Web Design News Archives - Page 16 of 54

Is SEO Dead?

August 8, 2025/0 Comments/in Web Design News/by

Short answer: Not yet.

But SEO as we know it is dying.

SEO used to work fairly consistently: write great content, sprinkle in keywords, land a few links — boom, rankings.

The better you followed the recipe, the better your results.

That worked because search was a relatively closed system.

Now?

It’s probabilistic.

You show up if you’ve done enough of the right things in enough places. If the system infers you’re part of the answer.

People have been announcing the death of SEO for years.

But this time, the question feels more urgent.

Google and LLM Unique Visitor Growth Projection (Moderate Case)

You might look at this projection from Semrush — showing traditional search declining while LLM traffic takes over — and call it: Game Over.

But here’s the thing:

Decline doesn’t equal death.

In this article, we’ll lay out exactly what happens as a channel moves from goldmine to ghost town — and show you where SEO sits on that curve today.

Spoiler: SEO isn’t dead yet.

But it’s changing.

And understanding that shift is how you can stay ahead.

What Makes a Marketing Channel “Dead”?

To determine whether SEO is dead, we need to understand how a marketing channel evolves.

Marketing channels follow a relatively standard lifecycle.

They start out as experimental, high-risk, and unproven (think Bluesky).

If they gain traction, they enter what Gary Vaynerchuk calls the “underpriced attention” phase. Even basic strategies see outsized returns.

Early Facebook Ads. Early TikTok. Peak LinkedIn.

But attention doesn’t stay cheap. As more people jump in, the channel becomes fairly priced.

It still delivers, but not without skill. You need strategy. Execution. Patience.

Email marketing today, for example.

Eventually, some channels tip into overpriced. You can still win — but only with deep pockets or elite execution.

Competitive Google Ads. Facebook Ads in 2025. Viable? Yes. Worth it? Not for everyone.

And then, some channels just… flatline. Negative ROI. Abandoned by 80%+ of marketers.

Still technically there — but not usually worth the time. Facebook organic for traffic, say, or Yellow Pages.

Phase	Name	Definition	Key Traits	Examples
0	Experimental / Unproven	New channel with unclear viability	Small user base, high failure risk, low cost, limited data	Bluesky, BeReal, Google+ (entire lifecycle)
1	Underpriced Attention	Proven demand, low competition	High ROI, easy wins, basic tactics work, early adopters benefit	Early Google Ads, Facebook Ads (2007–2012), TikTok organic (current)
2	Fairly Priced Attention	Balanced supply and demand	Requires skill, sustainable long-term, good ROI with consistent strategy	Email marketing (current), SEO (sophisticated strategies)
3	Overpriced Attention	ROI declining for average users	Expensive, competitive, only works with high budgets or elite execution	Competitive Google Ads, Facebook Ads (current), SEO (basic tactics)
4	Dead / Flatline	Channel no longer viable for most	80%+ of businesses exit, negative ROI, only useful in rare cases	Facebook organic (for traffic), Yellow Pages, Direct mail (for most businesses)

A single platform can have parts in completely different phases.

Facebook organic for website traffic? Dead.
Facebook organic for brand building and community? Still fairly priced.

And some channels that looked dead? They weren’t.

The Yellow Pages are Phase 4 in most cities. But in some rural areas, they still convert.
Direct mail is Phase 4 for most. But for hyper-local businesses, it can still be gold.

My point:

Phase 4 is rare.

Most channels don’t die. They evolve.

So, where does SEO sit on the curve?

Why People Keep Saying SEO Is Dead

Well, partly because marketers delight in announcing the death of clearly not dead things.

It’s a weird industry habit.

But also because SEO is sliding from Phase 2: Fairly Priced to Phase 3: Overpriced.

And when that happens, ROI drops, easy wins disappear, and frustration grows.

Traffic is dropping. Search behavior is shifting. The content landscape is flooded. And the job market feels unstable.

Put all that together?

It’s no surprise people are asking if SEO is on its last legs.

Let’s break down the four biggest reasons behind the panic — and separate signal from noise.

1. No-Click Search Results Are Killing Traffic

This didn’t start with AI answers.

Google’s been reducing clicks for a decade.

Knowledge panels, calculators, unit converters: Handled factual queries
Local packs & shopping carousels: Took over commercial-intent real estate
Featured snippets (2015): Answered questions directly in the SERP
People Also Ask (2016): Offered related answers—no clicks required
AI Overviews (2024): Just the next step

So why does it feel worse now?

Because it is.

AI Overviews are among the most disruptive features Google has ever introduced for organic traffic.

Their click-stealing impact rivals or exceeds Featured Snippets — and in some cases, even Knowledge Panels.

The biggest difference is:

AI Overviews affect a much broader range of queries — especially informational and non-branded ones.

SERP Feature	Year Introduced	Estimated Click Impact on Organic Results
AI Overviews	2023–2024	–34.5% CTR drop for position 1 results; average –15.49%; up to –37.04% in combo with snippets. Most impact seen on non-branded informational queries. Lower-ranked results see –27.04% CTR drop.
Featured Snippets	2014–2015	Featured snippet captures ~35% of clicks; CTR to regular results drops ~26%
Knowledge Panels	2012–2013	Significant drop in organic CTR; <50% of searches result in a click when shown
Calculators / Converters	2010s	No reliable data available on click impact, but the logic is clear: when Google converts 50 miles to kilometers instantly, users rarely need to visit a conversion website.

So yes, AI overviews are the latest in a long line of click-killing moves by Google.

Knowledge Panels hurt branded queries. AIOs impact every query type.

Calculators killed clicks for simple tasks. AIOs apply that behavior to everything.

If Featured Snippets were death by a thousand cuts, AIOs are a guillotine.

But here’s the twist:

Google’s AI Overviews aren’t pulling random answers out of thin air.

They’re sourcing from the same types of content that show up in organic search.

According to a study by Search Engine Land:

Blog posts (46%) and news articles (20%) make up the majority of sources cited by AIOs.
Structured, crawlable, keyword-aligned pages still earn visibility.
And, while ChatGPT skews towards Wikipedia and global news sources for its data, Google’s Gemini relies heavily on company blogs.

LLM	Top Sources	Avoids	SEO Strategy
ChatGPT	Wikipedia, Reuters, FT	Reddit, product pages	Build authority on neutral sources (Wikipedia, major news)
Gemini	Blogs, YouTube, PCMag	Low-quality UGC	Prioritize high-quality blogs and media reviews
Perplexity	NerdWallet, Investopedia, niche blogs	Low-quality UGC	Get on niche review sites, expert blogs, forums
AI Overviews	Reddit, YouTube, LinkedIn, product blogs	Homepages	Target forums, blogs, social Q&A, deep guides

In other words:

The SEO content you’re already creating still matters.

You just need to make it easier for AI to read and reuse.

Further reading: Want more tips for showing up in AIOs? Check out our guide to AI overviews.

2. Search Behavior Has Fragmented

We’re in the Search Everywhere era.

Google still dominates, but things are changing.

Gen-Z uses social media as a search engine.

Forbes – Younger Generations Are More Likely To Use Social Media To Search

40% of young US adults are getting their news on TikTok.

More Americans regularly get news on TikTok – Especially young adults

Forums like Reddit and Quora are booming.

LLMs currently make up around 5.6% of all search behavior, up from 1.3% in early 2024.

So yes, search behavior is changing.

But this shift doesn’t mean traditional search engines are obsolete.

94.4% of searchers still use SERPs.

They’re just more likely to consult other sources as well.

Further reading: Build a Search Everywhere Optimization strategy with our guide.

3. It Feels Like AI Content Is Everywhere

The theory goes that, because anyone can create content in minutes with AI, SEO becomes a race to the bottom.

And it’s true that it’s easier than ever to create SEO content at scale.

But in practice, most content is still being created by human beings — entirely or with AI assistance.

In June 2025, AI content made up around 16% of all content (down from 19% in January) according to Originality.AI.

Originality – AI content in Google search results

4. The SEO Job Market Might Be Tanking

SEO job listings dropped 37% in Q1 2024 compared to the same time in 2023.

But if you zoom in on the types of SEO roles being hired for across the year, the picture is more nuanced.

Some executional roles saw a dip in share over 2024:

Content SEO made up 12.6% of SEO listings in Q1 — just 9.9% by Q4
SEO Analyst roles dropped from 11.2% to 10.1%
Technical SEO inched down from 5.8% to 5.4%

Meanwhile, more senior roles gained share:

SEO Manager roles increased from 58% to 61%
Director of SEO grew from 10.3% to 11.6%
VP-level roles doubled their share — from 0.7% to 1.4%

The shift isn’t dramatic. But it’s directional.

Companies appear to be consolidating around smaller, more senior teams.

Less grunt work. More strategic oversight. And possibly, more reliance on AI or freelancers for execution.

So no, the SEO job market isn’t collapsing — just being restructured.

Why SEO Isn’t Dead in 2025

SEO today looks very different than it used to.

But it doesn’t meet the criteria of a dead marketing channel.

Search Volume Is Still Rising

Search activity isn’t shrinking—it’s growing.

Google search grew by over 21% in 2024, despite the impact of AI overviews. And it’s projected to increase again in 2025, according to estimates by Exploding Topics:

The narrative that searchers are switching over to LLMs is also flawed.

While people are using LLMs more and more, they aren’t necessarily using them for search.

Semrush says only 30% of ChatGPT prompts are similar to how people use search.

Things like:

Asking for information
Finding a website
Comparing options
Getting help with a purchase

The rest? More like chatting, writing, or brainstorming.

SEO Still Works

91% of marketers said SEO had a positive impact on their website performance and marketing goals in 2024.

Far from cutting SEO spend, companies are investing more.

The global SEO services market is expected to grow at a compound annual growth rate (CAGR) of 16.2%.

It’s booming, not dying.

AI Overviews aren’t everywhere (yet)

As of May 2025, they show up in just 13.14% of all Google searches.

That means traditional search still handles about 86% of queries — for now.

Sharing of Queries Triggering AI Overviews

More importantly, they’re still mostly triggered by low-value, informational queries.

But when it comes to commercial-intent keywords?

They’re still wide open.

Think long-tail phrases with CPCs over $2 and Keyword Difficulty under 30%.

That’s where you still need SEO.

SEO Job Listings Have Declined, But Only in Part

Entry-level and senior-level SEO roles actually increased in 2024.

This shift reflects more automation of routine SEO tasks — and heightened demand for strategic, senior-level expertise.

There are over 117,000 SEO jobs live on LinkedIn worldwide:

Looks like there’s still plenty of demand for SEO experts.

“Dead Channel” Test	Reality in 2025
80% abandonment	No — most businesses still earn value from SEO strategy and content.
Declining volume	No — search volume continues rising, with growth in both queries and impressions.
Drop in hiring or investment	Mixed — SEO roles dropped, but demand for skilled strategists remains strong. Investment in SEO is increasing YOY.
Platform redundancy	No — 91% of marketers confirm that SEO still works well

SEO Isn’t Dead — But It’s Changing Fast

SEO still drives results.

But ranking alone isn’t enough anymore.

To stay visible, you need to show up in search results and in AI-generated answers.

That’s where Generative Engine Optimization (GEO) comes in.

It’s not about abandoning SEO. It’s about building on it.

Learn how to optimize for AI search with our 7-step GEO playbook.

The post Is SEO Dead? appeared first on Backlinko.

Read more at Read More

ChatGPT-5 Is Here: What Search Marketers Need to Know

August 8, 2025/0 Comments/in Web Design News/by

ChatGPT-5 is here. Rolling out to 700M+ weekly users.

With it comes the usual hype and hot takes.

But if you’re in digital marketing, the real question is:

How does this change how people discover, research, and buy?

After months of using ChatGPT extensively (and watching competitors like Google, Perplexity, Claude, and Grok evolve), one thing’s clear:

The brands that win in AI search aren’t just chasing keywords and backlinks.

They’re building topical authority, earning third-party mentions, showing up on YouTube and social, and shaping how people talk about their brand.

In other words: they’re optimizing for how they get recommended in answers — no matter who’s asking the question.

If you want to see exactly how your brand shows up in AI answers, check out our guide to the best LLM tracking tools.

What’s New in ChatGPT-5

GPT-5 is definitely an improvement over GPT-4. But the early feeling among marketers, business owners, and even software developers is that it might not be the huge leap many thought it would be.

But still, in certain areas, there are some notable gains.

Here’s a breakdown of what’s new:

Overall Capabilities

In Sam Altman’s words: GPT-4 was like talking to a college student. GPT-5 is more like talking to an expert. A legitimate PhD in any topic area that you want. And it will be broadly available to the free tier, with limits.

For a lot of queries (think fairly basic questions), it’s much faster too. And while you used to have to choose which model to use for specific tasks to prioritize speed or raw ability, GPT-5 now makes that decision for you.

No more messing around with lots of different model names.

Better Writing

OpenAI claims that GPT-5 should write better, more natural content. For SEOs and digital marketers, this should mean improvements when it comes to AI-assisted content.

In particular, GPT-5 is significantly more accurate than its predecessors. Compared to previous models like GPT-4o and OpenAI o3, it hallucinates 4 to 10 times less often, depending on the task.

On typical ChatGPT prompts, the error rate drops to just 4.8% when using its “thinking” mode. This makes it much more reliable for research, planning, and everyday use.

But its outputs are still not a replacement for human-reviewed, high-quality content.

Coding

The biggest improvements with ChatGPT-5 over GPT-4, at least per OpenAI, are in the math and coding departments. The company seems particularly excited about its advanced coding abilities, trying to beat out competition from Google (Gemini) and Anthropic (Claude).

“It opens up a whole new world of vibe coding, with some rough edges.”

I can see these improved coding capabilities being particularly useful for custom use cases.

For example, I could upload my fitness levels and preferred workouts, then ask ChatGPT to build a workout app that can give me specific workouts and help me track my progress over time.

Voice Mode Enhancements

You get more control over how to interact with the chatbot and, eventually, also the voice assistant. You’ll be able to choose between styles like concise and professional, or thoughtful and supportive.

Memory

The goal in terms of memory is for ChatGPT to really understand what’s meaningful to you. This way, the tool has more context about your specific situation. This should in theory lead to more tailored responses.

Plus, by mid-August, ChatGPT is gaining access to Gmail and Google Calendar. I can see this being super powerful from a business organization and productivity perspective.

Safety

ChatGPT-5 is significantly less deceptive. They have completely overhauled how they do safety training. Before, it was either to outright refuse or comply. Now it’s more nuanced.

OpenAI also introduced a new concept called “safe completions.” Essentially, it should maximize helpfulness, within safety constraints. If the model has to refuse, it will tell you why.

Knowledge Cutoff

According to OpenAI’s documentation, the model’s training data cutoff was Oct 1, 2024.

That’s newer than GPT-4o’s October 2023 cutoff, so it has a better grasp of late-2024 news changes, other trends.

It means more up-to-date baseline knowledge — but you’ll still need real-time data for anything happening in 2025.

Note: As with any new major release, it’s worth testing out for yourself to understand its capabilities for your specific needs. It’s easy for reviewers to cherry pick examples of it working incredibly well or not so well. The only way to know for sure is to try it yourself.

What Marketers Need to Know

ChatGPT-5 is a clear step up from GPT-4, with huge potential for both business and personal use.

But the fundamentals for marketers haven’t changed — the way you use LLMs and what they mean for your strategy still comes down to the same core principles.

1. ChatGPT-5 Still Pulls From Search Engines

We don’t know the exact mix GPT-5 uses for live lookups.

It could still be leaning on Google like ChatGPT-4o. It could be Bing. Most likely, it’s a blend of both plus OpenAI’s own retrieval system.

Either way, the rule for marketers stays the same:

If you want to be in the mix for citations, you need to be findable in search engines
That means optimizing for the right terms, having a technically sound site, and matching search intent

Optimizing for AI doesn’t replace SEO. It just makes SEO table stakes for getting recommended in AI answers.

2. AI Visibility Is a Multi-Surface Challenge

Here’s the reality today:

ChatGPT currently dominates in terms of total users. And its usage is growing:

But aside from ChatGPT, you need to consider the larger AI search space.

While ChatGPT reaches ~5X more users than Google’s Gemini app, the gap is not necessarily going to stay like that.

Just think back to the rise of Slack.

Guess who eventually reached the most users?

And the broad LLM technology behind ChatGPT is being used by all of its competitors.

For Google, that’s in AI Overviews (which reach nearly 17% of US queries) and Google AI Mode (their chat search experience).

Smaller competitors like Claude, Perplexity, Grok are still gaining share fast.

What’s the pattern?

AI discovery is not just tied to one tool. It’s happening across multiple generative engines — all with their own rules.

You need a brand strategy that works across:

Prompts and questions
Web results and citations
Source quality and brand authority

Don’t just focus on ChatGPT because it’s the biggest, and your brand currently shows up there.

If your customers are using Google AI Mode, Claude, or Perplexity, and you’re not showing up in these tools, you’re leaving money on the table.

3. Brand Mentions > Backlinks

Search engines reward links.

LLMs reward mentions.

If your brand keeps showing up in high-quality content — and that content is clear, well-structured, and semantically relevant — you get pulled into more answers.

Whether GPT-5 now cites sources differently or not, it’s trained on the same core patterns, meaning:

Strong brands get surfaced more often.

If you want to future-proof your visibility:

Publish content that earns mentions naturally
Use clear product and brand language that LLMs can understand
Strengthen your position in category-defining content

Want to know where you stand right now?

Use Semrush’s AI SEO Toolkit to find out exactly how you fare against your competitors in terms of AI citations across Google AI Mode, SearchGPT, and Perplexity:

You’ll also see how often your brand is mentioned by these tools over time, so you can track the impact of your LLM optimization efforts:

4. Prompts Are the New Keywords

People don’t talk to LLMs like they search Google.

Instead of “best bed sheets,” they ask:

“What are the comfiest bed sheets that don’t get too hot at night?”
“I need high-quality sheets that won’t pill after a few washes. Any brand recs?”
“What do hotels use for sheets, and can I buy something similar for home?”

The winners in ChatGPT-5 aren’t the ones who just rank in Google.

They’re the ones whose brand comes up when your ideal customer asks tools like ChatGPT a high-intent question.

Optimize for this by building a prompt library based on customer jobs-to-be-done.

Do this even faster with tools like Semrush’s AI SEO Toolkit. Just enter your domain name and head to the “Questions” tab.

Scroll down and you’ll see questions real customers in your industry are asking.

Create new content around these questions, and use them to optimize your existing content.

Then, use the “Visibility” tab to monitor your share of voice across not just ChatGPT, but also Google’s AI Mode, Perplexity, and Gemini:

Semrush AI Toolkit – Share of Voice by Platform

How to Win With GPT-5

GPT-5 is faster, more accurate, and more powerful.

But it won’t change the underlying reality for marketers:

If your brand isn’t clear, trusted, and visible in high-quality content, you will be invisible in AI answers.

Learn more about what really matters in our guide to LLM visibility.

The post ChatGPT-5 Is Here: What Search Marketers Need to Know appeared first on Backlinko.

Read more at Read More

5 LLM Visibility Tools to Track Your Brand in AI Search (2025)

August 7, 2025/0 Comments/in Web Design News/by

LLMs like ChatGPT and Gemini are quickly becoming the first place people turn when researching brands, products, and services.

But most companies have no idea how they’re actually showing up.

That’s a huge blind spot — especially as AI-generated answers start shaping what people believe about your brand before they ever hit your site.

At Backlinko, we’ve already seen the shift.

Hundreds of thousands of visitors per month still come from organic search…

Domain Overview – Backlinko – Organic Traffic

But LLM-driven traffic is up 800% year-over-year. And accelerating.

That’s why tracking your visibility in AI search matters. Because it’s not just about traffic anymore — it’s about presence, perception, and positioning.

So: what tools can actually help you do that?

I’ve tested more than a dozen. These are the five that stand out. The ones I trust right now for speed, scale, and signal.

Some are scrappy startups. Others are built for enterprise.

But every tool on this list does one thing well:

They help you see how your brand shows up in ChatGPT, Gemini, Perplexity, Claude, and more.

Let’s break them down.

What to Look For in an LLM Tracking Tool

A lot of LLM tracking tools look impressive at first glance.

But once you dig in, many fall short — either because they’re built on a shaky foundation, limited scraping technology, or generic dashboards that miss what actually matters.

Here’s what to consider:

Real scale: Thousands of prompts. From the UI, not just the APIs. Otherwise, you miss key results (like tables and maps).
Multi-engine coverage: ChatGPT is table stakes. Top tools also track Google AI Mode, AI Overviews, Perplexity, Claude, and Copilot.
Actionable insights: Breakdowns by model, topic, sentiment. Bonus if it flags missed opportunities and quick wins.
Roadmap momentum: Is the team shipping fast? If not, skip it.
Global support: Need multi-language prompts or market-level insights? Not all tools can do it.
Enterprise-ready: Solid support. Clean data policies. And a team that’s leading the space, not chasing it.

1. Semrush AIO

Semrush AIO isn’t like the other tools on this list.

Yes, it’s on the more expensive side.

But I also think it’s the most complete product on the market right now for tracking your brand across LLMs.

Why?

Because Semrush has something most others don’t: infrastructure and scale.

They’ve spent over a decade building one of the most robust search visibility platforms, and now they’re applying that to AI.

My favorite feature is the Competitor Rankings and Market Analysis. Once you have your prompts, and categories, dialed in, you can really get a detailed look at your visibility across all (or each individual) LLM that you track.

Semrush AIO – Backlinko – Competitor Rankings

And then you can really start honing your strategy by focusing on the top-performing Source Domains and specific URLs.

Semrush AIO – Backlinko – Source Analysis

Plans & Pricing

Enterprise pricing upon request. Request a demo here.

Semrush AI SEO Toolkit starts at $99/month per domain. It gives you a solid snapshot of how your brand shows up in AI responses — great for just getting started.

LLMs Covered

ChatGPT, Google AI Overviews, Gemini, Claude, Grok, Perplexity, Deepseek

Key Capabilities

Real-time brand, product, and concept tracking
Quote-level visibility and sentiment scoring
Share of Voice metrics across platforms
Platform-by-platform performance insights
Workflow automation and optimization guidance
Deep integrations with Semrush’s core platform for multi-channel visibility

2. Profound

Profound is one of the more interesting new companies in the space right now.

They launched in 2024 and in June 2025 raised a $20M seed round to go all-in on AI search.

The product looks great. It feels fast. And they’re shipping like crazy.

Prompt-level insights, platform-by-platform visibility, real crawl logs. There’s a lot to like.

But one thing to watch: Profound is still new.

They don’t have the infrastructure or track record of the bigger players (yet).

So while the pace of innovation is impressive, the long-term durability is something to keep in mind.

Plans & Pricing

Starts at $499/month for 200 prompts. Enterprise plans available.

LLMs Covered

Lite plan includes: ChatGPT, Perplexity, Google AI Overviews, Microsoft Copilot. Enterprise plan includes Google AI Mode. And more on the horizon.

Key Capabilities

Prompt-level tracking + AI-generated prompt suggestions
Visibility and Share of Voice by topic, region, and platform
Citation analysis with URLs, domains, and page-level stats
Real-time LLM crawl and citation logs
Conversation Explorer with topic-level ChatGPT demand
“Actions” workspace for optimizing slugs, content, and targeting

3. ZipTie.Dev

ZipTie is one of the simplest tools on this list, and that’s exactly why it works.

There’s no bloat, no complex setup, and no sales process. You just plug in your brand and get visibility across ChatGPT, Perplexity, and Google’s AI Overviews.

It’s not built for teams that want deep prompt logic or workflow integrations.

But if you want fast answers, clean dashboards, and a dead-simple way to check how your brand is showing up in AI search, ZipTie gets the job done.

Great for early-stage teams or solo operators who want signal without complexity.

Plans & Pricing

Starts at $99/month (Basic plan with 400 AI search checks)

LLMs Covered

ChatGPT, Perplexity, Google AI Overviews

Key Capabilities

Tracks brand presence across top AI search engines
Provides visibility and citation data in one view
Includes prompt-based monitoring with simple tagging
Export-friendly dashboard and fast onboarding
Basic UI with just the essentials

4. Peec AI

Peec AI is one of the newest players in the LLM tracking space, founded in 2025 and backed by a €5.2M seed round.

The platform is built to monitor brand visibility and sentiment across major AI search engines while keeping the interface simple and focused.

You can track your active prompts:

And the top performing sources, to guide your strategy:

Plans & Pricing

Starter: $89/month (25 prompts, 3-country coverage)
Pro: $199/month(100 prompts, 5 countries)
Enterprise: $499+/month (300+ prompts, 10+ countries)
Add‑ons
- GPT‑4 Search: $19–$49
- Claude 4: $29–$159
- Gemini Search Preview: $99–$499

LLMs Covered

Included: ChatGPT, Perplexity, Google AI Overviews

Optional Add-ons: Claude 4, Gemini, GPT-4 (via SearchGPT plugin)

Key Capabilities

Tracks brand mentions, sentiment, and visibility across top LLMs
Clean, modern UI with prompt-level reporting and tagging
Country-specific visibility insights (multi-language capable)
Easy onboarding and export-friendly reports
Modular pricing for expanding LLM coverage without overpaying

5. Gumshoe.AI

Gumshoe AI is in public beta — no clear pricing or enterprise polish yet.

But its approach? I’m super interested.

Unlike tools that start with prompts, Gumshoe starts with personas.

You define your audience — their roles, goals, and pain points — and Gumshoe reverse-engineers the kinds of prompts they’re likely to ask across AI chat tools.

The project setup flow is what really stands out.

You start by verifying your brand positioning. Then you choose one analysis focus area — usually your clearest product or service.

From there, Gumshoe builds a list of rich, realistic target personas. Not fluffy archetypes like “SaaS Sally” or “Paul the Plumber” — actual roles with meaningful intent.

Then it generates detailed, relevant prompts based on those personas and associated topic clusters.

This is (early-stage) structured AI search research, tied directly to how your audience thinks and searches.

Plans & Pricing

None announced yet.

LLMs Covered

Perplexity AI Sonar, Google Gemini 2.5 Flash, OpenAI 4o Mini, Anthropic Claude 3.5

Key Capabilities

Persona-based prompt generation and tracking
Visibility scoring by persona, topic, and LLM
Citation source tracking across answers
Topic visibility matrix for how your brand is mentioned by each persona for a given topic

Whichever Tool You Choose, Just Start Tracking

Whether you’re measuring it or not, users are discovering your competitors through AI interactions. So, it’s a good idea to have your finger on the pulse.

To get started, pick one tool, add 3-5 competitors, and track 10+ prompts about your products/services for 30 days. You’ll start seeing where you have opportunities.

Don’t expect overnight changes. This is like early-stage SEO — you’re building a foundation for long-term authority.

Once you have the data, what do you do next? Take a look at our guide on Generative Engine Optimization. We show you how to influence how LLMs mention and cite your brand.

The post 5 LLM Visibility Tools to Track Your Brand in AI Search (2025) appeared first on Backlinko.

Read more at Read More

ChatGPT Is Using Google Search – We Tested It

August 6, 2025/0 Comments/in Web Design News/by

Last month, Abhishek Iyer ran a sharp experiment:

He created a brand-new nonsense term, got it indexed only in Google, and then asked ChatGPT about it.

ChatGPT returned a perfect summary — despite the fact that Bing had never seen the page.

That test got our attention.

So we ran our own.

We invented a new fake SEO term, NexorbalOptimization, published a dedicated page on Backlinko, and made sure only Googlebot could crawl it.

Then we waited.

The results confirmed what Abhishek — and a handful of others — have started to suspect:

ChatGPT Plus is using Google Search data. Not just Bing.

Here’s how we ran the test, what we found, and what this means for the future of AI search visibility.

Step 1: Create a Term That Doesn’t Exist

We made up a new SEO buzzword: NexorbalOptimization.

It had:

Zero mentions online
No search volume
No overlap with real words, acronyms, or brand names

We built a new page on Backlinko with fake-but-professional sounding content explaining what “NexorbalOptimization” supposedly is.

Here’s the live URL: https://backlinko.com/nexorbaloptimization

Step 2: Let Google In (and Block Everyone Else)

Next, we updated our robots.txt file with the following:

# Allow Googlebot to access the specific page
User-agent: Googlebot
Allow: /nexorbaloptimization
# Block all other bots from that page only
User-agent: *
Disallow: /nexorbaloptimization

We also made sure this URL wasn’t included in our public sitemap.xml file.

That meant:

Googlebot could crawl and index the page
Bing, Perplexity, DuckDuckGo, Claude, and other bots were blocked
The page was invisible to public crawlers and AI tools, unless they were using Google

We manually submitted the URL to Google Search Console and waited for indexing.

GSC – Inspect – Backlinko – Nexorbaloptimization

Step 3: Wait for Indexing, Then Ask ChatGPT

Once the page was live, it took a few hours to get indexed in Google:

Google SERP – Backlinko – Nexorbaloptimization

We confirmed that it still wasn’t indexed in Bing:

Bing SERP – Backlinko – Nexorbaloptimization

Or DuckDuckGo:

DuckDuckGo SERP – Backlinko – Nexorbaloptimization

Then, we tested a prompt in different LLMs / models:

What is nexorbaloptimization?

ChatGPT Plus (temporary chat, with web browsing) found our page and quoted it word-for-word:

ChatGPT Free (with web browsing, not logged in) couldn’t find anything:

Neither could Claude 4 Sonnet:

Interestingly, Perplexity was the only other one that managed to find it:

Perplexity – What is nexorbaloptimization?

The Results

Only ChatGPT Plus and Perplexity’s Free plan returned a valid answer based on the Backlinko page.

All other models either:

Returned nothing
Said the term didn’t exist
Or made something up without referencing the page

This confirmed two things:

Google was the only search engine that knew about the term
The AI responses reflected the exact phrasing, structure, and concepts from our made-up page

Why This Matters

There’s been speculation for months that ChatGPT specifically might be relying on more than just Bing.

OpenAI has an official partnership with Microsoft.

ChatGPT’s default browsing model is often described as using Bing.

But these experiments tell a different story.

Here’s what’s becoming increasingly clear:

1. ChatGPT Plus is indexing Google Search

Especially when other engines haven’t seen the page.

2. SEO visibility in Google directly influences AI answers

If your page doesn’t rank in Google, ChatGPT likely won’t “see” it — regardless of whether you rank in Bing or not.

3. Google is the trusted source of truth for LLMs

Not because it’s stated — but because it’s indexed faster, deeper, and more completely.

What This Means for SEO in the Age of AI

This test, and others like it, reveal something critical:

AI search visibility is becoming an extension of Google’s reliable index and search visibility.

You’re not just optimizing to appear in a SERP.

You’re optimizing to be pulled into a ChatGPT answer box.

Or a Perplexity paragraph.

Or a Gemini-generated comparison.

If Google doesn’t index you — many AI tools won’t surface you.

That makes indexation and crawl access even more strategic than before.

Why LLM Visibility Still Starts with Google (And How to Track It)

If you’re trying to understand where your brand shows up in AI-generated content, you need to start with a simple truth:

Google’s index is the foundation layer for most LLMs.

Even as tools like ChatGPT, Claude, and Perplexity generate answers on the fly, they’re pulling from a mix of:

Crawled web results (often from Google-indexed pages)
Structured data
High-authority brand mentions

If your content isn’t indexed — or isn’t ranking — it’s invisible to the most important LLMs.

That’s why traditional SEO fundamentals still matter:

Crawlability
Fast indexing
Content structured for semantic clarity
Owning your brand queries and product terms

Want to track your presence in AI tools?

You’ll need more than just a rank tracker.

Thinking Ahead

As LLMs become more influential in the discovery process, you’ll want to start tracking how your brand shows up across tools — not just in SERPs.

That means finding a tool (or set of tools) that:

Can scale with your brand and content footprint
Tracks citations, summaries, and AI-generated exposure
Is transparent about what it’s monitoring and how

If you’re already using Semrush, their AI SEO Toolkit is a solid starting point.

For enterprise teams managing multiple properties or international markets, Semrush Enterprise AIO adds more depth.

Bottom line:

LLM visibility is a new surface area. And the earlier you start tracking it, the better positioned you’ll be to influence it.

Want to Run the Test Yourself?

Invent a fake phrase
Create a page with unique content
Submit to Google Search Console
Block all other bots via robots.txt
Wait for indexing
Prompt ChatGPT (Plus with browsing) with a simple question
See what it says

This kind of sting-test isn’t just clever — it’s revealing how the AI discovery layer is actually working.

Shoutout

Big credit to Abhishek Iyer for running the original experiment that sparked this.

You can read his breakdown here.

We just followed the trail — with a slightly sillier term.

The post ChatGPT Is Using Google Search – We Tested It appeared first on Backlinko.

Read more at Read More

How Perplexity ranks content: Research uncovers core ranking factors and systems

August 5, 2025/0 Comments/in Search Engine Land, Web Design News/by

Want to know how content is scored, ranked, and in some cases, discarded by Perplexity? Independent researcher Metehan Yesilyurt analyzed browser-level interactions with Perplexity’s infrastructure to reveal how the AI answer engine evaluates and ranks content.

Why we care. Everybody involved with driving SEO and/or GEO success wants to understand how to gain visibility (citations and mentions) in AI answer engines. This research (albeit unverified at this point) offers some clues about Perplexity’s ranking signals, manual overrides, and content evaluation systems that could improve your optimization strategies for Perplexity (and possibly other answer engines) to gain a ranking advantage.

Entity search reranking system. One significant Perplexity system uncovered is a three-layer (L3) machine learning reranker. It is used for entity searches (people, companies, topics, concepts). Here’s how it works:

Initial results are retrieved and scored, like traditional search.
Then, L3 kicks in, applying stricter machine learning filters.
If too few results meet the threshold, the entire result set is scrapped.

This means quality signals and topical authority are super important for L3 – and keyword optimization isn’t enough, according to Yesilyurt.

Authoritative domains. Yesilyurt also discovered manual lists of authoritative domains (e.g., Amazon, GitHub, LinkedIn, Coursera). Yesilyurt wrote:

“This manual curation means that content associated with or referenced by these domains receives inherent authority boosts. The implication is clear: building relationships with these platforms or creating content that naturally incorporates their data provides algorithmic advantages.”

YouTube synchronization = ranking boost. Another interesting find: YouTube titles that exactly match Perplexity trending queries see enhanced visibility on both platforms.

This hints at cross-platform validation. Perplexity might validate trending interest using YouTube behavior – rewarding creators who act fast on emerging topics, according to Yesilyurt.

Core ranking factors. Yesilyurt documented dozens of what he called Perplexity’s “core ranking factors” that influence content visibility:

New post performance: Early clicks determine long-term visibility.
Topic classification: Tech, AI, and science get boosted; sports and entertainment get suppressed.
Time decay: Publish and update content frequently to avoid rapid visibility declines.
Semantic relevance: Content must be rich and comprehensive – not just keyword-matched.
User engagement: Clicks and historic engagement signals feed performance models.
Memory networks: Interlinked content clusters rank better together.
Feed distribution: Visibility in feeds is tightly controlled via cache limits and freshness timers.
Negative signals: User feedback and redundancy checks can bury underperforming content.

What’s next. Yesilyurt said success on Perplexity requires a combination of strategic topic selection, early user engagement, interconnected value, continuous optimization, and prioritizing quality over gaming.

Sound familiar? To me, it sure sounds like doing the SEO fundamentals.

Dig deeper. AI search is booming, but SEO is still not dead

The post. Breaking: Perplexity’s 59 Ranking Patterns and Secret Browser Architecture Revealed (With Code)

Read more at Read More

How to Run a Competitor Traffic Analysis (9 Steps)

August 5, 2025/0 Comments/in Web Design News/by

You know that feeling when you see a brand new competitor swooping in and snatching leads away from you?

It can make you start questioning your whole approach.

But instead of panicking, it’s far more useful to break down what they’re doing.

That way, you can cherry-pick their best ideas. And spot the gaps they’ve missed.

This post will show you exactly how to do that.

As you read it, imagine you’re a new pet supplies brand going head-to-head with the retailer Hollywood Feed.

To get the upper hand, you’ll need to understand how they’re driving traffic and converting customers, answering questions like:

Which channels bring the most visits and sales?
How much of their traffic is organic vs. paid?
Which pages, platforms, and campaigns are working best?

In this guide, you’ll learn how to run a competitor analysis to find the answers to these questions and more — regardless of your brand, industry, and experience.

Free resource: You can follow along with our Competitive Analysis Worksheet. Just open it up in another tab, and use this article as a guide to fill it out for your top 3-5 competitors.

Competitive Traffic Analysis Worksheet – Backlinko

Before you start, this guide assumes you’ve already covered the basics.

You know your ideal customer. You’ve nailed your positioning. You’re clear on the category or niche you’re competing in.

If not, start here: The Complete Guide to Market Research

It’ll make everything in this guide way more useful.

Let’s start by identifying your real competition.

Step 1: Spot the Competitors Grabbing Your Traffic

You need to build a live list of 5–10 competitors.

Begin Googling broad, high-intent terms like:

“best dog food”
“pet store near me” (or “pet store in [city]”)
“cat toys online”

Not sure where to start? Try this AI prompt to gather some terms you can then type into Google:

“What high-intent keywords do people use when searching for [your product/service] online?”

Make a note of:

Who ranks organically
Who’s running paid ads
Who’s in the local pack (map section that shows nearby businesses) or shopping results

Next, check out popular Reddit threads and pet owner forums. This is where you’ll often find smaller, more niche brand mentions. But they might still be your competitors depending on your location and/or stage of growth.

(As a bonus it’ll also often reveal the sentiment around your rivals from real customers.)

Now go to Google and look for “best of” listicles from publishers and bloggers.

The Spruce Pets – Best Places to Buy Dog Food

Find these by searching for modifiers like “best” and “cheapest” followed by:

[product] in [industry]
[product] in [city]
[product] for [specific need]
[product] under $[amount]
[product] in [year]
[industry] brands

Google SERP – Best dog food for sensitive stomach

Tip: Also check which competitors rank for these terms directly. These are generally high volume, competitive, and valuable. If your rivals rank for them, you likely want to as well.

Want a more straightforward way to find your rivals?

You can use an SEO platform like Semrush to instantly find your main competitors.

Just pop your domain into the Organic Research tool. Head to the “Competitors” tab and you’ll see the Competitive Positioning Map.

This shows your top rivals on a chart of the number of keywords they rank for vs. their organic search traffic.

Organic Research – Petfoodexpress – Competitors Map

You’ll also see more information below that about each competitor. Like common keywords, paid keywords, and more.

Note: A free Semrush account gives you 10 searches in the Organic Research tool per day. Or you can use this link to access a 14-day trial on a Semrush Pro subscription.

Finally, AI tools like ChatGPT can help uncover competitors that traffic tools might miss. Here are a few prompts you can try:

Use Case	Example Prompt	What It Reveals
General Discovery	What are the best places to buy [your product] in [your market]? E.g. What are the best places to buy pet supplies online in the U.S.?	Returns top names, but might sometimes surface lesser-known brands too
Niche-Specific	Top-rated [your business] for [your niche] in [your market] E.g., Top-rated pet stores for natural dog food in the U.S.	Highlights specialty brands focused on natural or premium products
Emerging and Hidden Players	Fastest-growing [your vertical] business in [your market] E.g., Fastest-growing pet retailers in the US	Surfaces rising brands that may not rank in traffic tools yet

Note that AI tools may personalize answers based on your chat history. Run prompts in a fresh window, and always verify unfamiliar results.

Pro tip: It’s easy to watch the big names and miss smaller players like Hollywood Feed who are gaining ground.

Don’t just check Google.

Search Reddit, niche listicles, and online communities to spot emerging competitors.

Reminder: Add these competitors to your copy of our competitor analysis worksheet.

Step 2: Find Your Edge by Comparing Products and Positioning

Once you’ve got your competitor list, go through them one by one, and start by looking at the basics:

What products do your competitors sell?
How do those products compare to yours?

Then, look at how they talk about themselves.

What value propositions are they leaning on: quality, price, convenience, or something else?

Head to their website to find this out.

Have a click around, paying particular attention to the product and category pages. Use what you find to fill out the “Product and Positioning” sections of our template:

You can use AI to gather a lot of this info even faster (although I still recommend actually visiting their website too).

Here’s an example of a prompt you could use:

I’m analyzing competitors to understand how to position my brand more effectively.

Here’s what I’d like help with:

My brand: [insert brief description — product, audience, values]

Competitors: [insert 3–5 competitor names]

For each competitor, please:

List their main products

Compare their offerings to mine in terms of variety, pricing, target customer, and positioning

Identify their core value propositions (price, convenience, quality, speed, etc.)

Describe their messaging tone and website language

Then suggest 2–3 ways I can differentiate — based on gaps or overlaps in their positioning. Format your answer using tables and bullet points

Here’s an example using Hollywood Feed and Chewy:

Section	Brand	Details
Product Comparison	Chewy	Wide selection: pet food (all types), toys, meds, grooming. Convenience-focused.
	Hollywood Feed	Natural/premium food, boutique accessories, regional in-store experience.
Value Propositions	Chewy	Convenience, speed, selection, 24/7 service.
	Hollywood Feed	High quality, local expertise, boutique service.
Messaging & Tone	Chewy	Warm, mass-market tone. “Trusted by millions.” Friendly and supportive.
	Hollywood Feed	Expert-led, local authority. “Nutrition-trained associates.” Boutique feel.
Differentiation Opportunities	1. Sustainable + subscription niche	Neither competitor clearly owns this space — potential to stand out.
	2. Ingredient transparency	Competitors mention quality, but don’t emphasize traceability or sourcing.
	3. Radical simplicity	Chewy offers everything; Hollywood Feed is regional. There’s room for a frictionless, curated experience.

Note: We’ve included a section at the end of the downloadable worksheet to go a step further and analyze your rivals’ customer experience and checkout flows.

Competitive Traffic Analysis Worksheet – Backlinko – Customer Experience Audit

There are too many checks to cover in detail here. But they’re still super important as they can help you understand where your rivals are winning at the end of the buyer journey.

Step 3: Analyze Their Traffic Channels

Looking at your competitor’s website traffic can tell you where they’re investing. And how fast they’re growing.

Here’s how.

Start with the Top-Level Traffic Numbers

Start by checking competitor website traffic in general. You can do this with a tool like Semrush’s Domain Overview (although there are other options out there — including our own free website traffic checker).

Domain Overview – Hollywood Feed – Search

Here’s what to check:

Total Traffic

Look for their estimated monthly visits.

A higher number doesn’t always mean more sales.

But it does show the scale of their online presence.

Domain Overview – Hollywood Feed – Overview

For example, Hollywood Feed has around 193K organic visits per month. That’s a significant number to contend with if I’m a new player, and I shouldn’t expect to reach that number overnight.

Paid vs. Organic

Comparing paid traffic to organic traffic reveals how your rivals are acquiring customers.

A brand with mostly organic traffic is typically investing in SEO and content.

A brand leaning on paid search or social is buying quick traffic. But they may be vulnerable to rising costs.

Hollywood Feed brings in only 8.4K from paid search. It looks like they’re betting on SEO over ads.

If your pet store has the budget to invest in paid search, you could reach customers they’re missing.

Further reading: Learn more about using paid ads effectively in our guide on advertising your business.

Traffic Share

Use traffic share metrics to compare competitor website traffic and understand where you fit in the picture.

For example, Hollywood Feed holds a 9% traffic share compared to its main competitors.

They’re a meaningful player in the market, but not the dominant one.

Branded vs. Non-Branded

Are people searching for their brand name or just looking for what they sell?

Hollywood Feed gets 68.1% of its traffic from branded keywords.

That shows strong name recognition but also reveals an opportunity.

Aim to rank for the non-branded, high-intent searches they’re missing.

Analyze Their Traffic Split

Moving away from just traffic, you can learn a lot about your competitor’s SEO and content marketing strategy from the outside.

You can do this with Semrush’s Organic Research tool.

Organic Research – Hollywoodfeed – Overview

Scroll down to see their top pages.

Are they blog posts, category pages, product pages, or store locators?

This helps you spot where they’re strongest, and where there might be opportunities.

Organic Research – Hollywoodfeed – Top Pages

For example, 61% of Hollywood Feed’s traffic goes to their home page.

This suggests strong brand recognition but potentially limited organic discovery.

Their location pages also drive some traffic, suggesting investment in local SEO.

Blog content contributes less than 3% of visits.

So there’s a chance to compete on content.

Next, look at their Keywords by Intent:

Informational keywords represent people looking for advice
Navigational keywords come from people searching for a specific site
Commercial keywords are searched by those comparing products
Transactional keywords are used by shoppers ready to buy

Note: Traffic numbers can look impressive, but context matters. A competitor with 200K visits might not be a real threat if most traffic is just browsing educational content. Focus on traffic quality and intent, not just volume.

Here’s the breakdown for Hollywood Feed:

Organic Research – Hollywoodfeed – Keywords by Intent

Their keywords primarily cover informational, commercial, and transactional intent. And it’s a pretty even split.

This means they reach searchers at every stage of the buying journey.

No obvious gaps here.

But as they’re evenly spread, you could consider going deeper on one keyword set to compete.

For instance, better product comparisons could help you compete for commercial keywords.

Further reading: For more tips on finding these opportunities, check out our full guide to uncovering competitor keywords.

Step 4: Look at Their Paid Media Performance

Next, check how your competitors are using paid media to drive traffic and sales.

Start with Google Ads.

Search for their brand name to find branded search ads.

Also, look for relevant non-branded keywords. Like “natural dog food” or “best dog treats.”

Google SERP – Best dog food delivery – Google Ads

Look for Google Search ads and Google Shopping ads (product images with prices).

Pro tip: Use Google’s Ads Transparency Center to browse a brand’s live and past ads.

Next, visit the Meta Ad Library and type in their brand name.

This will show you any active ads they’re running on Facebook or Instagram.

Meta Ad Library – Hollywood Feed – Results

You can do the same on TikTok’s Ad Library.

As you review their ads, pay attention to:

What products they’re promoting (specific brands, seasonal items, top-sellers)
What offers they’re using (discounts, bundles, subscriptions, free shipping)
Which platforms they’re investing in (Google, Facebook, Instagram, TikTok)

This gives you a snapshot of their paid strategy on social media.

Hollywood Feed’s Meta ads are a mix of product promotions and local messages.

You could stand out by using stronger calls to action.

You might also try content-driven ads or user-generated videos to boost engagement.

Further reading: You can also use this free Competitor Search Ads tool to spy on your competitors’ ads.

Step 5: Deep Dive Into Their Content and Messaging

Take a closer look at how your competitors are talking to their audience.

Start with their homepage copy.

Is it clear who they’re targeting and what makes them different?

Hollywood Feed does a good job of highlighting benefits upfront.

Same-day delivery. Curated product picks. “Why we’re a different breed” messaging.

It’s all there — baked right into the homepage.

Steal that move.

Make sure your top benefits are front and center.

What makes you different? Why should someone buy from you instead of the competition?

If that’s not obvious in the first few scrolls, fix it.

Also analyze their:

Product descriptions: Are they just listing features, or are they showing how their products solve problems? Do they use benefit-driven language?
Blog/educational content: Is their content deep, or is it thin and only covering the basics? Could you create more engaging, valuable blog posts for your audience to outrank and outcompete them?
Tone, style, and trust signals: Do they prominently feature social proof? Do they show off guarantees or certifications/awards?

Finally, look into their content structure.

Topic clusters are groups of related articles linked to a central pillar page. This can help build authority around key topics.

The Hollywood Feed University blog covers topics like pet care and nutrition.

But they haven’t built out strong topical clusters to organize this content.

When you click on a category, you get a list of articles, not a central pillar page.

That’s a missed SEO opportunity — and a chance for you to win.

Create clear pillar pages that link out to related content.

It helps Google understand your site and builds topical authority.

Compare the insights you gather with your own content to identify areas you can improve — and gaps you can fill.

Step 6: Explore Their Social Media Presence

Next, see which social media platforms your competitor uses.

Tip: B2C brands often use Facebook, Instagram, and TikTok. B2B brands usually focus on LinkedIn, X/Twitter, and YouTube.

Scroll through their recent posts and take note of the content formats they use.

Are they sharing educational posts, demos, customer stories, or thought leadership?

Look at follower engagement too.

Are people commenting, sharing, or ignoring the content?

Strong engagement signals an active community and loyal audience.

Finally, assess their brand personality and values.

Are they playful, bold, helpful, or professional?

For our pet food example, we find that Hollywood Feed is on Instagram. And they have a large following (around 35K followers).

Their social content leans into friendly, community-focused messaging, with discounts for followers.

You could stand out by adding more educational content.

You might also try more engaging formats, like videos or user-generated posts.

Step 7: Check Their LLM Visibility

Research from Semrush suggests that LLM traffic will overtake Google search by 2027.

That means getting visibility in AI answers is about to matter as much as (or more than) traditional rankings.

Here’s how to analyze your competitors’ LLM visibility to make sure you’re not falling behind:

First, open a fresh incognito window or use a VPN to avoid personalized results.

Then, in Google Search, look for an AI Overview by searching for broad, high-intent keywords. (Or take a look at the results in AI Mode.)

Think “best dog food delivery” or “top pet stores near me.”

Try the same searches in tools like Perplexity.ai and ChatGPT.

Look for mentions of your competitor’s brand name and links to their site in AI responses.

Also note the sentiment:

Are they being mentioned as a top brand?
What specific features are the AI tools calling out?
Are the AI responses pulling from reviews, or are they also citing round-up posts and forum discussions?

LLM visibility and optimization is a massive topic in its own right. This post would get too long if we tried to cover all the ways you can analyze your competitors’ performance in these tools.

So for a more detailed guide, check out our dedicated article on LLM visibility.

Step 8: Review Their Local SEO (If Applicable)

If your competitor has a physical presence, search for their brand name + city (e.g., “Hollywood Feed Austin TX”) in Google Search and Google Maps.

Look for their Google Business Profile.

Is it optimized with photos, opening hours, and reviews?

Do they rank for proximity-based keywords like “pet store near [city]” or “dog food delivery [city]”?

Hollywood Feed appears to be investing in local landing pages.

They have active Google Business Profiles for each store:

Hollywood Feed – Google Business Profiles

If you wanted to compete on a local search level, you’d better make sure you’ve done the same.

Further reading: Read our Google Business Profile guide to find out how to compete at the local level.

Step 9: Turn Competitive Insights Into Action

Now it’s time to bring all your research together so you can act on it.

If you’ve been following along with our competitor analysis worksheet, you’ll have a lot of info already.

I recommend filling it out for your top 3-5 competitors. Then, download our competitor analysis summary template.

Competitor Analysis Summary Template by Backlinko

Here’s where you’ll turn data into actionable strategies that you’ll use to beat your rivals.

It helps you dig deeper into what each competitor is doing well, where they’re falling short, and how you can differentiate.

Competitor Analysis Summary Template by Backlinko – Strenghts

Pro tip: Competitor insights are valuable. But they should never replace your own market research.

Use their playbook as a reference, not a roadmap.

And don’t try to beat them at everything. Find one or two clear openings and double down.

Don’t Just Copy Your Competitors — Outsmart Them

Competitor analysis isn’t about copying. It’s about learning.

Use this process to sharpen your edge, not mirror theirs.

Begin by picking one competitor and analyzing their online presence using the steps in this guide.

To help you get started, download the free Competitive Traffic Analysis Tracker.

The post How to Run a Competitor Traffic Analysis (9 Steps) appeared first on Backlinko.

Read more at Read More

Google Ads lets you test images, videos in Demand Gen campaigns

August 5, 2025/0 Comments/in Search Engine Land, Web Design News/by

Dealing with Google Ads frustrations: Poor support, suspensions and rising costs

Google is testing a new feature that allows advertisers to run A/B tests on images and videos within Demand Gen campaigns, marking a major step toward creative performance transparency.

How it works:

Create an A/B test with two experiment arms.
Google duplicates the campaign for comparison.
Add or remove images and/or videos in either arm.
Set traffic split (commonly 50/50) and total budget.
Define your experiment dates.
Optional: Review campaign opt-ins like video enhancements.

Note: Changes made to the control arm sync to the treatment arm – but not the other way around. Avoid editing the treatment campaign after setup.

Why we care. Until now, you’ve had limited tools to test how visuals perform in Demand Gen campaigns. This new A/B testing functionality gives you a structured way to compare creatives head-to-head and make data-backed decisions. You can now test different visuals across duplicated campaign arms and clearly measure which creatives drive better engagement and conversions.

Between the lines: This gives advertisers a clearer lens into which visual elements perform best – at a time when creative is increasingly driving performance in Google’s AI-heavy ecosystem.

Bottom line: With A/B testing for images and videos now available in Demand Gen campaigns, creative testing just got real. Leveraging it early will unlock stronger insights and more optimized results.

First seen. The update was first highlighted by Thomas Eccel, head of Google Ads at JvM IMPACT, on LinkedIn.

Read more at Read More

AI search fight: Cloudflare and Perplexity clash over crawling

August 5, 2025/0 Comments/in Search Engine Land, Web Design News/by

Cloudflare accused AI answer engine Perplexity of “stealth crawling,” saying it uses deceptive techniques to bypass website blocks and access content it’s been explicitly told not to touch.

In response, Perplexity said Cloudflare has a fundamental misunderstanding of how AI assistants work and accused the company of either publicity-seeking or technical incompetence.

The big picture. Cloudflare said Perplexity uses declared bots when it can, but switches to “stealth crawling” when blocked. That includes mimicking normal browser behavior, rotating IPs, and ignoring robots.txt rules (tactics that can be associated with scrapers and bad actors).

Cloudflare tested this by setting up honeytrap sites and found Perplexity answering questions using content it shouldn’t have been able to access.
Perplexity insisted its requests are made on behalf of users, not as preemptive crawling. The company says these are real-time fetches, akin to what a browser or email client does, and claims Cloudflare mistook its behavior for something it wasn’t.

Why we care. If AI assistants can sidestep robots.txt by posing as browsers, brands, creators, and publishers lose control over how and when their content is used. That breaks the old deal between search engines and websites.

What’s next. Cloudflare said it’s already blocking the behavior in question and expects Perplexity’s tactics to change in response. It’s calling for standardization of bot behavior through IETF (the Internet Engineering Task Force) and other policy efforts.

Perplexity, meanwhile, is doubling down on its identity as an agentic AI platform and says it shouldn’t be governed by rules designed for traditional web crawlers.

The blog posts. You can view the full back and forth here:

Cloudflare: Perplexity is using stealth, undeclared crawlers to evade website no-crawl directives
Perplexity: Agents or Bots? Making Sense of AI on the Open Web

Read more at Read More

From search to answer engines: How to optimize for the next era of discovery

August 5, 2025/0 Comments/in Search Engine Land, Web Design News/by

The shift from traditional search engines to AI-powered answer engines signals more than a technical upgrade.

It marks a fundamental change in how people discover, evaluate, and act on information.

Search is no longer a discrete game of isolated queries and static rankings.

It’s becoming an infinite game – one shaped by context, memory, and ongoing interaction.

For many users, large language models (LLMs) now offer a more effective starting point than classic search engines, especially when the task calls for clarity, research, or a more conversational experience.

How search evolved: From static queries to continuous conversations

Traditional search: A one-off query model

Traditional search engines (like classic Google Search) operate on a deterministic ranking model.

Content is parsed, analyzed, and displayed in SERPs largely as provided.

Ranking depends on known factors:

Content quality.
Site architecture.
Links.
User signals.

A user types a query, receives a list of results (“10 blue links”), clicks, and typically ends the interaction.

Each query is treated independently, with no memory between sessions.

This model supports advertising revenue by creating monetization opportunities for every new query.

AI-powered search: Built for continuity and context

AI-powered answer engines use a probabilistic ranking model.

They synthesize and display information by incorporating:

Reasoning steps.
Memory of prior interactions.
Dynamic data.

The same query can yield different results at different times.

These systems are built for ongoing, multiturn conversations, anticipating follow-up questions and refining answers in real time.

They operate continuously, even while you sleep, and focus on delivering direct, synthesized answers rather than just pointing to links.

How output and experience differ between search and answer engines

The differences between traditional search and AI-powered answer engines aren’t just technical. They show up in what users see and how they interact.

From output format to underlying signals, the user experience has fundamentally changed.

From link lists to zero-click answers

Traditional search engines: Return a ranked list of links generated by complex algorithms.
Answer engines: Deliver full answers, summaries, direct responses, or even product recommendations by blending large-scale training data with real-time web results. They reduce the need for users to click through multiple sites, leading to more zero-click experiences.

From keywords to context

Traditional search: Relies on keyword matching, backlinks, and on-page optimization.
AI search/generative engines: Rely on semantic clarity, contextual understanding, and relationships between entities enhanced by attention mechanisms and references in credible sources. Even content that doesn’t rank highly in traditional search may appear prominently in AI summaries if it is well-structured, topical, and cited across trusted platforms.

Key characteristics of answer engines

Conversational search

LLMs like ChatGPT, Google Gemini, and Perplexity enable conversational interactions, often serving as a more intuitive starting point for users seeking clarity, context, or nuanced understanding.

Queries tend to be longer and phrased as full questions or instructions.

Personalization and memory

Unlike traditional search, AI-powered search incorporates user context, such as:

Past queries.
Preferences.
Location.
Even data from connected ecosystems (e.g., Gmail within Google’s AI Mode).

This context allows the engine to deliver tailored, dynamic, and unique answers.

Dig deeper: How to boost your marketing revenue with personalization, connectivity and data

Query fan-out

Instead of processing a single query, answer engines deconstruct a user’s question into dozens or even hundreds of related, implicit, comparative, and personalized sub-queries.

These synthetic queries explore a broader content pool.

From one query, systems like AI Mode or AI Overviews:

Generate a constellation of search intents.
Retrieve responsive documents.
Build a custom corpus of relevant content.

Reasoning chains

AI models move beyond keyword matching, performing multi-step logical reasoning. They:

Interpret intent.
Formulate intermediate steps.
Synthesize coherent answers from multiple sources.

Multimodality

Answer engines can process information in various formats, including text, images, videos, audio, and structured data. They can:

Transcribe videos.
Extract claims from podcasts.
Interpret diagrams.
Integrate these inputs into synthesized outputs.

Dig deeper: Visual content and SEO: How to use images and videos in 2025

Chunk-level retrieval

Instead of retrieving or ranking entire pages, AI engines work at the passage level.

They extract and rank smaller, highly relevant chunks of content to build precise, context-rich answers.

Advanced processing features

User embeddings and personalization

Systems like Google’s AI Mode use vector-based profiles that represent each user’s history, preferences, and behavior.
This influences how queries are interpreted and how content is selected, synthesized and surfaced as a result – different users may receive different answers to the same query.

Deep reasoning

LLMs evaluate relationships between concepts, apply context, and weigh alternatives to generate responses.
Content is judged on how well it supports inference and problem-solving, not just keyword presence.

Pairwise ranking prompting

Candidate passages are compared directly against each other by the model to determine which is most relevant, precise, and complete.
This approach departs from traditional scoring models by favoring the best small sections rather than entire documents

A step-by-step guide to answer-engine-optimized content

Content best practices remain the same – it should be people-centric, helpful, entity-rich with healthy topical coverage based on audience intent.

However, the content creation process needs to incorporate answer-engine optimization best practices in the details.

Here’s our recommended seven-step process for content creation.

1. Content audit

When auditing existing content:

Check current visibility signals, including impressions, rich results, and whether the page is cited in AI platforms like Google AI Overviews, ChatGPT, or Perplexity.
Identify signs of content decay to establish a baseline for measuring improvement.
Spot and document issues such as:
- Topical gaps or missing subtopics.
- Unanswered user questions.
- Thin or shallow content sections.
- Outdated facts, broken references, or weak formatting.
- Grammatical errors, duplicate content, or poor page structure.

2. Content strategy

It is not all about creating new content.

Your content strategy should incorporate aligning existing content to the needs of answer engines.

Retain: High-converting content with high visibility and high traffic.
Enhance: Pages with high impressions but low click-through rate, pages with low visibility, impressions, and rich results.
Create: Content around topical gaps found in the audit.

3. Content refresh

Update existing content to close topical gaps to make information easily retrievable

4. Content chunking

This involves breaking long blocks into:

Scannable sections (H2/H3).
Bullet lists.
Tables,
A short TL;DR/FAQs.

Keep each chunk self-contained so LLMs can quote it without losing context, and cover just one idea per chunk.

Dig deeper: Chunk, cite, clarify, build: A content framework for AI search

5. Content enrichment

Fill in topical gaps by:

Expanding on related topics.
Adding fresh data.
Drawing on first-hand examples.
Referencing expert quotes.

Cover topics AI can’t easily synthesize on its own.

Cite and link to primary sources within the text (where relevant and meaningful) to boost credibility.

6. Layer on machine-readable signals

Insert or update schema markup (FAQPage, HowTo, Product, Article, etc.).

Use clear alt text and file names to describe images.

7. Publish → monitor → iterate

After publishing, track organic visibility, AI citation frequency, and user engagement and conversion.

Schedule content check-ins every 6–12 months (or after major core/AI updates) to keep facts, links, and schema current.

Make your content LLM-ready: A practical checklist

Below is a checklist you could incorporate in your process to ensure your content aligns with what LLMs and answer engines are looking for.

Map topics to query fan-out

Build topic clusters with pillar and cluster pages.
Cover related questions, intents, and sub-queries.
Ensure each section answers a specific question.

Optimize for assage-level retrieval

Use clear H2/H3 headings phrased as questions.
Break content into short paragraphs and bullet points.
Include tables, lists, and visuals with context.

Build depth and breadth

Cover topics comprehensively (definitions, FAQs, comparisons, use cases).
Anticipate follow-up questions and adjacent intents.

Personalize for diverse audiences

Write for multiple personas (beginner to expert).
Localize with region-specific details and schema.
Include multimodal elements (images w/ alt text, video transcripts, data tables).

Strengthen semantic and entity signals

Add schema markup (FAQPage, HowTo, Product).
Build external mentions and links from reputable sources.
Use clear relationships between concepts.

Show E-E-A-T and originality

Include author bios, credentials, and expertise.
Add proprietary data, case studies, and unique insights.

Ensure technical accessibility

Clean HTML, fast load times, AI-friendly crawling (robots.txt).
Maintain sitemap hygiene and internal linking.

Align with AI KPIs

Track citations, brand mentions, and AIV (attributed influence value).
Monitor engagement signals (scroll depth, time on page).
Refresh content regularly for accuracy and relevance.

Get the newsletter search marketers rely on.

See terms.

How SEO is evolving into GEO

As the mechanics of search evolve, so must our strategies.

GEO (generative engine optimization) builds on SEO’s foundations but adapts them for an environment where visibility depends on citations, context, and reasoning – not just rankings.

Many “new” AI search optimization tactics, such as focusing on conversational long-tail searches, multimodal content, digital PR, and clear content optimization, are essentially updated versions of long-standing SEO practices.

New metrics and goals

Traditional SEO metrics like rankings and traffic are becoming less relevant.

The focus shifts to being cited or mentioned in AI-generated answers, which becomes a key visibility event and a brand lift moment, rather than just driving traffic.

New KPIs at the top of the funnel include:

Search visibility.
Rich results.
Impressions.
LLM visibility.

With declining traffic, engagement, and conversion metrics become critical at the bottom of the funnel.

Relevance engineering

This emerging discipline involves:

Strategically engineering content at the passage level for semantic similarity.
Anticipating synthetic queries.
Optimizing for “embedding alignment” and “informational utility” to ensure the AI’s reasoning systems select your content.

Your website acts as a data hub.

This also means centralizing all types of data for consistency and vectorizing data for easy consumption, and distributing it across all channels is a critical step.

Importance of structured data

Implementing schema markup and structured data is crucial for GEO.

It helps AI engines understand content context, entities, and relationships, making it more likely for content to be accurately extracted and cited in AI responses (53% more likely).

Dig deeper: How to deploy advanced schema at scale

Brand authority and trust

AI models prioritize information from credible, authoritative, and trustworthy sources.

Building a strong brand presence across diverse platforms and earning reputable mentions (digital PR) is vital for AI search visibility, as LLMs may draw from forums, social media, and Q&A sites.

Connecting the dots: UX and omnichannel in the age of AI search

The typical user journey is no longer linear. The options for discovery have diversified with AI acting as a disruptor.

Most platforms are answering questions, are multimodal, delivering agentic and personalized experiences.

Your audience expects similar experiences on the sites they visit. As the user journey evolves, our approach to marketing needs to change, too.

In a linear journey, having channel-based strategies worked.

Consistency of messaging, content, visuals and experiences at every touchpoint are today key to success.

That means you need an audience strategy before mapping channels to the strategy.

Dig deeper: Integrating SEO into omnichannel marketing for seamless engagement

To make it happen effectively, you need to orchestrate the entire content experience – and that starts with your platform as the foundation.

Your website today needs to act as the data hub feeding multimodal information across channels.

How to make your content discoverable by LLMs

To show up in LLM-driven search experiences, your content needs more than depth. It needs structure, speed, and clarity.

Here’s how to make your site visible and machine-readable.

Foundational SEO

The fundamentals of SEO still apply.

LLMs have to crawl and index your content, so technical SEO elements like crawlability and indexability matter.

LLMs do not have the crawl budgets or computing power that Google and Bing have.

That makes speed and page experience critical to maximize crawling and indexing by LLMs

Digital assets

With search going multimodal, your digital assets – images and videos – matter more than they ever did.

Optimize your digital assets for visual search and make sure your page structure and elements include FAQs, comparisons, definitions, and use cases.

Structural integrity

Your site and content need to be both human and machine-readable.

Having high-quality, unique content that addresses the audience’s needs is no longer enough.

You need to mark it up with an advanced nested schema to make it machine-readable.

Deep topical coverage

Ensure your content aligns with the best practices of Google’s E-E-A-T.

People-first content that:

Is unique.
Demonstrates expertise.
Is authoritative.
Covers the topics that your audience cares about.

Make your content easy to find – and easy to use

While the building blocks of SEO are still relevant, aligning with LLM search calls for refining the finer points of your marketing strategy to put your audience before the channels.

Start with the basics and ensure your platform is set up to let you centralize, optimize and distribute content.

Adopt IndexNow to push your content to LLMs instead of waiting for them – with their limited computing and crawling capabilities – to crawl and find your content.

Thank you, Tushar Prabhu, for helping me pull this together.

Read more at Read More

Google Business Profiles Posts creation tool refreshed

August 5, 2025/0 Comments/in Search Engine Land, Web Design News/by

Google has updated the Google Posts creation tool within Google Business Profiles. The update makes it easier to use, by placing all the posts in a centralized location with an easier way to manage those posts.

This update should be live for all of you by now, as it quietly launched last Friday.

What changed. Google made several changes to the Google Posts screen, the changes were summarized by Lisa Landsman from the Google team. She wrote on LinkedIn the list of changes, which includes:

Centralized Posts Hub: The “Add Update” button has been replaced with a new management screen where you can easily see and manage all your posts in one place.
Simpler Creation Process: The post creation experience is now streamlined into a single dialog, allowing you to quickly create updates, events, or offers from one screen.
Enhanced Management View: You can now view key details for each post, such as creation date, status, and post type, making it easier to track and make changes.
Minor Visual Improvements: Google introduced small visual changes throughout the experience to make it more intuitive and enjoyable to use.

What it looks like. Here is a GIF of the new refreshed interface for Google Posts:

What are Google Posts. Google Posts allows businesses to post updates on your Business Profile to share announcements, offers, updates, and event details directly with your customers on Search and Maps. These posts show up within Google Maps and Google Search for searches on your business and within your Google local panel.

You can learn more about Google Posts in this help document.

Why we care. If you are a business with a local footprint or do marketing for a local business, Google Posts can help you get more attention and conversions for that business. By pushing updates, promotions, offers, events and so forth in your local listing on Google, it can attract new and repeat business for the organization.

This new interface may make things easier for you and your business to manage.

Read more at Read More