BacklinkoModify

2025-09-15 22:01:54

Answer Engine Optimization (AEO) is one of the most important topics in search right now.

It’s about making sure your brand shows up inside AI-generated answers — not just on traditional SERPs.

As large language models (LLMs) like ChatGPT, Gemini, and Perplexity reshape discovery, AEO ensures your content gets mentioned and cited where buyers are asking questions.

But here’s the bigger truth: AEO is just one piece of a larger shift.

We’re entering the era of Search Everywhere.

Discovery no longer happens in a single Google results page.

It’s happening across AI chat, overviews, forums, video, and social.

And new data shows just how fast this shift is accelerating.

New research from Semrush predicts that LLM traffic will overtake traditional Google search by the end of 2027.

And our own data suggests that’s likely to be true.

In just the past three months, we’ve seen an 800% year-over-year increase in referrals from LLMs.

We’re seeing tens of millions of additional impressions in Google Search Console as AI Overviews reshape how Google displays answers.

If your brand isn’t adapting, you risk disappearing from the channels your audience is already using.

In this guide, I’ll explain:

• What AEO is and how it differs from SEO
• Why your existing SEO foundation still matters (and what to evolve)
• Practical steps to optimize for answer engines and drive measurable results

What Is AEO and Why Does It Matter?

Answer Engine Optimization (AEO) is the practice of structuring and publishing content so that AI systems — like Google AI Overviews, AI Mode, ChatGPT, and Perplexity — pull your brand directly into their answers.

But AEO goes beyond tweaking a few pages. It’s about making your brand part of the conversation when people ask questions.

That requires three things:

• Publishing content in the right places where AI tools actively crawl and cite
• Earning brand mentions across the web (even without a link)
• Ensuring technical accessibility so AI crawlers can actually parse your content

These engines don’t rank “10 blue links.” They generate answers.

Sometimes they cite sources. Sometimes they don’t. Either way, the goal is to give the searcher everything they need without leaving the interface.

That changes your job. With AEO, you’re not only optimizing for a click — you’re optimizing to shape the answer itself.

Why AEO Matters Now

Traditional search is still a traffic driver. That won’t change overnight.

But discovery is moving fast:

• Success used to mean ranking #1.
• Soon there may be no “#1 spot” at all.
• The win condition is becoming the recommended solution — the brand AI platforms trust enough to include.

The data tells the story:

ChatGPT reached 100 million users faster than any app in history. And as of February 2025, it now has more than 400 million weekly users.

Google’s AI Overviews now appear on billions of searches every month — at least 13% of all SERPs.

And they appear for more than half of the keywords we track at Backlinko:

Answer engines are influencing YOUR audience too. So it makes sense to start optimizing for them now.

How AEO and SEO Work Together

Let’s clear up the biggest question:

“Isn’t this just SEO with a new name?”

In many ways, yes. But there’s a reason everyone is talking about AEO right now.

If you’ve been confused by all the acronyms — AEO, GEO (Generative Engine Optimization), AIO (AI Optimization) — here’s the point:

They all reflect the same shift. Search is no longer only about rankings. It’s about visibility in AI-powered answers.

Terms like AEO, GEO (Generative Engine Optimization), and AIO (AI Optimization) have exploded in interest — because they reflect a real shift.

And with all the acronyms flying around, it can be tough to know who to listen to.

We’re not saying AEO replaces SEO.

But it does help reframe your strategy for how discovery works now — across AI tools, social platforms, and new surfaces beyond traditional search.

From Traditional SEO to Search Everywhere

That means there’s good news:

If you’ve invested in good SEO, you’re already a lot of the way there.

AEO builds on the foundation of great SEO:

• Creating high-quality content for your specific audience
• Making it easy for search engines to access and understand
• Earning credible mentions across the web

These same elements help AI engines decide which brands to reference.

But here’s the difference:

AI engines don’t work exactly like Google.

That means some of your tactics (and what you track) need to evolve.

So let’s walk through how to do that.

7-Step AEO Action Plan

We’re still in the early days of understanding exactly how AI engines pull and prioritize content.

But one thing is clear:

You need to adapt or reprioritize some traditional SEO tactics for Answer Engine Optimization.

The first three steps below cover overarching best practices for AEO.

Steps 4-7 cover optimizing content for answer engines specifically (and how to track your results).

Step 1. Nail the Basics of SEO

As I said earlier, good AEO is also generally good SEO. But not everything you do as part of your wider SEO strategy is as important for answer engine optimization.

I won’t go through all the fundamentals of SEO here. We do that in our guide to the SEO basics.

Let’s focus on what really matters for answer engines.

Make Your Site Easy to Read (for Bots)

• Crawlable and indexable: If AI tools can’t access your pages, you won’t show up in answers
• Fast and mobile-friendly: Slow, clunky sites hurt UX — and your chances of getting cited
• Secure (HTTPS): This is now table stakes, and it builds trust with users and AI systems
• Server-side rendering: Some AI crawlers still struggle with JavaScript, so use server-side rendering as opposed to client-side rendering where you can

Show You’re Worth Trusting (E-E-A-T)

AI wants trustworthy sources. That means showing E-E-A-T:

• Experience: Share real results, personal use, or firsthand knowledge
• Expertise: Stick to topics you truly know — and go deep
• Authority: Get quoted, guest post, or contribute to well-known sites
• Trust: Use real author bios, cite sources, and include reviews or testimonials

Note: We’re not suggesting these AI tools have any sort of “system” built into them that aligns with what we call E-E-A-T. But it makes sense that they’ll prefer to cite content from reputable sources with expertise. This provides a better user experience and makes the AI tools themselves more reliable. Also, download our Free Template: E-E-A-T Evaluation Guide: 46-Point Audit

Step 2. Build Mentions and Co-Citations

AI systems don’t just look at backlinks to understand your authority. They pay attention to every mention of your brand across the web, even when those mentions don’t include a clickable link.

Backlinks are still important. But this changes how you should think about building your wider online presence.

Audit Your Current Mentions

Start by auditing where you’re currently mentioned. Search for your brand name, product names, and key team members across Google, social media, and industry forums.

Take note of what people are saying and where those conversations are happening.

You’ll probably find mentions you didn’t know existed. Some will be positive, others neutral, and a few might need your attention.

Also run your brand name and related terms through the AI tools themselves.

• Does Google’s AI Mode cite your brand as a source for relevant terms?
• Does ChatGPT know who your team members are?
• What kind of sentiment do the answers have when you just plainly ask the tools about your brand?

For a more in-depth sentiment analysis, use Semrush’s AI SEO Toolkit.

It’ll let you track your LLM visibility (a by-product of good AEO) in top tools compared to your rivals:

The tool compares your brand to your rivals in terms of AI visibility, market share, and sentiment:

And it’ll show you where your brand strengths are and where you can improve:

Want to track your brand’s AI visibility? Get a free interactive demo of Semrush’s AI SEO Toolkit to see how you can compare to competitors across ChatGPT, Claude, and other AI platforms.

Keep Building Quality Backlinks

Just because mentions are more important than before with AEO, it doesn’t mean you should abandon traditional link building. Backlinks still matter for SEO, and they often lead to the kind of authoritative mentions that AI systems value.

But expand your focus beyond just getting links.

Further reading: How to Get High Quality Backlinks

Aim to Build Co-Citations and Co-Occurences

There are a few different definitions out there of co-citation and co-occurence.

I’ll be honest: the definitions don’t matter as much as the implications. I’ve seen one source define co-citations as the exact thing another source calls co-occurence. So for this section, I’m just going to talk about what these are and why they matter, without getting bogged down in definitions.

The first important way to think of co-citations/co-occurences is simply the mention of one thing alongside another.

In the case of AEO, we’re usually talking about your brand or website being mentioned alongside a different website or topic/concept on another website.

For example, if your brand is Monday.com, you’ll pick up co-citations involving:

• Your competitors (ClickUp, Asana etc.)
• Key terms or categories associated with your business (like “project management software”)
• Specific concepts or questions related to what you do (e.g., “kanban boards” and “how to automate workflows”)

In Monday’s case, there are hundreds of pages out there that mention it alongside ClickUp and Asana in the context of “project management tools”:

This suggests to Google and other AI tools that Monday and ClickUp are both related to the term “project management tools” and are both popular providers of this kind of software.

The other common way to think about co-citations is mentions of your brand across different, often unrelated websites. For example, Monday being mentioned on Forbes and Zapier would be a co-citation involving them.

To sum it up:

• If two (or more) brands/websites are often mentioned alongside each other, AI tools will assume they are related (i.e., they’re competitors)
• If a brand is often mentioned in the context of a particular topic, concept, or industry, AI tools will assume the brand is related to those things (i.e., what you offer)
• If lots of different websites mention a particular brand, the AI tools will assume that brand is worth talking about (i.e., probably trustworthy)

Obviously, there’s a lot more to it, but this is a fairly basic overview of what’s going on.

How to Put This into Action

To build citations, co-citations, and co-occurences:

• Look for opportunities to get mentioned alongside your competitors. When publications write comparison articles or industry roundups, you want your name in that list. These co-citations help AI systems understand where you fit in your market.
• Participate in industry surveys and research studies. When analysts publish reports about your sector, being included gives you credibility (and any backlinks are a bonus).
• Get involved in relevant online communities. Answer questions on Reddit, contribute to LinkedIn discussions, and join industry-specific forums. These interactions create mentions in places where AI systems often look for authentic, community-driven insights.

The goal is to become a recognized voice in your space. The more often your brand appears in relevant contexts across the web, the more likely AI systems are to include you in their responses.

Step 3. Go Multi-Platform

Going beyond Google is something top SEOs have been telling us to do for a long time. But AI has made this an absolute must.

Platforms like Reddit, YouTube, and other user-generated content sites appear frequently in AI outputs.

So, a strong brand presence on these platforms could help you show up more often.

The benefits here are (at least) three-fold:

1. Being active on multiple platforms lets you reach your audience where they are. This helps you boost engagement, brand awareness, and, of course, drive more conversions.
2. AI tools don’t just look at Google search results. They pull from forums, social media, YouTube, and lots of other places beyond traditional SERPs.
3. Being active on multiple platforms means you’re less exposed to one particular algorithm or audience. Diversification is just good practice for a business.

Brian Dean did an excellent job of this when he was running Backlinko. That’s why you’ll see his videos appear in Google SERPs for ultra-competitive keywords like “how to do SEO”:

We’re taking our own advice here. In fact, it’s a big part of why we launched the Backlinko YouTube channel:

Here’s some quick-fire guidance for putting this into practice:

• People go to YouTube to learn how to do things, research products, and find solutions to their problems. This makes product reviews, tool comparisons, and in-depth tutorials great candidates for YouTube content.
• Podcast content and transcripts are beginning to surface in AI results (especially in Gemini). Building a presence here is a great opportunity to grab some AI visibility.
• TikTok and Instagram Reels reach younger audiences who increasingly use these apps for search. Short-form videos that answer common questions in your industry can drive discovery, and AI tools can also cite these in their responses to user questions.
• AI tools LOVE to cite Reddit as a source of user-generated answers (especially Google’s AI Overviews and AI Mode). To grow your presence on the platform, find subreddits where your target audience hangs out and share genuinely helpful advice when people ask questions related to your expertise. Don’t promote your business directly — focus on being useful first.
• LinkedIn works similarly to Reddit for B2B topics. Publish thoughtful posts and engage in relevant discussions to help establish your voice in professional circles. These interactions can then get picked up by AI systems looking for expert perspectives.

Step 4. Find Out What AI Platforms Are Citing for Your Niche

What’s a powerful way to understand both what to create and what topics to target?

To simply learn what AI tools are likely to include in their responses to questions that are relevant to your business.

Start by directly testing whether/how your content appears in AI tools right now. Go to ChatGPT, Claude, or Perplexity and ask questions that your content should answer.

In the example below, Backlinko is mentioned (great), but there’s also a YouTube video front and center. And forums are appearing too. These are places we might want to consider creating content or engaging with conversations.

As you do this for your brand, pay attention to the sources they cite:

• Are they commonly mentioning your competitors?
• What platforms do they tend to cite? (Reddit, YouTube etc.)
• What’s the sentiment of mentions of both your brand and your competitors?

As you do this, try different variations of the same question.

For example, you could ask “What’s the best email marketing software?”

Then try “Which email marketing tool should I use for my small business?”

Notice how the answers change and which sources get mentioned consistently.

In the example above, the first prompt mentioned MailerLite, which was absent in the list for small businesses. But the second prompt pushed Mailchimp to the top and mentioned three new options (Constant Contact, Brevo, and ActiveCampaign).

If you were MailerLite and trying to reach small businesses, you’d want to understand why you’re not being cited for that particular prompt.

Pro tip: Try it with different tools as well. They each have their own preferences when it comes to citing sources, so it’s a good idea to test a couple of them.

You can automate this process with tools like Profound or Peec AI. These platforms run prompts at scale, helping you understand how and where your brand appears. But they can be pricey.

That’s why I recommend you spend some time running these prompts manually at first.

By the way:

This isn’t just important for “big brands” or those selling products. You can (and should) do this if you run a blog, local business website, or even a personal portfolio.

For example, consultants and freelancers will find these tools often cite marketplaces like Upwork and Dribbble. If you don’t have a profile on there, you’ll likely struggle to get much AI visibility.

And if you’re a local business owner, you’ll often find specific service and location pages appear in AI responses:

This is useful for understanding the types of content you should be focusing on for AEO. Now it’s time to decide what topics to focus on in your content.

Step 5. Answer Your Audience’s Questions

The way people search with AI tools is fundamentally different from how we use traditional Google search. This changes how you should plan your content.

Traditional SEO taught you to target specific keywords. You’d create a page optimized for “healthy meal prep ideas” and try to rank for that phrase.

But what happens when people are instead searching for “what to cook for dinner when I’m trying to lose weight”?

The answer might involve healthy meal prep as a solution, but it’s a completely different prompt (not a search) that gets to that answer (not a SERP).

When you run these queries through Google’s AI Mode, you see two totally different sets of sources and content types.

For the “healthy meal prep ideas” query (which is a perfectly valid and searchable term), the focus is listicles, single recipes, and YouTube videos. And the format is categories (bowls, wraps, and sandwiches etc.) with specific recipes:

But for “what to cook for dinner when I’m trying to lose weight,” the sources are primarily lists, forum results, or articles specifically around weight loss.

In this case, the format of the answer is largely broad tips for cooking healthily and then some general cooking styles or meal types, rather than specific recipes:

As more users realize they can use conversational language to make their searches, longer queries will become more common. This makes this kind of intent analysis critical.

These longer, more specific queries represent huge opportunities. Most companies aren’t creating content that answers these detailed questions.

The more specific the question, the more likely you are to show up when AI systems look for authoritative answers. You want to own the long-tail queries that relate directly to your product or expertise.

But:

You obviously can’t reasonably expect to create content for every single long-tail query out there. So how do you approach this in an efficient way?

How to Choose the Questions to Answer

Start by listening to the actual questions your customers ask.

Check your customer support tickets, sales calls, and user feedback. These real questions from real people often make the best content topics — because they’re the same kinds of questions people will ask these AI tools.

Don’t have any customers? No problem.

Use community platforms to find these conversational queries. Reddit, Quora, and industry forums are goldmines for discovering how people actually talk about problems in your space.

Step 6. Structure Your Content for Answer Engines

AI systems process information differently than humans do. They break content into chunks and analyze how those pieces relate to each other.

Think of it like featured snippets but more granular, and for much more than just direct questions.

This means the way you structure your content directly impacts whether AI systems can understand and cite it effectively.

Note: A lot of what I say below is just good writing practice. So while this stuff isn’t necessarily “revolutionary,” these techniques are going to become more important as you focus on AEO
.

One Idea per Paragraph

Keep your paragraphs short and focused on one main idea.

When you stuff multiple concepts into a single paragraph, you make it harder for AI systems to extract the specific information they need.

Also avoid burying important information in the middle of long sentences or paragraphs. Front-load your key points so they’re easy to find and extract.

And guess what?

It also makes it easier for your human readers to understand too. So it’s a win-win.

Use Clear Headings

Use clear headings and subheadings to organize your content logically.

Think of these as signposts that help both readers and LLMs navigate your information. And make sure your content immediately under the headings logically ties to the heading itself.

For example, look at the headings in this section. Then read the first sentence under each one.

Notice how they’re all clearly linked?

This is a common technique when trying to rank for featured snippets. You’d have an H2 with some content that immediately answers the question…

…and this would rank for the featured snippet for that query:

This is still a valid strategy for traditional search. But for AEO, you need to have this mindset throughout your content.

Don’t make every H2 be a question (this will quickly end up looking over-optimized). But do make sure the content that follows your (logical) headings is clearly linked to the heading itself.

Break Up Complex Topics into Digestible Sections

If you’re explaining a complex or multi-step process, use numbered steps and clear transitions between each part.

This makes it easier for AI systems to pull out individual steps when someone asks for specific instructions. And it’ll make it much easier for your readers to follow.

Also write clear, concise summaries for complex topics. AI systems often look for these kinds of digestible explanations when they need to quickly convey information to users.

Include Quotes and Clear Statements

Include direct quotes and clear statements that AI systems can easily extract.

Why is this worth your time?

Because pages with quotes or statistics have been shown to have 30-40% higher visibility in AI answers.

So instead of saying “Email marketing could be an effective channel for your business,” write “Email marketing generates an average ROI of $42 for every dollar spent.”

Note: Don’t just flood your content with quotes and stats. Only include them when they actually add value to your content and are useful for your readers.

Use Schema Markup

Schema markup gives you another way to structure information for machines. This code helps systems understand what type of content you’re presenting.

For example, FAQ schema tells algorithms that you’re answering common questions. HowTo schema identifies step-by-step instructions.

You don’t need to be a developer to add schema markup. Many content management systems (like WordPress) have plugins that handle this automatically.

Make It Scannable

Use formatting like bold text to highlight important facts or conclusions and make it easier for readers to skim your content. This helps both human readers and AI systems identify the most important information quickly.

This has always been a big focus of content on Backlinko. We use lots of images to convey our most important points and add clarity through visualizations:

And we use clear headings to make our articles easy to follow:

The goal is to make your content as accessible as possible to both humans and machines. Well-structured content performs better across all types of search and discovery.

And if your content is enjoyable to engage with, it’s probably going to do a better job of converting users into customers as well.

Step 7. Track Your Visibility in LLMs

How often are tools like ChatGPT, Perplexity, or Gemini mentioning your brand?

If you’re not tracking this yet — you should be.

Tracking your visibility in AI-generated responses helps you understand what’s working and where you need to focus your efforts.

But where do you start? And what should you track?

Manual Testing as a Starting Point

Start with manual testing. This is the simplest way to see how you’re performing right now.

Ask the same questions across different AI platforms, like ChatGPT, Claude, Perplexity, and Google (both AI Mode and AI Overviews). Take screenshots of the responses and note which sources get cited.

Do this regularly, and you’ll start to see patterns in which types of content get mentioned and how your visibility changes over time.

Honestly though: you’re going to struggle to get a lot of meaningful data doing this manually. And it’s not scalable. Plus, so much of what an AI tool outputs to a user depends on the previous context, like:

• Past conversations
• Previous prompts within the same conversation
• Project or chat settings

This makes it challenging to get truly accurate data by yourself. This is really more of a “feel” test that, in the absence of dedicated tools, can provide a very rough idea of how answer engines perceive your brand.

Use LLM Tracking Tools

For more comprehensive tracking, dedicated tools can automate this process.

Platforms like Semrush Enterprise AIO help you track your brand’s visibility across AI platforms like ChatGPT, Claude, and Google’s AI Overviews.

It shows you exactly where you stand against competitors and gives you actionable steps to improve.

Competitive Rankings is my favorite feature. Instead of guessing why competitors might rank better in AI responses, you get actual data showing mention frequency and context.

Another option is Ziptie.dev. It’s not the most polished tool yet, but they’re doing some really interesting work — especially around surfacing unlinked mentions across AI outputs.

If you already have Semrush, then the Organic Research report within the SEO Toolkit does provide some tracking for Google AI Overviews specifically.

You can track which keywords you (or your competitors) rank for that have an AI Overview on the SERP. If you don’t currently appear in the overview, that’s a keyword worth targeting.

Tracking the keywords you do rank for in these AIOs over time can help you gauge the performance of your AEO strategy.

Why Talk to Your Boss (or Clients) About AEO?

You’ve seen the steps. Now you need a story.

AEO isn’t just a tactical shift — it’s a way to explain what’s changing in search without resorting to hype.

AEO helps you frame those changes clearly:

• Traditional SEO still works
• Your past investments are still paying off
• But the bar is higher now
• Visibility means more than rankings
• Your brand needs to be mentioned, cited, and trusted across every channel

AEO gives you the framework to explain what’s changing and how to stay ahead of it.

You Need to Start Now to Stay Visible

This space is evolving fast. New capabilities are rolling out monthly.

The key is to start tracking now so that you can benchmark where you are and spot new opportunities as AI search matures.

Grow your presence by adding a AEO approach on top of your SEO efforts:

• Continue optimizing for strong rankings and authority (AI still leans on this)
• But now, prioritize content and signals that AI engines are more likely to reference directly

Want to learn more about where the world of search is heading? Check out our video with Backlinko’s founder Brian Dean. We dive into how search habits are changing and how you can build a resilient, multi-channel brand.

The post Answer Engine Optimization (AEO): How to Win in AI Search appeared first on Backlinko.

2025-09-11 23:10:56

I analyzed over one million keywords across 10 industries.

The average cost per click (CPC) for Google Search ads in 2025 is $8.34. And the median CPC is $4.52.

Legal had the highest average CPC at $22.75.

Ecommerce had the lowest, at just $0.82 per click.

But there’s no flat rate for CPC.

Even if two advertisers bid on the same keyword, they won’t pay the same.

Costs can vary based on several factors — and CPC is just one part of the equation.

Google Ads pricing also involves other expenses that can affect your total budget.

In this guide, you’ll learn:

• How much Google Ads really cost
• What your budget should be
• How you can lower your ad costs (without hurting results)

Let’s dive in.

How Much Does a Google Ad Cost?

Google Ads can cost anywhere from $500 to $100,000 per month.

There’s no fixed rate. And CPCs can change from year to year based on competition and demand in your industry.

That’s why you set the budget that makes sense for your goals.

When I worked at marketing agencies, I’d see brands start with as little as $200 per month.

But in most cases, that isn’t enough to generate real data to measure performance, optimize targeting, or drive consistent leads.

It’s recommended to start with at least $500 a month.

I asked Sam Maugans (a PPC Director and Business Owner, FourHorse Digital LLC) how much does it cost for Google Ads. He said:

“Smaller companies can run remarketing campaigns for as little as $500 per month. Medium-sized businesses usually start out at around $5,000 and, with good performance, can increase their monthly budgets all the way up to $50,000. Similarly, larger businesses may start at $5,000 and over the years work their way up to $100,000 and even $1,000,000 a month.”

I talked to other experts as well.

Here’s what a typical monthly budget looks like, based on business size:

• Small business: From $500 to $5,000 per month
• Mid-size business: From $5,000 to $50,000 per month
• Large business: From $25,000 to $100,000+ per month

In the end, what you spend depends on how aggressive your goals are.

If you want more clicks and leads, you’ll need a larger budget to reach enough of the right people.

You can’t expect to generate 100 high-quality SaaS leads with just $500 a month. That kind of reach takes more spending.

And remember, not all clicks are equal.

A higher CPC can still be worth it if it brings in better-quality leads that are more likely to convert.

Use our Google Ads Budget Estimator to calculate your starting budget. Just plug in your CPC, lead goals, and conversion rate.

What You’re Paying for With Google Ads (and Why It’s Not Fixed)

Google doesn’t charge you to show your ad.

You only pay when someone clicks. That’s why it’s called pay-per-click (PPC).

This model mainly applies to Search ads, where you bid on keywords.

But other ad formats (like Display, YouTube, and Shopping) use different pricing.

Some charge you per view. Others per 1,000 impressions.

(We’ll cover this when we break down campaign types later in the guide.)

Still, all of them run on one thing: Google’s ad auction.

Every time someone searches, there’s a lightning-fast auction to decide whose ad shows and what they pay for that click.

For example:

Let’s say someone searches “divorce lawyer near me.” And they click on a Google search ad.

That single click could cost around $8.43 in the U.S.

But if they search for something like “dog groomer near me,” that click might only cost $1.35.

Same platform. Same system. Very different costs. Because the value of each click is different.

But here’s the thing:

You don’t always pay the amount you bid.

When you run a campaign, you set a maximum bid, which is the most you’re willing to pay for a click.

But what you pay is usually less.

That’s because Google’s auction considers more than just your bid when deciding which ad shows up and at what price.

So, what affects the cost of Google Ads beyond your max bid?

Let’s break down the seven biggest factors.

Factors That Impact Your Cost Per Click

How much Google Ads costs isn’t set in stone.

Your CPC can change dramatically depending on these seven factors:

Your Industry

Your cost per click depends heavily on the industry you’re in.

When I analyzed over one million keywords across 10 industries, the differences were huge.

Some industries consistently came in high. Because the value of a single lead is massive.

Others stayed low, likely due to lower margins or less commercial intent.

Here’s a breakdown of the average and median CPC for each industry in the dataset:

To put that into perspective:

A click for “dog bite lawyer san jose” costs around $229.

A click for “keto diet nutritionist” costs about $0.85

That’s not just a pricing difference. It reflects the value of a lead in each industry.

If you’re in a high-cost niche like legal, finance, or SaaS, you’ll need a bigger budget to compete.

But if you’re in ecommerce or real estate, your clicks are cheaper. And you can start smaller.

Methodology

This data is based on a sample of over one million keywords pulled from Semrush’s U.S. database (July 2025.)

We analyzed keywords across 10 industries, using between 7 and 35 seed keywords per industry, and extracted up to 30,000 related terms for each. (Keywords with zero search volume were removed.)

The final mix of commercial, transactional, navigational, and informational search queries gave us a realistic snapshot of what businesses pay to advertise on Google Search ads.

The Types of Keywords You Target

Different types of keywords affect how much you pay.

They vary by:

• Intent: Is the person ready to buy, or just looking for information?
• Length: Broad terms vs. long, specific phrases
• Match type: How closely a search needs to match your keyword

Broad, generic terms like “plumber” are comparatively affordable.

But, they’re less targeted. And often trigger your ad for searches that don’t match what you offer.

More specific terms like “emergency plumber in Chicago” tend to cost more.

But those clicks are from people who are ready to take action.

Match types also affect your cost:

• Broad match: Your ad can show for related terms, even if they don’t match exactly
• Phrase match: Your ad shows when the search includes your exact phrase
• Exact match: Your ad only shows for that specific keyword (or close variations)

Broad match usually brings cheaper clicks, but lower-quality traffic.

Exact match costs more, but tends to drive better results.

The more specific your targeting, the higher your cost per click is likely to be.

But you’ll waste less budget and attract people who are actually ready to buy.

That’s why keyword type plays a major role in how much an ad costs on Google.

Further reading: 7 Steps to Selecting High-Converting PPC Keywords

Location and Device Targeting

Where your ad runs — and on which device it appears — can affect your cost per click.

Targeting a competitive city usually means higher bids.

For example, the search term “plumber near me” costs $62.67 per click in Austin, Texas.

In Lincoln, Nebraska, that same keyword costs just $20.11.

Why?

Fewer advertisers. Less bidding. Lower CPC.

Similarly, device targeting affects cost as well.

Google Ads lets you set different bids for mobile, desktop, and tablet traffic.

Each device type can have its own CPC, depending on competition and performance.

For instance, if more advertisers are targeting mobile, clicks on mobile can cost more.

Or, if desktop traffic converts better in your industry, advertisers may bid higher there, which results in higher CPC.

Campaign Type (Search, Display, Shopping, YouTube)

So far, I’ve focused on Search ads, where you bid on keywords and pay when someone clicks.

That’s the most common format.

In fact, when most people say “Google Ads,” they’re usually talking about Search.

But Google Ads includes other campaign types too. And they’re priced differently.

With YouTube ads, your video can appear before, during, or after another video on YouTube.

You usually pay when someone watches a part of your ad. This is called cost-per-view (CPV).

Display ads are shown across Google’s Display Network, which includes websites and apps that run Google ads.

They’re often priced by impressions.

You’re charged per 1,000 views of your ad. Even if no one clicks.

Shopping ads show up in Google search results. But instead of text, they pull product images, prices, and titles from your product feed.

These ads are click-based, like Search. So, you pay every time someone clicks on it.

Each campaign type targets people differently. And Google Ads pricing varies depending on whether you’re running search, display, shopping, or YouTube ads.

That’s why your campaign type has a direct impact on how much you’ll pay.

Your Quality Score

Google doesn’t just look at your bid. It also scores the quality of your ad.

This is called Quality Score — a number from 1 to 10 that Google assigns to each keyword you target.

It’s based on:

• Expected click-through rate (CTR)
• How relevant your ad is to the keyword
• Your landing page experience

Each factor is graded as “Above average,” “Average,” or “Below average” compared to all other advertisers on Google Ads.

These ratings combine to form your overall Quality Score.

The higher your score, the less you pay for the same position.

The lower your score, the more you’ll need to bid to compete.

That means two advertisers can target the same keyword, but the one with the better ad and landing page might pay less per click.

This shows how much Google Ads costs is influenced by far more than your bid.

Your Bidding Strategy

Google Ads gives you two main ways to bid: manual or automated.

With manual bidding, you set the maximum amount you’re willing to pay for a click.

It works best when you already have historical data and know your ideal CPC. You’re in full control, but it takes more time to manage.

With automated bidding, you let Google set your bids based on your goals.

It tends to work better at scale, once Google has enough data to optimize toward those goals. That could be getting the most clicks, driving more conversions, or hitting a target cost per lead.

Here are the most common automated strategies and when to use them:

• Maximize Clicks: Good for driving traffic quickly, especially in early testing
• Maximize Conversions: Best when your goal is to get as many leads or sales as possible within budget
• Target CPA: Works well when you know your ideal cost per lead or sale
• Target ROAS: Best for ecommerce or campaigns where revenue tracking is set up, and you want to hit a specific return

If Google sees strong signals that a searcher is likely to convert, it may raise your bid automatically. Which can lead to higher CPCs.

Manual gives you more control. Automated gives you speed and scale.

The more control you want, the more work it takes. But giving up control may mean paying more.

Either way, your bidding strategy directly impacts what you pay. And how efficiently your budget gets spent.

How Your Account Is Set Up

Here’s a basic structure of a Google Ads account:

You create a campaign.

Inside that campaign are ad groups.

Each ad group includes a set of keywords, a specific ad, and a matching landing page.

Why does this matter? Because Google ranks your ad based on a combination of factors, including relevance.

And relevance depends on how tightly those elements match.

Let’s say you run one ad group for all your services: plumbing, HVAC, and electrical.

You use one ad and one landing page for all of it.

To Google, that looks messy. The ad isn’t specific. The landing page isn’t focused.

Someone searching for “emergency plumbing repair” sees a generic ad for “Plumbing, HVAC & Electrical Services.”

They land on a page trying to cover everything at once.

Relevance drops. So does your Quality Score. This results in a higher cost per click.

Now take the same budget and split those services into separate ad groups. Each with its own focused keywords, ad, and landing page.

Suddenly, your ads are more relevant. And Google rewards you with lower CPCs.

Other Costs Beyond Your CPC

Running Google Ads often comes with expenses outside of what you pay per click.

These can add up quickly:

• Tools and software: Keyword research platforms, landing page builders, or call tracking tools can cost $50–$300+ per month, but they help improve campaign performance
• Creative assets: Copywriting, landing page design, graphics, or video production. High-quality creative can boost CTR and conversions, but may require a few hundred to several thousand dollars.
• Management fees: Whether you hire a freelancer, agency, or in-house specialist, expect to budget $100 to $10,000+ monthly, depending on scope

Looking to hire a PPC agency or freelancer?

Download our Google Ads Vendor Evaluation Sheet to know exactly what questions to ask and what red flags to avoid.

How Much Should You Budget for Google Ads?

Start with a test budget.

Many small businesses begin with $500 to $5,000 in their first month.

That’s usually enough to get real traffic, measure early performance, and understand what’s working.

Set a number you’re comfortable testing. Then, apply that as your monthly cap inside Google Ads.

For example, $900 = $30/day.

But be cautious not to spread your budget too thin, says Kalo Krastev, Team Lead Performance Marketing (SEA) at ImmoScout24

“Small-budget Google Ads accounts struggle the most, because lower investment means a slower learning curve. A small business owner should plan a short, cost-intensive testing phase to figure out what works, like search terms, settings, and targeting.”

Let’s say you spend $1,000 and get 250 clicks.

If your site converts 1 in 25 visitors, that’s 10 customers at $100 each.

If your average sale brings in $300, that’s a 3X return.

• If your numbers look good, increase your monthly budget by 10-20%. (That’s enough to grow your reach without overspending too quickly.)
• If performance is weak, don’t increase the budget. Instead, review your targeting, ad copy, and landing page to find what’s holding things back.

Once your campaign is converting reliably, scaling up becomes simple.

You’ll know what you’re paying to get a customer. And how much more can you spend to get more of them.

As you scale, be careful not to bleed cash.

Here are some signs that you’re overspending on Google Ads:

• Cost per lead or customer is higher than your profit margin
• You’re paying for clicks on irrelevant keywords
• Campaigns run 24/7, but most conversions happen at certain times
• CTR is dropping while spend stays the same or increases

If you spot these, analyze your campaigns and take steps to lower the cost. Start with the tactics in the next section.

Note: Download our Google Ads Budget Estimator to calculate the budget for your first Google search ad campaign.

6 Ways to Lower Your Google Ads Costs

Spending more doesn’t always get you better results.

In fact, most small businesses overpay for clicks without realizing it.

I saw this all the time with the agency clients — campaigns wasting money on keywords or placements that had no chance of converting.

The good news?

You can bring your costs down without turning off campaigns or cutting corners.

Here are six ways to do that:

1. Improve Quality Score

Google Ads uses Quality Score to assess the quality of an ad.

Improving this score can help lower your cost per click.

Relevance is a big part of the equation.

Your ad should match what the person is searching for — both in wording and intent.

For example, someone searching for “roof leak repair” is more likely to click on an ad that says “Roof Leak Repair: Book a Local Pro” than something generic like “Plumbing and Roofing Services.”

You can also make your ad more clickable by adding assets like site links, callouts, or structured snippets.

These help your ad stand out in search results and attract more qualified clicks.

Your landing page needs to deliver a good experience, too.

It should load fast, work well on mobile, and convey the same message.

If the page feels off-topic or slow, your score drops and your costs go up.

When your keyword, ad, and landing page all align, it may increase your Quality Score and lower your CPC.

2. Use Negative Keywords to Stop Paying for Useless Clicks

Not every click is a good click.

Your ad might show up for searches that sound relevant, but aren’t.

For example: You sell premium leather sofas, but your ad shows for “free leather sofa giveaway.”

Someone clicks, you pay…and they bounce.

Negative keywords help you block that.

They tell Google: “Don’t show my ad if this word is in the search.”

Before you launch, consider adding common negatives like:

• “jobs” (people looking for employment)
• “template” or “example” (informational searches)
• “how to” (DIY intent)
• “free” (no intent to buy)

Here’s how adding “free” as a phrase match negative keyword blocks irrelevant searches:

Take some time to identify more negative keywords that are irrelevant to your offering and may not lead to conversions.

After your ads run, check the “Search terms” tab inside Google Ads.

It shows a list of terms that triggered your ad.

If you see anything that doesn’t match your offer, looks irrelevant, and has low conversions, add it to your negative keyword list.

3. Focus on Long-Tail Keywords with Higher Intent

Long-tail keywords are longer, more specific search phrases — usually 3 to 5 words.

And unlike short, generic keywords, they make it clear what the searcher actually wants.

Think:

• “roof leak repair near me” instead of just “roofing”
• “tax accountant for freelancers” instead of “accountant”

These get fewer searches.

But they’re cheaper, have less competition, and usually convert better.

Why?

Because someone searching for a long-tail keyword is further along in their journey. They’re not just browsing. They’re ready to act.

So, instead of going after broad, high-cost terms, focus your budget on these high-intent searches.

You can use Semrush’s Keyword Magic Tool to find long-tail keywords.

Open the tool, enter your seed phrase (e.g., “roof repair”), choose your target location, and click “Search.”

You’ll see a long list of keyword ideas.

Next, we’ll narrow it down using filters.

• Phrase Match: This keeps results closely related to your original phrase
• KD %: Set “To” as 29 to filter for low-competition keywords
• Advanced filters > Word Count: Set “From” as 3 to show only longer phrases
• Intent: Choose “Commercial” and “Transactional” to focus on buyers
• Exclude keywords: Remove irrelevant terms like “free” or “jobs”

Now you’re looking at a refined list of long-tail, high-intent keywords.

This is how you avoid broad, expensive clicks. And focus your budget on searchers who are ready to act.

4. Target Specific Locations to Lower Competition

One of the easiest ways to waste money on Google Ads?

Targeting a too-broad area.

If you’re a local business (or serve just a few regions), you don’t need your ads to show in places you don’t operate.

Running ads across a large area means more competition.

But narrowing your location targeting often leads to lower CPCs and better leads.

For example: Instead of targeting all of Texas, narrow it down to just the Dallas-Fort Worth area.

You’ll avoid competing with advertisers in Houston, Austin, and San Antonio — who are all bidding on the same keywords.

Same campaign. Same budget. Less competition.

Inside Google Ads, you can target by city, region, zip code, or even a radius around your address.

Start by focusing your budget where your best customers are.

You’ll cut waste and make your ad spend go further.

5. Run Ads When Your Customers Are Most Likely to Convert

Google’s Smart Bidding is smart, but it’s not magic.

If you’re running ads 24/7, it won’t automatically stop spending at 2 a.m. — even if those clicks rarely turn into customers.

That’s where ad scheduling comes in.

If you run a local business or only serve customers during specific hours, you don’t want to pay for clicks when no one’s around to respond.

For example:

If you’re a plumber or accountant and someone clicks your ad at 11 p.m., but your office opens at 9 a.m., they’ll probably move on before you can follow up.

In Google Ads, you can set your campaign to only run during your business hours.

You can also use the “Hour of the day” report to see exactly when conversions happen. So you can schedule your campaign based on real performance data.

Once you’ve got data, you can expand to early mornings or weekends if performance is strong.

Less waste. Better timing. Same budget.

6. Test Your Landing Pages to Maximize Budget

If you’re getting 100 clicks and only 2 leads, that’s not a CPC problem.

That’s a landing page problem.

The best ad in the world won’t help if the page people land on doesn’t convert.

I’ve worked with clients where we didn’t change the ad at all. Just added a few bullet points near the top of the page.

That one small tweak doubled their conversion rate.

Small changes like that can make a big difference in how many leads you get from the same ad spend.

For starters, you can tweak different parts of your landing page: the headline, form length, call to action, or how quickly your value is explained.

Here’s a simple landing page template to capture leads:

You can also add trust signals to make visitors feel safe enough to convert, like:

• Customer reviews
• Media mentions
• Money-back guarantees
• Security badges

If you want to go further, create two versions of your landing page: Version A and Version B.

Change just one thing between them.

Then, send traffic to both and see which one gets more leads.

When your conversion rate increases, your cost per lead goes down. This increases your ROI.

Try Landing Page Builder from Semrush to create new landing pages and run A/B tests.

Further reading: Landing Page Guide: Create Pages That Convert Super Well

What to Do Before You Launch Your First Google Ads Campaign

Google Ads can feel simple on the surface: set a budget, write an ad, go live.

But if you skip a few key steps before launch, your budget can disappear fast.

I’ve seen businesses launch campaigns without setting up conversion tracking.

Some forgot to set their location targeting and showed ads in cities they don’t even serve. Others launched without a daily budget cap and burned through hundreds in a single day.

Small misses like that lead to wasted clicks, high costs, and zero results.

That’s why I created a pre-launch checklist.

It walks you through the exact steps to take before your first campaign goes live across Search, Shopping, Display, and YouTube.

Download the Google Ads Pre-Launch Checklist

Ready to Create Your First Google Ad Campaign?

Start with a small, focused budget.

Use month one to get clicks, see what’s working, and spot what’s not.

Then, improve from there based on real data.

Use our Google Ads Budget Estimator to calculate your starting budget.

And once you’re ready to launch, use our Pre-Launch Checklist to set up your campaign the right way.

Check out this guide for the next steps: How to Run Google Ads: A 10-Step Guide

The post How Much Does Google Ads Cost? (2025 Data + Insights) appeared first on Backlinko.

2025-09-10 22:04:05

AI is already reshaping how buyers discover and choose brands.

When someone asks ChatGPT or Google AI Mode about your category, two things happen:

• Brands are mentioned in the answer
• Sources are cited as proof

Most companies get one or the other. Very few win both.

And that’s the problem.

According to the latest Semrush Enterprise AI Visibility Index, only a small fraction of companies appear in AI answers as both seen (mentions) and trusted (citations).

That gap is the opportunity.

We’re proposing the Seen & Trusted (S&T) Framework — a systematic approach to help your brand earn mentions in AI answers and citations as a trusted source.

Do both, and you multiply visibility, trust, and conversions across platforms like ChatGPT, Google AI Mode, and Perplexity.

SEO remains the foundation.

But AI doesn’t just look at your site. It pulls signals from review platforms, Reddit threads, news coverage, support docs, and community discussions.

When those signals are fragmented, your competitors will own the conversation.

This guide shows you exactly how to fix that with two playbooks:

• Get Seen: Win favorable mentions in AI answers
• Be Trusted: Earn citations as a reliable source

Run them together and you give AI no choice but to recognize, reference, and recommend your brand.

Why AI Search Strategy Isn’t Just SEO’s Job

Your SEO team can optimize every page on your site and still lose AI visibility to a competitor with weaker rankings but stronger brand signals.

Why? Because AI systems pull signals from everywhere, not just your website.

When AI generates responses, it mines:

• Review platforms for product comparisons
• Reddit threads for pricing complaints
• Developer forums for implementation details
• News sites for company credibility
• Support docs for feature explanations

The challenge is that these signals live across different teams.

For instance, your customer success team drives customer reviews on G2 and Capterra. But if they’re not tracking review quality and detail, AI has nothing substantive to cite when comparing products.

Similarly, your product team controls whether pricing and features are actually findable. Hide everything behind “Contact Sales” forms, and AI will either skip you entirely or make assumptions based on old Reddit threads.

Your PR team lands media coverage and analyst reports. These third-party mentions build the trust signals AI systems use to determine authority.

Your support and community teams shape what gets said in forums and Discord servers. Their responses (or silence) directly influence how AI understands your product.

SEO and content teams own the site structure and content creation. But that’s just one piece now.

Without coordination, you get strong performance in one area, killed by weakness in another.

To grow AI visibility, you need synchronized campaigns — not just an “optimize for AI” line item tacked onto everyone’s OKRs.

That’s where the Seen & Trusted Framework comes in. It gives every team a role in building the signals AI depends on.

Note for enterprises: Cross-departmental coordination is challenging.

Fortunately, any progress each team makes in their area directly improves AI visibility.

Better reviews? You win. More transparent pricing? You win. Active forum engagement? You win. It all compounds.

This guide can be your internal business case. Forward the data on AI visibility gaps to stakeholders who need to see the competitive threat.

Solve this, and you’ll gain a big edge over competitors who are stuck in silos.

Playbook 1 – How to Get Seen (The Sentiment Battle)

Getting “seen” means showing up in AI responses as a mentioned brand, even without a citation link.

When a user asks ChatGPT, “What are the best email marketing tools?” they get names like HubSpot, ActiveCampaign, and MailChimp.

These brands just won visibility without anyone clicking through.

But here’s a challenge:

You’re fighting for favorable mentions against every competitor and alternative solution.

This is the sentiment battle.

Because AI doesn’t just list brands. It characterizes them.

You might get mentioned as “expensive but comprehensive” or “affordable but limited.”

Like here, when I asked ChatGPT if ActiveCampaign is a good option:

In some cases, the response could be more negative than neutral. Like this:

These characterizations stick.

So, how can your brand get more mentions and have a positive sentiment around?

There are four main sources that AI systems mine for context.

Pro tip: Track how AI platforms perceive your brand using Semrush’s Enterprise AIO sentiment analysis.

It shows whether mentions across ChatGPT, Claude, and other LLMs are positive, neutral, or negative.

Step 1. Build Presence on the Right Review Sites

AI systems heavily weigh review platforms when comparing products. But not all reviews are equal.

A detailed review explaining your onboarding process carries more weight than fifty “Great product!” ratings.

AI needs substance, like specific features, use cases, and outcomes it can reference when answering queries.

G2 is one of the top sources for ChatGPT and Google AI Mode in the Digital Technology vertical, according to Semrush’s AI Visibility Index.

The platform gives AI everything it needs: reviews, features, pricing, and category comparisons all in one place.

Slack ranks among the top 20 brands by share of voice in AI responses for the Digital Technology vertical.

Share of voice is a weighted metric from Semrush that reflects how often and how prominently a brand is mentioned across AI responses.

Part of that success comes from their G2 strategy.

When I ask ChatGPT, “Is Slack worth it?” it cites G2 as one of the sources.

Look at Slack’s G2 reviews and you’ll see why.

Its pricing, features, and other information are properly listed and up-to-date

Users write detailed reviews about channel organization, workflow automation, and integration setups.

G2 isn’t the only platform that matters.

• For B2B SaaS: G2, Capterra, and GetApp
• For ecommerce: Amazon reviews
• For local/service businesses: Yelp and Google Reviews

In my experience, the depth of the review matters just as much as the platform — if not more.

You’ll see many very detailed product reviews as a source in AI answers from sites with low domain authority.

So, what does this mean in practice?

You need reviews from customers. And your review strategy needs four components:

• Timing: Email customers after they’ve used your product enough to give meaningful feedbac, but while the experience is still fresh
• Templates: Provide prompts highlighting specific features to discuss. “How did our API save you development time?” beats “Please review us.”
• Incentives: Reward detail over ratings. A $XX credit for reviews over 200 words can generate more AI-friendly content
• Engagement: Respond to every review. AI systems recognize vendor engagement as a trust signal.

Step 2. Participate in Community Discussions

Community platforms are where real product conversations happen. And AI systems are listening.

• Reddit threads comparing alternatives
• Stack Overflow discussions about implementation
• Quora answers explaining use cases

These unfiltered conversations shape how AI understands and recommends products.

Reddit and Quora consistently rank among the top sources cited by ChatGPT and Google AI Mode across industries.

Like in the Business & Professional Services vertical here:

Online form builder Tally is a great example of dominating community discussions and winning the AI search.

AI-powered search is now their biggest acquisition channel, with ChatGPT being their top referrer.

This is their weekly signup growth of the past year, driven by AI search:

How are they doing this?

Marie Martens, co-founder of Tally, writes:

“Inclusion of web browsing is turned on by default, which made forums, Reddit posts, blog mentions, and authentic UGC part of the AI’s source material… We’ve invested for years in showing up in those places by sharing what we learn, answering questions, and being human.”

Here’s Marie talking about her product on Reddit:

And answering users’ questions:

And partaking in ongoing conversations:

This authentic engagement creates the context AI needs.

So, when I ask ChatGPT what’s the best free online form builder, it mentions (and recommends) Tally.

Big brands like Zoho take part in Reddit discussions as well. To answer questions, address concerns, and control their brand sentiment.

Like here:

Zoho ranks among the top brands by share of voice in ChatGPT and Google AI Mode responses. Just behind Google.

The community platforms like Reddit, Overflow, Quora, and even LinkedIn matter a lot in AI visibility:

Your community and customer success teams should be active on these platforms.

But presence alone isn’t enough.

Your strategy needs authenticity.

How?

• Answer questions even when you’re not the solution
• Address common misconceptions about your product (don’t let misinformation take over threads)
• Share your actual product roadmap, including what you won’t build
• Give detailed, honest responses to user complaints, even if it means acknowledging past mistakes
• Encourage your product, support, or founder teams to answer technical or niche questions directly

AI systems can detect promotional language. They prioritize helpful responses over sales pitches.

The brands winning community presence treat forums like customer support, not marketing channels.

Step 3. Engineer UGC and Social Proof

User-generated content and social proof create a feedback loop that AI systems amplify.

• When customers share their wins on LinkedIn
• When users post before-and-after case studies
• When teams document their workflows publicly

…all of this becomes training data.

Brands with strong community engagement and visible social proof see higher mention rates across AI platforms.

Patagonia is a fitting example here.

When I ask ChatGPT about sustainable outdoor brands, Patagonia dominates the response.

In fact, Patagonia holds the highest share of voice in AI responses for the Fashion and Apparel vertical.

They consistently appear in discussions around “ethical fashion” and “sustainable brands.”

Not because they advertise, but because customers evangelize. And that advocacy is visible everywhere.

Customers regularly mention their positive experience with Patagonia’s exchange policy.

There are countless positive articles written on third-party platforms about their products.

And on social platforms like Instagram.

These real-world endorsements are the kind of social proof AI recognizes and amplifies.

No wonder Patagonia has a highly favorable sentiment score (according to the “Perception” report of the AI SEO Toolkit).

So, how do you get people creating content (and proof) that AI pays attention to?

• Encourage customers to leave ratings on trusted third-party sites
• Partner with micro-influencers to share authentic product stories, tips, and reviews in their own voice
• Invite users to post before-and-after results or creative use cases
• Design features or experiences users want to show off (like Spotify Wrapped)
• Reward customers who share feedback or use cases publicly (early access, shoutouts, or swag)
• Reply to every public mention or tag because AI recognizes visible engagement

The mistake most brands make?

Asking for just testimonials instead of conversations.

Don’t ask customers to “share their success story.” Ask them to help others solve the same problem they faced.

The resulting content is authentic, detailed, and exactly what AI systems look for.

Step 4. Secure “Best of” List Inclusions

Comparison articles and ‘best of’ lists are key sources for AI citations.

When TechRadar publishes an article on top “Project Management Tools for Remote Teams,” that article becomes source material for hundreds of AI responses.

When Live Science reviews running watches, those comparisons train AI’s product recommendations.

These third-party validations carry more weight than your own content ever could.

In fact, sites that publish “best of” listicles consistently appear as top sources for AI platforms — including Forbes, Business Insider, NerdWallet, and Tech Radar.

Garmin is a perfect example.

Their products appear in virtually every “best GPS watch” article across running, cycling, and outdoor publications.

Like in this Runner’s World article:

Or this piece in The Great Outdoors:

But what makes their strategy work is consistency across platforms.

Yes, the specs are the same by nature.

But what stands out is how consistently those specs, features, and images appear across independent sites.

That repetition reinforces trust for AI systems, which see the same details confirmed again and again.

So, when I ask ChatGPT, “Which is the best GPS watch?” it mentions Garmin.

And it doesn’t stop there. It highlights features that other third-party articles emphasize, like battery life, accuracy, solar charging, and water resistance.

This consistency across independent sources is why Garmin holds one of the highest shares of voice in ChatGPT and Google AI Mode responses for the Consumer Electronics vertical.

So, how do you land in these “best of” lists?

It starts with a great product. Without that, no list will save you.

That aside, you need to make journalists’ jobs easier. Most writers work under tight deadlines and will choose brands that provide ready-to-use assets over those that make them hunt.

So build a dedicated press kit page with specs, pricing, high-res images, and other assets.

Like Garmin does here:

Next, reach out to journalists and niche publications. Don’t wait for them to find you.

Timing matters a lot as well.

Most “best of” lists update annually. So, pitch your updates a few months before refreshes.

Also, don’t just target obvious lists. Focus on category expansion.

For instance, Garmin doesn’t just appear in “best GPS watch” roundups. They also feature in broader outdoor and fitness lists that cover running, cycling, and multisport gear.

That reach multiplies the mentions AI systems can cite.

The bottom line: AI visibility favors the brands that keep showing up in independent comparisons.

Secure those “best of” inclusions, and you increase your chances of being mentioned in AI answers.

Playbook 2 – How to Be Trusted (The Authority Game)

Getting mentioned is half the battle. Getting cited is the other half.

When AI systems cite your content, they’re not just naming you. They’re using you as evidence to support their answers.

Look at any ChatGPT or Google AI Mode response.

At the bottom or side, you’ll see a list of sources. These citations are what AI considers trustworthy enough to reference.

According to Semrush’s AI Visibility Index, certain sources dominate AI citations across industries. Like Wikipedia, Reddit, Forbes, TechRadar, Bankrate, and Tom’s Guide.

They have achieved, what I call, the “Citation Core” status.

Citation core (n.): A small group of sites and brands that every major AI platform trusts, cites, and uses as default sources.

Why do these platforms get cited so often?

AI systems trust sources with verified information, structured data, and established credibility. They need confidence in what they’re citing.

This is the authority game.

You’ve earned mentions through the sentiment battle. Now you need to build the trust that also earns you citations.

This is how you maximize your AI visibility.

Here are five ways to build that authority.

Step 1. Optimize Your Official Site for AI

AI platforms can only cite what they can crawl, parse, and understand.

If your details aren’t exposed in clean, readable code, you’re invisible. No matter how good your content is.

Use semantic HTML to structure your content.

That means marking up pricing tables, product specs, and feature lists with tags like <table>, <ul>, and <h2>.

Don’t tuck information inside endless <div>s or custom layouts that hide meaning.

Also, avoid relying on JavaScript to render your main content.

AI crawlers can’t read JavaScript.

If your pricing or docs load only after scripts fire or buttons click, those details will be skipped.

Almost every top-cited site in AI answers passes the Core Web Vitals assessment, which signals that the page loads fast, stays stable, and presents content in a clean structure.

Like Bankrate — the most cited source in Google AI Mode for the Finance vertical:

Or InStyle — the 8th most cited source on ChatGPT in the Fashion & Apparel vertical.

These sites consistently surface in AI responses because their pages are easy to crawl, fast to load, and simple to extract structured information from.

A lot of what you’ll do to optimize your site for AI is SEO 101.

• Structure all key information in native HTML elements (no custom wrappers)
• Keep important content visible on initial load (no tabs, accordions, or lazy-loaded sections)
• Use schema where it reinforces facts: pricing, product, FAQ, organization
• Run regular audits with JavaScript disabled to see what AI sees
• Minimize layout shifts and script dependencies that delay full render

For page-by-page analysis, you can use Google’s PageSpeed Insights.

To check your entire site’s health and performance, use Semrush’s Site Audit tool.

Get a detailed report showing technical issues on your website and how you can fix them.

At the end, you want a fast, stable, and easy-to-parse website.

That’s what earns AI citations.

Step 2. Maintain Wikipedia + Knowledge Graph Accuracy

AI systems rely on public data sources to build their understanding of your brand.

If that information is wrong, every answer AI generates about you will be too.

Wikipedia is one of the most cited sources on ChatGPT for all industries covered in Semrush’s AI Visibility Index.

Interestingly, Google AI Mode leans heavily on its Knowledge Graph to validate facts about companies and products.

When your Wikipedia page contains outdated info — or your Knowledge Graph shows old details — those inaccuracies get baked into AI responses.

That hurts trust, sentiment, and your chance of being cited in the long-term.

So your job is twofold:

1. Make sure your brand exists in these systems
2. Keep the data clean and current

Start with your Wikipedia page.

If you have one, audit it quarterly.

Fix factual errors, like outdated product names, revenue ranges, or leadership bios.

Support every edit with a credible third-party source: news coverage, analyst reports, or industry publications.

Wikipedia doesn’t allow brands to directly promote themselves. And promotional edits get removed.

But updates to fix factual errors usually stick. As long as you provide solid citations.

You can use the “Talk” page of your Wikipedia entry to propose corrections.

If you don’t have a Wikipedia page, you’ll need to meet notability guidelines.

That typically means coverage in multiple independent, well-known publications.

Once that’s in place, a neutral editor (not on your payroll) can create the page.

Next, fix your Knowledge Graph.

Google pulls its brand facts for its knowledge graph from multiple sources. Like Wikidata, Wikipedia, Crunchbase, social profiles, and your own schema markup.

Start by “claiming” your Knowledge Panel.

This means a knowledge panel already exists for your company when you search its name. You just have to claim it by verifying your identity.

If you don’t see one, you’ll need to feed Google more structured signals.

Start by adding or improving your Organization schema on your homepage.

Then, make sure your company has a proper Wikidata entry. Google may use this to build its Knowledge Graph.

Note: Adding your company to Wikidata is much easier than getting a full Wikipedia entry. But you still need to follow the guidelines. Stick to neutral language, avoid any promotional tone, and cite credible third-party sources.

A strong Wikipedia page and Google knowledge panel shape how AI understands your brand.

Get them right, and you build a foundation of factual authority that AI systems can trust.

Step 3. Publish Transparent Pricing

Hidden pricing creates negative sentiment that AI systems pick up and amplify.

When users can’t find your pricing, they turn to Reddit and LinkedIn. And the speculation isn’t always favorable.

For instance, Workaday doesn’t show its pricing.

And the Reddit comments aren’t helpful to its potential customers.

According to Semrush’s AI Visibility Index, when enterprise software hides pricing behind “Contact Sales,” AI uses speculative data points from Reddit and LinkedIn.

And it often links that brand with negative price sentiment.

Because AI systems are biased toward answering, even if it means citing speculation.

They’d rather quote a complaint from third-party sites about “probably expensive” than admit they don’t know.

Without clear pricing, you’re also excluded from value-comparison queries like “best budget option” or “most cost-effective for enterprises.”

Publishing transparent pricing creates reliable data that AI trusts over speculation.

Now I understand this isn’t always possible for every brand. Whether to show pricing depends on various other decisions and strategies.

But if you want to build trust for higher AI visibility and positive sentiment, transparent pricing is important.

Which means:

• Include tier breakdowns with feature comparisons
• Spell out annual vs. monthly options
• List any limitations or user caps
• Update your pricing on G2, Capterra, and other review sites

When reliable sources like your pricing page and G2 have clear information, AI stops turning to speculation.

That transparency becomes part of your brand identity and authority.

Step 4. Expand Documentation & FAQs

Your support docs and help center often get cited more than your homepage.

Because AI systems look for detailed, problem-solving content. Not marketing copy.

Apple holds one of the highest shares of voice in ChatGPT and Google AI Mode responses for the Consumer Electronics vertical.

Its support documentation appears consistently in AI citations across tech queries.

When I ask ChatGPT how to fix an iPhone issue, it cites support.apple.com.

Product documentation dominates citations in technical verticals.

Why?

Because it answers specific questions with step-by-step clarity.

Your product documentation is a citation goldmine if you structure it right.

Start by creating dedicated pages for common problems. “How to integrate [Product] with [Product]” beats a generic integrations page.

For example, Dialpad has dedicated pages for each app it integrates with.

And each page clearly explains how to connect both apps.

Next, write troubleshooting guides that address real user issues.

(You can learn about these issues from your sales teams, account managers, and social media conversations.)

Also, build a comprehensive FAQ library that actually answers questions. Not marketing-friendly softballs, but the hard questions users really ask.

Make sure every page is crawlable:

• Use static HTML for all documentation
• Create XML sitemaps specifically for docs
• Implement breadcrumb navigation
• Add schema markup for HowTo and FAQ content

The goal is to become the default source when AI needs to explain how your product works.

Not through SEO tricks, but by publishing the most helpful, detailed, accessible documentation in your space.

Step 5. Create Original Research That AI Wants to Cite

Original research gives AI systems something they can’t find anywhere else. Your data becomes the evidence they need.

Take SentinelOne as an example. It’s a well-known brand in cybersecurity.

They regularly publish threat reports, original data, and technical insights.

This is one of the reasons they often get cited as a source in AI responses.

In the intro, I said very few brands are both mentioned and cited by AI. Remember?

SentinelOne is one of those brands that has built dual authority.

According to Semrush’s AI Visibility Index, it’s the 15th most cited and 19th most mentioned brand in the Digital Technology vertical.

Because it publishes original insights that aren’t available anywhere.

And AI systems want: verified data, industry insights, and quotable statistics.

But not all research gets cited equally.

• Annual surveys with significant sample sizes (think: 500+) carry weight. But “State of [Industry]” reports based on 50 responses might not.
• Benchmark studies comparing real performance data become go-to references. But thinly-veiled sales pitches disguised as research might get ignored.

You can use your proprietary data to create original research reports.

Or team up with market research companies like Centiment that can help you collect data through surveys.

When creating these reports:

• Lead with key findings in bullet points
• Include methodology details for credibility
• Provide downloadable data sets when possible
• Add structured data markup for datasets

Also, promote findings through press releases and industry publications.

When Forbes, TechCrunch, and other leading publications cover your research, AI systems are more likely to notice.

Like this SentinelOne report covered by Forbes:

The compound effect here is powerful.

Your research gets cited by news outlets → which gets cited by AI → which drives more coverage → which builds more authority.

That’s how you go from being mentioned to being the source everyone (including AI) trusts.

Pulling It All Together – Running Both Playbooks

You’ve seen the framework. Now it’s time to execute.

Step 1. Audit Your Current AI Visibility

Start by understanding your baseline.

Run test queries in ChatGPT and Google AI Mode. Search for your brand, your category, your product, and the problems you solve.

Note where you’re mentioned (in the answer itself) and where you’re cited (in the source list). Screenshot everything.

If you’re using Semrush’s Enterprise AIO, you can use Competitor Rankings to see how often your brand shows up in AI answers compared to your competitors.

Step 2. Build Parallel Campaigns

Both playbooks need to run simultaneously.

You can’t wait to be “seen” before building trust.

• Playbook 1 (Seen): Customer success drives review campaigns. Community managers engage in forums. PR pushes for “best of” list inclusion.
• Playbook 2 (Trusted): Product publishes transparent pricing. SEO and engineering improve site structure. Support expands help content. Marketing creates original research.

The key is coordination.

Create a shared dashboard to track each team’s contributions to AI visibility.

Step 3. Monitor and Iterate

AI visibility shifts fast. What worked last month might not work today.

Track your mentions and citations monthly.

Use an LLM tracking tool like Semrush or a manual prompt list to see how you’re showing up (and how often).

Further reading: 5 LLM Visibility Tools to Track Your Brand in AI Search

Watch for imbalances.

Strong mentions but weak citations? Focus on authority signals from Playbook 2.

Cited often but rarely mentioned? Ramp up your community and sentiment work.

Also: watch your competitors. When someone jumps in AI visibility, reverse-engineer what changed.

New PR coverage? More reviews? A pricing update?

The brands winning AI search aren’t waiting for perfect strategies. They’re testing, learning, and adjusting faster than their competition.

The AI Visibility Window is Open

In addition to listing your brand, AI platforms influence what buyers see, trust, and choose.

And right now, AI visibility is anyone’s game. Only a few brands in each industry have cracked the code of being both mentioned and cited.

That means even established giants can be outmaneuvered if you move faster on AI strategy.

So while competitors debate whether AI search matters, you can build the presence that captures tomorrow’s buyers.

The Seen & Trusted Framework gives you the direction.

Run both playbooks. At once.

The post AI Search Strategy: The Seen & Trusted Brand Framework appeared first on Backlinko.

2025-08-25 21:41:01

If you do any kind of marketing, you’ve probably come across at least one of these acronyms recently:

• GEO: Generative Engine Optimization
• AEO: Answer Engine Optimization
• LLMO: Large Language Model Optimization
• AIO: Artificial Intelligence Optimization

Here’s the truth:

They all mean essentially the same thing.

But they are subtly different from SEO (search engine optimization). This article will tell you where they’re similar, where they’re different, and what you need to know as a marketer.

SEO vs. Everything Else Explained

There might be shades of nuance between these acronyms, but the goal with all of them is the same. They all aim to optimize your (or your client’s) online presence to appear in more AI responses in tools like ChatGPT, Perplexity, and Google’s AI Mode.

Okay, so if they’re so similar: why the need for all these acronyms in the first place?

Why All the Acronyms?

The main reason we have so many acronyms like GEO, AIO, LLMO, and AEO is that AI optimization in general is still very new. This means people from all corners of marketing have been coming across new concepts, ideas, and techniques at the same time.

Naturally, people call things different names as they try to differentiate themselves from traditional SEO — and all the other new acronyms appearing on the scene.

Why do they do that?

Various reasons:

• They want to appear to be at the forefront of digital marketing
• Their bosses have told them they need to do it
• They’re trying to offer new services in a volatile marketplace

There’s nothing wrong with any of these reasons. But it does make it confusing for the rest of us.

And it’s clear that a lot of people are searching for these new terms:

And the trends over time are clear too, as search demand for these new terms has skyrocketed in the past year:

One term in particular, “AI Optimization,” has really exploded:

Are They Replacing SEO?

Short answer: no.

Can you guess which keyword I blurred out in the first screenshot above?

That’s right: search engine optimization.

More than 40K searches each month. And the acronym “SEO”?

Almost a quarter of a million searches each month in the US alone:

(The other acronyms aren’t “mainstream” enough to use as a data point here. For example, AEO is American Eagle Outfitters, and GEO can mean a hundred different things.)

Clearly, search volumes don’t tell the whole story, but SEO is definitely still the more popular term right now.

And the Google Trend graph is the final nail in the “Is SEO Dead?” coffin:

That’s right, search demand for SEO has actually grown over the past year. But you’ll see here that “AI Optimization” is arguably “trendier” right now than SEO.

And that makes sense, because people and businesses are concerned about how to optimize for AI systems. There is a shift in the industry from pure SEO to some form of optimization for the likes of ChatGPT and AI Mode.

Businesses are even hiring for “GEO Experts”:

And agencies are pivoting to offer AI search services:

So what these acronyms are all about is a very real thing. But it’s not a complete revolution when you compare it to search engine optimization.

Quick Summary of SEO vs. GEO/AEO/LLMO/AIO

Here’s what’s actually happening. There are really only two distinct approaches, SEO vs. the rest:

Where They’re Actually the Same (Spoiler: Almost Everything)

Despite the different names, these approaches share most of the same features and tactics:

• The goal is the same: While visibility is perhaps the word you’ll see associated with success in the AI era, the goal for businesses is still to get more customers and drive revenue. Whether that’s from search engines or ChatGPT, it’s still the bottom-line number that business owners care about.
• Content quality is paramount: All of these optimization methods prioritize high-quality, authoritative content. Whether you’re targeting Google’s search results or ChatGPT’s responses, you need genuine expertise and accurate information.
• Structure matters everywhere: Clear headings, logical flow, and well-organized information help both search engines and AI systems understand your content. A messy blog post won’t rank well anywhere.
• Authority signals are universal: Backlinks, domain authority, and expertise signals matter across all platforms. AI systems often rely on the same trust signals that traditional search engines use (although citations, not just links, matter more for AI optimization).
• User intent drives everything: Whether someone types a query into Google or asks ChatGPT a question, they want a useful answer. Content that genuinely helps people will generally perform well regardless of the platform.

Where They Actually Differ (The Few Real Distinctions)

The differences between these approaches are smaller than the marketing suggests:

• Links vs. citations: In traditional SEO, a big driver of your authority and whether you’ll rank is the quality of your backlink profile. In AI optimization, where you’re cited across the web matters more than just the links you have.
• Traffic vs. citations: The broader business goals are still the same (to get customers and make money). But SEO is clearly more focused on driving traffic while AI optimization is, at least on the surface, about getting cited in AI responses.
• Response format: Keyword-optimized, long-form content was often the winning strategy for SEO. AI-optimized content focuses on direct, quotable answers to specific questions.
• Measurement challenges: You can easily track your SEO performance with tools like Google Analytics. Measuring AI visibility requires newer tools and different metrics, and it’s not always possible to accurately map out the customer journey.

But here’s what’s important: you don’t choose between these approaches. A well-optimized piece of content will perform across all these platforms simultaneously.

What This Means for Your Business

Now you know where there is and isn’t overlap between SEO, GEO, AIO, and all the other acronyms.

But what do you actually do with this information?

Content Research Gets More Complex

You can’t just look at keyword search volume anymore. You need to understand what questions people are asking AI systems and what answers those systems are currently providing.

This means your content team needs to research across multiple platforms:

• Google search results
• ChatGPT responses
• Perplexity citations
• AI Mode and AI Overviews

You need to understand where you’re being cited and where you’re not. But you also need to understand why other sites are being mentioned. This way, you can create content that’s also more likely to get cited.

Writing Becomes Answer-First

Writers need to structure content so AI systems can easily extract quotable segments for their answers.

That means:

• Descriptive subheadings
• Clear transitions between sections
• Direct answers early in each section
• Simple language where possible
• Short sentences and paragraphs

Editor’s Note: This is one that we feel quite strongly about at Backlinko. This is NOT new: it’s just good writing practice. But it is more important than ever, and if you weren’t already doing these things, you need to start now.

Content Investment Increases

Creating content that performs well across multiple search platforms requires more time and expertise. And you might even need to start creating content on different platforms too.

Why?

Because appearing in AI responses isn’t just about writing great blog posts. These tools love to reference user-generated content, forums like Reddit, and YouTube videos.

This means you’ll need to consider creating content beyond your website.

New KPIs to Track

Website traffic is still important, but it’s not the only success metric. You need to start measuring:

• Brand mention frequency in AI responses
• Citation accuracy across AI platforms (i.e., are the tools saying the right things about your brand?)
• Share of voice in AI-generated answers
• Brand sentiment in AI outputs

A tool that does all four of these is Semrush’s AI SEO Toolkit.

It’ll show your brand’s overall visibility and share of voice in AI tools like ChatGPT, Google AI Mode, and Perplexity:

You can also see how these tools perceive your brand versus your rivals:

The tool also shows you how often you’re cited compared to your competitors:

Finally, you can also find out the questions real users are asking about your industry:

You can use the AI SEO Toolkit’s insights to create and optimize your content for the questions users are asking. And you can optimize your overall visibility to ensure AI tools are saying the right things about your brand.

How to Explain It All to Your Boss/Stakeholders

Your boss and stakeholders in your business are going to hear about the likes of GEO and AIO and have questions for you. There’s no avoiding that.

This means you need to be able to explain the shift in plain business language — without the jargon and without triggering panic.

Here’s how to do it.

Lead with the Reality, Not the Acronym

Your CMO doesn’t care if it’s SEO, GEO, or AEO.

They care if your brand is visible when it matters.

Don’t start with “We need to do GEO now.” Start with “Our customers are getting answers from AI systems, and we need to make sure we’re part of those answers.”

This immediately connects to business outcomes instead of marketing tactics.

Be Honest About the Uncertainty

Don’t pretend you have a perfect read on how AI engines source answers. (Nobody does.)

Say:

“Some factors are proven — authority, relevance, clarity, and trust. Others are emerging, and we’re still testing things. Here’s what we know, and here’s what we’re learning.”

That honesty builds more trust than overconfidence.

Leadership teams have seen too many “revolutionary” marketing tactics fizzle out. Make it clear you’re being strategic, not just chasing trends.

Anchor to Business Impact

Shift the conversation from traffic to results that leadership cares about:

• Revenue from organic sources
• Pipeline influenced by organic visibility
• Brand lift and share of voice
• Cost per acquisition trends
• Customer lifetime value from organic channels

Instead of saying “We need to optimize for ChatGPT,” say:

“We expect fewer casual visits but higher conversion rates from people who find us through these new channels.”

This frames the expected change as quality improvement, not traffic loss.

Highlight the Win-Win Investments

Lay out the actions that are worth investing in, no matter what:

• Deeper audience research: Understanding exactly what questions your prospects ask (across all platforms) improves everything from product development to sales conversations
• Answer-ready content: Content that directly addresses customer questions performs better everywhere: traditional search, social media, sales enablement, and AI systems
• Brand and topic mentions in trusted sources: Getting coverage and citations from authoritative websites helps with traditional SEO, brand awareness, and AI visibility
• Strong UX and review presence: Better website experience and more customer reviews can improve conversion rates, regardless of where the traffic comes from
• Measuring what matters: Tracking brand mentions, share of voice, and conversion quality gives you better business intelligence for any marketing channel

These efforts are likely to work in SEO, GEO, or any other flavor of optimization. They’re just good marketing practices.

Highlighting these gives leadership confidence that you’re not betting everything on one unproven tactic. And it tells them that no matter what, these are things you should be doing anyway.

Position the Expansion as an Advantage

Make it clear this isn’t about more work for the same payoff.

It’s about capturing market share while competitors are still figuring things out:

“Most of our competitors are still focused only on traditional search. We have a 6-12 month window to establish authority in AI systems before they catch up.”

This positions your team as forward-thinking, not reactive.

Address the Obvious Concerns

You’re going to get questions, no doubt about it. Here’s how to answer the most common ones:

Question: “How much will this cost?”

Answer: “Most of the work builds on our existing content strategy. We’re expanding our definition of search optimization, not replacing it.”

Break down the investment:

• Content creation (already budgeted)
• New monitoring tools (modest monthly cost)
• Team training (one-time investment)
• Testing and optimization (part of ongoing marketing)

Question: “How do we measure success?”

Answer: “We’ll track traditional metrics plus brand visibility across AI platforms. Success means maintaining our current organic performance while building presence in emerging channels.”

Set up a dashboard that shows both traditional SEO metrics and AI citation tracking side by side. (Or use a tool like Semrush to do this for you.)

Question: “What if this is just a fad?”

Answer: “The underlying strategy — creating authoritative, helpful content and offering a great user experience — is the foundation of good marketing. We’re just making sure that our content performs well across more search platforms.”

Frame it as good marketing practices and risk mitigation, not trend-following.

Provide a Clear Timeline

Month 1-2 (Foundation):

• Audit existing content to understand its AI optimization potential
• Set up monitoring tools for AI citations
• Train team on new optimization principles

Month 3-4 (Testing):

• Optimize select pieces of content for AI systems
• Measure performance across traditional and AI search platforms
• Refine approach based on results

Month 5-6 (Scaling):

• Apply learnings to broader content strategy
• Expand monitoring and optimization efforts
• Report on impact to organic performance overall

Scripts for Explaining What You Do

When your job involves optimizing for AI systems, explaining what you actually do can be tricky. Here are a few ready-to-use scripts for different situations.

For Your Boss/Senior Stakeholders

“I’m expanding our search optimization strategy to include AI-powered platforms. We’re making sure our brand shows up when people ask ChatGPT, Perplexity, or Google’s AI Mode about our industry. The same content quality that drives our current organic success will now work across multiple new discovery channels.”

For Family and Friends

“You know how people used to only Google things? Now they ask ChatGPT or voice assistants as well, or even instead. I make sure our company shows up in those AI answers when people ask about our industry. It’s like SEO but for AI. Instead of trying to rank #1 on Google, I’m trying to get our company mentioned when AI gives people recommendations.”

For Professional Profiles (LinkedIn, Resume, etc.)

“I help companies maintain and expand their organic visibility as search evolves beyond traditional engines to include AI-powered platforms like ChatGPT, Claude, and Google’s AI Mode.”

For Prospective Clients/Customers

“We help companies get found by customers regardless of how they search — whether that’s Google, ChatGPT, or any other AI tool. Our approach combines traditional SEO with optimization for AI systems that are increasingly answering customer questions.”

For Industry Peers/Conferences

“The fundamentals of search optimization haven’t changed — authority, relevance, and user value still matter. But we’re now optimizing for systems that synthesize information rather than just ranking it. A lot of the tactics are familiar, but the platforms we’re optimizing for are expanding.”

How to Thrive in the AI Era of Search

Whether you call it SEO, GEO, AIO, or LLMO, the fundamentals of optimization and creating great content don’t change.

The goals shift a little, and how you measure success will differ compared to pure SEO.

But how you win in the AI era of search just requires an evolution of how you were doing things before.

To stay ahead of the game, check out these resources for more information:

• Search Everywhere Optimization Guide (+ Free Checklist)
• LLM Visibility: The SEO Metric No One Is Reporting On (Yet)
• 5 LLM Visibility Tools to Track Your Brand in AI Search (2025)

The post SEO vs. GEO, AEO, LLMO: What Marketers Need to Know appeared first on Backlinko.

2025-08-20 21:30:37

Want backlinks from Forbes, HubSpot, or Insider? Without paying a cent?

Journalist outreach is how you do it.

And in 2025, it’s still one of the most effective ways to earn authority links that actually move the needle.

We also run Traffic Think Tank, and we used this tactic to 10x visibility and revenue in the past year.

And built our authority in the increasingly important AI / LLM ecosystem:

This guide was created with insights from the team at Jolly SEO — the pros behind thousands of earned media wins.

Plus, we’re including our free Journalist Outreach Toolkit to help you implement everything immediately.

In this post, you’ll learn how to:

• Manage the overwhelming flow of media requests
• Write pitches journalists actually use
• Earn backlinks that boost rankings and trust
• Track ROI and prove value to stakeholders

Let’s break it down.

Step 1: Define Your Goals

If you don’t know what success looks like, you’ll waste time chasing the wrong wins.

Before you write a single pitch, get clear on what your business needs from journalist outreach.

Are you after stronger SEO performance? Brand visibility? Long-term relationships with the media?

Your goals will shape everything — from the platforms you prioritize to how you evaluate results.

For instance, let’s say you’re a B2B SaaS marketer trying to rank a key feature page.

Look for HARO or Qwoted queries where the topic aligns with the problem your product solves.

If you can offer a helpful, relevant perspective — one that happens to mention your company or approach — that’s a win. Even if the link doesn’t show up right away.

The bottom line?
When you know what wins you’re aiming for, you’re far more likely to hit them.

Greg Heilers, co-founder of Jolly SEO, puts it simply:

“Depending on your criteria, writing skill, and site/figurehead optimization, you can achieve a win as frequently as 1 in every 3 pitches.”

Step 2: Establish Realistic Expectations (This Will Save Your Sanity)

Most people give up on journalist outreach too soon.

Not because the tactic doesn’t work — but because their expectations are wildly off.

They expect quick wins, a high response rate, and instant SEO impact.

The reality is slower, less glamorous, and a lot more sustainable if you approach it with the right mindset.

Typical Success Rates (and What to Expect Over Time)

Even top-tier media outreach experts don’t land every pitch.

For beginners, a 3–5% response rate is normal. As you gain experience, that can climb to 8–12%, and with refined systems and strong positioning, 15–20% is achievable.

That means you might need to send 10–30 pitches just to earn one mention.

This isn’t failure — it’s the math behind consistent results.

So, what does that actually look like over time?

• Month 1: You’re learning the workflow. Scanning opportunities, testing your messaging, and getting familiar with the process. Landing even one or two mentions is a meaningful start.
• Month 3: You start to see patterns. Which types of queries are worth your time. Which angles tend to get picked up. You might even get quoted by the same journalist twice.
• Month 6: You have momentum. Pitches get easier. You might even start getting inbound requests from writers who’ve seen your previous contributions.

The payoff builds slowly — but it compounds.

Beyond the byline: Search is evolving fast. Journalist quotes are now surfacing in tools like ChatGPT, Perplexity, and Claude. If you’re featured in a top-tier article, there’s a real chance your name, company, or insight will show up in AI-generated answers.

Why Most Pitches Fail (And It’s Not Your Fault)

The biggest myth in journalist outreach is that great writing is enough.

Spoiler: It’s not.

Journalists get dozens — sometimes hundreds — of pitches for a single request.

Many already have sources in mind.

Others are on tight deadlines and go with the first relevant response they see. If your pitch arrives an hour late, it might not get opened at all.

This doesn’t mean your pitch was bad. It means timing and fit beat polish more often than not.

Step 3: Set Up Your Inbox and Tracking

The fastest way to burn out in journalist outreach?

Drowning in irrelevant pitches, deadlines you’ll never meet, and inbox chaos.

Here’s the good news: A few quick workflows can save you hours a week and help you stay consistent over time.

Make Your Emails Credible at a Glance

Journalists scan dozens of emails a day, and first impressions matter.

A polished inbox setup instantly signals trust and professionalism.

Include:

• Branded email address: Avoid generic Gmail accounts when possible. Use a domain-linked email to show legitimacy.
• Uploaded headshot: Many platforms now require it
• Branded signature: Add your name, title, company, LinkedIn, and a link to your website. Make it easy for journalists to verify who you are.
  

  

You don’t need a huge platform. You just need to look like someone worth quoting.

Build a Simple Filtering System

Start by organizing your inbox to reduce the cognitive load.

Create folders or labels by platform (e.g., “HARO Outreach”), and add filters to automatically route incoming queries.

Then, block off 15-minute review windows, no more than three times a day.

You don’t need to monitor your inbox all day — just be consistent.

Use the “5-second scan” rule: if it’s not clearly relevant within a few seconds, archive and move on.

Use Fast, Practical Qualification Criteria

Not every opportunity is worth your time — and trying to pitch everything will tank your efficiency.

For each request, ask:

• Is this in my area of expertise? If not, don’t force a fit. Weak relevance leads to ignored pitches.
• Do I meet the specific requirements? Many queries ask for certain job titles or credentials. Skip it if you’re not eligible.
• Is the deadline realistic? If you can’t hit the cutoff, don’t let it clog your pipeline.
• Is the publication worth your time? Not every outlet will align with your goals. Use your win criteria (from Step 1) to filter.

For instance, if you’re a freelance content strategist, a request asking for insights from “Fortune 500 CEOs” is a clear pass.

Save your effort for a request that matches your actual experience.

Step 4: Choose Your Platforms Strategically

Not all journalist outreach platforms are created equal.

Some are great for quick wins. Others shine when you’re targeting high-authority publications or niche audiences.

The key isn’t choosing the platform with the most opportunities — it’s choosing the one that aligns with your actual goals.

That means considering more than just volume.

You’ll want to look at average link quality, pitch-to-publication turnaround, cost, and whether the requests match your expertise.

Don’t feel like you need to master every platform out of the gate.

Start with one or two that align with your goals, get really good at using them, and expand once your workflow is dialed in.

How to Choose the Right Platform (Fast)

Not sure where to start? Think of this as your cheat sheet for getting started.

• Just getting your reps in? Start with Featured — it’s simple, fast, and great for building confidence early.
• Need high-authority links that actually move rankings? Go with Qwoted — it consistently surfaces high domain rating (DR) opportunities from recognizable media outlets.
• Want placements in premium, name-brand publications? Choose ProfNet — fewer opportunities, but often higher caliber if you have the budget.
• Targeting marketers, founders, or SaaS buyers? Help a B2B Writer delivers curated, niche-relevant requests in your exact lane.
• Need a high volume of relevant opportunities to work with? Source of Sources gives you a steady stream of niche pitches — just be ready to filter.
• Looking for general-topic visibility at scale? HARO still delivers breadth and quantity — just expect to dig for quality.

Looking for country-specific platforms?

Many regions have their own journalist request tools worth exploring. For example, SourceBottle is widely used in Australia, and ResponseSource is popular among PR pros and journalists in the U.K.

Just try a quick Google search like “journalist request platform [your country].”

You’ll usually uncover a few local options — no massive directory needed.

Step 5: Write Pitches That Win (Without Taking Forever)

The best pitches don’t win because they’re long or clever.

They win because they’re skimmable, useful, and immediately quotable.

Your job isn’t to impress the journalist — it’s to make their job easier.

Establish Credibility in 8 Words or Less

Start with a strong subject line. Greg emphasizes combining relevance with instant credibility.

Use this structure:

Examples:

• SaaS CEO’s Take on Fixing Churn
• SEO Consultant’s Local Link Playbook
• Copywriter’s Formula for High-Converting Headlines

Then, build your pitch. It should look something like this:

Pro tip: AI tools can help you brainstorm angles — but the final quotes should sound human, specific, and ready to publish. Use AI for speed, not substitution.

Make Your Quotes Instantly Usable

Journalists aren’t grading your writing.

They’re looking for clean, usable quotes they can drop straight into a draft.

As Greg puts it:

“Journalists want quotes they can immediately copy and paste into their articles, no changes needed.”

Here’s how to make that happen:

Pro tip: For the full checklist — and why each step matters — use the Pitch Checklist tab in our journalist outreach toolkit.

Not all pitches are created equal.

Here’s what gets picked up — and what gets ignored.

❌ Bloated, vague, and completely unusable:

✅Clear, specific, and quote-ready:

Pitch Faster Without Losing Quality

Greg recommends prewriting as much as possible so you’re never starting your press outreach from scratch.

Have 3–4 versions of your bio ready to go, tailored for different beats (e.g., SaaS, marketing, AI).

Build a few quote templates for your most common talking points. And give yourself a hard limit: Aim to finish each pitch in 10 minutes or less.

The more reps you get, the easier this becomes.

Don’t forget your first line does heavy lifting. It shows up in inbox previews and often determines whether your pitch even gets opened. Make it count.

Caveat: Structure helps, but sameness kills. AI tools and mass pitching have flooded inboxes with lookalike answers. Don’t just fill in a template — say something only you would say. That’s what gets quoted.

Yes, You’re Qualified. Here’s Why.

One of the biggest blockers in journalist outreach? Thinking you’re not “qualified” to respond.

But here’s the truth: You don’t need a blue checkmark or a book deal to be helpful.

If you can help readers understand something better or offer a useful perspective, you’re already ahead.

Credibility doesn’t mean status. It means relevance.

That could be your job title, your years of experience, a client result, or just a smart way of framing the problem.

When in doubt, try this five-part framework to surface story ideas from your own work:

• The situation: What were you working on?
• The challenge: What made it tricky?
• Your approach: What did you try or test?
• The result: What changed? What worked?
• The insight: What do you wish you’d known earlier?

The bottom line?

If you’ve solved what they’re writing about, you belong in their inbox.

Step 6: Master the Follow-Up (Without Being Annoying)

It’s tempting to send a pitch and move on.

But following up is one of the easiest ways to multiply the value of your efforts.

It’s low-effort, high-return, and totally underused.

The key is to keep it respectful, useful, and brief. Here’s how to do it without sounding pushy.

Turn Mentions Into Links

Let’s say you’ve been quoted but not linked.

Here’s a simple, polite ask that turns visibility into real SEO value:

Turn Replies Into Relationships

The journalists who quote you today could become recurring collaborators — if you give them a reason to remember you.

Done right, a follow-up turns one good pitch into long-term visibility, stronger links, and a journalist who might actually remember your name.

Step 7: Find Hidden Wins (Most People Miss These)

You might already be getting results — and not even know it.

At Jolly SEO, Greg sees it constantly.

“People message me and say, ‘I’ve sent dozens of pitches, but I can’t get any wins. What am I doing wrong?’

My first question is always: ‘Have you tried looking for them yet?’”

The good news?

You don’t need expensive tools or a manual content audit. A few smart searches and a weekly routine are all it takes.

Use Google Search Operators

Advanced search syntax lets you find live mentions with precision. Run these searches weekly to uncover wins:

• “Your Name” + “Your Brand Name”
• “CEO of [Brand]” site:targetpublication.com
• “[Your unique quote]” site:[domain]

Use quotes to force exact matches and ”site:” to limit the search to specific outlets.

Set Up Google Alerts

Track new mentions passively by creating alerts for:

• Your name + company
• Your job title (e.g., “CMO of Backlinko”)
• Distinctive quotes or phrasing you tend to use

This won’t catch everything, but it will help surface a steady stream of new wins.

Manual Checking Schedule

Most people stop after they hit “send.”

But Greg estimates you’ll never be told about 90% of your wins.

So if you don’t go looking, you’ll never even know they happened.

Build a simple check-in routine:

• Weekly: Run your branded Google searches
• Monthly: Review recent articles from journalists you’ve pitched
• Quarterly: Use SEO tools (like Ahrefs or Semrush) to spot backlinks or citations

Pro tip: Use the Win Finder (in the toolkit) to uncover hidden mentions.

Step 8: Build Your Journalist Network

Every pitch is more than a one-time shot at a link — it’s the start of a potential relationship.

If a journalist quotes you once, there’s a good chance they’ll want insights from you again.

But only if you make it easy, relevant, and respectful to stay in touch.

Track Relationships Like You Track Links

Use a simple CRM (even a spreadsheet works) to track journalist contacts the same way you’d track sales prospects:

• Name + outlet
• Contact info + beat
• History (quoted, linked, mentioned)
• Relationship stage (cold, warm, repeat, advocate)
• Last contact date + next follow-up

If you’ve contributed to multiple stories or gotten links from the same writer, mark them as high-priority for future outreach. These are your warmest leads.

Build Trust Without Pitching

You don’t need a quote request to stay visible.

In fact, the best relationship-building moments often happen when you’re not asking for anything.

Promote their articles on social with a thoughtful comment — not just a tag. If you come across a story angle or source that fits their beat, send it their way.

If they mentioned a topic they’re covering next month, follow up. Even better: introduce them to another trusted source in your network.

These small, useful gestures build familiarity over time.

That’s how you become more than a random inbox name. You move from pitching to being pitched.

Pro tip: Use our Outreach CRM Tracker (in the toolkit) to start tracking pitches and wins instantly.

Step 9: Measure and Prove ROI

If you’re investing time, you need to show what it’s worth — to your team, your stakeholders, or your clients.

That means going beyond raw link counts and telling the full story of impact.

Track What Matters

Link counts are a starting point, but they’re not the whole picture.

Look at which platforms consistently deliver wins, how many hours go into each link, and which journalists become repeat collaborators.

Track your mentions, even when there’s no link.

Watch for traffic spikes after a story goes live, and pay attention to whether rankings improve on pages earning coverage.

For example, if a single article mention leads to a 12% lift in branded search and earns a backlink to your pricing page, that’s clear momentum.

When you combine reach, effort, and outcome, you start to see the full return.

Use a Simple ROI Framework

When you need to quantify results for stakeholders, use this basic formula to translate time and effort into value:

For example:

You earned five links in a month — all from DR 70+ publications.

Let’s say the average market cost for that caliber of link is $800, and you assign a DR adjustment factor of 1 (used to reflect link quality; 1.0 = solid, relevant fit):

Link value: $800 (avg. link cost) x 5 links = $4,000

Time investment: 12 hours × $100/hr = $1,200

ROI: ($4,000 – $1,200) / $1,200 × 100 = 233%

Now compare that to sponsored content, digital PR retainers, or even PPC — and suddenly, this starts looking like a serious channel.

Build a Stakeholder-Ready Report

The final piece is packaging your results in a way that stakeholders understand and care about.

Keep it simple, visual, and focused on outcomes:

• A summary of links earned by domain authority range
• Growth in brand mentions across media and social
• Traffic lift or ranking movement tied to earned placements
• Estimated link value compared to paid alternatives
• A standout example or case study from that month

When stakeholders can see the momentum — not just the metrics — they’re far more likely to stay bought in.

Start Earning Links That Actually Matter

You’ve got everything you need to get started. Now, it’s time to make your move.

Write a pitch today. Just one.

Don’t overthink it.

Grab the Journalist Outreach Toolkit, find a real query, and put your perspective to work.

Then, send it — and give yourself a shot at a win most people never even try for.

The post Journalist Outreach: 9 Steps to Earn High-Authority Links appeared first on Backlinko.

2025-08-18 22:02:29

More of your customers are using AI to research products before they buy. Are you prepared?

To put this into perspective:

Last year, you might’ve searched “best bed sheets” on Google and scrolled through a few links or a Shopping ad.

This year, you’re asking ChatGPT:

“I sleep hot and have sensitive skin. Can you recommend some breathable bed sheets that won’t irritate me?”

Totally different input. Totally different rules for showing up.

AI Search still cares about the fundamentals — content, crawlability, internal links, and high-quality backlinks. But now, your visibility is influenced by more than just your website.

AI models reflect the full picture:

• What people say about your brand
• Where you’re mentioned
• How your product is reviewed

It’s not just keyword targeting — it’s relevance engineering.

Shoutout to Mike King @ iPullRank for coining this term.

That’s where AI Search Optimization comes in.

In this guide, you’ll learn how to:

• Make your product pages visible and understandable to LLMs
• Structure your data with schema and product feeds
• Submit your catalog to AI search platforms
• Shift from keyword targeting to prompts and personas
• Build an AI-friendly brand presence across the web
• Track your visibility in a probabilistic, answer-first world

The future of ecommerce search isn’t about rankings. It’s about being part of the answer. This guide will show you how.

Step 1: Make Your PDPs Crawlable and Renderable

Before you do anything, start here: can bots actually see your product content?

When people started taking AI tools and chatbots seriously in 2022/23, some site owners turned to blocking their crawlers from accessing their site.

But if you block the crawler, it won’t be able to serve your pages in its responses.

Don’t Block AI Crawlers in Your Robots.txt File

Unless you actively took the step to block them, you shouldn’t need to do anything here. But it’s still worth verifying there are no lines in your robots.txt file like:

User-agent: GPTBot
Disallow: /

Don’t Serve Important Content Using JavaScript

The other aspect of crawlability to consider is how you’re serving your content.

Because right now, bots from the likes of ChatGPT and Perplexity do not appear to process JavaScript (although Google’s Gemini can). If your content is being loaded dynamically, they’re likely missing it completely.

That includes:

• Product descriptions
• Pricing
• Images
• Schema markup

If it’s not in the raw HTML, LLMs like these can’t see it. And if they can’t see it, you won’t show up in AI-generated product recommendations.

To make sure you’re not causing crawling issues here, you first need to understand how your ecommerce platform handles JavaScript. Every platform is different:

• Shopify: Generally fine, but watch out for third-party apps injecting schema or content via JS.
• WooCommerce: Depends heavily on your theme. Many use plugins that load parts of the page with JS.
• Custom stacks: If you’re using React, Vue, or similar frameworks, check whether product pages render server-side or after load.

Next, check your PDPs manually. You can do this by right-clicking and selecting “Inspect” in your browser.

Then press Command+Shift+P on Mac, or Control+Shift+P on Windows/Linux.

In the Command Menu, start typing “javascript” and then select “Disable JavaScript”:

Reload the page, and you’ll see how it looks without JavaScript enabled — in other words, how LLMs like ChatGPT see the page:

In the Nike example above, the LLM would still see key info like the product title, description, and price.

But in the example below…

…it would see nothing.

You can see on the right that there’s still page code loading. But nothing is actually displayed to the user with JavaScript disabled. Meaning AI tools wouldn’t be able to pull any info from this page.

If you are using apps or components that rely on JavaScript to display key content, talk to your dev team about server-side rendering (SSR) or prerendering. The goal is to ensure all critical product info is delivered in the first HTML response.

Further reading: What Is JavaScript SEO? 6 Best Practices to Boost Rankings

Step 2: Add Structured Schema Markup

Once your product pages are crawlable, the next step is making them understandable.

Structured data — specifically Schema.org markup in JSON-LD format — helps systems like ChatGPT, Perplexity, and Google understand what your product is, how much it costs, whether it’s in stock, and more.

In the world of SEO, we’ve long used schema markup to improve how our pages appear in traditional search results.

Here’s an example of a traditional Google results enhanced with schema markup, appearing as a rich snippets:

But for LLM visibility, schema helps the AI tools understand key details about your products. Which makes it easier for them to pull in your products when they’re making recommendations for users.

How do we know this?

Because Microsoft has told us. The tech giant, a major investor in OpenAI (behind ChatGPT), said:

“[Structured data] makes it easier for search engines not only to index your content, but to surface it accurately and richly in search results, shopping experiences, and AI-driven assistants.”

(Interestingly, Microsoft/Bing recommends combining this with IndexNow — a service that automatically pings search engines when you update your content.)

Plus, using structured data just makes sense — it helps make it easier for complex machines to understand our content. Whether that’s a search engine or an LLM, providing more context is generally always going to be a good idea.

Here’s how to use structured data to improve your ecommerce store’s LLM visibility:

Focus on Product Pages First

While there’s value in marking up other templates (like category pages, blog posts, or FAQs), your product pages are where it counts most.

This is the data that LLMs and search engines will use to:

• Associate your product with relevant categories and attributes
• Match your offering to long-tail purchase prompts
• Feed structured knowledge into their product and shopping systems

Here are the fields to include:

• @type: Product
• GTIN, SKU, MPN
• Brand
• Description
• Offer block (price, currency, availability, URL)
• Review/rating info if available

Use your schema to reflect reality, not just fill fields. But also add as much context as you can.

If your product is eco-friendly, US-made, sweatproof — encode it. The better your markup, the more context LLMs have to surface your product in nuanced prompts.

Validate Your Schema and Confirm It’s Visible

Check your schema is valid with tools like:

• Google Rich Results Test
• Schema.org Validator

Make sure the schema is present in the raw HTML — not loaded with JavaScript.

Bonus: Extend to Reviews, FAQs, HowTo

Once your product markup is solid, consider adding:

• Review and AggregateRating blocks
• FAQPage markup for your PDPs or Help Center
• HowTo schema for tutorial content or sharing post-purchase use cases

These all help build context around your product and can influence how LLMs present or recommend it.

Once you’ve marked up your product pages, the next step is scaling an effective structure across your entire catalog. That’s where a high-quality product feed comes in.

Step 3: Build a High-Quality Product Feed

Structured feeds have been essential for Google Shopping, Meta Advantage+, and TikTok Shop for a while.

And now, they’re becoming equally important for AI-powered discovery. Especially as platforms like Perplexity and OpenAI build out product recommendation systems.

Think of your feed as the dataset LLMs will eventually pull from when answering questions like this:

Perplexity has launched a Merchant Program accepting feed uploads, called the Perplexity Merchant Program. This lets ecommerce sellers have even more control over how their products can appear in AI responses.

Plus, OpenAI is quietly testing ways to let store owners upload feeds to improve their AI responses for product recommendations.

These feeds will likely drive future AI shopping experiences across chat, search, and even voice interfaces.

So how do you set your product feeds up in an LLM-friendly way?

What to Include

To optimize your product feeds for AI, start with the essentials:

• Product title
• Description
• Price
• Availability
• Product URL
• GTIN or MPN + Brand
• Image URL

Note: Tools like ChatGPT may still generate their own versions of some of these (like titles). But it’ll still typically use information from places like your product feeds to inform its responses.

After you’ve added the basics, layer in high-value fields like:

• Category or taxonomy
• Color, material, and size variants
• Shipping cost and speed
• Review count and star rating
• Custom labels for campaigns or segmentation

Use the same language your customers use.

This means writing product information the way your customers actually talk and search, not how your internal teams or suppliers describe things. For example:

Instead of:

“Athletic footwear with moisture-wicking synthetic upper”

Write:

“Running shoes that keep your feet dry”

How do you find out how they talk?

Look at your customer reviews, support tickets, and search queries that already drive traffic to your store.

For example, they might search for “cozy sweater” not “knitted pullover.” This can inform your title and description choices.

How to Submit Product Feeds to LLMs

Here’s how to submit your product feeds for three of the biggest AI interfaces.

Perplexity:

In 2024, Perplexity launched their Merchant Program. This fuels the platform’s shopping experience for Pro users. Your products may appear in carousel-style answers and shopping-focused prompts, and shoppers can buy without leaving Perplexity.

You can find out more about the program and sign up here.

OpenAI (ChatGPT):

OpenAI is piloting product discovery via ChatGPT’s “Search + Product Discovery” initiative. They’re exploring using uploaded feeds to power future buying experiences inside ChatGP.

Fill out this interest form to apply.

Google Merchant Center (AI Mode and Gemini):

Google’s Merchant Center feeds power Shopping Ads, organic Shopping listings, and likely influence how Google’s AI systems interpret and surface your products in AI Mode and AI Overviews.

Step 4: Monitor LLM Crawlers

Once you’ve put all the steps in place to make your ecommerce store crawlable by LLMs, the next step is to make sure they’re actually accessing your content and product pages.

Here’s how to do that:

Set Up Bot Monitoring

Use server logs or your CDN (like Cloudflare, Fastly, or Akamai) to track requests from:

• GPTBot: This user agent is used by OpenAI to crawl web content that may be used in training their generative AI foundation models.
• OAI-SearchBot: Used by OpenAI to link to and surface websites in search results in ChatGPT’s search features.
• PerplexityBot: Identifies Perplexity’s AI search crawler when it accesses websites.
• Google uses various Googlebot user agents to crawl the web, depending on the type of content being crawled (e.g., desktop, mobile, images). You can find a detailed list of common Googlebot user agent strings and their purposes in resources from Google for Developers.

For each of these bots, track:

• Which pages they’re crawling (PDPs, collection pages, sitemap, feed)
• How often they come back
• How crawl patterns evolve over time

This helps confirm they’re discovering your content and gives you a baseline to measure progress.

Step 5: Shift from Keyword Lists to Prompts and Personas

Keyword research is still important. But you also need to think about how your customers are likely to prompt AI tools when looking for products like yours.

LLMs answer questions, interpret context, and make recommendations based on how people naturally speak.

That means you need to rethink how you optimize for product discovery. Not by keywords alone, but by personas, use cases, and prompt formats.

Start With What You Know

Your best-performing SEO and paid search keywords are still the foundation. They tell you:

• Which products and categories convert
• How people describe their intent in short-form searches
• Which attributes drive action (e.g., “cooling sheets,” “queen size,” “organic cotton”)

Use these to anchor your prompt strategy — but expand outward.

Think in Prompts, Not Just Queries

As people become more savvy with how AI tools work, more and more shoppers are going beyond just typing in “best bed sheets.” They’re asking:

Medium-length prompts:

• “Best cooling sheets for hot sleepers”
• “Softest bed sheets under $100”
• “What kind of sheets stay on the bed all night?”

Longer, context-rich prompts:

• “I’m a side sleeper who gets hot at night. What bed sheets will stay cool and not cling to my skin?”
• “Looking for breathable, hypoallergenic sheets that work well in humid climates”
• “I have sensitive skin and eczema. What’s a good sheet material that won’t irritate me?”

Your goal is to build context around your products that lines up with this kind of language and framing.

Note: You can’t predict exactly what your customers will ask, and there are infinite ways they can do it. But thinking about prompts — not just keywords — will put you in a good place to be able to optimize your ecommerce pages for LLMs.

Map Your Catalog to Prompt-Based Use Cases

Think in layers:

• By need: cooling, breathable, wrinkle-resistant, organic
• By persona: hot sleeper, allergy sufferer, luxury buyer, college student
• By situation: new apartment, guest bedroom, summer refresh, wedding registry
• By problem: sheets come loose, feel scratchy, trap heat, shrink in the wash

This is how you start to think of your items like answers and solutions, not just products.

Use These Prompts to Guide Content and Merchandising

Let this prompt structure inform your:

• Product page copy and comparison points
• Blog posts and videos
• Social media posts
• FAQs and Help Center content
• Category names and filters
• Product feed descriptions and attributes

LLMs can pull from all of it — so make sure you’re using the kind of language your real customers use everywhere.

Step 6: Seed Your Brand Across the Web

Even if your site is crawlable, your schema is perfect, and your feed is super optimized — LLMs still learn about your brand based on what people are saying about you elsewhere.

They’re trained on massive web-scale datasets, so third-party content — like reviews, Reddit mentions, YouTube transcripts, forums, blog posts — can carry as much (or more) weight than your owned channels.

If you want to show up in AI answers, your brand needs to already exist in the wider conversation.

Where You Want to Show Up

AI tools like ChatGPT, Perplexity, and Claude all lean on third-party review sites and forums in their answers to brand and product-related queries.

These are the places you’ll want to show up in order to be included in those answers:

• Review sites: Trustpilot, Amazon, Google Reviews, BBB, niche review sites
• Reddit, Quora, & niche forums: Participate in threads and subtly seed your product category (without being spammy)
• YouTube: Appear in titles, transcripts, and product comparisons — even if you’re not the creator (consider partnering with creators to do this)
• Affiliate content: Get included in roundups, listicles, and side-by-side comparisons

Showing up in these places is half the battle. The other component is how you show up.

Ideally, you’ll want to be mentioned alongside competitors (“like Brooklinen but…”). And in the right, relevant context (“these are some of the best cooling sheets for eczema”).

A lot of this is going to be completely out of your control (especially on platforms like Reddit). But good marketing practices can make it more likely that people will naturally talk about your brand in the way you want them to.

This Is Just Good Marketing

Gaining LLM visibility is a byproduct of an effective multichannel marketing strategy.

If you’re running a strong content program, building brand awareness, and actively participating in your category — you’re already seeding relevance.

What’s new is the urgency: LLMs are already using these signals to decide which brands deserve to be recommended.

Related: See our LLM Seeding Playbook for tactics, templates, and outreach strategies.

Step 7: Track Your AI Search Visibility

In traditional SEO, visibility was deterministic: rank #1 for a keyword, get X% of clicks.

That model is breaking.

AI-powered discovery works differently. Your brand might appear in one version of a response, but not the next.

Whether your ecommerce store is included depends on how the user phrases their prompt, how much brand recognition you have, and how often you’re referenced across the web.

So, your measurement strategy needs to adapt.

What to Track

Start by building a prompt library — real questions your customers might ask:

• Organize prompts by topic (e.g., cooling sheets, organic materials, luxury bedding)
• Group them by persona (e.g., hot sleepers, allergy sufferers, budget-conscious buyers)
• Then choose a tool to test visibility: like Semrush AI SEO Toolkit, Peec.AI, or Profound

Here’s how it looks in Semrush’s AI SEO Toolkit:

For each prompt, ask:

• Does your brand show up?
• If not, who does?
• What sources are the tools citing?
• What kind of language are the tools using?

Over time, this gives you a clearer picture of how visible your brand is across different use cases.

LLM Optimization Is Still New, But It’s Gaining Traction Fast

AI-driven search is already reshaping how people discover products. The shift is subtle now, but it won’t stay that way for long.

What used to be a clear SEO vs. paid search strategy is now blending into a broader question:

When someone asks a smart machine what to buy… will it know you exist?

This guide gave you a playbook to start answering that question:

• Clean up your technical foundation (crawlability, schema, product feeds)
• Rethink your discovery strategy around prompts and personas
• Show up across the web in ways that reinforce what makes your brand unique

It’s a lot. But the good news?

If you’ve already invested in great products, strong messaging, and a multi-channel strategy, you’re not starting from scratch.

Still need help nailing the fundamentals?

Check out these guides:

• 9 Ecommerce Website Examples to Copy for Better Results
• 11 Ecommerce Marketing Strategies to Drive Traffic and Sales
• Ecommerce SEO: 6 Proven Strategies to Rank Higher

The post 7 Steps to Optimize Your Ecommerce Store for AI Search appeared first on Backlinko.