How vibe coding is changing search marketing workflows

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Vibe coding for search marketers

Search marketers are starting to build, not just optimize.

Across SEO and PPC teams, vibe coding and AI-powered development tools are shrinking the gap between idea and execution – from weeks of developer queues to hours of hands-on experimentation. 

These tools don’t replace developers, but they do let search teams create and test interactive content on their own timelines.

That matters because Google’s AI Overviews are pulling more answers directly into the SERP, leaving fewer clicks for brand websites. 

In a zero-click environment, the ability to build unique, useful, conversion-focused tools is becoming one of the most practical ways search marketers can respond.

What is vibe coding?

Vibe coding is a way of building software by directing AI systems through natural language rather than writing most of the code by hand. 

Instead of working line by line, the builder focuses on intent – what the tool should do, how it should look, and how it should respond – while the AI handles implementation.

The term was popularized in early 2025 by OpenAI co-founder Andrej Karpathy, who described a loose, exploratory style of building where ideas are tested quickly, and code becomes secondary to outcomes. 

His framing captured both the appeal and the risk: AI makes it possible to build functional tools at speed, but it also encourages shortcuts that can lead to fragile or poorly understood systems.

Andrej Karpathy on X

Since then, a growing ecosystem of AI-powered development platforms has made this approach accessible well beyond engineering teams. 

Tools like Replit, Lovable, and Cursor allow non-developers to design, deploy, and iterate on web-based tools with minimal setup. 

The result is a shift in who gets to build – and how quickly ideas can move from concept to production.

That speed, however, doesn’t remove the need for judgment. 

Vibe coding works best when it’s treated as a craft, not a shortcut. 

Blindly accepting AI-generated changes, skipping review, or treating tools as disposable experiments creates technical debt just as quickly as it creates momentum. 

Mastering vibe coding means learning how to guide, question, and refine what the AI produces – not just “see stuff, say stuff, run stuff.”

This balance between speed and discipline is what makes vibe coding relevant for search marketers, and why it demands more than curiosity to use well.

Vibe coding vs. vibe marketing

Vibe coding should not be confused with vibe marketing. 

AI no-code tools used for vibe coding are designed to build things – applications, tools, and interactive experiences. 

AI automation platforms used for vibe marketing, such as N8N, Gumloop, and Make, are built to connect tools and systems together.

For example, N8N can be used to automate workflows between products, content, or agents created with Replit. 

These automation platforms extend the value of vibe-coded tools by connecting them to systems like WordPress, Slack, HubSpot, and Meta.

Used together, vibe coding and AI automation allow search teams to both build and operationalize what they create.

 Why vibe coding matters for search marketing

The search marketer's guide to vibe coding

In the future, AI-powered coding platforms will likely become a default part of the marketing skill set, much like knowing how to use Microsoft Excel is today. 

AI won’t take your job – but someone who knows how to use AI might. 

We recently interviewed candidates for a director of SEO and AI optimization role.

None of the people we spoke with were actively vibe coding or had used AI-powered development software for SEO or marketing.

That gap was notable. 

As more companies add these tools to their technology stacks and ways of working, hands-on experience with them is likely to become increasingly relevant.

Vibe coding lets search marketers quickly build interactive tools that are useful, conversion-focused, and difficult for Google to replicate through AI Overviews or other SERP features.

For paid search, this means teams can rapidly test interactive content ideas and drive traffic to them to evaluate whether they increase leads or sales. 

These platforms can also be used to build or enhance scripts, improve workflows, and support other operational needs.

For SEO, vibe coding makes it possible to add meaningful utility to pages and websites, which can increase engagement and encourage users to return. 

Returning visitors matter because, according to Google’s AI Mode patent, user state – which includes engagement – plays a significant role in how results are generated in AI Overviews and AI Mode.

Google’s AI Mode patent - Sheet 9 of 11

For agency founders, CEOs, CFOs, and other group leaders, these tools also make it possible to build custom internal systems to support how their businesses actually operate. 

For example, I used Replit to build an internal growth forecasting and management tool.

Internal growth forecasting and management tool - Replit

It allows me to create annual forecasts with assumptions, margins, and P&L modeling to manage the SEO and AI optimization group. 

There isn’t off-the-shelf software that fully supports those needs.

Vibe coding tools can also be cost-effective. 

In one case, I was quoted $55,000 and a three-month timeline to build an interactive calculator for a client. 

Using Replit, I built a more robust version in under a week on a $20-per-month plan.

Beyond efficiency, the most important reason to develop these skills is the ability to teach them. 

Helping clients learn how to build and adapt alongside you is increasingly part of the value agencies provide.

In a widely shared LinkedIn post about how agencies should approach AI, Chime CMO Vinneet Mehra argued that agencies and holding companies need to move from “we’ll do it for you” to “we’ll build it with you.” 

In-house teams aren’t going away, he wrote, so agencies need to partner with them by offering copilots, playbooks, and embedded pods that help brands become AI-native marketers.

Being early to adopt and understand vibe coding can become a competitive advantage. 

Used well, it allows teams to navigate a zero-click search environment while empowering clients and strengthening long-term working relationships – the kind that make agencies harder to replace.

Top vibe coding platforms for search marketers

There are many vibe coding platforms on the market, with new ones continuing to launch as interest grows. Below are several leading options worth exploring.

AI development tool
and experience level		 Pros Cons
Google AI Studio
(Intermediate)		 • Direct access to Google’s latest Gemini models.
• Seamless integration with Google ecosystem (Maps, Sheets, etc.).
• Free tier available for experimentation.		 • Locked into Google’s ecosystem and Gemini models.
• Limited flexibility compared to open platforms.
• Smaller community/resources compared to established tools.
Lovable
(Beginner)		 • Rapid full-stack app generation from natural language.
• Handles database setup automatically. 
• Minimal coding knowledge required.		 • Relatively new platform with less maturity.
• Limited customization for complex applications.
• Generated code may need refinement for production.
Figma Make
(Intermediate)		 • Seamless design to code workflow within.
• Ideal for teams already using Figma.
• Bridges gap between designers and developers.		 • Requires Figma subscription and ecosystem.
• Newer tool, still evolving features.
• Code output may need developer review for production.
Replit
(Intermediate)		 • All-in-one platform (code, deploy, host).
• Strong integration capabilities with third-party tools.
• No local setup required.		 • Performance can lag compared to local development.
• Free tier has significant limitations.
• Fees can add up based on usage.
Cursor
(Advanced)		 • Powerful AI assistance for experienced developers.
• Works locally with your existing workflow.
• Advanced code understanding and generation.		 • Steeper learning curve, requires coding knowledge.
• Need to download the software GitHub dependency for some features.

For beginners:

  • Lovable is the most user-friendly option for those with little coding experience. 
  • Figma Make is also intuitive and works well for teams already using Figma. 
  • Replit is also relatively easy to use and does not require prior coding experience.

For developers, Replit and Cursor offer deeper tooling and are better suited for integrations with other systems, such as CRMs and CMS platforms.

Google AI Studio is broader in scope and offers direct connections to Google products, including Google Maps and Gemini, making it useful for teams working within Google’s ecosystem.

You should test several of these tools to find the one that best fits your needs. 

I prefer Replit, but I will be using Figma Make because our creative teams already work in Figma. 

Bubble is also worth exploring if you are new to coding, while Windsurf may be a better fit for more advanced users.

Practical SEO and PPC applications: What you can build today

There is no shortage of things you can build with vibe coding platforms. 

The more important question is what interactive content you should build – tools that do not already exist, solve a real problem, and give users a reason to return. 

Conversion focus matters, but usefulness comes first.

Common use cases include:

  • Lead generation tools
    • Interactive calculators, such as ROI estimators and cost analyzers.
    • Quiz funnels with email capture.
    • Free tools, including word counters and SEO analyzers
  • Content optimization tools
    • Keyword density checkers.
    • Readability analyzers.
    • Meta title and description generators
  • Conversion rate optimization
    • Product recommenders.
    • Personalization engines.
  • Data analysis and reporting
    • Custom analytics dashboards.
    • Rank tracking visualizations.
    • Competitor analysis scrapers, with appropriate ethical considerations.

Articles can only take you so far in a zero-click environment, where AI Overviews increasingly provide direct answers and absorb traffic. 

Interactive content should be an integral part of a modern search and content strategy, particularly for brands seeking to enhance visibility in both traditional and generative search engines, including ChatGPT. 

Well-designed tools can earn backlinks, increase time on site, drive repeat visits, and improve engagement signals that are associated with stronger search performance.

For example, we use AI development software as part of the SEO and content strategy for a client serving accounting firms and bookkeeping professionals. 

Our research led to the development of an AI-powered accounting ROI calculator designed to help accountants and bookkeeping firms understand the potential return on investment from using AI across different parts of their businesses.

The calculator addresses several core questions:

  • Why AI adoption matters for their firm.
  • Where AI can deliver the most impact.
  • What the expected ROI could be.

It fills a gap where clear answers did not previously exist and represents the kind of experience Google AI Overviews cannot easily replace.

AI adoption ROI calculator

The tool is educational by design. 

AI ROI calculator for accounting firms

It explains which tasks can be automated with AI, displays results directly on screen, forecasts a break-even point, and allows users to download a PDF summary of their results.

AI ROI calculator features

AI development software has also enabled us to design additional calculators that deliver practical value to the client’s target audience by addressing problems they cannot easily solve elsewhere.

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A 7-step vibe coding process for search marketers

Vibe coding works best when it follows a structured workflow. 

The steps below outline a practical process search marketers can use to plan, build, test, and launch interactive tools using AI-powered development platforms.

Step 1: Research and ideation

Run SERP analysis, competitor research, and customer surveys, and use audience research tools such as SparkToro to identify gaps where AI Overviews leave room for interactive tools. 

Include sales, PR, legal, compliance, and cybersecurity teams early in the process. 

That collaboration is especially important when building tools for clients. 

When possible, involve customers or target audiences during research, ideation, and testing.

Step 2: Create your content specification document

Create a content specification document to define what you want to build before you start. 

This document should outline functionality, inputs, outputs, and constraints to help guide the vibe coding software and reduce errors. 

Include as much training context as possible, such as brand colors, tone of voice, links, PDFs, and reference materials. 

The more detail provided upfront, the better the results.

Use this Interactive Content Specification Brief template, and review the instructions before getting started.

Step 3: Design before functionality

Begin with wireframes and front-end design before building functionality. 

Replit prompts for this approach during setup, and it helps reduce rework later. 

Getting the design close to final before moving into logic makes it easier to evaluate usability. 

Design changes can always be made later.

Step 4: Prompt like a product manager

After submitting the specification document, continue prompting to refine the build. 

Ask the AI why it made specific decisions and how changes affect the system. 

In practice, targeted questions lead to fewer errors and more predictable outcomes.

Prompt like a product manager

Step 5: Deploy and test

Deploy the tool to a test URL to confirm it behaves as expected.

If the tool will be embedded on other sites, test it in those environments as well. 

Security configurations can block API calls or integrations depending on the host site. 

I encountered this when integrating a Replit build with Klaviyo. 

After reviewing the deployment context, the issue was resolved.

Step 6: Update the content specification document

Have the AI update the content specification document to reflect the final version of what was built. 

This creates a record of decisions, changes, and requirements and makes future updates or rebuilds easier. 

Save this document for reference.

Step 7: Launch

Push the interactive content live using a custom domain or by embedding it on your site. 

Plan distribution and promotion alongside the launch. 

This is why involving PR, sales, and marketing teams from the beginning of the project matters.

They play a role in ensuring the content reaches the right audience.

The dark side of vibe coding and important watchouts

Vibe coding tools are powerful, but understanding their limitations is just as important as understanding their strengths. 

The main risks fall into three areas: 

  • Security and compliance.
  • Price creep.
  • Technical debt.

Security and compliance 

While impressive, vibe coding tools can introduce security gaps. 

AI-generated code does not always follow best practices for API usage, data encryption, authentication, or regulatory requirements such as GDPR or ADA compliance. 

Any vibe-coded tool should be reviewed by security, legal, and compliance professionals before launch, especially if it collects user data. 

Privacy-by-design principles should also be documented upfront in the content specification document.

These platforms are improving. 

For example, some tools now offer automated security scans that flag issues before deployment and suggest fixes. 

Even so, human review remains essential.

Price creep

Another common risk is what could be described as the “vibe coding hangover.” 

A tool that starts as a quick experiment can quietly become business-critical, while costs scale alongside usage. 

Monthly subscriptions that appear inexpensive at first can grow rapidly as traffic increases, databases expand, or additional API calls are required.

In some cases, self-hosting a vibe-coded project makes more sense than relying on platform-hosted infrastructure. 

Hosting independently can help control costs by avoiding per-use or per-visit charges.

Technical debt

Vibe coding can also create technical debt. 

Tools can break unexpectedly, leaving teams staring at code they no longer fully understand – a risk Karpathy highlighted in his original description of the approach. 

This is why “Accept all” should never be the default. 

Reviewing AI explanations, asking why changes were made, and understanding tradeoffs are critical habits.

Most platforms provide detailed change logs, version history, and rollback options, which makes it possible to recover when something breaks. 

Updating the content specification document at major milestones also helps maintain clarity as projects evolve.

Vibe coding is your competitive edge

AI Overviews and zero-click search are changing how value is created in search. 

Traffic is not returning to past norms, and competing on content alone is becoming less reliable. 

The advantage increasingly goes to teams that build interactive experiences Google cannot easily replicate – tools that require user input and deliver specific, useful outcomes.

Vibe coding makes that possible. 

The approach matters: start with research and a clear specification, design before functionality, prompt with intent, and iterate with discipline. 

Speed without structure creates risk, which is why understanding what the AI builds is as important as shipping quickly.

The tools are accessible. Lovable lowers the barrier to entry, Cursor supports advanced workflows, and Replit offers flexibility across use cases. 

Many platforms are free to start. The real cost is not testing what’s possible.

More importantly, vibe coding shifts how teams work together. 

Agencies and in-house teams are moving from “we’ll do it for you” to “we’ll build it with you.” 

Teams that develop this capability can adapt to a zero-click search environment while building stronger, more durable partnerships.

Build something. Learn from it. The competitive advantage is often one prompt away.

Read more at Read More

What successful brand-agency partnerships look like in 2026

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What successful brand-agency partnerships look like in 2026

Brand-agency partnerships look very different today than they did even a few years ago, and by 2026 that gap will only widen. 

Internal marketing teams are more sophisticated, digital channels are more specialized, and the role agencies play is no longer one-size-fits-all. 

As a result, the companies that get the most value from agency relationships aren’t always the biggest spenders. 

They’re the ones that are clear about what they need and what they don’t.

That clarity starts with understanding the true role an agency should play inside your organization. 

Too many partnerships struggle because expectations and responsibilities were never properly aligned from the start. 

When that foundation is off, even strong execution can fall flat.

After working with thousands of businesses across various industries and growth stages, we consistently observe that agency success falls into two distinct partnership models, primarily shaped by company size and internal marketing maturity.

Model 1: Execution-first partnerships (large companies)

If your company generates more than $50 million in annual online revenue, you likely already have a strong internal marketing team. 

Strategy, goal-setting, and planning live in-house. What you need from an agency is deep platform expertise and consistent, high-level execution.

At this stage, agencies function as specialist operators that:

  • Activate the roadmap your team has already defined.
  • Optimize performance inside specific channels.
  • Bring advanced technical knowledge that would be inefficient to replicate internally.

When something underperforms, a strong agency partner doesn’t rush to tactics. 

They help determine whether the issue lies in execution, shifting market conditions, or a broader strategic blind spot – and they bring the data needed to support course correction.

Model 2: Integrated growth partners (small to mid-size companies)

For companies under $50 million in annual online revenue, the agency relationship is different. 

Internal teams are often lean, stretched, or still developing core digital expertise. 

In these cases, agencies don’t just execute – they help shape the entire growth strategy.

Here, the right agency partner becomes an extension of the marketing department that can:

  • Guide platform selection.
  • Develop cross-channel strategies.
  • Execute campaigns.
  • Provide direction on tools, tracking, and infrastructure. 

The relationship is more integrated because it has to be.

For many growing businesses, agencies offer access to senior-level expertise at a fraction of the cost of building a full in-house team. 

That tradeoff often creates the best possible balance between speed, strategy, and financial reality.

Dig deeper: How to hire an SEO agency: The definitive guide

Finding the right agency partner

Most companies approach agency selection the wrong way. 

Here’s how to improve your odds of finding a partner that actually fits your needs.

Ditch the RFPs

Many large companies use the request for proposal (RFP) process to solicit potential partners. 

However, RFPs often favor vendors that excel at paperwork over those that prioritize performance. 

From an agency perspective, if you don’t already know you’ve won an RFP, you’re not going to win it. 

They act more as rubber stamps for a decision that has already been made.

Large companies should instead leverage their connections. 

If you’re running a large internal marketing department, you probably already know dozens of professionals who could provide referrals. 

Use that network to find firms doing great work, then reach out to them directly. 

Smaller businesses should talk to their peers about trusted marketing vendors and then check reviews to validate those recommendations.

No agency is perfect, and every agency will have some dissatisfied clients. 

But if you see patterns of negative reviews emerge, you should stay away.    

Request an audit

Once you’ve identified a few potential partners, ask them to audit your current marketing setup. 

In most cases, digital marketing agencies conduct these audits for free. 

Keep in mind that during an audit, many agencies will point out what you’re doing wrong. 

But the goal is to receive honest, constructive feedback that offers insight into what’s working and what’s possible.

The audit process will look different depending on the company’s size. 

  • For larger companies, agencies should only audit the platforms they’ll be working on. 
  • Smaller companies need a broader audit across the entire marketing funnel. 

These agencies won’t be working in a vacuum. 

Every element of marketing is interrelated, so they’ll need to know who manages each stage of the funnel and whether they’re doing a good job.  

Companies of all sizes should collect audits from multiple sources. 

This enables you to compare recommendations and understand if the partnership will be a good fit. 

Large companies need partners that can integrate with their internal processes. 

Smaller companies need to pick vendors with people they actually want to work with. 

Both considerations are critical in ensuring long-term success.

Setting achievable goals

Once you’ve selected the right agency partner, it’s time to define your goals. 

It’s an unfortunate reality that most business leaders set marketing goals that don’t align with their business goals, which puts agency partners in an untenable position before the relationship even gets off the ground. 

Good agencies should challenge your goals before you even sign a contract. They should push you to dream bigger or rein you in if your expectations are unrealistic. 

If a potential client in the beauty space says they want a tenfold return on ad spend (ROAS) while jumping their non-brand spend from $20,000 to $100,000, a good agency should know enough to push back. 

Your potential partner should understand the economics of your business and help ensure your marketing goals align with your business goals. 

Often they don’t, which is where good agencies add immediate value.

Dig deeper: How to find your next PPC agency: 12 top tips

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Maintaining a productive partnership

Once the work begins, you need to keep your agency accountable. Here’s how.

Contract length

Larger companies typically sign 12-month contracts with their agency vendors. 

They value stability and performance, and longer contract terms provide agencies with the time needed to establish themselves within the marketing operation. 

Smaller companies can’t afford to bind themselves to an underperforming agency for an entire calendar year. 

If you’re hiring an agency partner at a smaller company, opt instead for a three-month agreement that automatically renews to month-to-month. 

Challenge and conflict are healthy

The most productive business-agency partnership often involves some conflict from time to time. 

Great partners will challenge your thinking regularly, which can sometimes create discomfort. 

But if everything is always smooth sailing, you probably aren’t growing or improving. 

The goal instead is to have productive conversations that involve healthy disagreement and constant refinement.  

Ongoing accountability

If you’re overseeing a brand-agency partnership, you should establish regular reviews that compare progress to the opportunities identified in the agency’s initial audit. 

For smaller companies, quarterly reviews make sense. They align with the contract structure and allow you to recalibrate budget allocation.

Larger companies might review monthly or quarterly, depending on spend and complexity. 

However, context here matters. You need to understand if your industry is growing or shrinking to judge your agency’s work. 

For example, if your industry is down 10% year-over-year and your sales are flat, you’re outperforming your competitors. 

Often, the agency or brand can obtain this information from their representatives on platforms such as Google, Microsoft, Amazon, or Meta.

Innovation and testing

Great agency partners will proactively bring new growth ideas to the table, which is particularly valuable for smaller businesses.

Large companies also benefit from outside ideas and should establish dedicated budgets for testing.

After all, if your agency isn’t investing at least a small portion of the budget into new, untested ideas, brands will find themselves falling behind competitors that are.

Innovation isn’t just about testing what works today. It’s about understanding what’s coming next.

Great agency partners should help you see what’s coming 6-12 months out, and prepare your marketing to meet those new conditions. 

Businesses need an agency’s expertise, which becomes insight over the longer term.

Without it, they’ll be flying blind.    

Dig deeper: How to onboard an SEO agency the right way

When to make an agency change

Not every brand-agency partnership succeeds, even with the best intentions. 

If your gut is telling you something isn’t working or that something could be working better, here are a few red flags that might indicate it’s time to make a change.

Your business isn’t growing 

Your marketing efforts should revolve around finding new-to-brand customers. Full stop. 

If your business isn’t growing and your industry is stable or growing, that’s a big red flag that marketing isn’t working. 

Once an agency stops being a partner in growth, it’s time to make a change. 

Your agency isn’t pushing innovation

The marketing ecosystem is constantly changing:

  • Customer needs evolve.
  • Platforms update features.
  • New tools emerge that upend old processes. 

If your agency isn’t bringing new ideas or exploring new ways to reach customers, your marketing is stagnating. 

In these instances, an outside audit can reveal deficiencies and potential opportunities.  

Your agency can’t explain performance

If your agency can’t contextualize your performance – good or bad – within the broader marketing ecosystem, it’s a strong indication they don’t understand your sales funnel.

Channel experts should know how their performance is affected by upper-funnel activities and how those activities affect bottom-funnel activities. 

Marketing agencies for smaller businesses should know enough about the entire marketing operation and understand how performance in one area impacts another. 

Dig deeper: Avoiding cookie-cutter SEO: 8 red flags to watch out for

The marketing reality check

The best marketing in the world won’t help a bad business grow. 

A good company, combined with good leadership and a good agency, is the secret sauce of successful growth. 

If one of those elements is missing, marketing will never accomplish what you hope it will. 

Getting great results within a brand-agency partnership isn’t about huge marketing budgets or fancy advertising awards. 

Instead, it’s about understanding what role your agency should play, and choosing a partner equipped to fill it. 

When your needs align with an agency’s specific capabilities, that’s where the real growth happens. 

Choosing an agency partner isn’t a one-time decision. 

It’s an ongoing process that includes accountability, perpetual refinement, and, sometimes, healthy disagreement. 

While this process certainly isn’t easy, it’s worth getting right.  

Read more at Read More

AI search is growing, but SEO fundamentals still drive most traffic

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AI search is growing, but SEO fundamentals still drive most traffic

Generative AI is everywhere right now. It dominates conference agendas, fills LinkedIn feeds, and is reshaping how many businesses think about organic search. 

Brands are racing to optimize for AI Overviews, build vector embeddings, map semantic clusters, and rework content models around LLMs.

What gets far less attention is a basic reality: for most websites, AI platforms still drive a small share of overall traffic. 

AI search is growing, no question. 

But in most cases, total referral sessions from all LLM platforms combined amount to only about 2% to 3% of the organic traffic Google alone delivers.

AI referral sessions vs Google organic clicks

Despite that gap, many teams are spending more time chasing AI strategies than fixing simple, high-impact SEO fundamentals that continue to drive measurable results. 

Instead of improving what matters most today, they are overinvesting in the future while underperforming in the present.

This article examines how a narrow focus on AI can obscure proven SEO tactics and highlights practical examples and real-world data showing how those fundamentals still move the needle today.

1. Quick SEO wins are still delivering outsized gains

In an era where everyone is obsessed with things like vector embeddings and semantic relationships, it’s easy to forget that small updates can have a big impact. 

For example, title tags are still one of the simplest and most effective SEO levers to pull. 

And they are often one of the on-page elements that most websites get wrong, either by targeting the wrong keywords, not including variations, or targeting nothing at all.

Just a few weeks ago, a client saw a win by simply adding “& [keyword]” to the existing title tag on their homepage. Nothing else was changed.

Keyword rankings shot up, as did clicks and impressions for queries containing that keyword.

Results - Updating existing title tags
Results - Updating existing title tags Oct-Nov 2025

This was all achieved simply by changing the title tag on one page. 

Couple that with other tactics, such as on-page copy edits, internal linking, and backlinking across multiple pages, and growth will continue. 

It may seem basic, but it still works. 

And if you only focus on advanced GEO strategies, you may overlook simple tactics that provide immediate, observable impact. 

2. Content freshness and authority still matter for competitive keywords

Another tactic that has faded from view with the rise of AI is what’s often called the skyscraper technique. 

It involves identifying a set of keywords and the pages that already rank for them, then publishing a materially stronger version designed to outperform the existing results.

It’s true that the web is saturated with content on similar topics, especially for keywords visible in most research tools.

But when a site has sufficient authority, a clear right to win, and content freshness, this approach can still be highly effective.

I’ve seen this work repeatedly. 

Here’s Google Search Console data from a recent article we published for a client on a popular, long-standing topic with many competing pages already ranking. 

The post climbed to No. 2 almost immediately and began generating net-new clicks and impressions.

Results - Skyscraper content

Why did it work? 

The site has strong authority, and much of the content ranking ahead of it was outdated and stale.

If you’re hesitant to publish the thousandth article on an established topic, that hesitation is understandable. 

This approach won’t work for every site. But ignoring it entirely can mean passing up clear, high-confidence wins like these.

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3. User experience remains a critical conversion lever

Hype around AI-driven shopping experiences has led some teams to believe traditional website optimization is becoming obsolete. 

There is a growing assumption that AI assistants will soon handle most interactions or that users will convert directly within AI platforms without ever reaching a website.

Some of that future is beginning to take shape, particularly for ecommerce brands experimenting with features like Instant Checkout in ChatGPT. 

But many websites are not selling products. 

And even for those that are, most brands still receive a significant volume of traffic from traditional search and continue to rely on calls to action and on-page signals to drive conversions.

It also makes little difference how a user arrives – via organic search, paid search, AI referrals, or direct visits. 

A fast site, a strong user experience, and a clear conversion funnel remain essential.

There are also clear performance gains tied to optimizing these elements. 

Here are the results we recently achieved for a client following a simple CTR test:

Results - CTR test

Brands that continue to invest in user experience and conversion rate optimization will outperform those that do not. 

That gap is likely to widen the longer teams wait for AI to fully replace the conversion funnel.

AI is reshaping search, but what works still matters

There is no dispute that AI is reshaping the search landscape. 

It’s changing user behavior, influencing SERPs, and complicating attribution models. 

The bigger risk for many businesses, however, is not underestimating AI but overcorrecting for it.

Traditional organic search remains the primary traffic source for most websites, and SEO fundamentals still deliver when executed well. 

  • Quick wins are real. 
  • Higher-quality content continues to be rewarded. 
  • User experience optimization shows no signs of becoming irrelevant. 

These are just a few examples of tactics that remain effective today.

Importantly, these efforts do not operate in isolation. 

Improving a website’s fundamentals can strengthen organic visibility while also supporting paid search performance and LLM visibility.

Staying informed about AI developments and planning for what’s ahead is essential. 

It should not come at the expense of the strategies that are currently driving measurable growth.

Read more at Read More

Google expands Performance Max channel reporting to MCCs

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Google’s token auction: When LLMs write the ads in real time

Google appears to be rolling out the Performance Max Channel Performance report at the MCC level, giving agencies and large advertisers a long-awaited view of channel-level performance across multiple accounts.

What’s new: The Channel Performance report, previously limited to individual accounts, is now surfacing in some manager (MCC) accounts. Google had previously confirmed the feature was coming, but this marks one of the first confirmed sightings in live environments.

Why we care. MCC-level visibility allows agencies to analyze how Performance Max allocates spend and drives results across channels—Search, Display, YouTube, Discover, Gmail, and Shopping—without logging into each account individually. That’s a major efficiency gain for teams managing large portfolios.

What to watch. When and how quickly the feature becomes available across all MCCs, and whether Google expands the report with deeper metrics or export options.

First seen. This update was first picked up by head of Ecommerce Insights at Smarter Ecommerce, Mike Ryan, who very recently published a guide on How to use Google’s Channel Performance reports.

Bottom line. MCC-level Channel Performance reporting signals another step toward making Performance Max less of a black box—especially for agencies that need cross-account insight at scale.

Read more at Read More

Why Google is deleting reviews at record levels

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Why Google is deleting reviews at record levels

In 2025, Google is removing reviews at unprecedented rates – and it is not accidental.

Our industry analysis of 60,000 Google Business Profiles shows that deletions are being driven by a mix of:

  • Automated moderation.
  • Industry-wide risk factors.
  • Increased enforcement against incentivized reviews.
  • Local regulatory pressure.

Together, these forces have significant implications for businesses and local search visibility.

Review deletions are on the up globally

Weekly deleted reviews - Jan to Jul 2025

Data collected from tens of thousands of Google Business Profile listings across multiple countries by GMBapi.com show a sharp increase in deleted reviews between January and July 2025. 

The surge began accelerating toward the end of Q1 and gained momentum mid-year, with a growing share of monitored locations experiencing at least one review removal in a given week.

This is not limited to negative feedback. 

While one-star reviews continue to be taken down, five-star reviews now account for a sizable share of deletions. 

That pattern suggests Google is applying stricter enforcement, including on positive reviews, as it works to maintain authenticity and trust. 

More recently, Google has begun asking members of its Local Guide community whether businesses are incentivizing reviews, likely in response to AI-driven flags for suspicious activity.

Dig deeper: Google’s review deletions: Why 5-star reviews are disappearing

Not all industries are treated the same

Review deletion patterns vary significantly by business category.

Restaurants account for the highest volume of deleted reviews, followed by home services, brick-and-mortar retail, and construction. 

These categories generate large volumes of reviews, and removals occur across both recent and older submissions. 

That distribution points to ongoing enforcement, not isolated cleanup efforts.

By contrast, medical services, beauty, and professional services see fewer deletions overall. 

However, closer analysis reveals distinct and consistent patterns within those categories.

What review ratings reveal about industry bias

Top 10 meta categories- Deleted review rating mix

Looking at deleted reviews as a share of total removals within each category reveals distinct moderation patterns.

In restaurants and general retail, deleted reviews are relatively evenly distributed across one- to five-star ratings. 

By contrast, medical services and home services show a strong skew toward five-star review deletions, with far fewer removals in the middle of the rating spectrum. 

That imbalance suggests positive reviews in higher-risk or regulated categories face closer scrutiny, likely tied to concerns around trust, safety, and compliance.

These differences do not appear to stem from manual, category-specific policy decisions. 

Instead, they reflect how Google’s automated systems adjust enforcement based on perceived industry risk.

Dig deeper: 7 local SEO wins you get from keyword-rich Google reviews

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Timing matters: Early vs. retroactive deletions

The age of a review plays a significant role in when it is removed.

In medical and home services, a large share of deleted reviews disappear within the first six months after posting. 

That timing points to early intervention by automated systems evaluating language, reviewer behavior, and other risk signals.

Restaurants and brick-and-mortar retail show a different pattern. 

Many deleted reviews in these categories are more than two years old, suggesting retroactive enforcement as detection systems improve or new suspicious patterns emerge. 

It may also reflect efforts to refresh older review profiles.

For businesses, this means reviews can disappear long after they are posted, often without warning.

Geography adds further complexity

Industry alone does not tell the full story. Location matters.

Top 10 meta categories by deleted reviews (stacked by rating)

In English-speaking markets such as the U.S., UK, Canada, and Australia, deleted reviews skew heavily toward five-star ratings. 

That trend aligns with increased AI-driven moderation aimed at reducing review spam and incentivized positive feedback.

Germany stands apart. 

Analysis of thousands of German business listings shows a higher share of deleted reviews are low-rated, and most are removed within weeks of posting. 

This pattern aligns with Germany’s strict defamation laws, which permit businesses to legally challenge negative reviews and require platforms to take prompt action upon notification.

In short:

  • AI-driven enforcement dominates in many English-speaking markets.
  • Legal takedowns play a much larger role in Germany.

What this means for local SEO and small business owners

The rise in review deletions creates two primary challenges.

  • Trust erosion: When legitimate reviews, whether positive or negative, disappear without explanation, confidence in review platforms begins to weaken.
  • Data distortion: Deleted reviews affect star ratings, performance benchmarks, and conversion signals that businesses rely on for local SEO and reputation management.

For SEO practitioners, small businesses, and multi-location brands, review monitoring is no longer optional. 

Understanding when, where, and which reviews are removed is now as important as generating them.

Dig deeper: Why Google reviews will power up your local SEO

The forces reshaping review visibility

Three developments are shaping review visibility:

  • More automated moderation, with AI evaluating reviews in real time and retroactively.
  • Greater legal influence in regions with strict defamation laws.
  • Increased reliance on third-party monitoring tools as businesses seek independent records of review deletion activity.

As moderation becomes more automated and more influenced by local law, sentiment alone will not guarantee review visibility. 

In local SEO, reviews – especially recent ones with detailed context – remain a critical authority signal for both users and search engines.

Staying ahead now means not only collecting new reviews, but also closely tracking and understanding removals. 

Reputation management increasingly requires attention on both fronts.

Read more at Read More

Image SEO for multimodal AI

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Decoding the machine gaze- Image SEO for multimodal AI

For the past decade, image SEO was largely a matter of technical hygiene:

  • Compressing JPEGs to appease impatient visitors.
  • Writing alt text for accessibility.
  • Implementing lazy loading to keep LCP scores in the green. 

While these practices remain foundational to a healthy site, the rise of large, multimodal models such as ChatGPT and Gemini has introduced new possibilities and challenges.

Multimodal search embeds content types into a shared vector space. 

We are now optimizing for the “machine gaze.” 

Generative search makes most content machine-readable by segmenting media into chunks and extracting text from visuals through optical character recognition (OCR). 

Images must be legible to the machine eye. 

If an AI cannot parse the text on product packaging due to low contrast or hallucinates details because of poor resolution, that is a serious problem.

This article deconstructs the machine gaze, shifting the focus from loading speed to machine readability.

Technical hygiene still matters

Before optimizing for machine comprehension, we must respect the gatekeeper: performance. 

Images are a double-edged sword. 

They drive engagement but are often the primary cause of layout instability and slow speeds. 

The standard for “good enough” has moved beyond WebP. 

Once the asset loads, the real work begins.

Dig deeper: How multimodal discovery is redefining SEO in the AI era

Designing for the machine eye: Pixel-level readability

To large language models (LLMs), images, audio, and video are sources of structured data. 

They use a process called visual tokenization to break an image into a grid of patches, or visual tokens, converting raw pixels into a sequence of vectors.

This unified modeling allows AI to process “a picture of a [image token] on a table” as a single coherent sentence.

These systems rely on OCR to extract text directly from visuals. 

This is where quality becomes a ranking factor.

If an image is heavily compressed with lossy artifacts, the resulting visual tokens become noisy.

Poor resolution can cause the model to misinterpret those tokens, leading to hallucinations in which the AI confidently describes objects or text that do not actually exist because the “visual words” were unclear.

Reframing alt text as grounding

For large language models, alt text serves a new function: grounding. 

It acts as a semantic signpost that forces the model to resolve ambiguous visual tokens, helping confirm its interpretation of an image.

As Zhang, Zhu, and Tambe noted:

  • “By inserting text tokens near relevant visual patches, we create semantic signposts that reveal true content-based cross-modal attention scores, guiding the model.” 

Tip: By describing the physical aspects of the image – the lighting, the layout, and the text on the object – you provide the high-quality training data that helps the machine eye correlate visual tokens with text tokens.

The OCR failure points audit

Search agents like Google Lens and Gemini use OCR to read ingredients, instructions, and features directly from images. 

They can then answer complex user queries. 

As a result, image SEO now extends to physical packaging.

Current labeling regulations – FDA 21 CFR 101.2 and EU 1169/2011 – allow type sizes as small as 4.5 pt to 6 pt, or 0.9 mm, on compact packaging. 

  • “In case of packaging or containers the largest surface of which has an area of less than 80 cm², the x-height of the font size referred to in paragraph 2 shall be equal to or greater than 0.9 mm.” 

While this satisfies the human eye, it fails the machine gaze. 

The minimum pixel resolution required for OCR-readable text is far higher. 

Character height should be at least 30 pixels. 

Low contrast is also an issue. Contrast should reach 40 grayscale values. 

Be wary of stylized fonts, which can cause OCR systems to mistake a lowercase “l” for a “1” or a “b” for an “8.”

Beyond contrast, reflective finishes create additional problems. 

Glossy packaging reflects light, producing glare that obscures text. 

Packaging should be treated as a machine-readability feature.

If an AI cannot parse a packaging photo because of glare or a script font, it may hallucinate information or, worse, omit the product entirely.

Originality as a proxy for experience and effort

Originality can feel like a subjective creative trait, but it can be quantified as a measurable data point.

Original images act as a canonical signal. 

The Google Cloud Vision API includes a feature called WebDetection, which returns lists of fullMatchingImages – exact duplicates found across the web – and pagesWithMatchingImages. 

If your URL has the earliest index date for a unique set of visual tokens (i.e., a specific product angle), Google credits your page as the origin of that visual information, boosting its “experience” score.

Dig deeper: Visual content and SEO: How to use images and videos

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The co-occurrence audit

AI identifies every object in an image and uses their relationships to infer attributes about a brand, price point, and target audience. 

This makes product adjacency a ranking signal. To evaluate it, you need to audit your visual entities.

You can test this using tools such as the Google Vision API. 

For a systematic audit of an entire media library, you need to pull the raw JSON using the OBJECT_LOCALIZATION feature. 

The API returns object labels such as “watch,” “plastic bag” and “disposable cup.”

Google provides this example, where the API returns the following information for the objects in the image:

Name mid Score Bounds
Bicycle wheel /m/01bqk0 0.89648587 (0.32076266, 0.78941387), (0.43812272, 0.78941387), (0.43812272, 0.97331065), (0.32076266, 0.97331065)
Bicycle /m/0199g 0.886761 (0.312, 0.6616471), (0.638353, 0.6616471), (0.638353, 0.9705882), (0.312, 0.9705882)
Bicycle wheel /m/01bqk0 0.6345275 (0.5125398, 0.760708), (0.6256646, 0.760708), (0.6256646, 0.94601655), (0.5125398, 0.94601655)

Good to know: mid contains a machine-generated identifier (MID) corresponding to a label’s Google Knowledge Graph entry. 

The API does not know whether this context is good or bad. 

You do, so check whether the visual neighbors are telling the same story as your price tag.

Lord Leathercraft blue leather watch band

By photographing a blue leather watch next to a vintage brass compass and a warm wood-grain surface, Lord Leathercraft engineers a specific semantic signal: heritage exploration. 

The co-occurrence of analog mechanics, aged metal, and tactile suede infers a persona of timeless adventure and old-world sophistication.

Photograph that same watch next to a neon energy drink and a plastic digital stopwatch, and the narrative shifts through dissonance. 

The visual context now signals mass-market utility, diluting the entity’s perceived value.

Dig deeper: How to make products machine-readable for multimodal AI search

Quantifying emotional resonance

Beyond objects, these models are increasingly adept at reading sentiment. 

APIs, such as Google Cloud Vision, can quantify emotional attributes by assigning confidence scores to emotions like “joy,” “sorrow,” and “surprise” detected in human faces. 

This creates a new optimization vector: emotional alignment. 

If you are selling fun summer outfits, but the models appear moody or neutral – a common trope in high-fashion photography – the AI may de-prioritize the image for that query because the visual sentiment conflicts with search intent.

For a quick spot check without writing code, use Google Cloud Vision’s live drag-and-drop demo to review the four primary emotions: joy, sorrow, anger, and surprise. 

For positive intents, such as “happy family dinner,” you want the joy attribute to register as VERY_LIKELY. 

If it reads POSSIBLE or UNLIKELY, the signal is too weak for the machine to confidently index the image as happy.

For a more rigorous audit:

  • Run a batch of images through the API. 
  • Look specifically at the faceAnnotations object in the JSON response by sending a FACE_DETECTION feature request. 
  • Review the likelihood fields. 

The API returns these values as enums or fixed categories. 

This example comes directly from the official documentation:

          "rollAngle": 1.5912293,
          "panAngle": -22.01964,
          "tiltAngle": -1.4997566,
          "detectionConfidence": 0.9310801,
          "landmarkingConfidence": 0.5775582,
          "joyLikelihood": "VERY_LIKELY",
          "sorrowLikelihood": "VERY_UNLIKELY",
          "angerLikelihood": "VERY_UNLIKELY",
          "surpriseLikelihood": "VERY_UNLIKELY",
          "underExposedLikelihood": "VERY_UNLIKELY",
          "blurredLikelihood": "VERY_UNLIKELY",
          "headwearLikelihood": "POSSIBLE"

The API grades emotion on a fixed scale. 

The goal is to move primary images from POSSIBLE to LIKELY or VERY_LIKELY for the target emotion.

  • UNKNOWN (data gap).
  • VERY_UNLIKELY (strong negative signal).
  • UNLIKELY.
  • POSSIBLE (neutral or ambiguous).
  • LIKELY.
  • VERY_LIKELY (strong positive signal – target this).

Use these benchmarks

You cannot optimize for emotional resonance if the machine can barely see the human. 

If detectionConfidence is below 0.60, the AI is struggling to identify a face. 

As a result, any emotion readings tied to that face are statistically unreliable noise.

  • 0.90+ (Ideal): High-definition, front-facing, well-lit. The AI is certain. Trust the sentiment score.
  • 0.70-0.89 (Acceptable): Good enough for background faces or secondary lifestyle shots.
  • < 0.60 (Failure): The face is likely too small, blurry, side-profile, or blocked by shadows or sunglasses. 

While Google documentation does not provide this guidance, and Microsoft offers limited access to its Azure AI Face service, Amazon Rekognition documentation notes that: 

  • “[A] lower threshold (e.g., 80%) might suffice for identifying family members in photos.”

Closing the semantic gap between pixels and meaning

Treat visual assets with the same editorial rigor and strategic intent as primary content. 

The semantic gap between image and text is disappearing. 

Images are processed as part of the language sequence.

The quality, clarity, and semantic accuracy of the pixels themselves now matter as much as the keywords on the page.

Read more at Read More

How to build search visibility before demand exists

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How to build search visibility before demand exists

Discovery now happens before search demand is visible in Google.

In 2026, interest forms across social feeds, communities, and AI-generated answers – long before it shows up as keyword search volume. 

By the time demand appears in SEO tools, the opportunity to shape how a concept is understood has already passed.

This creates a problem for how search marketing research is typically done. 

Keyword tools, search volume, and Google Trends are lagging indicators. 

They reveal what people cared about yesterday, not what they are starting to explore now. 

In a landscape shaped by AI Overviews, social SERPs, and shrinking organic real estate, arriving late means competing inside narratives already defined by someone else.

Exploding Topics sits upstream of this shift. 

It helps surface emerging themes, behaviors, and conversations while they are still forming – before they harden into keywords, content clusters, and product categories. 

Used properly, it is not just a trend tool. It is a way to plan SEO, content, digital PR, and social-led search proactively.

This article breaks down how to use Exploding Topics to identify future entities, validate them through social search, and build search visibility before demand peaks.

Use Exploding Topics Trend Analytics to identify future entities – not just topics

Most marketers who use Exploding Topics already understand its value for content ideation, and we will cover that. 

But its bigger opportunity is identifying future entities – concepts that search engines and AI systems will soon recognize as distinct “things,” not just keyword variations.

This matters because modern search no longer operates purely on keywords. 

Google’s AI Overviews, ChatGPT, and other LLM-powered systems organize information around entities and relationships. 

Once an entity is established, the narrative around it hardens. 

Arrive late, and you are competing inside a story that has already been defined. 

Exploding Topics gives you visibility early enough to act before that happens.

Example: Weighted sleep masks

In Exploding Topics, you might notice “weighted sleep mask” rising steadily. 

Search volume remains low, and most keyword tools understate its importance. 

At a glance, it looks like a niche product trend that is easy to ignore.

Look closer, and the signals are stronger:

  • The phrase is consistent and repeatable.
  • Adjacent topics are rising alongside it, including deep pressure sleep, anxiety sleep tools, and vagus nerve stimulation.
  • Questions that signal intent are increasing.
  • Early discussion focuses on understanding the concept, not just buying a product.

This is the point where something shifts from being a product with an adjective to a named solution. In other words, it is becoming an entity.

The traditional play

Most brands wait until:

  • Search demand becomes obvious, acting in December 2025 rather than July 2025.
  • Competitors launch dedicated product pages.
  • Affiliates and publishers surface “best” and “vs.” content.

Only then do they create:

  • A category page.
  • A “What is a weighted sleep mask?” article or social-search activation.
  • SEO content designed to chase presence, such as FAQs, SERP features, and rankings.

By this point, the entity already exists, and the story around it has largely been written by someone else. 

In this case, NodPod is clearly dominating the entity.

Acting earlier, while the entity is forming

Using Exploding Topics well means acting earlier, while the entity is still being defined. Instead of starting with a product page, you:

  • Publish a clear, authoritative explanation of what a weighted sleep mask is.
  • Explain why deep pressure can help with sleep and anxiety.
  • Address who it is for – and who it is not.
  • Create supporting content that adds context, such as comparisons with weighted blankets or safety considerations.

This work can be done quickly and at scale through reactive PR and social search activations. 

You are not optimizing for keywords yet. 

You are teaching social algorithms, search engines, and AI systems what the concept means and associating your brand with that explanation from the start.

This is how brands can win at search in 2026 and beyond. 

This early, proactive approach:

  • Helps search systems understand new concepts faster.
  • Increases the chance your framing is reused in AI-generated answers.
  • Positions your brand as the authority on the entity – not just a seller within the conversation.

Dig deeper: Beyond Google: How to put a total search strategy together

Validate emerging entities through social search

Identifying an emerging entity is only the first step. 

The real risk is not being early to a conversation. It is being early to something that never takes off.

This is where many SEO teams stall. 

They wait for search volume and arrive too late, publish on instinct and hope demand follows, or freeze under uncertainty and do nothing.

There is a better middle ground: validate emerging entities through social search research and activation tests before scaling them into owned SEO and on-site experiences.

Exploding Topics is straightforward. It shows what might matter. Social platforms tell you whether your audience actually cares.

How social search becomes your validation layer

Once Exploding Topics surfaces a potential emerging entity, the next step is not Keyword Planner. 

It is native search across platforms such as TikTok, Reddit, and YouTube, using either built-in trend tools or basic platform search.

You are looking for signals like:

  • Multiple creators independently explaining the same concept.
  • Comment sections filled with questions such as “Does this actually work?” or “Is this safe?”.
  • Repeated framing, metaphors, or demonstrations.
  • Early how-to or comparison content, even if production quality is low.

These signals point to intent. 

Curiosity is turning into understanding. 

Historically, this phase has always preceded measurable search demand.

Revisiting the weighted sleep mask example

After spotting “weighted sleep mask” in Exploding Topics, you might search for it on TikTok.

What you want to see is a lack of heavy brand advertising. 

Mature ecommerce pushes or TikTok Shop funnels suggest the market is already established. 

Instead, look for creators – not brand channels – testing products, discussing solutions, and exploring the underlying problem.

  • Focus on videos that explain pains, needs, and motivations, such as why pressure may help with anxiety. 
  • Check the comments for comparisons to other solutions. 
  • Look for questions raised in videos and comment threads.

Tools like Buzzabout.AI can help do this at scale through topic analysis and AI-assisted research.

These signals answer two critical questions:

  • Are people actively trying to understand this concept?
  • What language, framing, and objections are forming before SEO data exists?

That is validation.

Rethinking how SEO strategy gets built

This is where search strategy shifts. 

Instead of asking, “Is there enough volume to justify content creation?” the better question is, “Is there enough curiosity to justify building authority early?”

If social signals are weak:

  • Pause.
  • De-risk by testing with creators outside your owned channels.
  • Avoid heavy investment in content that takes months to rank.

If signals are strong:

  • Scale with confidence.
  • Work with creators and activate brand channels.
  • Invest in entity pages, hubs, FAQs, comparisons, and PLP optimization.

In this model, fast-moving social platforms become the testing layer.

SEO is not the experiment, it’is the compounding layer.

Dig deeper: Social and UGC: The trust engines powering search everywhere

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Editorial digital PR that earns links and LLM citations

Most digital PR still works backward.

  • A trend reaches mainstream awareness.
  • Journalists write about it.
  • Brands scramble to comment.
  • PR teams try to extract links from a story that already exists. 

The result is short-term coverage, diluted impact, and little lasting search advantage.

Exploding Topics makes it possible to reverse that dynamic by surfacing editorial narratives before they are obvious and positioning your brand as one of the sources that helps define them.

In 2026, this matters more than ever. 

Links still matter, but they are no longer the only outcome that counts. 

Brand mentions, explanations, and citations increasingly feed the systems behind AI Overviews, ChatGPT, Perplexity, and other LLM-driven discovery experiences.

Why early narratives outperform reactive PR

When a topic is everywhere, journalists are aggregating. When a topic is emerging, they are still asking questions.

Exploding Topics surfaces concepts at the stage where:

  • There is no consensus narrative.
  • Definitions are inconsistent.
  • Journalists are looking for clarity, not quotes.
  • “What is this?” stories have not yet been written.

This is the point where brands can move from commenting on a conversation to shaping it.

From trend-jacker to narrative owner

Instead of pitching “our brand’s take on X,” you lead with early signals you are seeing, why a concept is emerging now, and what it suggests about consumer behavior or the market.

The difference is subtle but important.

You are no longer reacting to coverage that already exists. 

You are creating the framing that journalists, publishers, and, eventually, AI systems reuse. 

LLMs do not learn from rankings alone. 

They learn from editorial context, repeated explanations, and how trusted publications describe and define emerging concepts over time.

Done consistently, this approach compounds. 

As your brand becomes associated with spotting and explaining emerging narratives early, you move from reactive commentary to trusted source. 

Journalists begin to recognize where useful insight comes from, and that trust carries into more established coverage later on. You are no longer pitching for inclusion. 

Your perspective is actively sought out.

The result is early narrative ownership and stronger access when mainstream coverage follows.

An editorial window before mainstream coverage

Before “weighted sleep mask” became a crowded ecommerce term in early 2025, there was a clear editorial window.

Journalists had not yet published stories asking:

  • “What is a weighted sleep mask?”
  • “Are weighted sleep masks safe?”
  • “Do they actually work for anxiety?” 

That was the opportunity.

A PR-led approach at this stage includes:

  • Supplying journalists with expert explanations of deep pressure and sleep.
  • Sharing early insight into why the product category is emerging.
  • Contextualizing it alongside weighted blankets and other anxiety tools.

The result is not just coverage. It connects PR to search, curiosity, and discovery by helping define the concept itself. 

That earns links, builds brand mentions, and signals authority around emerging entities that LLMs are more likely to cite and summarize over time.

Dig deeper: Why PR is becoming more essential for AI search visibility

Content roadmaps and briefs that don’t rely on search volume

Search volume is a poor starting point for content briefing.

It reflects interest only after a topic is established, language has stabilized, and the SERP is already crowded. 

Used as a primary input, it pushes teams to chase demand instead of building authority. 

That is why so many brands end up rewriting the same “What is X?” post year after year.

Better briefs start upstream. 

They use Exploding Topics to spot what is forming and social search to understand how people are trying to make sense of it.

Reframing the briefing process

The core shift is moving away from briefs built around keywords and volumes and toward briefs built around audience intent.

That means focusing on three things:

  • Problems people are beginning to articulate.
  • Concepts that are not yet clearly defined or are actively debated.
  • Language that is inconsistent, emotional, or exploratory.

When content is approached this way, the objective changes. 

It is no longer “create X to rank for Y.” 

It becomes “explain X so the audience does not experience Y.” 

That shift matters.

Designing content that compounds instead of expiring

The goal for SEO content teams in 2026 and beyond should be to brief content that defines a concept clearly. That includes:

  • Connecting it to adjacent ideas.
  • Comparing it to established solutions.
  • Answering questions within conversations that are still forming.

This does not always require written content. 

The same work can happen through social search activations or digital PR.

Approached this way, content grows into demand rather than chasing it.

Instead of being rewritten every time search volume changes, it evolves through updates, expansion, and, where possible, stronger internal linking. 

As interest grows, the content does not need replacing. It needs refining. 

This is the type of material AI and LLMs tend to reference – timely, clear, explanatory, and grounded in real questions.

Publication isn’t the end

Publishing and waiting for content to rank is no longer the end of the brief.

Teams need a clear plan for distribution and reuse.

For emerging topics, that means contributing insight in relevant Reddit threads, Discord communities, niche forums, and creator comment sections. 

Not to drop links, but to answer questions, share explanations, and test framing in public. 

Those conversations feed back into the content itself, improving clarity and increasing the likelihood that your explanation is the one others repeat.

With a social search activation approach, brands can scale messaging quickly by working with partners who interpret and distribute the brief in their own voice. 

When this works, SEO content stops being static and starts acting like a living reference point – one that contributes to culture and builds lasting brand recognition.

Dig deeper: Beyond SERP visibility: 7 success criteria for organic search in 2026

Where this leaves SEO in 2026

Search demand does not appear fully formed. 

It develops across social platforms, communities, and AI-driven discovery long before it registers as keyword volume.

  • Exploding Topics helps surface what is emerging. 
  • Social search shows whether people are trying to understand it. 
  • Digital PR shapes how those ideas are defined and cited. 
  • SEO compounds that work by reinforcing narratives that are already taking shape, rather than trying to test or invent them after the fact.

In this model, SEO is the layer that turns early insight and clear explanation into durable visibility across Google, social platforms, and AI-generated answers.

Search no longer starts on Google. The teams that act on that reality will influence what people search for next.

Read more at Read More

What is a redirect? Types, how to set them up, and impact on SEO 

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Ever clicked a link and landed on a “Page Not Found” error? Redirects prevent that. They send visitors and search engines to the right page automatically. Redirects are crucial for both SEO and user experience. For SEO, they preserve link equity and keep your rankings intact. Additionally, it enhances the user experience, as no one likes dead ends. 

Table of contents

Key takeaways

  • A redirect automatically sends users and search engines from one URL to another, preventing errors like ‘Page Not Found.’
  • Redirects are crucial for SEO and user experience, preserving link equity and maintaining rankings.
  • Different types of redirects exist: 301 for permanent moves and 302 for temporary ones.
  • Avoid client-side redirects, such as meta refresh or JavaScript, as they can harm SEO.
  • Use Yoast SEO Premium to easily set up and manage redirects on your site.

What is a redirect? 

A redirect is a method that automatically sends users and search engines from one URL to another. For example, if you delete a page, a redirect can send visitors to a new or related page instead of a 404 error. 

How redirects work

  1. A user or search engine requests a URL (e.g., yoursite.com/page-old).
  2. The server responds with a redirect instruction.
  3. The browser or search engine follows the redirect to the new URL (e.g., yoursite.com/page-new).

Redirects can point to any URL, even on a different domain. 

Why redirects matter 

Redirects keep your website running smoothly. Without them, visitors hit dead ends, links break, and search engines get lost. They’re not just technical fixes, because they protect your traffic, preserve rankings, and make sure users land where they’re supposed to. Whether you’re moving a page, fixing a typo in a URL, or removing old content, redirects make sure that nothing gets left behind. 

When to use a redirect 

Use redirects in these scenarios: 

  1. Deleted pages: Redirect to a similar page to preserve traffic. 
  2. Domain changes: Redirect the old domain to the new one. 
  3. HTTP→HTTPS: Redirect insecure URLs to secure ones. 
  4. URL restructuring: Redirect old URLs to new ones (e.g., /blog/post → /articles/post). 
  5. Temporary changes: Use a 302 for A/B tests or maintenance pages. 

Types of redirects 

There are various types of redirects, each serving a distinct purpose. Some are permanent, some are temporary, and some you should avoid altogether. Here’s what you need to know to pick the right one. 

Not all redirects work the same way. A 301 redirect tells search engines a page has moved permanently, while a 302 redirect signals a temporary change. Client-side redirects, like meta refresh or JavaScript, exist because they’re sometimes the only option on restrictive hosting platforms or static sites, but they often create more problems than they solve. Below, we break down each type, explain when to use it, and discuss its implications for your SEO. 

Redirect types at a glance 

Redirect type  Use case  When to use  Browser impact  SEO impact  SEO risk 
301  Permanent move  Deleted pages, domain changes, HTTP→HTTPS  Cached forever  Passes (almost) all link equity  None if used correctly 
302  Temporary move  A/B testing, maintenance pages  Not cached  May not pass link equity  Can dilute SEO if used long-term 
307  Temporary move (strict)  API calls, temporary content shifts  Not cached  Search engines may ignore  High if misused 
308  Permanent move (strict)  Rare; use 301 instead  Cached forever  Passes link equity  None 
Meta Refresh  Client-side redirect  Avoid where possible  Slow, not cached  Unreliable  High (hurts UX/SEO) 
JavaScript  Client-side redirect  Avoid where possible  Slow, not cached  Unreliable  High (hurts UX/SEO) 

301 redirects: Permanent moves 

A 301 redirect tells browsers and search engines that a page has moved permanently. Use it when: 

  • You delete a page and want to send visitors to a similar one.
  • You change your domain name.
  • You switch from HTTP to HTTPS.

SEO impact: 301 redirects pass virtually all link equity to the new URL. But be sure to never redirect to irrelevant pages, as this can confuse users and hurt SEO. For example, redirecting a deleted blog post about “best running shoes” to your homepage, instead of a similar post about running gear. This wastes link equity and frustrates visitors. 

Example HTTP header: 

HTTP/1.1 301 Moved Permanently 
Location: https://example.com/new-page

302 redirects: Temporary moves 

A 302 redirect tells browsers and search engines that a move is temporary. Use it for: 

  • A/B testing different versions of a page.
  • Temporary promotions or sales pages.
  • Maintenance pages.

SEO impact: 302 redirects typically don’t pass ranking power like 301s. Google treats them as temporary, so they may not preserve SEO value. For permanent moves, always use a 301 to ensure link equity transfers smoothly. 

Examples of when to use a 301 and 302 redirect:  

Example 1: Temporary out-of-stock product (302): An online store redirects example.com/red-sneakers to example.com/blue-sneakers while red sneakers are restocked. A 302 redirect keeps the original URL alive for future use. 

Example 2: A permanent domain change (301): A company moves from old-site.com to new-site.com. A 301 redirect makes sure visitors and search engines land on the new domain while preserving SEO rankings. 

307 and 308 redirects: Strict rules 

These redirects follow HTTP rules more strictly than 301 or 302: 

  1. Same method: If a browser sends a POST request, the redirect must also use POST. 
  2. Caching: 
    • 307: Never cached (temporary). 
    • 308: Always cached (permanent). 

When to use them: 

  • 307: For temporary redirects where you must keep the same HTTP method (e.g., forms or API calls). 
  • 308: Almost never, use a 301 instead. 

For most sites: Stick with 301 (permanent) or 302 (temporary). These are for specific technical cases only. 

What to know about client-side redirects:

Client-side redirects, such as meta refresh or JavaScript, execute within the browser instead of on the server. They’re rarely the right choice, but here’s why you might encounter them: 

  • Meta refresh: A HTML tag that redirects after a delay (e.g., “You’ll be redirected in 5 seconds…”).
  • JavaScript redirects: Code that changes the URL after the page loads.

Why should you avoid them? 

  • Slow: The browser must load the page first, then redirect.
  • Unreliable: Search engines may ignore them, hurting SEO.
  • Bad UX: Users see a flash of the original page before redirecting.
  • Security risks: JavaScript redirects can be exploited for phishing. 

When they’re used (despite the risks): 

  • Shared hosting with no server access. 
  • Legacy systems or static HTML sites.
  • Ad tracking or A/B testing tools.

Stick with server-side redirects (301/302) whenever possible. If you must use a client-side redirect, test it thoroughly and monitor for SEO issues. 

How redirects impact SEO 

Redirects do more than just send users to a new URL. They shape how search engines crawl, index, and rank your site. A well-planned redirect preserves traffic and rankings. A sloppy one can break both. Here’s what you need to know about their impact. 

Ranking power 

301 redirects pass most of the link equity from the old URL to the new one. This helps maintain your rankings. 302 redirects may not pass ranking power, especially if used long-term. 

Crawl budget 

Too many redirects can slow down how quickly search engines crawl your site. Avoid redirect chains (A→B→C) to save crawl budget. 

User experience 

Redirects prevent 404 errors and keep users engaged. A smooth redirect experience can reduce bounce rates. 

Common redirect mistakes 

Redirects seem simple, but small errors can cause big problems. Here are the most common mistakes and how to avoid them. 

Redirect chains 

A redirect chain happens when one URL redirects to another, which redirects to another, and so on. For example:  

  • old-page → new-page → updated-page → final-page

Why it’s bad: 

  • Slows down the user experience. 
  • Wastes crawl budget, as search engines may stop following the chain before reaching the final URL. 
  • Dilutes ranking power with each hop. 

How to fix it: 

  • Map old URLs directly to their final destination. 
  • Use tools like Screaming Frog to find and fix chains. 

Redirect loops 

A redirect loop sends users and search engines in circles. For example:  

  • page-A → page-B → page-A → page-B...

Why it’s bad: 

  • Users see an error page (e.g., “Too many redirects”). 
  • Search engines can’t access the content, so it won’t rank. 

How to fix it: 

  • Check your redirect rules for cblonflicts. 
  • Test redirects with a tool like Redirect Path (Chrome extension) or curl -v in the terminal. 

Using 302s for permanent moves 

A 302 redirect is meant for temporary changes, but many sites use it for permanent moves. For example: 

  • Redirecting old-product to new-product with a 302 and leaving it for years. 

Why it’s bad: 

  • Search engines may not pass link equity to the new URL. 
  • The old URL might stay in search results longer than intended. 

How to fix it: 

  • Use a 301 for permanent moves. 
  • If you accidentally used a 302, switch it to a 301 as soon as possible. 

Redirecting to irrelevant pages 

Redirecting a page to unrelated content confuses users and search engines. For example: 

  • Redirecting a blog post about “best running shoes” to the homepage or a page about “kitchen appliances”. 

Why it’s bad: 

  • Users land on content they didn’t expect, increasing bounce rates. 
  • Search engines may ignore the redirect or penalize it for being manipulative. 
  • Wastes ranking power that could have been passed to a relevant page. 

How to fix it: 

  • Always redirect to the most relevant page available. 
  • If no relevant page exists, let the old URL return a 404 or 410 error instead. 

Ignoring internal links after redirects 

After setting up a redirect, many sites forget to update internal links. For example: 

  • Redirecting old-page to new-page but keeping links to old-page in the site’s navigation or blog posts. 

Why it’s bad: 

  • Internal links to the old URL force users and search engines through the redirect, slowing down the experience. 
  • Wastes crawl budget and dilutes ranking power. 

How to fix it: 

  • Update all internal links to point directly to the new URL. 
  • Use a tool like Screaming Frog to find and fix outdated links. 

Not testing redirects 

Assuming redirects work without testing can lead to surprises. For example: 

  • Setting up a redirect but not checking if it sends users to the right place. 
  • Missing errors like 404s or redirect loops. 

Why it’s bad: 

  • Broken redirects frustrate users and hurt SEO. 
  • Search engines may drop pages from the index if they can’t access them. 

How to fix it: 

  • Test every redirect manually or with a tool. 
  • Check Google Search Console for crawl errors after implementing redirects. 

Redirecting everything to the homepage 

When a page is deleted, some sites redirect all traffic to the homepage. For example: 

  • Redirecting old-blog-post to example.com instead of a relevant blog post. 

Why it’s bad: 

  • Confuses users who expected specific content. 
  • Search engines may see this as a “soft 404” and ignore the redirect. 
  • Wastes ranking power that could have been passed to a relevant page. 

How to fix it: 

  • Redirect to the most relevant page available. 
  • If no relevant page exists, return a 404 or 410 error. 

Forgetting to update sitemaps 

After setting up redirects, many sites forget to update their XML sitemaps. For example: 

  • Keeping the old URL in the sitemap while redirecting it to a new URL. 

Why it’s bad: 

  • Sends mixed signals to search engines. 
  • Wastes crawl budget on outdated URLs. 

How to fix it: 

  • Remove old URLs from the sitemap. 
  • Add the new URLs to help search engines discover them faster. 

Using redirects for thin or duplicate content 

Some sites use redirects to hide thin or duplicate content. For example, redirecting multiple low-quality pages to a single high-quality page to “clean up” the site. 

Why it’s bad: 

  • Search engines may see this as manipulative. 
  • Doesn’t address the root problem, which is low-quality content. 

How to fix it: 

  • Improve or consolidate content instead of redirecting. 
  • Use canonical tags if duplicate content is unavoidable. 

Not monitoring redirects over time 

Redirects aren’t a set-it-and-forget-it task. For example: 

  • Setting up a redirect and never checking if it’s still needed or working. 

Why it’s bad: 

  • Redirects can break over time (e.g., due to site updates or server changes). 
  • Unnecessary redirects waste crawl budget. 

How to fix it: 

  • Audit redirects regularly (e.g., every 6 months). 
  • Remove redirects that are no longer needed. 

How to set up a redirect 

Setting up redirects isn’t complicated, but the steps vary depending on your platform. Below, you’ll find straightforward instructions for the most common setups, whether you’re using WordPress, Apache, Nginx, or Cloudflare.  

Pick the method that matches your setup and follow along. If you’re unsure which to use, start with the platform you’re most comfortable with. 

WordPress (using Yoast SEO Premium) 

Yoast SEO Premium makes it easy to set up redirects, especially when you delete or move content. Here’s how to do it: 

Option 1: Manual redirects 

  1. Go to Yoast SEO → Redirects in your WordPress dashboard. 
  2. Enter the old URL (the one you want to redirect from). 
  3. Enter the new URL (the one you want to redirect to). 
  4. Select the redirect type: 
  • 301 (Permanent): For deleted or permanently moved pages. 
  • 302 (Found): For short-term changes. 
  1. Click Add Redirect. 
Manually redirecting a URL in Yoast’s redirect manager

Option 2: Automatic redirects when deleting content 

Yoast SEO can create redirects automatically when you delete a post or page. Here’s how: 

  1. Go to Posts or Pages in your WordPress dashboard. 
  2. Find the post or page you want to delete and click Trash. 
  3. Yoast SEO will show a pop-up asking what you’d like to do with the deleted content. You’ll see two options: 
    • Redirect to another URL: Enter a new URL to send visitors to. 
    • Return a 410 Content Deleted header: Inform search engines that the page is permanently deleted and should be removed from their index. 
  4. Select your preferred option and confirm. 

This feature saves time and ensures visitors land on the right page. No manual setup required. 

Need help with redirects? Try Yoast SEO Premium

No code, no hassle. Just smarter redirects and many other invaluable tools.

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Apache (.htaccess file) 

Apache uses the .htaccess file to manage redirects. If your site runs on Apache, this is the simplest way to set them up. Add the rules below to your .htaccess file, ensuring it is located in the root directory of your site. 

Add these lines to your .htaccess file: 

# 301 Redirect 
Redirect 301 /old-page.html /new-page.html
# 302 Redirect 
Redirect 302 /temporary-page.html /new-page.html

Nginx (server config) 

Nginx handles redirects in the server configuration file. If your site runs on Nginx, add these rules to your server block and then reload the service to apply the changes. 

Add this to your server configuration: 

# 301 Redirect 
server { 
    listen 80; 
    server_name example.com; 
    return 301 https://example.com$request_uri; 
}
# 302 Redirect 
server { 
    listen 80; 
    server_name example.com; 
    location = /old-page { 
        return 302 /new-page; 
    } 
}

Cloudflare (page rules) 

Cloudflare allows you to set up redirects without modifying server files. Create a page rule to forward traffic from one URL to another, without requiring any coding. Simply enter the old and new URLs, select the redirect type, and click Save. 

  1. Go to Rules → Page Rules. 
  2. Enter the old URL (e.g., example.com/old-page). 
  3. Select Forwarding URL and choose 301 or 302. 
  4. Enter the new URL (e.g., https://example.com/new-page). 

Troubleshooting redirects 

Redirects don’t always work as expected. A typo, a cached page, or a conflicting rule can break them, or worse, create loops that frustrate users and search engines. Below are the most common issues and how to fix them.  

If something’s not working, start with the basics: check for errors, test thoroughly, and clear your cache. The solutions are usually simpler than they seem. 

Why isn’t my redirect working? 

  • Check for typos: Ensure the URLs are correct. 
  • Clear your cache: Browsers cache 301 redirects aggressively. 
  • Test with curl: Run curl -v http://yoursite.com/old-url to see the HTTP headers. 

Can redirects hurt SEO? 

Yes, if you: 

  • Create redirect chains (A→B→C) 
  • Use 302s for permanent moves 
  • Redirect to irrelevant pages 

How do I find broken redirects? 

  • Use Google Search Console → Coverage report. 
  • Use Screaming Frog to crawl your site for 404s and redirects. 

What’s the difference between a 301 and 308 redirect? 

  • 301: Most common for permanent moves. Broad browser support. 
  • 308: Strict permanent redirect. Rarely used. Same SEO impact as 301. 

What is a proxy redirect? 

A proxy redirect keeps the URL the same in the browser but fetches content from a different location. Used for load balancing or A/B testing. Avoid for SEO, as search engines may not follow them. 

Conclusion about redirects

Redirects are a simple but powerful tool. A redirect automatically sends users and search engines from one URL to another. As a result, they keep your site running smoothly and preserve SEO value and ranking power. Remember: 

  • Use 301 redirects for permanent moves. 
  • Use 302 redirects for temporary changes. 
  • Avoid client-side redirects, such as meta refresh or JavaScript. 

Need help? Try Yoast SEO Premium’s redirect manager.  

The post What is a redirect? Types, how to set them up, and impact on SEO  appeared first on Yoast.

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The December 2025 edition of the SEO Update by Yoast: AI search, publisher deals & more

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Missed the final SEO Update by Yoast of 2025? Our in-house principal SEOs, Carolyn Shelby and Alex Moss, broke down December’s biggest search shifts, from Gemini’s integration to Google’s publisher deals, and answered your burning questions. Don’t forget to watch the replay and sign up for the next edition!

Watch the full replay below (or read on for the highlights).

2025 in a nutshell: The three biggest SEO shifts

2025 was the year AI officially took over search. Here’s what mattered most:

  1. From rankings to retrieval: AI overviews and chat interfaces made being cited more important than ranking #1.
  2. EEAT became non-negotiable: Google (and users) demanded real expertise, not just keyword-stuffed content.
  3. Publishers vs. AI: Lawsuits and deals reshaped how content is licensed and monetized.

Want the full breakdown? Our in-depth 2025 SEO recap post will be released next week. Also, hear Carolyn and Alex share their insights in the December SEO Update by Yoast on YouTube.

Key takeaways from the episode

AI search isn’t coming, because it’s already here

Action: Audit your content for retrieval (not just rankings). Use tools like Yoast’s Brand Insights AI visibility tracker to see where you’re cited in AI responses in LLMs like ChatGPT and Perplexity.

Google’s publisher deals: A band-aid or the future?

  • Google struck deals with major publishers (e.g., news sites) to license content for AI training. This is to avoid lawsuits and maintain ad revenue.
  • The catch: This doesn’t solve the long-term problem. Publishers still rely on traffic, and AI overviews are siphoning clicks.

Action: If you’re in publishing, diversify traffic sources (email, social, direct). For everyone else, monitor how these deals affect your niche.

Shopify’s AI UX agent: A glimpse of the future

  • Shopify’s SimGym simulates user behavior to identify UX issues, without skewing analytics.
  • Why it matters: AI-driven CRO tools are getting smarter. If you’re not testing UX with AI, competitors will.

Action: Experiment with AI UX tools (even free ones like Hotjar’s AI insights).

Google Search Console gets smarter

  • AI-powered insights: Search Console now suggests questions to analyze your data (e.g., “Why did impressions drop for X query?”).
  • Social channel tracking: YouTube, Reddit, and other social traffic now appear in Search Console.

Action: Use these tools to spot trends before they become problems.

llms.txt: Worth the 5 minutes?

Action: Add llms.txt if you’re curious, but don’t expect miracles.

Q&A highlights

Carolyn and Alex answered live questions during the webinar. Here are the top three:

1. Should we stop using background images to improve load speed?

  • Carolyn: “Optimize them, but don’t stress. Focus on non-blocking load times. If the image is lazy-loaded and doesn’t delay interactivity, it’s fine.”
  • Alex: “Test it. If your audience cares about visuals (e.g., fashion, design), keep them. If not, simplify.”

2. Can we make big changes during a Google core update?

  • Carolyn: “Act like there’s no update. If you need to make changes, make them. Google’s updates are continuous, so they’re not a deadline.”
  • Alex: “Worst case? You’ll see fluctuations. But if your site’s broken, fix it now.”

3. FAQ pages or FAQs on every page?

  • Alex: “Both. Put unique FAQs on product/service pages. Use a central FAQ for shared questions (e.g., shipping, returns).”
  • Carolyn: “Avoid hiding answers in toggles, because AI won’t read them.”

Stay ahead in 2026

The news in this December edition of the SEO Update by Yoast proves one thing: SEO is changing faster than ever. Whether it’s AI-driven search, publisher deals, or smarter tools, the rules are being rewritten at a rapid pace.

Here’s how to keep up:

  • Join us for the next SEO Update by Yoast on January 27, 2026. We’ll dive into the latest trends and explore their implications for your strategy. Sign up now.
  • Missed the 2025 recap? Our in-depth post will be released next week; don’t forget to read it!

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Why you should use synonyms and related keywords

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Search engines have become significantly more intelligent than they were in the past. You no longer need to repeat the same keyword a dozen times to be noticed. Google’s AI models, as well as large language models like ChatGPT and Gemini, now understand meaning, intent, and context. So, does that mean you don’t need to use synonyms and related keywords? Of course not, and to avoid any confusion, you should definitely. Using synonyms and related keywords isn’t just about improving your writing style. It also helps both people and search engines interpret what your page is about.

Table of contents

Key takeaways

  • Search engines now understand context, making it essential to use synonyms and related keywords for improved clarity.
  • Using synonyms enhances readability and helps both people and search engines understand the content’s meaning more effectively.
  • Tools like Yoast SEO Premium can suggest related keywords, making the writing process easier.
  • Focus on natural language rather than keyword density to enhance your SEO strategy.
  • Writing for readers and AI involves selecting word choices that create engaging and informative content.

What are synonyms and related keyphrases?

A synonym is a word that shares the same or a very similar meaning as another. For example, “fast” and “quick” are synonyms.

A related keyphrase, on the other hand, isn’t necessarily a direct synonym; it’s a word or phrase connected to the same topic. If your main keyphrase is chocolate candy, then sweets, dessert, or sugary treats could all be related keyphrases.

When you use synonyms and related keywords, you make your writing more natural to read and more informative. You also help search engines understand your topic in greater depth, which improves your chances of appearing in relevant searches.

Why variation matters for SEO and readability

Modern SEO copywriting and readability are all about helping people and search engines understand the context of your writing. When you vary your word choice and use synonyms and related keywords, you make your text more engaging for readers and clearer for algorithms.

If you’ve ever read a page that repeats the same keyword endlessly, you know how mechanical it feels. Years ago, that might have worked. Today, it can frustrate readers and even harm your SEO.

Using synonyms and related keywords also improves your readability score, a ranking factor that reflects how easy your text is to follow. When your content is varied, visitors stay longer, bounce less, and gain a better understanding of you.

How search engines and AI understand language today

Search engines rely on natural language processing (NLP) and machine learning to interpret meaning. Instead of simply counting keywords, they analyze how words relate to each other in context.

That’s why a post about AI copywriting tools can appear in searches for AI content writing software. Google understands those terms belong to the same topic. This is part of semantic SEO, which involves optimizing content so that search engines can grasp its overall context rather than just individual words.

By naturally incorporating synonyms and related keywords, you help Google recognize that your content addresses a broader range of questions related to your topic.

Understanding search intent is crucial here. Once you know what users expect to find, you can use language that naturally fits their intent while still covering your main keyphrases.

Keyword density versus natural language

In early SEO, keyword density, or the percentage of times a keyword appeared in your text, was seen as a signal of relevance. But search engines have outgrown that. Today, keyword density has little to no impact on search engine rankings.

Still, using your synonyms and related keywords naturally throughout your text can help clarify context. The key is balance: write as if you’re explaining the topic to a colleague or client.

Yoast SEO’s readability and SEO guidelines highlight why tone, pacing, and sentence length are now essential parts of optimization. The goal isn’t to count words, it’s to communicate clearly.

If you remember the candy shop analogy from before, let’s look at a real-world example. If you type in ‘best candy store New York’ on Google, the results will show pages about ‘candy stores’ and ‘candy shops’. Google understands that ‘store’ and ‘shop’ are synonyms and treats them as such. 

example of a google search showing results for both candy stores and shops in new york as it is a synonym
Snippets from the search result page for the search ‘best candy store New York’

This doesn’t detract from the fact that you should still incorporate your focus keyword a few times throughout your post. After all, the focus keyword is still the word or phrase your audience was searching for. These are the words your audience uses and will expect to find in your text. That exact match remains important. However, to avoid using your keyword too many times, also known as keyword stuffing, you can use synonyms and related keywords to achieve a more natural flow of language. That way, you can rank on these keywords while keeping your text attractive and readable.

Find related keyphrases using our Semrush integration

Yoast SEO can help you find related keyphrases based on your focus keyword, saving you time and hassle. All you need to do is click the button to ‘Get related keyphrases’; you’ll find it right underneath your focus keyword in the Yoast SEO sidebar. You’ll see a list of related keywords and search trend data when you click that button.

the related keyphrases feature in yoast seo showing results related to backpack essentials
This is how the related keyphrases feature looks in Yoast SEO

As a Yoast SEO Premium or Yoast SEO for Shopify user, you can add up to five related keyphrases to your SEO analysis. This lets you optimize your text for these additional terms similarly to your focus keyphrase. As always, you’ll see our familiar feedback bullets to guide you. If you’re a Yoast SEO Free user, you can explore related keyphrases using the tool, but you won’t be able to add these to your SEO analysis.

Yoast SEO can help you balance the use of your keywords, synonyms, and related keywords by recognizing word forms in different languages. If you want to know more, you can read about the related keywords feature in Yoast SEO for WordPress and the related keywords featured in Yoast SEO for Shopify.

How often should you use synonyms and related keywords?

The use of synonyms versus the use of focus keywords is not an exact science. The most important criterion is the way readers will experience your text. So, read and re-read it. Is it engaging and easy to read? Or are you getting annoyed by the constant use of a certain term? Be critical of your writing and ask others for feedback on your text. 

As mentioned earlier, you can add your related keywords to the analysis in Yoast SEO Premium and Yoast SEO for Shopify. By adding these, the plugin can check whether you’re using them in your text. Your focus keyword remains the most important keyword, though, and that’s why the plugin is less strict in its analysis of your related keyphrases.

related keyphrases in yoast seo expand the terms you are ranking for
You can add keyphrases that are related to your focus keyphrase in Yoast SEO Premium and Yoast SEO for Shopify

You’ll also be able to add synonyms of your focus and related keywords when you use our Premium SEO analysis or Yoast SEO for Shopify. These analyses include checks to ensure you’ve used these synonyms in your text and your meta description, introduction, subheadings, or image alt text. Moreover, our keyphrase distribution check will reward you for alternately using your keyphrase and its synonyms throughout your text.

synonyms in yoast seo help expand the vocabulary in the article
You can add multiple synonyms for your focus keyphrase in Yoast SEO Premium and Yoast SEO for Shopify

Make those related keyphrases and synonyms work for you

As we mentioned earlier, Google has come a long way since its early days in the field of SEO. It can understand texts, consider related concepts and synonyms, and recognize related entities. This enables it to serve its users with the best results. And part of being the best result is ensuring your texts are easy to read. Google wants to serve readable texts.

So make sure you deliver! Consider synonyms for your keyword or keyphrase and utilize them to your advantage. Take a moment to come up with a few alternatives for your keyword. Additionally, consider topics closely related to your keyword. You’ll notice that writing a naturally flowing text becomes much easier when you don’t have to use your focus keyword in every other sentence. Using synonyms and related key phrases helps Google understand the context of your text, which increases your chances of ranking.

In conclusion

Using synonyms and related keywords isn’t about tricking algorithms. It’s about writing naturally for humans while helping machines interpret meaning. When you vary your word choice, your writing becomes clearer, richer, and more engaging. That’s what today’s search engines reward: real content that genuinely helps users and shows topical depth.

Read more: Does readability rank? On ease of reading and SEO »

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