use Yoast SEO’s schema blocks to simplify implementation.

German court rules Google liable for false AI overview claims

A German court ruled that Google can be sued for false claims made in AI overviews. This sets a precedent for holding AI systems accountable for inaccurate information.

Why it matters: 

If Google’s AI cites false or harmful information about your business, you now have legal recourse in Germany. However, prevention is better than litigation.

Actionable takeaway: 

  • Monitor AI overviews for inaccuracies about your brand.
  • Publish accurate, crawlable content to counteract misinformation.
  • If you find false claims, correct them at the source, such as on Reddit or in forums, and report them to Google.

Google’s open knowledge format: A new way to structure content

Google introduced the Open Knowledge Format (OKF), a way to catalog site content in markdown for AI consumption. This is part of Google’s push for structured, AI-friendly content.

Why it matters: 

While Google’s search team advises against duplicate markdown versions of pages, the engineering team is building tools like OKF. This suggests structured content will play a bigger role in AI-driven search.

Actionable takeaway: 

  • Wait and watch, as OKF is new, and adoption isn’t urgent yet.
  • Focus on structured content, like schema, clear headings, visible text.
  • Avoid gating critical information behind interactive elements, such as accordions and tabs.

Yoast news: Performance upgrades and new features

We rolled out performance improvements in versions 27.8 and 27.9, of Yoast SEO, including:

  • Faster admin pages and post editor for large sites.
  • Speed boosts for SEO analysis. For instance, a sitemap query on a 2M-page site dropped from 300 seconds to 25 milliseconds.
  • Yoast Duplicate Post plugin upgrades, including improved Rewrite and Republish functionality for easier content repurposing.

Sign up for the next SEO Update by Yoast

The next SEO Update by Yoast is on August 25, 2026, at 4:00 PM CET (10:00 AM EST). Sign up to join live!

The post The June 2026 SEO Update by Yoast recap appeared first on Yoast.

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Google makes recipes in AI Mode more publisher friendly

Google has released an update to the recipe results within AI Mode to make them more publisher-friendly. Google added the creator name, recipe ratings and number of ingredients to these AI Mode results for some recipes.

What is new. Robby Stein from Google said there are now “prominent links at the top of responses with useful details and images – like the creator name, recipe ratings and number of ingredients.” He added that this should make it “even easier to discover and visit recipe pages with AI Mode.”

We also spotted Google testing top stories carousels in the AI Overviews, but this does not seem to be live yet.

What it looks like. Here is a screenshot of the treatment:

Previously. Robby Stein, back in March, also announced changes to the recipe results in AI Mode. Then he said, “We’ve heard feedback on recipe results in AI Mode, and we’re making updates to better connect people with recipe creators on the web.”

These changes are to help reduce the AI recipe slop that we see for a lot of these queries.

Why we care. Recipe bloggers, well, content creators in general, have not been happy with how traffic from Google’s AI experiences did not send as much traffic as the traditional search results. Here we see Google trying to make changes to encourage more searchers to click from those AI experiences to the bloggers website.

If Google can add more clickable link units to the AI experiences in search, that can help improve the publisher-Google relationship.

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Microsoft expands Performance Max testing with new experiment types

Microsoft Ads: How it compares to Google Ads and tips for getting started

Microsoft is bringing experimentation to Performance Max campaigns, giving advertisers new ways to test campaign changes and measure incremental impact without disrupting live performance.

What’s new:

  • Uplift experiments let advertisers measure the incremental impact of Performance Max campaigns against a control group.
  • Upgrade experiments allow advertisers to compare an existing campaign with an upgraded Performance Max version before fully rolling out changes.

Both experiment types are available under Campaigns > Experiments for eligible accounts.

Why we care. Until now, Microsoft Ads experiments were limited to Search campaigns. Expanding testing to Performance Max gives advertisers a safer way to validate campaign changes, optimize performance, and make data-driven decisions before committing budget.

Between the lines. As experimentation expands, Microsoft has also renamed its existing experiment offering to Search optimization experiments, distinguishing it from the new Performance Max testing capabilities. The move reflects Microsoft’s broader push to provide advertisers with more sophisticated optimisation tools across automated campaign formats.

The bottom line. Microsoft is closing a key gap in its Performance Max offering by introducing dedicated experiment types, giving advertisers more confidence when testing upgrades and measuring the true impact of automated campaigns.

First spotted. The help docs were spotted by PPC News Feed founder, Hana Kobzová.

Dig deeper.

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Google Ads redesigns All Campaigns selector

How to use Performance Planner and Reach Planner in Google Ads

Google is updating the All Campaigns selector with a redesigned interface that makes it easier for advertisers to navigate large and complex account structures.

What’s happening. The new All Campaigns selector is rolling out across Google Ads, bringing a refreshed layout and improved navigation tools.

What’s new:

  • The selector has been moved to a new location in the interface.
  • Campaigns now appear in an expandable hierarchical view, making campaign groups and nested structures easier to browse.
  • A new search function lets advertisers quickly locate campaigns and campaign groups.

Why we care. The update could save time for advertisers managing large accounts by making it faster to navigate between campaigns, particularly in accounts with multiple campaign groups or complex organisational structures.

The bottom line. Google’s redesigned All Campaigns selector aims to streamline campaign management with a clearer hierarchy and built-in search, helping advertisers navigate complex accounts more efficiently.

First spotted. The update was identified by performance marketer Vivek Gupta on LinkedIn, and is rolling out gradually, so it may not yet be available in every Google Ads account.

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Google renames age estimation ads policy as global age assurance expands

Google is updating its advertising policy to clarify how it limits certain ads while estimating a user’s age, offering advertisers more transparency as it expands age assurance technology worldwide.

What’s happening. Google has renamed its Default Ads Treatment policy to “Categories restricted while Google is estimating a user’s age.” The change better reflects that the restrictions are temporary and only apply while Google’s systems determine a user’s age.

What’s changing:

  • The policy has a new name to more clearly describe its purpose.
  • Google has updated the policy language to emphasise that the restrictions are interim protections during the age estimation process.
  • Enforcement remains unchanged.

What’s different: Google has also narrowed the list of ad categories restricted during the age estimation process.

Previously, Google restricted ads for:

  • Adult content and pornography
  • Alcohol
  • Gambling
  • Shocking content

The updated policy now restricts only:

  • Adult content and pornography
  • Alcohol
  • Gambling

Why we care. The update doesn’t introduce new advertising restrictions, but it provides greater clarity on when and why certain ads may not be served. Advertisers in affected verticals can better understand that these limitations are tied to Google’s age estimation process rather than permanent policy changes.

The bottom line. Nothing changes for advertisers operationally, but Google’s updated policy makes it clearer that restrictions on adult, alcohol and gambling ads are temporary safeguards while a user’s age is being estimated.

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Google adds new YouTube brand campaign measurement tools

The Fujiwhara effect on YouTube: AI, Shorts, and the rise of duplicate content

Google is expanding measurement capabilities for YouTube brand campaigns, giving advertisers better visibility into how video ads drive engagement, brand interest, and downstream business outcomes.

What’s new:

  • Shorts Ad Actions for Video View Campaigns: Advertisers running Video View Campaigns that are opted into YouTube Shorts will now automatically benefit from Shorts Ad Actions in budget optimization. Google is also adding new reporting columns to measure these interactions.
  • Attributed Branded Searches: Now available globally in Google Ads, this new reporting metric measures branded Google searches that occur after users see or view a YouTube ad, helping advertisers quantify how awareness campaigns influence purchase intent.

Why we care. It can be hard for marketers to connect upper-funnel YouTube campaigns with measurable business outcomes. These updates provide stronger signals that link brand advertising to engagement and search intent, making it easier to justify brand investment and optimise campaigns.

By the numbers:

  • According to Google, YouTube Shorts ads that generated more than 10 seconds of watch time and a like delivered:
    • 15% higher brand consideration
    • 20% higher brand favourability, according to Google.
  • Google also says that every additional branded search generated is associated with an average $31 increase in sales.

Between the lines. Google continues to blur the distinction between brand and performance marketing by introducing metrics that connect awareness campaigns with downstream actions. Attributed Branded Searches, in particular, gives advertisers another way to demonstrate that YouTube campaigns can influence high-intent behaviour before a conversion takes place.

The bottom line. Google’s latest measurement updates help advertisers better prove the value of YouTube brand campaigns by linking video engagement and branded search activity to business outcomes—offering stronger evidence that upper-funnel advertising can drive measurable results.

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The new SEO stack: What replaces your old toolset

New SEO stack old toolset

Generative AI and automation are bringing excitement to some SEO professionals and anxiety to others. With 87% of Americans reading AI summaries, you’re falling behind if you’re not adapting your toolset to this trend.

Moving from rigid enterprise tools to agile, AI-driven ones positions you as a forward-thinking authority with clients or your employer.

This how-to will help you guide clients, employers, or your team through that shift.

Here’s what an old SEO stack looks like

SEO practices remain relevant because the company’s generative AI features are rooted in:

  • Core search ranking systems.
  • Quality systems.

Here’s a traditional “SEO stack”:

Rank trackers

Tracking keywords used to be every campaign’s heartbeat. Add target keywords, monitor SERP positions, and higher rankings would drive more search traffic. But rankings have fragmented over the last few years.

SEOs are now tracking:

  • AI Overviews
  • Local packs
  • Shopping carousels
  • And so much more.

A third-place local pack ranking might drive two or three times more traffic than a number one AI Overview ranking.

Keyword tools

What are people searching for? With a crystal ball, you could optimize for specific queries and target certain groups. Keyword research lets you write content that matches those queries and user intent.

You’ll choose keywords based on:

  • Difficulty
  • Search volume
  • Intent
  • Other factors

Dozens of options help you find keywords for campaigns, and some competitors had more access to keyword data than others.

Lagging search volume data may have hurt your campaign, but it still showed past performance.

For example, you might target a keyword with 10,000 monthly visits. But just because it reached that volume last month doesn’t mean it will perform the same this month. Volume could double or fall to a tenth of last month’s level.

The problem in today’s search environment is that a keyword with tens of thousands of clicks in 2022 may now appear in an AI Overview. Zero-click searches may steal your traffic, making some once high-click queries irrelevant or not worth the same investment.

Even if search volume hasn’t dropped, the opportunity has.

Site audit tools

Crawlers still crawl your site and interpret its content. Getting a complete picture of how these crawlers see your website has always been crucial to SEO.

Audit tools help you identify:

  • Broken links
  • Redirect issues
  • Missing metadata
  • Slow pages
  • Thin content
  • Other issues on your site

But don’t put these audit tools on the shelf just yet. You’ll still need them to know whether your site is technically healthy. Crawl audits don’t guarantee that your content will surface.

Factors such as brand mentions are crucial signals for inclusion in LLMs like ChatGPT, Claude, and Gemini.

Unfortunately, many site audit tools in your old stack lack mention-tracking functionality.

So while you may still rely on your old stack, it’s time to add new tools that cover these signals and change how you operate as an SEO professional.

Here’s what a new SEO stack looks like

IIf you’re still optimizing only for Google, it’s time to shift gears. Between the first and second half of 2025, LLM referral traffic grew by 80%. Conversion rates reached 18%, but LLM referrals still accounted for 2% or less of total traffic, according to the dataset.

Now is the time to shift to a new stack that helps you leverage growing LLM referrals.

Add the following to your SEO tech stack to stay ahead of the competition:

LLMs

You want your site to show up in LLMs, but these same tools can help power your SEO strategy. For example, you might use:

  • ChatGPT: Connect ChatGPT with Google Search Console to automate your SEO analysis, as I show you how to do in arecent article here.
  • Claude: Use Claude to write your copy, refine metadata and conduct a full content audit.
  • Gemini: Hop on Gemini to help generate schema markup, compare competitor sites with your own, or find issues with your site.

LLMs can help with everything from data analysis to competitor research.

Use the LLM you’re most comfortable with for these tasks, but keep human oversight in place. Use these tools to improve performance, not replace the human element.

Large datasets that once took hours, days, or weeks to review now take minutes with these tools. Keep learning LLMs and how to integrate them into your workflow.

APIs

Old dashboards with CSV exports into Excel were once standard. You logged into Google Search Console (GSC) and exported data. While it may sound too technical, LLMs can now help you connect to APIs for:

  • Google Search Console
  • Google Analytics

LLMs can help you authenticate requests and parse JSON. With this skill, you can open up a workflow

Lightweight scripts

Python scripts are now available to any SEO with some skill and Claude Code, or similar options in ChatGPT or Gemini. You can easily create scripts that:

  • Pull your top pages from GSC
  • Compare titles to character limits
  • Flag 30-day changes
  • Create a CSV output for you

Rather than waiting for vendor tools to add a feature that removes a performance bottleneck, create a script that does the same thing.

A hundred-line script can handle much of the work you used to do by hand, without a new license or SaaS upsell. If you hand the script to someone else, they can see the exact logic behind it.

Notebooks / local workflows

Your SEO team has data in many places:

  • Shared folders
  • Google Sheets
  • Notion docs

You might have a three-year content audit tracker in Google Sheets. A spreadsheet with monthly CSV dumps from your favorite tools leaves you with files you must manually open and decipher.

Notebooks and local workflows change how data fragmentation slows your team down.

Instead, Notebooks interpret these files and turn them into action. For example, a script may pull data, an API surfaces the signal, and LLMs make sense of the data and put the output into your Notebook.

Notebooks also offer the benefit of:

  • Consistent data formats
  • Shared access to data
  • Documented logic

SEO teams need to be agile and scalable to grow with the new era of search optimization and generative AI. Rather than starting over every time they need to pull data, teams can use local workflows for data consistency.

Creating hybrid workflows to mix old and new SEO stacks

Is your old SEO stack obsolete? No. Are these new tools the only ones you need? No. Hybrid workflows and search engine optimization stacks offer the best of both worlds.

Tool + custom script + AI layer

You’ll need to experiment to create a hybrid workflow that works best for your clients, projects, and teams. One hypothetical workflow that combines the old and new stack for well-rounded SEO includes:

  • Crawling the site with an audit tool, such as Screaming Frog
  • Running a Python script that dissects the file and joins it with GSC data
  • Scripts that flag pages where you have a lot of impressions but low clicks
  • Sending flagged pages to an LLM to evaluate titles against search intent
  • Putting LLM output into a Notebook or spreadsheet for editors to review
  • Turning approvals into change logs

Tasks like these used to take weeks, so teams put them on the back burner. At the enterprise level, teams quickly felt overwhelmed by this much data. But when you combine old and new SEO stacks, you can complete larger projects in a fraction of the time.

Replacing your current SEO stack with one that’s more agile and built for today’s massive datasets will make you an invaluable asset to any SEO team.

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Why broad targeting makes creative your best qualifier

Broad targeting creative qualifier

Across Google Ads, Meta, and TikTok, platforms are pushing you toward broader, AI-driven targeting. Performance Max, Advantage+ campaigns, and TikTok’s automated audience expansion give algorithms more room to find converters while reducing your control over who sees an ad.

This is fundamentally changing how campaigns are qualified.

As targeting broadens, creative has become one of the most important signals for both users and algorithms. Identifying the right audience is moving out of audience settings and into the message itself.

Broad targeting is making creative your best qualifier.

The shift from audience qualification to creative qualification

For years, performance marketers treated targeting as the primary lever for improving lead quality:

  • Need prospective graduate students? Layer education interests, demographics, and remarketing audiences.
  • Need patients seeking specialized care? Build audiences around health-related behaviors and intent signals.
  • Need insurance shoppers? Narrow targeting by age, life stage, and consumer interests.

These approaches aren’t disappearing, but their influence is shrinking. Platforms increasingly ask you to provide broad audience inputs, strong conversion signals, and compelling creative, then let machine learning determine who’s most likely to convert.

Meta’s Advantage+ ecosystem, Google’s Performance Max campaigns, and TikTok’s recommendation engine all operate on this principle.

The challenge is that algorithms still need signals.

Conversion data remains the strongest signal, but creative is becoming more important in helping platforms understand who should engage with an ad. Every headline, image, video, and call to action provides context about the intended audience and desired action.

Creative is no longer just a persuasion tool.

It’s now a targeting signal.

Why broad targeting requires more intentional creative

Many advertisers still create ads as if targeting will qualify the audience.

Messaging often stays broad because you assume audience settings will narrow who sees the ad. But when platforms expand beyond tightly defined segments, vague creative can attract engagement from people unlikely to become qualified leads.

The consequences are familiar:

  • Lower lead quality.
  • Increased cost per qualified lead.
  • Less efficient optimization.
  • Noisier conversion data.

Instead, you need creative that clearly communicates who the offer is for—and just as importantly, who it isn’t for.

The goal isn’t simply more clicks or video views.

The goal is engagement from the right people.

When creative clearly identifies the audience, users can self-select. Qualified prospects lean in. Unqualified prospects move on. Both outcomes improve campaign performance and give machine learning systems cleaner signals.

Higher education: When creative becomes the targeting layer

Higher education marketers are already seeing this shift.

Historically, campaigns relied heavily on demographic filters, education interests, degree status, and segmented audience lists to reach prospective students.

Today, many strong-performing campaigns use broad lookalike audiences, Advantage+ audiences, or broad prospecting structures designed to maximize audience size and algorithmic learning.

But broader audiences create a challenge.

If a university is promoting an online Master of Science in Data Analytics program, it doesn’t need just any prospective student. It needs prospective students who meet specific admission and career criteria.

  • Perhaps they already hold a bachelor’s degree.
  • Perhaps they have professional experience.
  • Perhaps they want to move into leadership or pivot into a more technical career path.

Rather than relying only on targeting settings to communicate those distinctions, build them directly into the creative.

Consider the difference between these two headlines:

Generic:

  • “Advance your career with a Data Analytics degree.”

Qualifying:

  • “Built for bachelor’s degree holders ready to advance into leadership – earn your online M.S. in Data Analytics.”

The second example immediately signals who the program is for. Undergraduate prospects are less likely to engage, while qualified graduate prospects are more likely to click, convert, and reinforce positive optimization signals.

The creative itself becomes the qualification mechanism.

Google Performance Max: Creative guides the algorithm

Google Performance Max may be the clearest example of this industry-wide shift.

Despite the name, audience signals are not strict targeting controls. They’re starting points that help Google’s systems learn. Ultimately, Google determines where and to whom ads are shown across Search, YouTube, Display, Discover, Gmail, and Maps.

Because advertisers have less direct control over audience selection, creative assets become increasingly important in helping Google’s systems understand who should respond.

Imagine a healthcare provider promoting orthopedic services.

A generic headline might read:

  • “Expert Care for Your Health Needs.”

While technically accurate, it offers little context regarding the intended audience.

A more effective alternative might be:

  • “Persistent Knee Pain? Meet with Our Orthopedic Specialists.”

The second headline identifies a specific need, a specific audience, and a specific solution. Users immediately understand whether the message applies to them, and Google’s systems receive stronger engagement signals from people actively experiencing that problem.

The same principle applies across insurance, legal services, financial services, and education.

When Performance Max creative clearly identifies the audience and their need state, advertisers help Google’s machine learning systems learn faster and optimize toward more qualified outcomes.

TikTok: The first three seconds matter more than ever

TikTok has always relied heavily on content signals to determine who sees a video.

As the platform continues investing in automation and audience expansion, creative becomes even more critical.

The opening seconds of a video often determine not only whether a user continues watching but also how TikTok categorizes and distributes the content.

For lead generation campaigns, qualification should begin immediately.

A graduate program might open with:

  • “Already have a bachelor’s degree and looking for your next career move?”

An insurance provider might start with:

  • “Shopping for Medicare coverage this year?”

A law firm specializing in workplace injury cases could lead with:

  • “Were you injured on the job within the last 12 months?”

These openings accomplish two objectives simultaneously.

First, they quickly tell viewers whether the content is relevant to them.

Second, they provide TikTok’s algorithm with stronger behavioral signals about who engages with the video. Qualified prospects are more likely to continue watching and take action. Unqualified viewers are more likely to scroll past.

That self-selection process improves audience learning over time.

Creative is now a performance lever

One of the biggest mistakes you can make today is treating creative as something that happens after strategy and targeting are finalized.

In increasingly automated advertising environments, creative is strategy.

The message, visuals, hooks, and calls to action no longer serve only a branding or conversion role. They help platforms determine who should see the ad in the first place.

That means creative and media teams must work together more closely than ever.

When building campaigns, marketers should ask:

  • Does this creative clearly identify who the offer is for?
  • Does it communicate relevant qualifications or prerequisites?
  • Would an unqualified prospect immediately recognize that the message isn’t intended for them?
  • Are we helping both users and algorithms understand our ideal audience?

If the answer is no, the campaign may be relying too heavily on targeting to solve a problem that creative is now better positioned to address.

The future of qualification is creative

As Google, Meta, and TikTok keep expanding AI-driven targeting, you’ll likely have even less control over audience selection than you do today.

Qualification doesn’t disappear—it shifts into the creative itself.

What once happened primarily through audience settings is increasingly happening through messaging, visuals, and creative strategy.

You must embrace that shift to thrive in this environment. That means:

  • Writing headlines that identify the intended audience.
  • Creating videos that establish audience fit in the first few seconds.
  • Building qualifications, prerequisites, and intent signals directly into the message.

Every ad speaks to two audiences at once: the user and the algorithm.

Platforms are handling more targeting than ever, but they still need direction.

Increasingly, that direction comes from creative. In a world of broad targeting, creative isn’t just the message — it’s the qualifier.

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