Absent from conversations your customers are having with large language models (LLMs) about your category.

Or worse, showing up inaccurately, with outdated or incorrect information that’ll hurt your sales.

Without prompt tracking, you’d never know.

Prompt tracking (sometimes called LLM visibility tracking) is the practice of monitoring how your brand shows up in AI answers over time, through mentions or citations.

It’s different from traditional SEO rank tracking, which tells you where your URLs appear on search engine results pages (SERPS) for specific keywords.

With rank tracking, you ask, “How close are we to position 1?”

But LLMs don’t answer questions with a static list of 10 blue links.

They pull from massive amounts of information to generate a unique response every time, tailored to the user and the context of the conversation.

You can even ask the same question twice and get two different answers.

In this search experience, it matters less whether your brand is mentioned first, and more that it says true positive things about you to the right people — consistently, across many runs of similar prompts.

But without a system to monitor it, you’re flying blind.

Prompt tracking gives you the directional intelligence to spot AI visibility gaps — the queries you’re consistently not showing up for — and close them.

This guide shows you exactly how. You’ll walk away with a free tracking template, a step-by-step system, and two real-world expert setups you can steal.

Free template: Download our prompt tracking spreadsheet to start understanding your brand’s AI visibility across LLMs ASAP.

Why Brands Need to Track Prompts

According to a study from Orbit Media, 55% of US internet users rely on AI as their primary or frequent research tool. Thirty-two percent use it for product recommendations.

Translation: A growing share of buyers are learning about you in AI tools. Without ever visiting your website.

Overall AI visibility scores tell you whether you’re showing up. Prompt tracking tells you where and how.

It can help you understand:

• The types of questions you’re showing up for and where they fall on the customer journey (ToFu, MoFu, or BoFu?)
• The questions your competitors are pushing you out of (and your share of voice on important topics)
• The sentiment around your brand mentions
• The questions you’re getting cited for, but not recommended (sometimes called ghost ranking)

This level of data helps you spot specific trends and gaps in your AI visibility over time.

Then, you can prioritize exactly what to fix.

Take Gong, the sales call intelligence tool.

Their AI visibility score is a respectable 65.

Free tool: Get your own score using Backlinko’s free AI visibility score checker.

They show up for prompts at all three stages of the funnel.

With prompt tracking, Gong can focus on conversations most likely to drive revenue and stop spending time and money tracking ones that won’t.

If their mention rate stays low on key BoFu topics over time, that’s a signal to update on-site or third-party content.

They can also see which relevant topics competitors are owning while they’re absent.

For example, Gong’s Engage product helps with lead generation.

But Salesforce and Hubspot consistently own these prompts.

This tells Gong two things:

1. Their audience isn’t aware of their lead generation use case
2. They need more content around it to train AI platforms to mention them

Sentiment prompts like ‘Is Gong worth the price?’ and prompts that surface ghost ranking can reveal similar trends and gaps.

The important thing is to track data over time.

AI answers are non-deterministic. The same prompt can return different brands across different runs.

Regular, repeated tracking is how you get meaningful signals you can act on.

When LLM Prompt Tracking Isn’t Worth It (and When It Is)

Prompt tracking isn’t for everyone.

Plenty of businesses spend time and budget on it and still walk away with data they can’t use.

Prompt tracking is NOT worth it when:

• Your audience isn’t using AI to find solutions in your category
• Your site isn’t set up to be crawled by AI
• You don’t publish content regularly
• You’re not looking for competitive or brand narrative insights
• You need a single KPI to report upward
• You don’t have bandwidth to act on insights

TL;DR: Prompt tracking yields valuable insights — but only if you’re set up to act on them.

If you are set up, the returns can be significant.

Take Gong, the sales call intelligence tool. It’s a great candidate for prompt tracking.

It has a full content engine that publishes across multiple channels (blog, reports, video, media coverage, audio, and more).

They compete in a crowded category where comparison prompts are common.

And they serve a buyer (sales leaders) who increasingly uses AI to evaluate software.

(Seventy-one percent of B2B software buyers now rely on AI chatbots for product research, according to G2, up from 60% in 2025.)

On the other hand, a local HVAC company that gets all its leads from Google Business Profile (GBP) and word-of-mouth doesn’t need prompt tracking. At least not yet.

Even if AI is overlooking them, building a content engine from scratch just to fix that isn’t a realistic investment.

Building Your Prompt Set: What to Include and Why

Don’t try to track every possible prompt your customers could be using.

Instead, focus on prompts you actually care about getting mentioned or cited in.

They should map directly to your product offering, audience pain points, and moments close to purchase.

Types of Prompts to Include

Tracking these four types of prompts over time will yield the most helpful insights:

• Evaluation prompts: “Best tool for x use case” and specific feature queries
• Reputation prompts: “Is x product worth the price?”
• Comparison prompts: “Alternatives to x product,” “x tool vs. x tool,” “best x tools”
• Gap prompts: Priority topics your competitors are pushing you out of

The first three are focused on understanding how your product is being recommended in buying conversations.

The last one is about understanding your competitive landscape and where you could improve.

Pro tip: Don’t just track one prompt for each type. Looking at answers for a single prompt is just noise. Reviewing a cluster of prompts over time is a real signal.

Margaret Kapitany, Offsite SEO Lead at Hootsuite, shares how she focuses her prompt set:

The prompts worth tracking are the ones that most closely mirror how a potential buyer would actually ask their AI for help, especially close to a purchase decision. For me at Hootsuite, that means prompts that cover comparison, evaluation, and recommendation queries from a social media manager or CMO, phrased the way they’d talk to a colleague or trusted industry peer.

What that looks like in practice at Hootsuite:

Where to Find Prompts Worth Tracking

Find prompts wherever you normally go to learn about your audience.

To find prompts worth tracking, look at:

• Keyword research: Commercial and Transactional intent queries like “best x software”
• Google’s “People also ask” (PAA) boxes: Comparison and evaluation questions like “Best alternative to x” or “does x integrate with y”
• Perplexity’s related questions: Similar to PAA, comparison and evaluation questions
• Reddit, Quora, Facebook Groups in your industry: Repeated questions, especially ones that compare options or express frustration
• Sales call transcripts: Repeated questions asked right before or during a purchase decision
• Semrush prompt suggestions for your brand: Queries tied to buying decisions that you or your competitors are showing up for

Pro tip: For every question you uncover, do a quick gut check: “If someone asked an LLM this, would I want to see my brand show up? Would I be upset if it didn’t?” If the answer is “Yes, and yes,” keep it.

Let’s return to Gong as an example of how to find prompts.

Keyword research shows me the questions people are asking Google about my category, how popular they are, and the language they use.

If I use a tool like Semrush, I can filter to Commercial or Transactional intent keywords (the ones labeled “C” or “T”). And add the most popular and relevant ones to my prompt tracker.

Then, I can dig through Reddit forums my audience frequents to find repeated frustrations and buyer queries.

I would take “Sales enablement tech stack suggestions,” “AI tools for sales enablement.” I’d ignore the queries about SMBs or startups because those aren’t Gong’s target audience.

Next, I’d extract the comparison or evaluative prompts Perplexity surfaces when I prompt it with terms related to my business.

For Gong, I used “best conversational insights tool for sales” to find some good candidates:

• Gong vs. Chorus (or any other competitor on this list)
• Which conversational insights tool has the best ROI for enterprises?

Pro tip: When writing prompts, don’t agonize over exact wording the way you would with keywords. LLMs cluster semantically similar queries together. Track a few natural variants, like “best sales enablement software” and “top sales enablement tools.”

These sources are solid, but you’re still inferring and collecting them manually is slow.

Semrush’s AI Visibility tool gives you what none of these sources can: real LLM prompt volume data.

The exact prompts your audience runs in LLMs and how often they’re using them, ranked by frequency.

This grounds your prompt set in real demand that’s always up to date.

You can be sure you’re tracking questions your users are actually asking.

From this list for Gong, I’d choose to track prompts under “AI-Driven Sales Enablement” and “Sales Coaching and Enablement Tools,” as they’re BoFu queries related to my product.

Organize By Product or Use Case

To build your first prompt set, start small.

All you need is 20-30 prompts over 4-6 broad categories that align with your product offering or use cases.

Ensure every category includes a mix of your four types of high-value prompts and add them as tags.

For a B2B SaaS company like Asana, this prompt tracking setup could look like the following:

Pro tip: Use branded prompts only for comparison and reputation tracking, as they can inflate your visibility score. Keep the rest of your prompt set unbranded so you actually learn where you’re getting found, not just where you’re already known.

This setup lets you easily see which categories you’re winning and losing in over time.

Or, what types of answers you need to do a better job of showing up in.

Example: Hootsuite Prompt Set

You may decide to add more tags or organize your prompts in a different way as you expand.

For example, Margaret uses multiple different tags — not just categories — for her prompt set for Hootsuite.

We’ve built out prompts in three ways:

• Funnel stages, with most of our attention on conversion
• Our target industries, with tailored terminology
• Intent type: comparative, evaluative, integrative (e.g. “works with X tool”), and problem-led (“how do I solve Y”)

Almost all of our prompts carry multiple tags, e.g., BoFu + Healthcare + Evaluative. That tagging is what lets me slice the data later.

When leadership asks for numbers, she can report on which industries Hootsuite is most visible in, or cross-reference visibility for BoFu prompts with direct traffic trends.

Margaret’s setup shows an important lesson: However you build your prompt set, structure it so you can answer the questions you’ll want to ask later.

How to Track Prompts: Step-by-Step Process

All you need to get started with prompt tracking is a spreadsheet and 30 minutes a week.

Free template: Download our Prompt Tracking Template by Backlinko to follow along with the steps below.

Step 1. Set Up Your Tracking Sheet

With our tracker, you can log the following for each prompt:

• The prompt itself
• Category
• Tags (e.g., type, industry)
• The LLM you’re testing it in
• Whether your brand was mentioned (yes/no)
• Whether you were cited (yes/no)
• Sentiment of the mention (positive, neutral, negative)
• Competitors mentioned
• The date

Customize it to whatever makes sense for your business.

Step 2. Run Each Prompt Across Multiple LLMs

Different LLMs pull from different sources, so answers will be different across all of them.

Tracking prompts from only one LLM won’t give you a full picture of your brand’s presence in AI search.

Ideally track prompts in all major LLMs, including:

• ChatGPT
• Gemini
• Perplexity
• Claude

If you need to save time, review Presenc AI’s 2026 platform demographics report to identify which LLMs your audience actually uses and focus on those.

Pro tip: Make sure you’re using a temporary chat to run your prompts. Your regular chat window will serve you an answer that takes into account everything it knows about you from past conversations. You want to track what an LLM might recommend to anyone, not just you specifically.

Step 3. Run Each Prompt at Least Twice Per Session (Optional)

Answers will vary run to run. So if you have the time, run each prompt 2-3 times per session for more reliable data.

You’ll catch when your brand shows up one out of three times (a 33% mention rate).

If you don’t have time, don’t worry. You’ll still see trends over time.

Step 4. Log Competitor Mentions, Too

Competitor data is half the value of prompt tracking.

Seeing a competitor get mentioned consistently in a category you’re performing less well in is a signal.

Maybe they published a new comparison page. Or were included in an influential report.

Look into their strategy to see what they’ve done to improve and learn from them.

Step 5. Track Weekly. Action on Data Monthly.

Regular prompt monitoring on a weekly basis is often enough to catch shifts.

It gives LLMs enough time to crawl and learn from new or updated content.

But don’t make any decisions with only one week of data.

A single week of low visibility in a category could be a fluke. Four weeks of it is a trend worth acting on.

(We’ll cover what to do when you spot one in the “How to Read and Act on Prompt Data” section below).

In this example, Asana shows up with a low citation rate for two LLMs only one week out of four.

Rushing to fix that ASAP could turn out to be a waste of time.

Step 6. Upgrade to an Automated Prompt Tracking Tool

Manual LLM visibility tracking is a great way to validate that you can actually get some useful insights from the practice.

But if you want to grow your prompt set beyond 20-30 prompts, it’s going to start taking much longer.

A tool like Semrush can help you move faster and suggest actionable opportunities based on your data.

To get started, open the Visibility Overview dashboard, enter your domain, and click “Check AI Visibility.”

You’ll see a summary of how often LLMs mention your brand, which competitors are mentioned alongside you, and a breakdown across each LLM.

Scroll down for a list of prompts where you’re already getting mentioned. Click “Opportunities” to see your gap prompts.

Click “Monitor” on the prompts you want to include in your prompt set.

Pick the LLMs you want to monitor, paste in your prompts, and hit “Start Tracking.”

You can add tags by intent, topic, or campaign so you can slice the data later.

Further reading: See how the top AI visibility tools stack up on pricing, LLM coverage, and reporting features.

Example: How an Agency Tracks Prompts for E-Commerce Brands

When you’re tracking hundreds of prompts across multiple clients, a basic spreadsheet won’t be enough.

Jonny Nastor, Founder & Head of Strategy at Digital Commerce Partners, knows this firsthand.

He built a prompt tracking map based on the theory that most buyers ask LLMs about a specific job they need done or task to accomplish. Then filter by their specific situation (a.k.a. constraints).

For example, when shopping for smart doorbells, a buyer might search “best video doorbell with no monthly subscription fees.”

The job to be done is “best doorbell.” The constraint is cost (low fees or no subscription).

He calls it a “Constraint Map.” Every intersection of job and constraint in the map becomes a prompt.

He gets ideas for constraints from keyword modifier data. In Semrush, you can see these in the Keyword Magic Tool.

He also pairs each prompt with search volume data to roughly understand its popularity and prioritize accordingly.

He runs his prompts across ChatGPT, Perplexity, and Gemini automatically through their APIs to log how each one responds.

Depending on the client’s needs, he tracks one or all of the following AI visibility metrics for each prompt:

• How many times the brand was cited by LLMs
• The brand’s recommendation (or mention) rate
• Instances of ghost ranking

For this client, it was only citations on Bing’s AI search.

For each metric, he watches for trends over time, not drawing any conclusions based on one week of data.

He also audits content readiness with a mix of the following (again, depending on client needs):

• If a page exists to address the prompt
• If that page links directly to the specific products that answer the prompt
• If product details (attributes) like price, dimensions, compatibility, etc., are listed on the page
• If the content on the page is extractable by an LLM (e.g., no bot-blocking settings or JavaScript-heavy rendering that prevent AI crawlers from accessing the page)

This tells him exactly what to fix so AI is more likely to recommend the brand.

This system surfaced ~52,000 monthly searches with zero AI coverage for one of Jonny’s clients. And a content strategy for the next quarter.

How to Read and Act on Prompt Data

Generative AI prompt tracking data might seem hard to trust at face value.

LLMs give variable answers even in temporary chats.

Platforms push silent model updates that tweak source weighting.

And training data bias is real. One study found LLMs often favor global brands over local ones, meaning you might be invisible in your category because of the model’s defaults rather than your content.

Margaret at Hootsuite found the changing outputs of LLMs surprising when she first started prompt tracking:

It was way more chaotic than I expected. The same prompt can return a totally different brand list on ChatGPT vs Gemini vs Perplexity. “AI visibility” isn’t just a single thing to optimize for: you’re effectively running parallel strategies, and they don’t transfer cleanly, and answers will fluctuate constantly.

This variance doesn’t mean prompt tracking data is useless.

But it is the reason you need to track trends over time instead of getting hung up on moment-specific snapshots.

Here are a few meaningful signals to watch for.

Increased (or Decreased) Frequency Over Time

A consistent rise in mentions or citations usually means your content efforts are working.

A consistent drop could mean a competitor is gaining ground or a key piece of content has gone stale.

Action to take: If the trend is up, note what you published in the weeks before the lift. That’s your playbook. Keep doing it.

If it’s down for four or more consecutive weeks, pick one fix for that category:

• Refresh a stale piece with updated data
• Publish a new comparison page targeting the prompts you’re losing
• Pitch a third-party source that’s being cited in that space

Consistent Source Inclusion

If you repeatedly see the same third-party sources cited in your LLM visibility tracking data, stop and take note.

It means the LLMs trust these sources.

And third-party sources are powerful for AI visibility. Airops found 85% of brand mentions come from third-party pages.

For example, if G2, TechRadar, and Capterra keep appearing across your evaluation prompts, those are your priority pitches.

Semrush’s AI Visibility Overview can help identify sources.

You can see your top “Cited Sources” and “Source Opportunities” (where you’re not being mentioned but your competitors are).

Action to take: Make a list of the sources that keep showing up. For each one, check if you’re already featured. If so, is your listing current and accurate?

Then, pick one you’re missing from and pitch it. A contributed piece, product review campaign, or quote request can all work.

Unless you’re correcting a mention, don’t try to pitch competitors’ sites. They’re not likely to accept.

And don’t only focus on categories you’re losing. Reinforcing visibility in categories you’re already winning is valuable too.

Movement from Mention to Citation

If you used to get mentioned and now only get cited as a source, you’ve slipped into what Jonny calls “ghost ranking” territory:

“Your content shows up in the citation panel, but the AI recommends a competitor.”

Like this example from Teva.

An increase in your “ghost ranking count” over weeks means it’s time to investigate.

Jonny knows this first hand:

Our prompt tracking showed our agency was being cited on agency-directory pages (Trustpilot, Clutch, Semrush) but ghost-ranked at an 83% rate. AI was using directory content as the source of truth, then recommending whichever agency had the densest, most-named presence.

Action to take: Find the sources showing up in the citation panel and audit your presence on each one. Fuller profiles, more reviews, and accurate product details all help convert a citation into a recommendation.

For Teva, this means pitching to be included in the cited articles by REI, backpacker.com, and Outdoor Gear Lab.

It also means updating their own pages (including the ones being cited) with more or newer details.

Then, watching to see if they get less ghost rankings over time.

Common Misreads to Watch for

When you first start generative AI prompt tracking, try to avoid getting tripped up by the following false conclusions.

“Our AI visibility dropped this week. Something’s wrong.”

One week of low visibility or mentions is likely natural variability.

Wait for four consecutive weeks before treating it as a trend worth acting on.

“Our score looks low. We need more content.”

A score can be low for multiple reasons, and the fix isn’t always new content.

Sometimes it’s getting included in more third-party sources or forum threads. Or getting more customer reviews.

If you’re just starting out, you may need to go back to your prompts and make sure they’re not too vague or top-of-funnel.

For example, a broad query like “mesh wifi” may return a definition answer rather than a list of brands.

“Our overall visibility improved after adding more prompts to our tracker. We’re doing something right.”

Adding more prompts to your prompt set will usually make it look like your AI visibility has increased. You’re getting mentioned in more prompts.

“Our overall visibility improved after adding more branded queries. We’re doing something right.”

A branded query is one that mentions your brand name. Of course you get mentioned in the answer.

That doesn’t tell you anything useful.

Limit tracking branded prompts to comparison and reputation prompts. And keep them in a separate cluster so you can filter them when measuring your overall AI visibility.

Weekly Prompt Tracking Workflow

Turning prompt tracking data into a strategy is where you prove the value.

Margaret starts by looking at topics where Hootsuite has low visibility.

Then I look at individual prompt answers to see “What does the internet think about us in this category, and how do we change that?” This usually translates into a few concrete questions for further research:

• Where are the third-party listicles, comparison posts, and analyst write-ups that the model is pulling from, and are we represented accurately on them?
• Do we have a first-party comparison or evaluation page that an LLM can confidently cite, written for the actual buyer in that vertical?
• Do we have our customers (ex. case studies, reviews) reinforcing the same message?

From here, she can recommend actions like updating a case study or getting a mention in a third-party listicle.

Here’s a simple workflow you can use to turn your prompt monitoring routine into AI visibility gains over time.

Pro tip: Don’t expect overnight wins. LLMs take time to reflect new content. Watch for directional improvement over weeks and months. You’re not chasing a score; you’re watching whether your gaps are closing over time.

Step 1. Review prompt cluster trends weekly: What’s the visibility score for your BOFU prompts? Has it fallen for your healthcare cluster? Or a specific use case category?

Step 2. Spot recurring gaps: Note any clusters, categories, or topics that have been underperforming for four weeks or more.

Step 2a. Plan one fix per cluster: Use your content strategy brain to determine the most impactful fix.

That might be:

• Publishing a new comparison page to improve a BOFU prompt cluster’s score
• Updating an existing article with fresher data
• Publishing a type of content you haven’t tried yet on this topic (e.g., video, podcast, social post)

Step 3. Identify recurring third-party sources: Note sources AI consistently cites across your categories. Reddit? LinkedIn? G2? YouTube creators? A trade publication?

Step 3a. Pitch one source you’re missing from: If accepted, you’ll build more off-site authority and increase your chances of being mentioned in the answers you care about.

Bonus resource: Pitching a journalist or news outlet? Use our Journalist Pitch Template, designed by PR experts, to get started quickly.

Start Winning AI Visibility with Prompt Tracking

Prompt tracking isn’t a scoreboard. It’s a compass.

The brands that get real value out of prompt tracking aren’t monitoring every possible prompt.

And they aren’t reacting to one bad week.

They focus on bottom-of-funnel prompts and follow the direction of the graph, not the dot.

Now, it’s your turn:

• Build a set of 20 relevant prompts
• Download our free prompt tracking template
• Log and review data for 30 minutes every week

Once you’re up-and-running, dig into our complete AI optimization guide to get tips on how to fix the issues prompt tracking surfaces.

The post Prompt Tracking: How to Find (and Fix) Your AI Visibility Gaps appeared first on Backlinko.

A study by Muck Rack found that 84% of AI citations come from earned media, third-party sources like editorial coverage, reviews, and forums.

In AI search, third-party validation beats self-promotion.

Publishing onsite content is still important, no doubt. But your AI visibility is mostly shaped by what happens outside your website.

The more frequently your brand name appears across the web, the more likely LLMs are to recognize, trust, and eventually recommend you.

In this guide, I’ll show you six proven digital PR strategies to earn more backlinks and brand mentions, strengthen your offsite authority, and increase your visibility in AI-generated answers.

Why Digital PR Now Shapes AI Visibility

AI systems go well beyond reading your website.

They pull information from dozens of sources across the web, then combine it into a single answer.

The brands that win in AI search are those that appear consistently across those sources.

That’s where digital PR comes in.

It’s how you get featured in the right publications that AI systems already read and reference.

The more places you show up, the more familiar and trustworthy your brand looks to those models.

Here are six digital PR strategies to start building that presence.

Strategy 1: Data-Led PR

Data-led PR revolves around publishing original research and statistical roundups, and distributing the data to relevant publications.

This is one of the most effective ways to build high-quality backlinks.

Why?

Because journalists, bloggers, and marketers are constantly looking for credible data to support their content.

How It Boosts AI Visibility

Backlinks matter a lot for SEO. And they still matter for AI visibility.

Semrush’s study of 1,000 domains found that brands with stronger backlink authority are more likely to appear in AI-generated answers.

Seer Interactive’s study backs this up:

The top two metrics that impact AI visibility are domain authority and high-quality backlinks (from DA 60+ sites).

Data-led content is how you earn those quality backlinks. People love citing fresh numbers.

I helped one of my clients, Resource Guru, put together the “Agency Overworking Report 2025.”

Since it was published, this report has generated 21 backlinks naturally, including coverage in Forbes.

It’s also consistently being cited in AI answers.

How to Do It

First, publish your data-led content.

You have several options:

• Conduct new research nobody has done before: This is an excellent choice if you’re in a growing field like GEO, where data is scarce, and any credible study will attract attention.
• Update existing studies: Find stats that haven’t been refreshed in over two years. Outdated data is everywhere, and writers actively look for newer numbers to replace them. If you can be the source that fills that gap, you’ll earn the citation.
• Compile existing statistics: You don’t always need to generate new data. Aggregating hard-to-find stats into one well-organized resource can be just as link-worthy.

Once your data is live, pitch it proactively.

Find articles in your niche that reference outdated statistics or cite sources that no longer exist. Reach out to the authors and offer your fresher data as a replacement.

Also, pitch your new data to existing statistical roundups in your niche. These pages are usually updated frequently, so the author is more open to new additions.

Here’s an example of a good pitch that I received for my AI SEO stat roundup:

Strategy 2: AI Citation Outreach

AI citation outreach is the practice of securing placements in the specific sources AI models already pull from.

In my experience, it’s the quickest way to start earning brand mentions in AI responses.

How It Boosts AI Visibility

If you can get into the content AI cites, you can influence the answers AI gives.

For example, my agency Position Digital was included in Exposure Ninja’s listicle on “The Best AI Search Optimisation Agencies in 2026.”

And since that listicle was cited by ChatGPT, my agency ended up being recommended in one of the answers.

How to Do It

LLMs cite content differently. Each model has its own preferences, tendencies, and patterns.

For example, I asked AI Mode and ChatGPT to recommend the best SEO tools.

Here’s what ChatGPT said:

And here’s the AI Mode answer:

Similar answers. But totally different citations.

So, you need to tailor your strategy to each AI model you want to target.

1. Research user prompts

Start by mapping out the prompts your target audience is likely to type into AI tools.

AI companies haven’t given us prompt data yet, so we’ll have to settle for educated guesses.

Here are some good places to start:

Alternatively, you can use Semrush’s AI Visibility Toolkit to find out exactly what your audience is typing into LLMs.

2. Monitor the cited pages

Once you have your prompt list, run each prompt through each AI model and note which pages are cited.

If you don’t want to do it manually, Semrush’s AI Visibility Toolkit shows you the sources for each prompt.

You can also use ListBrew to surface “best X” listicles and comparison pages that already get cited in AI answers for your target prompts.

3. Find the contacts

Find the contact information for each opportunity using tools like Hunter and Apollo.

Tip: Prioritize someone who has editorial control over the content, like the author or content editor, rather than generic email addresses like hello@domain.com.

4. Send personalized pitches

Reach out to each prospect and ask to be included in the content.

Keep the pitch short and specific to their piece. To increase your chances, offer something in return, such as:

• A free trial or demo of your product
• A reciprocal mention in one of your own high-traffic pieces

Also, prepare a short blurb that the author can easily copy and paste into the content. It seems simple, but it makes a big difference.

Here’s an example of a pitch I sent during one of my listicle outreach campaigns:

Strategy 3: Reactive PR

Most digital PR campaigns take weeks or even months to prepare and execute.

Reactive PR is about speed — being the first one to respond to breaking news, viral trends, and emerging topics.

How It Boosts AI Visibility

LLM training data has a cutoff date.

When someone asks about a current event, the model can’t rely on what it already knows. It has to search the web for fresh sources.

That’s your window.

When a story first breaks, there are usually only a few credible sources covering it.

If your brand is among the first to publish useful commentary, analysis, or original reporting, your content has a much higher chance of being surfaced and cited by AI systems.

Here’s a solid example:

Search Engine Journal was among the first media outlets to report on Google’s new SEO guidelines.

The piece has since gained over 16,000 readers, 500 backlinks, and several AI citations.

How to Do It

The biggest challenge with reactive PR is spotting trending stories before they become a trend.

By the time a topic is dominating headlines, you’re already too late.

Success comes from identifying emerging conversations while they’re still gaining traction.

A few ways to do that:

• Join online communities: Many trends gain momentum on Reddit, X, and Slack before they receive mainstream coverage.
• Follow industry leaders on LinkedIn: Experts often share breaking news, observations, and predictions here before publishing full articles or reports.
• Follow the major players in your industry: Product launches, partnerships, acquisitions, funding rounds, and policy changes often create PR opportunities. The sooner you spot these developments, the faster you can react.
• Track journalist requests: Platforms like Qwoted, Featured, and JournoRequests can reveal stories that journalists are actively working on before they’re published.
• Use Google Trends and Exploding Topics: These tools help you find emerging topics that your audience is searching for right now.

A secondary layer of this process is monitoring how stories spread across publications.

Many trends don’t appear out of nowhere in major media — they first circulate through smaller blogs and niche industry sites.

Tracking this ripple effect helps you identify narratives early and position your response while the topic is still evolving.

• Set up Google Alerts: Create alerts for important keywords, competitors, and industry topics so you get notified as soon as new stories are published.
• Monitor industry newsletters: Curated newsletters are often one of the fastest ways to discover emerging trends and conversations.

Once you spot an opportunity, move quickly.

Write a report or a commentary piece on your website and social media, and pitch the story to major news outlets in your field.

Strategy 4: Ego Bait

Ego bait involves creating content that features industry experts and influencers.

The goal is to stroke their ego, making them more likely to share your content, mention your brand, or link back to your site.

How It Boosts AI Visibility

Featuring recognized experts can improve AI visibility in two ways.

First, it increases the credibility of your content.

An AI SEO study found that pages containing expert quotes receive 4.1 citations in ChatGPT on average, compared to 2.4 for pages without them.

And we’ve seen it firsthand.

Our article on SEO competitor analysis features insights from 20 experts, and it’s cited by both Google’s AI Overviews and AI Mode.

Expert commentary acts as a trust signal, making the content more authoritative and cite-worthy.

Second, it creates a distribution channel.

When experts are featured in your content, many will share it with their audience, mention it on social media, link to it from their websites, or include it in newsletters.

As those mentions and backlinks accumulate, your brand becomes more visible across the web.

Stronger brand visibility = stronger LLM visibility.

How to Do It

There are three types of ego-bait content you can create:

1. Expert roundups

Use journalist outreach platforms like MentionMatch, Featured.com, and Qwoted to gather expert insights for your content.

Choose the best quotes and feature them on your blog post.

Once it’s live, tag every contributor in your LinkedIn post.

Most will reshare it, comment, or at minimum engage with it, which extends your reach well beyond your own following.

2. Case studies and success stories

Highlight real results from customers, partners, or collaborators.

A well-written case study flatters the subject, gives them something worth sharing, and adds a layer of credibility that generic content can’t replicate.

3. Top experts or influencers lists

Curate lists of respected people, companies, or voices in your category.

Examples include:

• Top SEO Experts in 2026
• Most Influential AI Search Voices
• Leading Growth Marketers in SaaS

Being included in a curated list is often incentive enough for people to share it, especially if the selection feels credible and relevant.

This type of structured content is also highly citable by AI systems.

Strategy 5: Thought Leadership

SEO content is built to rank.

Thought leadership content is designed to establish you as a recognizable voice — both for people and LLMs.

And when you already have an established presence, it’s much easier to market your business.

How It Boosts AI Visibility

Most content gets ignored because it fails to give people a reason to engage.

Thought-provoking content, on the other hand, is designed to challenge assumptions, introduce new perspectives, and spark discussion.

Just look at this “controversial take” from Khanh Linh Le.

This post generated an unusually high number of comments relative to its likes because it challenged conventional thinking and encouraged debate.

Some people agreed. Others pushed back. But everyone had something to say.

That’s the goal: to drive engagement.

Engagement drives shares. Shares drive mentions across blogs, forums, social platforms, and publications.

And when a lot of people talk about you, AI pays attention.

How to Do It

1. Build a LinkedIn presence

The first step is to start posting on LinkedIn.

Why?

Because at the time of Semrush’s study, LinkedIn was the second-most-cited domain in ChatGPT, AI Mode, and Perplexity.

Some tips:

• Publish consistently: AI citations reward relevance and consistency more than virality. The Semrush study found that 75% of cited authors post at least one post per week.
• Take a stance: Share opinions, challenge assumptions, and weigh in on debates happening in your industry. Posts that take a clear stance generate far more engagement than informational updates.
• Use your personal and company pages: Some LLMs like Perplexity gravitate more towards company pages, while others like ChatGPT and AI Mode like citing personal pages.

2. Write guest posts for major publications

Guest blogging is a great way to distribute your ideas and share your expertise in high-authority publications.

When multiple authoritative sources cover the same topic and all point back to you as the originating voice, AI models start to recognize you as the go-to authority on that subject.

At Position Digital, I’ve developed a framework called the Guest Post (GP) Engine.

Here’s how it works:

I publish a blog post on my website.

I then publish variations of that post on other publications, ideally those with a high website authority.

As an example, I wrote about “Content Refreshes” on the Position Digital blog.

I then wrote guest posts on the same topic on Sitebulb and Surfer SEO.

All three articles are now cited by AI Overviews.

3. Appear as podcast guests

Podcasts are one of the most underutilized thought leadership channels.

A single appearance can generate:

• Mentions on the host’s website
• Show notes and transcripts
• Social media clips
• Newsletter features
• Citations from future content creators

If you’re just getting started, don’t chase after big, established shows.

Start small. Build relationships with newer podcasts in your niche.

Smaller shows are easier to get on, their hosts are often more engaged, and the content still gets indexed and cited.

As your reputation grows, the bigger opportunities follow naturally.

Strategy 6: Community Building

Community building is about establishing your brand’s presence in third-party forums, review sites, and customer rating platforms that AI models treat as trusted, independent sources.

This way, your brand is validated not just by what you say about yourself, but by what neutral platforms say about you.

How It Boosts AI Visibility

AI models trust neutral, community-driven sources over brand-owned marketing.

It’s not an opinion. It’s backed by actual data.

According to another AI visibility study by Semrush, LLMs cite Reddit threads about Microsoft products much more frequently than Microsoft’s own blog.

Let that sink in.

And it’s not just forums like Reddit. Review platforms like Trustpilot and G2, where users can share authentic reviews and ratings, carry significant weight too.

Seer Interactive also did a study of 800k AI responses and found that brands with no Trustpilot profile have a median AI citation rate of just 1%.

Brands with even a minimal profile, as few as 1 to 13 reviews, jump to 53.5%.

The implication is clear:

If AI has to choose between what a brand says about itself and what hundreds of independent users say about that brand, it will often favor the latter.

How to Do It

1. Contribute insights on Q&A platforms like Reddit and Quora

These communities are scraped heavily by AI models and frequently cited in responses.

But be careful, Reddit and Quora communities have a low tolerance for overt self-promotion.

Accounts that exist purely to promote a product get flagged, downvoted, or banned.

The key is to participate as a real contributor, not as a marketer.

Be transparent about who you are and what company you represent, but focus primarily on being helpful.

Further reading: Reddit Marketing in 3 Hours/Week: From 0 Karma to Real Cred

A good approach is to contribute meaningfully to 3–5 relevant threads per week.

Only mention your brand when it is genuinely relevant to the question or adds value to the discussion.

You can also host an AMA (Ask Me Anything) session to share your knowledge while building brand awareness.

2. Create optimized profiles in review sites

Depending on your niche, set up and optimize your profiles on review platforms like:

• G2, GetApp, and Software Advice for B2B SaaS
• Trustpilot and Clutch for agencies and service providers
• Tripadvisor and Google Reviews for hospitality and local businesses

After that, make sure to ask your existing customers to leave positive reviews and ratings.

3. Write content on Medium

Medium is another platform that AI frequently cites, according to the Semrush study above.

Use it to republish condensed versions of your best content or share original perspectives that complement your main blog.

Publishing the same ideas on Medium that you’d put on your own site gives those ideas a better chance of being cited.

Show Up Where AI is Already Looking

The quickest path to AI citations is getting into the pages AI already trusts.

Start by using Semrush’s AI Visibility Toolkit to uncover the prompts your audience is typing into AI chatbots.

Then, review the sources each AI platform cites for those prompts and find a way to earn a placement there.

When you’re ready to go deeper into how to optimize for citations and influence AI answers, read this guide on LLM seeding.

The post 6 Digital PR Strategies to Boost AI Visibility appeared first on Backlinko.

“Guestographics”.

Specifically, I’ll show you how Perrin used this technique to hit Google’s first page for a bunch of his target keywords.

Let’s dive right in.

The Guestographic Method:
An SEO Strategy That Gets Results

Guestographics work for one simple reason:

They make your content MUCH easier to share.

I published a post a while back that outlines the entire process: How to Get Backlinks With Guestographics.

So if you haven’t read that post, go check it out.

In that post I reveal how The Guestographic Method increased my organic traffic by more than 175%:

And Guestographics are one reason that Backlinko ranks in the top spot on Google for “on page SEO”:

Does this sound like something you’d like to try?

Keep reading…

How Perrin and David Used Guestographics to Skyrocket Their Rankings (And Traffic)

I just showed you how well Guestographics worked for me.

Now it’s time to reveal Perrin and David’s results.

First up, we have Perrin Carrell.

A while back, Perrin launched a pet blog called HerePup.

Why did Perrin make this blog?

Well, a few months before Perrin picked up a cute little black puppy from an animal shelter (Chewie).

Like most new dog owners, Perrin searched for the best dog food for Chewie…

…but he didn’t find any content that blew him away.

That’s when Perrin realized that he had a HUGE opportunity staring him in the face:

There aren’t any dog blogs with mind-blowing content. Why not make the first one?

In Perrin’s own words:

“I saw a few smaller blogs ranking for low-competition keywords. I thought I could top what they were doing. I also noticed that authoritative pet blogs were getting insane traffic. Even though it was going to be really tough to beat these bigger sites, that showed me that the ceiling in this niche was really high.”
Perrin Carrell

After dozens of late-night writing sessions, Perrin’s site went live:

(Note: Perrin’s original name for the blog was Chewie Says. But he recently changed it to Here Pup.)

That’s the good news.

The bad news? The dog blog space is dominated by a handful of massive authority sites.

That means that Perrin is going toe-to-toe with mega-sites like PetMD.com and Cesar “The Dog Whisperer” Millan.

You could even say that it’s a dog-eat-dog world (sorry, I couldn’t resist ? ).

To have a fighting chance against these massive authority sites, Perrin had two options:

Option #1: He could grind away on his blog, publish on a set schedule, and HOPE he got traffic (“The Publish and Pray Approach”).

Option #2: He could create (and promote) a few pieces of amazing content.

Fortunately for Perrin and his new blog, he pulled the trigger on option #2.

And he decided to kick things off with Guestographics.

How did it go?

Guestographics boosted his organic search engine traffic by 963% in just 6-weeks:

And thanks to placements on a handful of popular pet blogs…

…and The Huffington Post…

…he also funneled over 1000 targeted referral visitors to his site:

Not bad for a brand new blog.

Note: His secret was NOT a $10,000 infographic. As you’ll see in a minute, the design had very little to do with Perrin’s success.

With that out of the way, it’s time for me to walk you through the step-by-step process.

Step 1: Create and Publish a (Really Good) Infographic

Here’s the deal:

Despite what most “content marketing gurus” would have you believe, design plays a VERY small part in an infographic’s success.

In fact, choosing the right topic is 90% of the game.

And that’s where Perrin’s infographic — 22 Ways Dogs Make Humans Healthier — hits a home run:

Sure, his infographic looks really nice.

But it wouldn’t have done NEARLY as well without a topic that dog lovers cared about.

Now:

Perrin had a hunch that dog owners would want to learn that Mr. Fluffy Pants improves their health.

So he searched for “dogs and human health”.

And he came across this slideshow from WebMD ranking on the first page:

(Yes, that’s really what it looks like.)

As Perrin puts it:

“That’s not a good article. It’s just fun facts with cute blurbs. There’s no design or research to speak of. I knew I could do it better, and one of the ways I wanted to improve it was to make an infographic.”
Perrin Carrell

Even though the WebMD page leaves A LOT to be desired, it attracted backlinks from over 300 referring domains:

In other words, Perrin saw that there was proven demand for content about “ways that pets improve human health”.

But not just any information…

…demand for visual content.

So Perrin decided to create an infographic around that proven topic.

First, he spent a day researching content for the infographic.

Then he hired a freelance designer to take his list of bullet points…

…and turn it into a professional infographic.

Looks nice, right?

As you probably know, publishing something valuable isn’t enough to generate quality backlinks and targeted traffic.

If you’re serious about getting results from your content, you need to strategically promote it.

This leads us to step #2…

Step 2: Find People That Are Interested In Your Infographic

Once your infographic is ready, it’s time to make a list of people that might want to check it out.

The easiest way to do that? Search for keywords that describe your infographic’s topic.

For example:

Let’s say that you just published an infographic about the Paleo Diet.

You’d Google keywords like “Paleo diet”, “Paleo diet recipes”, “what is the Paleo Diet?” etc.

And Google will show you a list of blogs that tend to cover that topic:

You can even use Google Suggest to get even more keyword ideas:

Here’s how Perrin found his Guestographic prospects:

Like I just outlined, Perrin searched in Google using keywords like “pets and health.”

But he didn’t stop there…

He also searched for keywords like “top 50 dog blogs”.

These “best of” keywords hooked Perrin up with hand-curated lists of popular pet blogs:

Once you’ve found a quality blog in your niche, here’s what to do next:

Step 3: See If They’re Interested In Your Infographic

Most people pitch bloggers the complete WRONG way.

Instead of gauging interest with a feeler message, they go straight for the hard sell.

You’ve probably received some of these annoying emails yourself.

Have you ever replied to any of them?

I didn’t think so. 🙂

That’s why you want to start off the Guestographic outreach process with a quick email…

…A quick email that simply asks them if they want to see your infographic.

Here’s a tested script you can use:

And here’s the the exact feeler email that Perrin sent out:

See how Perrin’s message is completely different than most pushy outreach emails?

He’s just asking if they’d like to see the infographic… which is an easy sell.

In other words, you don’t want to link to anything in your first email.

Why not?

When someone sees a link in an email from someone they don’t know, they think: “this person must want something”.

And they hit the delete button.

But when you send an email that simply asks if they want to see your content, it’s usually received with open arms.

In fact, Perrin sent 92 emails…

…and he got 5 conversions (that’s a 5.4% conversion rate).

Solid.

Now:

Once you get a response back saying, “sure, send it over”, like this…

…it’s time for step #4.

Step 4: Make Sharing Your Infographic a Breeze (AKA, “The Bribe”)

When you want another site to link to you, you need to remember one thing:

The more barriers you remove, the more success you’ll have.

(This is true of anything in marketing… not just email outreach.)

Well, what’s the ONE thing that prevents people from sharing an infographic?

The fact that they have to write a unique introduction to go along with it!

Well, the beauty of Guestographics is that you remove that barrier.

How?

By writing that introduction for them.

This is the template that I use:

And here’s the email that Perrin sent to the people that liked his infographic:

And because you’re making their life easier, your response rate will be MUCH better than a pushy pitch:

When someone says “sure, send me an introduction”, send them a high-quality 200-250 word intro.

Oops. I almost forgot.

Here’s the script to use when you send your intro:

And here’s the email Perrin used to send people his unique introduction:

Step 5: Add a Link In Your Introduction

This is important:

The unique introduction doesn’t just make sharing your infographic easier.

It also makes your link MUCH more powerful.

How?

Unlike most infographic backlinks, which appear automatically when someone shares your infographic using an embed code, like this…

…Guestographic links are surrounded by unique content in the introduction.

Links in the intro boost your referral traffic and is better for SEO.

In total, Perrin’s Guestographics campaign brought in 8 niche-relevant, white hat backlinks.

(5 came from Guestographics. The other 3 were natural placements that happened after his infographic spread around the web.)

That’s a total cost of $25/link. Not bad.

The post How to Rank on Page 1 of Google FAST (In-Depth Case Study) appeared first on Backlinko.

This makes sense once you understand query fan-out, a background process AI systems use to build answers.

When someone asks ChatGPT or Perplexity a question, it doesn’t default to the best-ranking page.

Instead, it runs related searches behind the scenes, pulling from the most relevant and reliable sources, regardless of position.

If your brand doesn’t show up in those searches (whether through your own content or third parties), you’re unlikely to make it into the answer.

High rankings don’t hurt, of course.

But in AI search, coverage and retrievability are king.

In this guide, I’ll teach you how to optimize your content strategy for query fan-out to help increase your AI visibility.

You’ll learn:

• Why LLMs use query fan-out
• How it behaves differently across major AI platforms
• Why it changes how you create and structure content
• A 6-step workflow for earning more citations in AI search

Free template: Our Query Fan-Out Audit Template includes ready-to-use spreadsheets for logging money prompts, sub-queries, and content gaps — plus a checklist to keep you on track. Download it now to follow along.

First, I’ll dive deeper into how query fan-out works.

What Is Query Fan-Out?

Query fan-out is a process AI search systems use to break a single user query into multiple sub-queries to create the most helpful response.

In other words, the AI “fans” the query out into a series of related sub-questions to build a more complete picture of the topic.

It then pulls information from multiple sources — editorial sites, Reddit threads, comparison and product pages — and synthesizes it into a single comprehensive answer.

AI systems use query fan-out for a few reasons:

• Confirm information: A single source might be wrong or biased. Running parallel sub-queries allows the system to cross-reference multiple sources and find consensus before committing to an answer.
• Handle complex, specific queries: When a question has multiple layers, like comparing two products across price, reliability, and long-term value, fan-out breaks it into manageable pieces that the system can research independently.
• Answer the real question: Someone searching “best toothbrush” probably also wants to know about price, battery life, and durability, even if they didn’t say so. Fan-out anticipates those needs and gathers evidence upfront.

For example, a search for “best toothbrush” might trigger sub-queries like “best electric toothbrushes [year]” and “best toothbrushes for sensitive gums.”

This helps the AI build a more complete and useful answer:

The AI then synthesizes those findings into a single answer that covers everything the user might want to know: top picks, price ranges, use-case breakdowns, and comparisons.

In this way, it anticipates the user’s needs, even though the original prompt (best toothbrush) was just two words.

What Query Fan-Out Is NOT

Now that we’ve covered what query fan-out is, let’s clear up a few common misconceptions.

Query fan-out is not:

• Keyword research: This is the process of finding terms your audience searches for. Query fan-out is something AI systems do automatically, behind the scenes, every time someone asks a question.
• People Also Ask: PAA is a visible SERP feature that shows users what else they might want to search. Fan-out happens in the background whether you can see it or not.
• A fixed set of queries: Only 27% of fan-out sub-queries remain consistent across repeated searches, according to a SurferSEO study. Sub-queries vary by phrasing, user context, and platform.

Further reading: AI SEO Myths, Debunked: A No-BS Guide for Marketers

Why Query Fan-Out Matters for AI Visibility

Understanding what query fan-out is only gets you so far. The real question is: What does it mean for your content strategy?

Here are four shifts that should make you rethink how you approach content.

You Don’t Need Top Rankings to Get AI Citations

Top rankings don’t automatically translate to AI citations.

When AI breaks a query into sub-queries, it pulls the most relevant and complete source for each one, regardless of where it ranks.

ChatGPT cites pages in position 21+ almost 90% of the time, according to a Semrush study.

Perplexity and Google show the same pattern.

AI Retrieves Passages, Not Pages

Rather than directing users to a page, AI systems scan your content and synthesize the exact passage that resolves a query.

This means that the earlier you answer a question, the better your chances of being extracted.

The data backs this up.

44.2% of citations in ChatGPT responses come from the first 30% of a page, while 31.1% come from the middle, and 24.7% from the final third, according to growth advisor Kevin Indig’s analysis of 1.2 million ChatGPT responses.

You’re Competing Across a Whole Topic, Not Individual Keywords

SEO often revolves around individual keywords. Query fan-out revolves around comprehensive coverage.

That’s why broad, well-connected coverage across a topic (think pillar pages and topic clusters) can help you earn more AI visibility.

Pro tip: Pages that rank for fan-out queries (not just the main query) are 161% more likely to get cited, according to a SurferSEO AI Overviews study.

Query Fan-Out Collapses the Buying Journey

We were taught that buyers move linearly — awareness, consideration, decision — and have long optimized content for each stage.

With AI, those stages collapse into one.

A single high-intent question triggers the system to fan out.

It pulls awareness-level context, consideration-level comparisons, and decision-level specifics into one answer.

The entire buying journey can now happen in a single interaction. So your content needs to work across the full funnel, not just the stage you’re targeting.

Pro tip: Want to work through these steps as you read? Our free Query Fan-Out Audit Template has spreadsheets for tracking your money prompts, sub-queries, intent buckets, and content gaps — plus a checklist to keep the full workflow on track.

The Query Fan-Out Workflow: 6 Steps to Earn More AI Citations

This six-step workflow shows you how to earn more AI citations by identifying and targeting high-impact sub-queries.

It’s repeatable, so you can follow these steps for every topic that matters to your business.

Note: Each AI platform handles fan-out differently, from the number of sub-queries it runs to how it cites sources. We cover the platform differences in depth after the workflow.

Step 1: Find Your Money Prompts

Money prompts are the conversational phrases or questions your ideal customer would ask an AI tool when trying to solve the problem your product or service addresses.

Money prompts are:

• Typically long-tail and highly specific
• Tied to a real use case or constraint
• Close to a decision, not just browsing

Think of money prompts as the AI SEO equivalent of money keywords: high-commercial-intent keywords designed to drive sales.

For example, “noise-canceling headphones ” is a keyword.

“What noise-canceling headphones are best for working from home with kids around, and cost under $300?” is a money prompt.

Look for money prompts where your audience asks questions:

• Customer support tickets
• Community forums
• Sales call transcripts
• Internal chat logs
• Google Search Console queries

For example, when I searched for noise-canceling headphones on Reddit, I found multiple money prompts in real users’ posts.

Like this one that asks for the best noise-canceling headphones for telehealth:

And this one asking for durable headphones that will last longer than 2 years:

Forums and transcripts are a good starting point. But you’ll need a dedicated tool to find money prompts using real AI search data.

Semrush’s AI Visibility Toolkit tells you exactly what users type into AI tools, along with the AI’s response.

To show you how it works, I’ll use Bose, a well-known headphone brand, as an example.

Note: I’ll be using Semrush to show you how to complete the query fan-out workflow. If you don’t have a subscription, sign up for a free trial of Semrush One, which includes the AI Visibility Toolkit and Semrush Pro.

First, I searched Bose’s domain in the Visibility Overview tool.

The “Topics & Sources” report revealed over 123.7K prompts where the brand already appears in AI answers.

Filtering by “noise canceling” let me dig deeper into topic-specific money prompts like “noise-canceling headphones for sensory issues.”

Clicking the prompt provides a full breakdown: the AI’s response, every brand mentioned alongside yours, and the exact sources it cited.

Follow the same process for your own domain.

These prompts are your highest-priority money prompts — your audience is already searching them, and AI is already answering them.

Don’t have AI visibility yet? Use the Prompt Research tool.

Enter a broad topic to see the prompts that generate the most AI results in your industry.

As you find relevant prompts, add them to your spreadsheet.

Even a few money prompts give you enough to work with for the next step.

Step 2: Generate Your Fan-Out Set

There are two ways to generate fan-out sets: manually or with a dedicated fan-out tool.

The manual approach is free and helps you understand how fan-out behaves, while tools are faster and better suited to working at scale.

I’ll start with the manual method.

Paste this prompt template into any AI platform to get a fan-out set:

Expand this question into the sub-queries an AI system might search to answer it: [your money prompt].

When I ran my Reddit money prompt through ChatGPT, it returned sub-queries grouped into categories:

• “Core Product Category”
• “Durability & Longevity”
• “Battery & Hardware Lifespan”
• “Reliability & Failure Rates”

Each category is a potential content gap you’ll address in Step 4.

Run your money prompt through multiple AI tools to get a more complete picture, since each platform tends to expand prompts differently.

Pro tip: Manual research is a solid starting point, but outputs can contain inaccuracies or hallucinations. A dedicated fan-out tool simulates how different AI platforms expand your query and returns an organized list of sub-queries you can act on immediately.

For a faster option, Backlinko’s free ChatGPT Query Fan-Out Tool is worth trying.

Install the Chrome extension, open ChatGPT, and ask your money prompt. The extension captures the response in real time and breaks down every sub-query ChatGPT ran behind the scenes.

When I ran a prompt through it, the panel showed:

• Each sub-query the model generated
• The metadata behind the response, including model version
• Every URL cited, categorized by type: sources, products, images, and news

As you gather sub-queries, assign a query type to each — this tells you what kind of content you’ll need to create in the next step.

Use these definitions to categorize them.

Step 3: Bucket Sub-Queries by Intent Type

Bucketing by intent tells you what types of content to create and the ideal format for each.

To categorize a sub-query, answer this question: What does the person actually want to do after getting an answer?

Consider an example from the noise-canceling headphones query fan-out set: “Sony vs Bose Noise Canceling Headphones.”

Someone asking this is weighing two specific products against each other, so it’s a “comparison” query.

The right format for this query is a head-to-head comparison page or table, not a general buying guide or listicle.

The intent isn’t always this obvious, and some sub-queries may fit more than one bucket.

When that happens, place it where the strongest intent lies.

Here’s a general guide to the main intent buckets and what each one calls for:

Step 4: Audit Your Existing Content for Gaps

Once you’ve bucketed your sub-queries by intent and format, check which ones your site already covers and which ones it doesn’t (aka content gaps).

Start by searching your own site.

Type “site:yourdomain.com [sub-query topic]” into Google.

For example, running “site:bose.com noise canceling headphones” surfaces all their pages on that topic.

From here, evaluate each page against the sub-query it should cover:

• Coverage: Does it directly answer the sub-query, or just mention the topic in passing?
• Format: Is it the right content format for the intent?
• Self-contained answers: Can the answer stand on its own, without the reader needing to look anywhere else?

Categorize each page by its coverage level:

For each sub-query, you’ll also want to know which competitors are showing up for your money prompts.

Run your money prompts through AI platforms to gather this information manually. Or refer back to your research from the AI Visibility Toolkit in Step 1.

Click any prompt to see which brands were mentioned and the exact sources the AI cited.

Already showing up alongside competitors? That’s a prompt worth protecting — focus on strengthening your coverage so you stay in the answer.

If competitors are showing up and you’re not, that’s a gap worth closing before they own it.

Step 5: Structure Your Content So AI Can Extract It

Creating the right content is only half the job. The other half is making it easy for AI to find, parse, and use.

Start by filling the gaps you identified in Step 4.

For sub-queries with no coverage, create dedicated pages or sections that target them directly.

For partial coverage, add self-contained answers to existing pages that resolve the sub-query without needing surrounding context.

Then, structure everything so AI can extract it cleanly:

• Address specific questions directly — lead with the answer, not background context
• Use content chunking: Break content into focused sections with clear headings, short paragraphs, and bullet points
• Front-load key information early in the page or section
• Use clear, precise language, including specific product names, figures, and use-case-specific wording
• Add FAQ sections

Here’s what this looks like in action.

Bose has over 63.9K mentions across AI platforms in the U.S. alone:

It helps that they’re a household name. But their content is also built to be extracted.

Their product pages front-load specific claims as scannable elements — “24 hours of battery life” and “legendary noise cancelation” — rather than burying them in copy.

Key specs are organized into structured comparison tables:

And they build dedicated landing pages for use cases like flying, using descriptive, scenario-specific language.

This matters because AI fans out into use-case-specific sub-queries.

When I searched “best noise-canceling headphones for flight anxiety,” AI Mode recommended Bose, using nearly identical language from Bose’s flight landing page.

When a user’s prompt matches the scenario your page was built for, AI systems may be more likely to pull from it.

This is a clear example of that in action.

You don’t need a complete site overhaul to make this work.

Even restructuring a few high-priority pages to address your fan-out gaps can improve your chances of being extracted and cited.

Step 6: Measure Your Performance in AI Search

Once your content is structured and live, track your performance in LLMs.

Start with the money prompts you identified in Step 1.

For each one, you want to know:

• Are you showing up? Is your brand mentioned or recommended in the response?
• Is what it says accurate? Are the claims the AI makes about your brand correct, or is it pulling outdated or wrong information?
• How do you compare? Which competitors appear in the same response, and how are they positioned relative to you?

If you’re tracking manually, run them through multiple LLMs (in a private or incognito window) and record what you find.

But once you’re tracking dozens of sub-queries across platforms, manually tracking gets messy (and time-consuming).

I use Semrush’s Prompt Tracker to automate the process.

It alerts you to changes in mentions for your money prompts, so you don’t have to keep re-running them yourself.

Another helpful tool is the Visibility Overview.

It provides an AI visibility score that tracks how often you’re showing up in AI answers compared to competitors.

The Perception tool tracks sentiment so you know how LLMs describe your brand — and if they mention competitors more favorably.

It also breaks down the factors driving that sentiment.

For Bose, “industry-leading noise cancellation” shows up as a strength, while “over-the-ear models not sweatproof” flags a use-case they could address with targeted content.

Tracking should be an ongoing process.

Revisit your money prompts regularly and update your content as new sub-queries emerge or competitors gain ground.

How Query Fan-Out Works Across Different Platforms

How content surfaces in an AI answer depends on several factors:

• Whether the system searches the live web or draws from its training knowledge
• How many sub-queries it runs
• Which sources it favors, and how it cites them

Understanding those patterns helps you make smarter decisions about content structure, format, and where to focus your optimization effort.

Plus, if a competitor outperforms you in a specific LLM, understanding how that platform handles fan-out can help you figure out why.

Note: Some of the behavior described below is based on how each system describes its own reasoning when prompted. LLMs aren’t always reliable narrators of their own processes, so treat these observations as directional rather than definitive.

ChatGPT

For simple, informational queries, ChatGPT usually responds from its training data without running a live search.

But that changes when the question requires fresh information, comparisons, or real-world data.

When I asked which car I should buy (Toyota vs. Honda) in Thinking mode, ChatGPT spent about 22 seconds reasoning through the question.

Then, it produced an answer drawn from 41 cited sources

That’s query fan-out in action: one prompt, varied sources, and multiple sub-queries running behind the scenes.

By default, you can’t see the sub-queries ChatGPT runs. But I’ll show you how to find them (don’t worry — it’s easier than it looks).

Note: This DevTools method only works in the web version of ChatGPT. You can’t access sub-query data on mobile or in the desktop app.

First, search a money prompt in ChatGPT.

Then, look at your browser’s address bar and copy the slug that appears after chatgpt.com/c/ — that’s the unique ID for your conversation

Next, right-click anywhere on the page and select “Inspect.”

A developer panel will open on the side of your screen:

• Click “Network” at the top of that panel
• Paste the slug you copied into the filter bar
• Refresh the page

Click on the fetch version of the slug (here, it’s the second option under the Name column).

Then, open the Response tab.

Once it loads, press Ctrl+F (or Cmd+F on Mac) and search for the word “queries.”

What appears is the exact set of internal searches ChatGPT ran before producing its answer.

For the Toyota vs Honda prompt, ChatGPT generated queries around:

• Vehicle specifications
• Fuel economy
• Reliability
• Safety ratings
• Long-term ownership costs

Once you have the sub-queries, cross-reference them against your content.

Are you targeting each one? Do your pages use the same language ChatGPT is searching for — “long-term ownership costs” rather than just “value”?

ChatGPT often pulls from third-party sources like Reddit threads, review sites, and comparison pages.

So topical authority matters here — not just what’s on your site, but whether your brand shows up across the sources ChatGPT is likely to retrieve.

Perplexity

Perplexity runs two types of fan-out simultaneously:

1. Internal fan-out — scans your prior conversation history for relevant context
2. External fan-out — searches the external web for relevant information

The final answer draws on both layers, which means your content needs to work for a range of user situations, not just one.

For the Toyota vs. Honda question, Perplexity’s first batch of sub-queries had nothing to do with the cars.

Instead, it checked whether I’d previously mentioned anything that could shape its recommendation.

Like budget constraints, driving habits, or past questions about either brand.

Only after that internal scan did it launch external searches about reliability, ownership cost, and safety ratings.

What this means for your content: Perplexity may pair your page with context you can’t predict: a user’s past questions, constraints, or preferences.

Your content needs to be specific and self-contained enough to remain accurate and useful no matter the surrounding context.

Claude

Claude takes a different approach.

Rather than immediately running sub-queries, it asks clarifying questions first. Then, it generates a response tailored to your answers.

When I asked the Toyota vs. Honda question, Claude presented a preference widget before producing an answer.

Once I responded, it generated a recommendation tailored to my priorities.

Because it clarifies intent before searching, Claude tends to generate fewer, more targeted fan-out sub-queries than other platforms.

The implication for your content: Answer specific, well-defined use cases directly rather than trying to cover every angle on a single page.

Google AI Overviews and AI Mode

AI Overviews appear as concise, AI-generated summaries with sources listed in a clickable sidebar.

They work by synthesizing Google’s existing web index into a tighter, more contained summary.

AI Mode, by contrast, is a dedicated conversational search tab designed for complex, multi‑part questions.

Like AI Overviews, it draws on Google’s index to generate answers, but it offers more interaction and depth.

Neither platform exposes the sub-queries it runs.

But SEOs have found a way to extract Google’s fan-outs using Screaming Frog configured with a Gemini API. Watch Dan Hinckley’s tutorial for a full walkthrough.

For both, the optimization focus is the same: Front-load your answers, use descriptive subheadings, and structure content so individual passages stand on their own.

AI Search Runs on Query Fan-Out — Your Content Strategy Should Too

High rankings alone won’t earn AI mentions.

The brands showing up are the ones covering the questions their audience is actually asking and making that content easy for AI to extract and cite.

You’ve got the query fan-out framework. Now it’s about execution.

Start with one money prompt, map the sub-queries, and audit where your content stands.

Then work through the gaps, one topic at a time.

Next, dive deeper into how to get your brand seen and trusted across AI platforms with our AI search strategy guide.

The post Query Fan-Out: What It Is and How It Affects AI Visibility appeared first on Backlinko.

Awesome!

This post contains 9 proven link-building strategies that are working GREAT right now.

(In 2022.)

Let’s get started!

1. Use Data to Get Links From News Sites and Blogs

In one of my recent guides I covered how to use HARO to become a source for reporters.

And that’s something you should DEFINITELY be doing.

But HARO connects you with journalists who are planning features in advance.

And what else do reporters do? They report the news of course! And the news doesn’t work on a set schedule.

So… if there’s breaking news related to your niche, that’s a HUGE opportunity to pick up mentions and links.

Here’s what to do:

1. Monitor the news for new mentions of your site’s main topics

The easiest way to do that is by setting up a Google alert or BuzzSumo Alert.

2. Reach out to reporters with added VALUE

If you’re going to get a link from a news site, you’re going to have to put in some work.

You have to provide real value to the reporter. And ideally, make their life easier.

Reaching out and saying “I see you wrote about this, I wrote about it too.” will quickly get you flagged as a spammer.

How do you provide value? Here are some ideas:

1. Give them a quote with personal insight from your industry. Include your credentials.
2. Offer unique data or statistics.
3. Offer an alternative take.
4. Create an infographic or custom visual that they can embed in their story.

Whichever way you go, there’s one thing that’s SUPER important…

You need to act FAST.

Today’s newspaper is tomorrow’s recycling. So ideally you want to reach out the same day that the news is breaking.

Pro tip: Create a personal black book of journalists who cover your industry. Then ping them as soon as you see a story breaking. That way you might catch them while they are still working on an article for publication.

2. Scale The Skyscraper Technique

Yup, skyscraper content is still my #1 go-to tactic for building high quality links.

In fact, this piece of Skyscraper Content that I published a while ago has already racked up 5,6K backlinks:

The best part? This approach is SUPER simple. In fact, it’s so simple, I can boil it down to just 3 steps:

1. Find a popular piece of content in your niche. Hint: popular = lots of backlinks.
2. Make something even better.
3. Promote the heck out of it!

With that, here are a few extra tips to help you scale this strategy.

Find Popular Content

Your first point of call is Google. Search a popular keyword in your niche, and it’s a safe bet that the page ranking at #1 will have backlinks powering that #1 ranking.

But say you’re not sure which topic is going to be best for attracting links. Is there a way to take out the guesswork?

Yup.

(Note: you’ll need an account from Semrush or any other SEO tool for this.)

Semrush and other link analysis tools have a report called “Best by links”. This will show you the most linked-to pages on any site.

For example, you can see that my Google Ranking Factors post has picked up links from almost 5K domains!

So plug in a competitor’s site, find their most popular pages, and you’re set. Easy peasy.

Make Something (a LOT) Better

Found a page to skyscraper? Great. Your next step is to create something even better.

But…

…making your page “a little” better isn’t going to cut it.

If you REALLY want to pull in those links you’re going to have to make something a LOT better.

In fact, I try to make my skyscraper content 5-10x better than the current top page.

How do I do it?

Easy. I work out what’s missing. Then, fill in those gaps.

Here are a few tips from my personal checklist:

1. Does the ranking page go in-depth on the topic? If not, I’ll make sure I cover EVERYTHING it skipped.
2. Is the ranking page text heavy? If so, I’ll include TONS of high-quality images in my post to make it more visually appealing.
3. Does the ranking page include video? If not I’ll add one to mine. In fact, I’ll probably do that anyway!
4. Does the ranking page include 10 tips? Then I’ll include 20. Doubling is a good starting point.
5. Does the ranking page include links to related resources? If not, I’ll make sure mine does.

I’ve yet to find a page that I can’t 10x with a little thought and a lot of hard work.

For example, a few months ago I noticed that most posts about “how to get more YouTube subscribers” sucked.

Specifically:

• They were written by people that don’t have successful YouTube channels
• They cited outdated strategies, techniques and features
• They didn’t have any visuals to show you how to implement each strategy
• They all regurgitated the same tired strategies

So I set out to create something WAY better.

Unlike the other posts that I read, my post had:

• Real life examples of how I used the tips to grow my channel
• New strategies that you couldn’t find anywhere else
• Lots of screenshots and visuals to make the techniques easy to understand (and use)

Promote The Heck Out Of It

Reaching out to people you featured in your content is a good place to start with content promotion.

Besides that, here are some other tips:

1. Reach out to people who linked to your competitor’s page.
2. Reach out to people who commented on your competitor’s page.
3. Reach out to people who shared your competitor’s page on social.
4. Reach out to people who linked to other pages in the top 10.

Build a big prospect list… and go nuts!

Pro tip: Check out Skyscraper 2.0 to find out how to take this thing to the next level!

3. Moving Man Method 2.0

Nailed “The Moving Man Method”?

Here’s another way to nab quality links from outdated content.

(Moving Man Method 2.0.)

This time… instead of focusing on businesses that have gone pop or rebranded, we’ll leverage outdated information.

Why? Because things change!

Here’s a super simple example.

Let’s say we had a page that ranked the most popular websites in the world.

Well, some time ago YouTube overtook Facebook as the second most visited website on the planet.

And guess what happened? Suddenly there were a TON of pages that contain outdated information:

Over 11,000 of them to be precise!

(And that’s just one query…)

So, we’ve now got a perfect “in”.

We can:

1. Reach out to all the sites with the old info.
2. Let them know that it’s changed.
3. Point them to our own page while we’re there!

Pro Tip: If something has changed recently in your industry, then use Google’s date function to find articles published prior to the change.

4. Double Down on Effective Content Formats

When it comes to creating content that will attract quality links I don’t like to rely on guesswork. And neither should you.

There are a number of proven content formats that people LOVE to link to:

• List Posts
• Quizzes
• “Why” Posts
• “How to” Posts
• Infographics
• Videos

That said, every industry is different. In your space videos might work best. And for others, it’s list posts.

So I recommend trying out a few different formats… and seeing what works best for you.

Then, double down on those formats.

Pro tip: Combine two or more of these formats into one piece. Hint: A “How To” post in list format, or a “Why” post with an infographic or video would do the trick.

5. Podcast Link Building

A while ago I was checking out where one of the sites in my niche got their backlinks from.

And I noticed that a big chunk of their backlinks came from going on podcasts.

So I decided to become a guest on as many podcasts as I could.

In fact, I appeared on over 50 podcasts over the next year and a half.

Not only did these podcasts send some serious traffic my way…

But they resulted in tons of backlinks.

So:

How do you find podcasts to go on?

First, grab a headshot of someone in your niche that goes on a lot of podcasts. Then, put their headshot into Google reverse image search.

And you’re set:

6. Resource Page Link Building

What’s the purpose of a resource page? To link out to other useful pages!

And that’s a link builder’s dream.

All you gotta’ do is:

1. Find em’.
2. Make sure you have something that’s worthy of a link.
3. Reach out.

I’ll be honest:

Finding them is probably the hardest part. So here are 10 advanced Google searches that will help:

1. “{your keyword}” + inurl:resources
2. “{your keyword}” + inurl:links
3. “{your keyword}” + inurl:recommended
4. “{your keyword}” + “top websites”
5. “{your keyword}” + “top sites”
6. “{your keyword}” + “recommended websites”
7. “{your keyword}” + “recommended resources”
8. “{your keyword}” + “further reading”
9. “{your keyword}” + “recommended reading”
10. “{your keyword}” + “useful sites”

Pro tip: Flipping this round, a well curated, super helpful resource page on your own site can be great for picking up quality links. You can even try reaching out to OTHER resource pages to suggest they link to YOUR resource page. Sounds a bit like Inception… but it works!

7. Unlinked Brand Mentions

If someone mentions your brand in an article but doesn’t include a link, that’s a HUGE opportunity.

All you gotta do is reach out…

…and 9 times out of 10 you’ll get a link.

I recommend setting up an alert for your brand name.

That way you’ll get a notification any time your business is mentioned on the web.

Pro tip: Got a branded technique like “The Moving Man Method”? Then set up an alert for that too!

8. Name Your Strategies

Heard of “The Moving Man Method” or “The Skyscraper Technique”?

Well… both those terms were coined by yours truly 🙂

This means whenever someone is writing about them…

…I get another quality backlink!

Can you do the same?

Sure! All you have to do is:

1. Figure out a process or strategy that’s unique to your business.
2. Give it a catchy name.
3. Write about it!

And it’s writing about the process that’s key. Because you’ll only get links if:

1. Your strategy is SUPER useful.
2. You can prove it works.

This is why I always feature real-life case studies when I reveal a new strategy or technique.

9. Two-Step Email Outreach

A softly, softly approach to the outreach can often yield better results than straight asking for a link right off the bat.

Try using feeler emails like the one below to warm up your prospects:

Pro tip: I also use this technique before launching a new post. I’ll reach out to a prospect and tell them what’s coming, then ask permission to send it their way when I publish. Most of the time the answer is a resounding YES! A little courtesy goes a long way in outreach.

Ready To Grab Some High-Quality Backlinks?

All of the above tactics are tried and tested. And I’ve used them to grow Backlinko’s search traffic from ZERO to over 175,000 unique visits per month.

Bonus: they’re also 100% white hat. So no need to worry about getting slammed by a Google update.

The post How to Build AWESOME Backlinks <br>in 2022 (9 Proven Strategies) appeared first on Backlinko.

Just look at Great Jones, a kitchenware company.

Their Dutch oven (called The Dutchess) is beautiful, well-reviewed, and featured in industry-leading sites like Vogue, the New York Times, Bon Appétit, and The Kitchn.

But search “best Dutch ovens” on Google or ask an LLM for recommendations, and the brand rarely appears.

It’s not that Great Jones lacks content or press.

What’s missing is the pattern — a consistent, positive framing that ties the brand to Dutch ovens across its own site and third parties.

Without this, search engines and large language models (LLMs) can’t confidently connect the brand to the topic, so they default to the names with stronger signals.

Many brands have some version of this gap. And AI search has only made it more visible.

The good news: You can build this pattern.

In this guide, I’ll show you how using the Topical Authority Pyramid, a framework I created to turn your brand into the go-to name in your niche.

This framework builds on conversations with Amanda Milligan, Content and Growth Manager at Semrush, and my work in brand positioning across ecommerce, SaaS, and finance.

What Is Topical Authority?

Topical authority is your site’s earned reputation for expertise on a specific subject. It forms when your brand and topic appear together repeatedly across the sources that buyers, search engines, and LLMs trust.

Think about the brands you automatically connect with certain topics.

Like these:

You didn’t consciously decide to make those associations.

They formed because those brands kept showing up with the same message, in the same spaces, around the same topic.

That’s topical authority — and it’s also how search engines and LLMs learn which brands are most strongly associated with a topic.

The Topical Authority Pyramid Framework

Topical authority has traditionally been defined by content volume and breadth of coverage.

Publish comprehensively on a subject, and you’d own it.

That’s no longer enough.

As Amanda explains:

The phrase “topical authority” has been around for a long time, but the thinking around it has evolved significantly. At its core, it’s always been about your brand becoming associated with specific topics. What’s changed is how we try to build that association.

Today, search engines and LLMs look for more than coverage. They look for a clear position on the topic and external evidence that supports it.

To address this, I created the Topical Authority Pyramid:

The Pyramid breaks topical authority into three layers:

• Foundational authority: On-site content and credibility signals that demonstrate experience, expertise, authoritativeness, and trustworthiness (E-E-A-T), and category fit. (Think category pages, about pages, author bios, comparison content, FAQs, customer reviews, case studies, and more.) Still important, but not enough on its own.
• Point of view (POV-led authority): A specific, consistent angle that separates you from every other brand covering the same ground. It gives buyers a reason to choose you and AI systems the confidence to recommend you over competitors.
• Proof-backed authority: Third-party signals (mentions, reviews, citations, and data) that back up your POV across the wider web. It turns your POV from self-declared to independently verified.

Each layer works alongside the others to establish your brand as the expert in your niche and earn more visibility in search engines and LLMs.

Many brands, including Great Jones, have strong foundational authority and scattered proof, but no consistent POV tying it all together.

Here’s how to build all three.

Free resource: Download our free Topical Authority Audit template to audit your topics, score competitor authority, and track your progress. Fill it out as you work through each step below or at your own pace.

Step 1: Audit Your Topic Reputation

Your brand likely already has a topical reputation, whether you’ve shaped it intentionally or not.

Audit it before deciding what to build.

Research Your Current On-Site Associations

The gap between what you publish and what you want to be known for may be wider than you expect.

This is something Amanda has experienced firsthand:

When I did content audits, I’d inventory every piece of content by topic. You might find you have dozens of pieces on something that isn’t even your priority, and only five on the topic you actually want to own. That mismatch is exactly what a topic audit is designed to surface because what you’ve published is what you’re telling Google and buyers your priorities are.

The fastest way to assess this is with Semrush’s Organic Rankings tool.

Enter your domain to automatically see your brand’s strongest topic associations, organized by the topics getting visibility.

When I did this for Great Jones, their strongest topical associations were “recipes” and “celebrity chefs.”

Dutch ovens barely registered.

Yet, the Dutchess is their primary product.

And “Dutch oven” alone gets over 200,000 monthly Google searches.

Great Jones has a big opportunity to increase their topical authority for Dutch ovens and convert some of this search interest into sales.

These are the kind of topical association gaps you want to surface in this step.

Two more places to look:

• Google Search Console: Go to “Performance” > Queries and sort by clicks or impressions. You’ll see the topics that attract users to your site.
• Branded queries on Google and LLMs: Search “[your brand] + your topic” and “what is [your brand] known for” to see how search engines and LLMs describe you

Audit Your Off-Site Presence

Next, review your third-party coverage: mentions, reviews, roundups, and editorial press.

This is where many brands have the biggest gap, and it’s the one AI systems appear to weigh most heavily.

Run these checks:

• Search “[your brand] + [topic]” and look beyond your own site: What’s showing? Industry blogs? Reddit? Editorial coverage? Or nothing?
• Ask an LLM: “What are the best [topic] brands?” and “Where would you recommend buying [topic]?” See whether your brand surfaces and what it’s associated with.
• Check “best of” lists, roundups, and comparison articles for your topic: Are you in them? If so, where do you rank and how are you described? If not, who is?

A quick off-site audit for Great Jones showed me they’ve earned coverage any kitchenware brand would envy: features in major lifestyle publications and partnerships with prominent chefs and influencers.

But when you look specifically at Dutch oven coverage, the off-site gap is obvious.

Most of the top-ranking articles are a few years old (or older):

And the overall sentiment is inconsistent.

For example, in Food & Wine’s Dutch oven roundup, the Dutchess appears under the “Other” section (rather than “Top Picks”) with a caveat about heating issues.

In this Bon Appétit roundup of the best Dutch ovens, Great Jones is categorized under “Dutch ovens we don’t recommend.”

They’re also notably missing from some use-case roundups, like this one from Serious Eats:

In Reddit threads where buyers are actively looking for Dutch oven recommendations, Great Jones rarely comes up.

When it does, many of the threads are from years ago:

Great Jones has real brand equity to build on.

But it’s just not adding up to a solid reputation in Dutch ovens — yet.

Step 2: Choose the Topic You’ll Build Authority Around

You can’t build authority on everything at once.

This step narrows your focus to one topic worth owning based on a few crucial factors:

• What drives revenue
• Where competitors are weak
• Where your brand has room to claim a position

Build and Prioritize Your Topic List

Start by listing the topics you want buyers, search engines, and LLMs to associate with your brand.

Begin with the obvious ones: the products, categories, use cases, and problems you want to be known for.

Then expand with adjacent topics buyers already care about.

For Great Jones, that might include slow cooking, one-pot meals, kitchen gifting, or cookware care.

Look especially for topics where you already have traction, competitors are weak, or your brand should be associated but currently isn’t.

Once you’ve identified 10 to 15 topics, add them to the “Topic Audit & Scoring” tab in your spreadsheet.

Next, narrow the list down.

Not every topic on your list is worth building a reputation around right now.

For each one, ask two questions:

Do you want to own it? Does it drive revenue, support a product you sell, or build a reputation that brings buyers to you?

How urgent is it?

• High: Directly tied to revenue and an opportunity you can act on now
• Medium: Tied to revenue, but the opportunity or timing isn’t right yet
• Low: Worth tracking but not acting on yet, or no direct business connection

You should end up with three to five high-priority topics to investigate next.

Run a Query Audit

Now test each shortlisted topic to see who already owns the space and where there’s room for your brand to carve out a position.

For each topic, run four queries on Google and LLMs:

As you run each query, note:

• Which formats show up most: editorial lists, reviews, Reddit threads, brand pages
• Whether AI systems name specific brands without being asked (unprompted)
• Whether community results show buyers asking for recommendations or comparing options

Record this in the “Query Audit” tab of your spreadsheet.

If a query shows buying intent but the top results barely address it, that’s a topical authority opportunity.

For example, when I search “Dutch ovens” and “best Dutch ovens,” the same brands consistently come up: Le Creuset, Staub, Lodge, and Caraway.

But rarely Great Jones.

And for “Dutch oven for gifting,” ChatGPT didn’t mention Great Jones at all.

Great Jones only appears when buyers already know to look for them.

More importantly, some topics, such as gifting, aesthetics, and non-toxic coating, are not clearly owned by any brand.

That’s where the opportunity is.

Score by Association Strength

After the Query Audit, score your presence on each topic against three competitors on a 0 to 3-point scale.

The score reflects your overall standing across the Topical Authority Pyramid: foundational, POV, and proof combined:

Note: This isn’t a precise measurement. Use your observations, priorities, and market knowledge to guide the score.

Score your brand first, then each competitor.

After your scoring is complete, look for high-priority topics where you scored a 1 or 2 and at least one competitor scored a 0 or 1.

Those are topics where buyer demand is real, you have some footing, and no competitor has locked it down — the conditions for a winnable position.

For Great Jones, “Dutch ovens for gifting” fits the pattern: high priority, room to claim it, and no clear leader.

By the end, you should have one topic to focus on.

• Have more than one? Choose the one closest to revenue or where the gap between your current and desired reputation is smallest.
• Have none? Go niche. Instead of “Dutch ovens,” try “enameled cast iron Dutch ovens.” A narrower topic is easier to own and still builds toward the bigger one.

Step 3: Identify Your Topic POV

You’ve identified one viable topic. Next, decide what reputation to build around it.

Your POV is the specific angle you own inside that space.

It’s what makes your brand distinct to buyers, search engines, and AI systems.

Like these brands — same topic, completely different associations:

Research What’s Already Owned

Before identifying your POV, map what dominant brands in your space are already known for.

These are the POVs to avoid. Going after any of them directly means competing for territory another brand has spent years building.

Start with your notes from the Query Audit. The patterns there tell you a lot about which competitors own what.

To go deeper, use the Semrush AI Visibility Toolkit.

The Brand Performance tool tells you which associations your competitors are winning across AI-generated answers (and how your own brand compares).

For Great Jones, the obvious territories are taken:

• Le Creuset owns heritage
• Staub and All-Clad lean on professional-grade performance
• Lodge owns value

No brand has clearly claimed gifting Dutch ovens, visual appeal, or beginner cooking.

(Semrush shows Great Jones is leading on design, which gives them a head start.)

These gaps are where your POV lives.

Choose Your POV

Before committing to a POV, ask three questions:

• Does it drive revenue or connect to a product or service you sell?
• Can you defend the POV with what you already have — features, data, customer behavior, and/or expertise?
• Is the territory open across search and LLMs?

If a candidate fails any of the three, drop it. It won’t hold up once you start building proof around it.

For Great Jones, “gifting” passes all three questions.

People already buy Dutch ovens as gifts.

Customers already mention its “super attractive,” “modern,” and “beautiful” design in on-site reviews, which aligns perfectly with a gifting POV:

And no competitor has clearly made “gifting” their territory yet.

Write Your POV as One Sentence

Your POV should be easy to grasp and repeat.

Writing it as one sentence is the test. If you can’t, it’s likely not sharp enough yet.

For Great Jones, the POV could be:

• Gifting: Great Jones is the Dutch oven for the milestone moments: weddings, housewarmings, and “I want this to mean something” gifts
• Aesthetics: Great Jones is the Dutch oven you give when you want the gift to stay on the counter, not the cabinet
• Beginner: Great Jones is the Dutch oven that turns beginners into confident home cooks

Each POV targets a different buyer and a different reason to choose Dutch ovens.

Step 4: Map Your POV Proof Architecture

This step is where you plan your proof — the concrete evidence that backs up your POV — across your own site and the wider web.

You’re not building anything yet.

You’re mapping what proof you’ll need at each stage of the buyer journey, so you have a clear blueprint to follow.

Audit Your Proof Across the Buyer Journey

A POV without proof is just a claim.

To build credibility, you need evidence that backs up two things:

You belong in the category

You’re the go-to brand for the POV you’ve claimed

And you need to reinforce this at every stage of the buying journey with a different kind of proof:

To run your audit, go through each belief in the table and identify which proof assets you already have and which are missing.

Use the POV Proof Planner in your template to record your findings:

For Great Jones’s gifting POV, a quick proof audit surfaces:

• Consideration proof exists: The brand has features in the New York Times, Good Housekeeping, and many others, but most aren’t connected to gifting or were published years ago
• Comparison proof is sparse: Some decision-stage proof tied to gifting exists for Great Jones, but it’s not consistent enough to increase AI recommendations

Step 5: Build Your On-Site Foundation

Before search engines and LLMs can associate your brand with your POV, you need to establish it on your site.

This step is about building that foundation: the hub and supporting pages where your topic, POV, and early proof signals all come together.

Create a Hub Page for Your POV

Your hub page is the central authority document for your POV.

It defines the topic, explains why it matters, and routes buyers to supporting pages that go deeper.

Side note: If you’ve built pillar pages and topic clusters before, this will feel familiar. The structure is similar, but the organizing principle is proof and belief, not coverage and keywords.

For Great Jones, that could be a “Dutch oven gifting guide.”

It would link to the Dutch oven product page and explain why Dutch ovens make exceptional gifts.

Supporting pages, such as gift basket ideas, a gifting FAQ, and a report on cookware gifting would also be linked.

If you’ve been publishing for a while, you may already have a page that can serve as the hub: a category page, a subcategory page, or an industry-specific landing page.

Build Supporting Pages

Supporting pages go deeper than the hub.

Each one proves a specific aspect of your POV at a specific stage of the buyer journey.

Go back to the proof assets you mapped in Step 4 — they tell you what you need to prove and at which stage.

Your supporting pages are how you do it.

For Great Jones, the comparison stage is a clear gap.

To convince buyers the Dutchess is a better gift than the alternatives, they need dedicated comparison pages, backed by awards, endorsements from leading industry sites and public figures, and head-to-head data.

Other supporting pages might include:

• Dutch oven gift basket ideas: What to pair it with and how to present it, backed by customer photos and a relevant publication feature
• Gifting FAQ: Sizing, monogramming, return policies, with real customer questions pulled from reviews
• The Gift-Worthy Dutch Oven Report: Proprietary survey data on how customers buy, give, and display the product

Pro tip: Strengthen your hub and cluster pages with on-site trust signals. Include author bios that show real niche experience in the topic, named expert sources or contributors, and an About or editorial page that clearly ties your brand and contributors to the category.

Identify what pages you need, and fill out the rest of the “On-Site Foundation Planner” tab in your template.

Structure Each Page for Readers and Machines

Lead with the most important information first — also known as the inverted pyramid.

It makes your pages easier for readers to scan and for machines to interpret.

Then, make sure each page has:

• Clear section headings: Labeled so readers and machines immediately understand what each section covers
• POV language: Reuse the same phrases and framing tied to your angle throughout
• Schema markup: Structured data that helps search engines and AI systems understand your content and context
• Semantic HTML: Proper use of HTML tags so machines can correctly interpret your page structure

Link Your Pages

Each hub and supporting page proves something on its own.

Link them together, and you create a proof system.

Follow these internal linking best practices:

• Link from the hub to your 5–10 most important supporting pages in the body. Not just in the nav, breadcrumbs, or footer.
• Link every supporting page back to the hub. Keep key pages within 2–3 clicks of each other.
• Use descriptive, relevant anchor text to help people and machines understand what the linked page is about

Step 6: Create an Off-Site Proof System

A strong POV and foundation won’t get you into AI answers if the association exists only on your site.

This is one of the biggest shifts in how topical authority works, as Amanda explains:

Topical authority isn’t just about what’s on your site anymore. You need third-party sources — coverage, mentions, appearances, even reviews — independently reinforcing the same association. If the only place your brand is tied to a topic is your own content, that’s often not enough to build the pattern that AI systems and search engines need to trust you on it.

This step reinforces your POV in the places buyers and AI systems already trust.

Start with One Signature Proof Point

A signature proof point is an original, specific story or finding about your topic.

Something others outside your brand would want to reference, share, or build on.

That could be:

• Proprietary data from your own sales, customer behavior, or research
• A trend you’ve spotted and named before anyone else
• A contrarian observation backed by evidence

For Great Jones and the gifting POV, the insight has to tie Dutch ovens to gifting.

They might pull data from their own sales — say, a 4x spike in Dutch oven purchases in the two weeks before Mother’s Day — and turn it into a “State of Mother’s Day Gift-Giving” report.

That report becomes a press pitch to lifestyle publications, a video on their YouTube channel, and a thread on Reddit’s r/gifts.

One insight, multiple placements, all reinforcing the same association: Great Jones = gifting.

To find yours, start with your proof assets from Step 4.

Look for patterns in your data, reviews, industry trends, or customer behavior.

Distribute Your Proof Point

Once you have a signature insight, decide where and how to distribute it.

There are four main buckets:

• Brand channels: Content you publish directly to audiences you’ve built: email newsletters, marketplaces, review sites, podcasts, social media, SMS or loyalty messaging, local profiles
• Community: Discussions in spaces your buyers already trust, such as Reddit, niche forums and industry groups, social media comments and communities
• Partners: Others who extend your reach into new audiences, including affiliates, influencers, retail partners, and integrations
• Earned: Third-party coverage you pitch but don’t control, such as media mentions, press features, user-generated content, and editorial placements

For each bucket, identify the specific publications, platforms, or communities where your insight is most relevant.

Not sure where to start?

Run a search on Google or an LLM related to your proof point and look at the sites that rank and the sources that get cited.

Those are the places worth showing up in. List them in the “Off-Site Proof Planner” tab of your template.

For Great Jones, some of that infrastructure is already in place.

They already have the social media following, media clout, and collaborations with names like cookbook author Molly Baz.

What they need is a focused distribution of insights around their gifting POV.

That might look like:

• Briefing partner creators on a gifting-specific collaboration, like pitching fresh coverage that ties the Molly Baz collab to gifting
• Pitching their Mother’s Day gifting sales data to lifestyle publications already covering Dutch ovens
• Reframing existing social content around the gifting angle

Related reading: LLM Seeding: A New SEO Strategy to Get Mentioned by LLMs

Step 7: Track Topical Authority Progress

You’ve built the full Topical Authority Pyramid.

Now check whether it’s starting to influence how search engines and LLMs describe your brand.

Use the “Progress Tracker” tab in your spreadsheet to record what you find at 30, 60, and 90-day intervals.

Foundational Layer: Are You Showing Up More?

Coverage tracking tells you whether your topical footprint is growing:

Go back to your Step 2 notes. How many of your four query types surfaced your brand unprompted? Run them again and compare.

Also monitor pages ranking for queries you didn’t directly target, and rising impressions for queries related to your topic.

For Great Jones, the baseline visibility was weak for many non-brand Dutch oven queries.

Showing up in two or three queries at 90 days — especially “Dutch ovens for gifting” — would be a real sign of progress.

Tools that help:

• Semrush’s Organic Rankings tool (the Topics report) for association trends
• Semrush AI Visibility Toolkit: The Visibility Overview tool to see whether your AI Visibility score and mention count are climbing, and Prompt Tracking to re-run your query set on a set cadence
• Google Search Console for impressions and queries by page
• Surfer SEO for coverage gaps

POV Layer: Are You Being Described Correctly?

The POV layer tracks language. Specifically, whether mentions of your brand are increasingly paired with your POV.

Run POV-specific prompts monthly and check the wording.

For Great Jones, that’s searches like “Dutch oven wedding gift” or “best Dutch oven to give as a gift.”

And when the Dutchess shows up in reviews, comparisons, and “best of” listicles, watch for the language around it.

Is it being called “a great house-warming gift,” “splurge-worthy,” or “the kind of gift that gets displayed”?

That’s the POV landing.

Tools that help:

• Brand24 to track web and social mentions
• Semrush’s Perception tool for sentiment trends, and Narrative Drivers for the attributes and phrases AI ties to your brand

Proof Layer: Are Others Confirming Your POV?

The proof layer tracks third-party confirmation.

Are media mentions, third-party pages, and niche communities backing up the POV you want to own?

Start with your proof point.

Are others citing or referencing it? That’s a signal your off-site distribution is working.

Then, go broader.

Run [Your Brand] + [POV] queries on Google and an LLM.

Check whether you’re appearing in more third-party sources associated with your POV.

Are buyers recommending you unprompted in Reddit or niche communities? Are your hub pages attracting links from relevant sites?

When your brand appears, is it being described in relation to your POV?

For Great Jones, that might be a gift guide naming the Dutchess as the go-to Dutch oven for wedding gifts.

Tools that help:

• Google Alerts for basic brand mention tracking, or Meltwater for a more robust option
• Semrush’s Competitor Research tool to surface sites citing competitors but not you, and Narrative Drivers for the Top Cited Domains shaping your topic

Build the Pattern That Wins in AI Search

Great Jones proves that great press and a great product aren’t enough for topical authority.

If search engines and LLMs don’t have clear associations attached to your brand, showing up online will be a struggle — no matter what Vogue thinks of you.

But that’s fixable.

The Topical Authority Pyramid gives you the framework:

• A strong foundation that proves you belong in the category
• A POV that makes you distinct
• Proof that backs it up across the web

Once your first topic takes shape, expand.

Follow the Topical Authority Pyramid for your next topic, claim more territory, and deepen your authority in adjacent spaces.

Do this well, and search engines and LLMs may just start recommending you by default.

Want a repeatable way to monitor your AI visibility over time? Our AI visibility audit guide walks you through it step by step.

The post How to Build Topical Authority in the AI Search Era (7 Steps) appeared first on Backlinko.

Now you can’t afford to keep them siloed.

Google and LLMs both rely on third-party signals — backlinks, brand mentions, expert commentary, and coverage in trusted publications — to decide which brands deserve visibility.

PR and SEO both generate those signals, but most teams still operate independently.

When they do collaborate, it’s usually to treat PR as a link-building opportunity rather than a real partnership.

This leaves authority on the table.

But the real gains happen when these teams operate as one.

In this article, you’ll learn a five-step playbook for turning PR and SEO into an always-on authority engine.

I also spoke with two digital PR experts about how they’re partnering with SEO to build more authority across search, media, and LLMs.

Free resource: Download our PR + SEO Outreach Planner to align pitching, prioritize outlets, and track results. It includes a pitch ownership guide for deciding who pitches what and when.

Step 1: Align PR and SEO Research

An always-on PR and SEO partnership starts with shared intelligence.

Without it, you get predictable gaps:

• Content that ranks but doesn’t earn media mentions or AI citations
• Coverage that builds awareness but doesn’t improve search visibility
• AI citations and media coverage that go to competitors because they published first

Use PR Insights to Identify Emerging Content Opportunities

The biggest authority wins don’t come from PR and SEO staying in their own lanes.

They come from each team sharing insights that shape angles, assets, and placements.

For PR, this could be:

A sudden spike in journalist inquiries or media coverage around a topic

A new phrase or framing gaining traction among industry voices

Recurring themes across newsletters, conferences, or trade publications

Britt Klontz, digital PR consultant and founder of Vada Communications, says the strongest results come when PR and SEO combine their strengths at the ideation stage:

The best collaborations with SEO happen when PR is brought in early, before an asset or campaign is completed. We used to ask, ‘Can PR promote this?’ Now we ask, ‘How do we build something together that will help with search, media, and brand visibility from the start?’

To facilitate this partnership, build a regular channel for PR to flag insights to SEO.

This could be a shared Slack channel, spreadsheet, or standing agenda item.

For example, when I was the editor of the Hootsuite Blog, our PR team notified us that LinkedIn was shutting down its “Elevate” feature and suggested we should write a blog post about it.

No search volume existed yet, but we created the content anyway.

The post started gaining backlinks and driving a surprising amount of demo requests almost immediately.

Months later, the search volume appeared. And our post ranked #1.

Today, it still ranks near the top of the SERPs for terms like “LinkedIn elevate alternatives.”

AI tools like Claude also use the blog post as a top source for relevant prompts:

That’s the power of PR and SEO sharing information and acting on it quickly.

Rankings, backlinks, and AI citations that would have gone to a competitor built lasting authority for Hootsuite instead.

Use SEO Insights to Inform Content Topics

SEO has signals PR can act on too, including which topics are heating up and editorial gaps.

When conducting keyword research for PR, SEO should flag two things:

• Informational gaps: Questions audiences are actively searching for, but no one is answering well yet
• Trending terms in your niche: Journalists are likely already interested, which gives PR a clear opening

That’s why Rola Tfaili, communications manager for North America at Xero, brings SEO into her process from the start:

I want SEO insights — like emerging search trends, keyword gaps, and audience intent — to directly shape our PR narratives and campaign angles from the outset, before content is developed.

Here’s how you can do the same.

Not all keyword tools show you trends over time, so I’ll use Semrush for this step.

Note: If you don’t have a subscription, sign up for a free trial of Semrush One, which includes Semrush Pro and the AI Visibility Toolkit.

Search any term in the Keyword Magic Tool and look at the “SERP Features” column.

Two features in particular signal strong PR potential:

• News and Top Stories: Google surfaces these for time-sensitive or trending queries — sometimes within 24–72 hours of a news event. If your topic triggers these features, journalists are actively covering it, and PR has an immediate opening.
• Discussions and Forums: This signals that audiences are seeking advice or firsthand experience on the topic, which is often a sign of unmet demand and/or increasing interest

Next, use the Keyword Overview tool’s 12-month trend graph to confirm whether a topic is gaining momentum, seasonal, or fading.

A consistently rising trend is your strongest signal — media interest is likely to be building as well.

Pro tip: Don’t overlook existing topics. A trending term you already own is a valuable opportunity. PR can pitch it to journalists as a timely angle, repurpose it into new formats, or use it as a hook for a broader campaign.

For LLMs, you need a tool like Semrush’s AI Visibility Toolkit that shows actual prompt data, not just search queries.

This gives you insight into the exact prompts your competitors are earning AI visibility for, but you aren’t.

Those gaps are worth flagging to PR, especially if competitors are being cited as authorities on topics your brand should own.

Use your shared doc or Slack channel to provide real-time insights, so neither team works from stale data.

Topics that show up in both PR’s emerging trends and SEO’s keyword data are your highest-priority opportunities.

Step 2: Collaborate on AI-Ready Assets

An AI-ready asset is built to be found, cited, and trusted by search engines and AI models (while being valuable to humans).

This is also called answer engine optimization (AEO), which is the process of creating and structuring content for AI systems.

It can include optimizations like:

• Headings that mirror how people search
• Front-loaded key stats, details, and definitions
• Sections that focus on one core idea
• Bullet lists and tables that make key information more extractable

When you combine PR’s distribution power with SEO’s technical expertise, you get assets that earn visibility across search, media, and LLMs.

Original Research and Reports

Original data has long helped brands earn backlinks — now, it helps you build AI visibility too.

A collaborative workflow for this asset would look something like this:

SEO identifies the topic based on search demand and content gaps, and PR validates whether the angle is pitchable and shapes the findings into quotable hooks.

Together, they design the study so it’s structured for citations, with a clear methodology, front-loaded stats, and branded visuals that are easy to share.

SEO content teams might be tempted to create this type of asset on their own, then ask PR to pitch it.

But Britt says if PR is involved earlier, they can help answer questions like:

• Is this a real story?
• Is there a sharper edge here?
• Do we need more reliable data?
• Is there a better hook that fits the time?
• Would it be more interesting if an expert gave their opinion?

That kind of information can make an asset more useful and impactful.

Pro tip: Give your asset a unique, branded name — like ‘The State of X Report’ or ‘The X Index.’ If journalists mention it without linking, people can still search for it and find you.

Don’t limit original data to a blog post.

High-value assets should have their own crawlable landing page — no gates, no PDF-only content.

Use the same URL each year for recurring assets to build authority. Then, link these pages to related content on your site (and vice versa).

This way, search engines and AI see your topical coverage as connected, not random.

Free Tools

Free tools that solve a specific pain point earn AI visibility, backlinks, and return visits long after launch.

This includes calculators, templates, checklists, and interactive assets.

The gap here is usually distribution.

SEO can build and optimize tools, but without PR’s contacts and timing, even the best ones can be limited by organic performance.

A strong hook helps, too.

Britt says an asset is easier to promote when it “blends search insights with something more personal, like proprietary data, a strong point of view, or a story angle that is relevant right now.”

The payoff is an asset that is reported on and shared widely across channels.

NerdWallet’s tariff calculator is a good example of this in action.

It launched as tariffs dominated headlines — and earned media coverage because of it.

Podcasts

A branded podcast can generate tons of coverage, review articles, and inclusion in “best podcasts on X topic” listicles.

Getting your experts on other podcasts is also valuable for building authority and visibility.

Third-party mentions get your brand and subject matter experts into the conversation, both in search engines and LLMs.

PR typically drives guest placements, but SEO can identify which shows already rank or get cited by AI for your target topics, so you’re pitching the ones that build the most authority.

Press Releases

When published on your site and optimized properly, press releases can become standalone, crawlable assets that increase your AI mentions.

In fact, press release citations in LLMs grew 5x between July and December 2025, according to Muck Rack.

To get the most out of press releases, both teams need to contribute.

Rola has seen the benefit of this collaboration firsthand:

For key assets like press releases, we integrate SEO insights early — before content is developed — and include SEO in the review process to ensure we’re maximizing visibility.

PR shapes the story and the hook. SEO makes sure the on-site version is crawlable, optimized, backed by citable data, and linked to related assets.

So the press release doesn’t just generate buzz, it feeds your broader authority.

Explainer Content

Explainers are easy-to-digest resources (usually articles or videos) that simplify complex topics or highlight key info about your brand.

They help journalists and LLMs write accurately and consistently about you — especially if your category is niche or complex.

SEO can use keyword and prompt data to identify the questions your explainers should answer and structure them so AI can parse and cite individual sections.

PR knows which questions journalists and analysts ask most often — and where the current gaps are in how your brand gets described.

The format can vary:

• One-page proof point packet with key stats and third-party validation that PR sends alongside pitches
• YouTube video with citable brand facts or product details
• Dedicated pressroom that organizes assets by category with founder bios and press releases

(Bonus points for all three.)

Step 3: Co-Build Your Third-Party Presence

Brands are 6.5x more likely to appear in AI answers through third-party signals than their own content, according to AirOps.

This means PR and SEO have a real opportunity to work together to build more visibility across search and LLMs.

Rola sees this as an important shift for PR teams:

When we align closely with SEO to ensure our key messages land in credible, third-party outlets, we’re not just generating press; we’re helping position the brand to appear in AI search platforms. That intersection between PR, SEO, and now AEO is where I think we’ll see the most measurable impact moving forward.

Expert Commentary

When your experts are quoted consistently — on your own site, social media, and in trusted publications — Google and LLMs begin to associate them (and your brand) with that topic.

The biggest coordination gap is knowing where to focus.

SEO has the data on which topics have the most search and AI demand — and which publications are already earning citations for them. PR knows which journalists and outlets are most receptive and what angles resonate.

Together, they can pinpoint the exact publications and topics where a placement will improve results for both teams.

Then shape the commentary accordingly.

Concrete, data-backed quotes with a specific stat or firsthand insight are far more citable than generic thought leadership — especially for AI, which favors specificity it can extract and serve directly in an answer.

Getting your experts quoted online is a strong start — but it works best when paired with the other authority-building sources below.

Further reading: 5 Best HARO Alternatives (Expert Review)

Review Sites and Forums

Review sites like G2, Yelp, Google Reviews, and Trustpilot are trusted by AI for the same reason they’re trusted by humans.

They aggregate specific, unbiased information about products from verified users.

And AI frequently cites them for product recommendations:

Reviews across multiple sites also strengthen your brand’s authority signals.

It gives AI detailed evidence of what category you belong in, your core features and pricing, and why you should be trusted.

Forums work similarly — AI pulls from Reddit threads and Quora answers when users ask for honest recommendations or firsthand experience.

Brands that show up authentically and positively in these conversations earn another layer of trust signals.

You can’t control these mentions, but consistently showing up as a helpful, knowledgeable voice in your category’s communities builds the kind of organic mentions AI models trust.

PR and SEO should jointly identify which review sites and forums matter most in your industry.

Keep review profiles current and monitor relevant forum conversations for opportunities to contribute genuinely.

Further reading: How to Build a Brand Subreddit: Full Setup Guide (+ Examples)

Wikipedia

A Wikipedia page gives Google and AI a neutral, third-party source of facts about your brand.

It also helps establish your brand as a recognized entity in Google’s Knowledge Graph.

It’s a common source for Google’s Knowledge Graph, and it’s baked into LLM training data.

But to qualify for a page, you need to meet Wikipedia’s Notability Criteria.

This includes having significant coverage in reliable, independent sources that address your brand directly and in detail.

PR can help you earn this kind of coverage by pitching stories about your company to journalists in reputable publications.

Once you have a page, you won’t be allowed to edit it directly, as Wikipedia’s rules prevent self-promotion.

But SEO can monitor the page for inaccuracies and flag corrections, and PR can handle reputation monitoring to keep the narrative positive.

Pro tip: Use the same brand name, category language, and positioning everywhere: across your website, social profiles, press releases, and review site listings. The more consistent your language, the more confidently AI and Google can categorize and recommend your brand.

Step 4: Unify Your Outreach Strategy

If PR and SEO know what — and to whom — each team is pitching, you avoid mixed messages and misaligned timing.

And your odds of a yes go up.

It doesn’t take much to fix. Just a shared source list, a strategy to split pitching, and a regular check-in to stay aligned.

Pro tip: Download our PR + SEO Outreach Planner to put the tips in this section into action.

Build a Shared Target Source List

SEO has a list of high-authority domains that show up in organic rankings and AI citations. PR has a list of journalists, analysts, creators, and publications that influence their category.

Merging these gives you a single view of every third-party source worth going after.

Build it as a shared spreadsheet with three columns:

• PR Sources
• SEO Sources
• AI Citation Sources

Then prioritize.

Any source that appears on more than one list goes to the top. It has double (or triple) the potential to impact your authority and visibility.

Pro tip: Update your list quarterly as sources can shift fast — especially in LLMs.

Create a shared pitch doc to go with your source list. Use PR’s standard pitch brief, or if one doesn’t exist, create one. Include headline stats, agreed-upon positioning language, and target URLs.

Whoever sends the final pitch customizes it to their contact. But using the shared pitch doc as a starting point ensures your basic story stays consistent.
Split Pitching by Strengths
Many high-priority pitches will need both PR and SEO to weigh in. But not all.

Divide the work of pitching based on what each team does best.

Generally, that means structured, technical placements for SEO and editorial, relationship-based placements for PR.

Your company may want to organize these tasks differently depending on industry or org structure, but here’s what I suggest:

Plan Pitching in Advance

Meet quarterly or monthly — whatever works for your schedules — to decide who is going to pitch what, to which outlets, and when.

This will help prioritize high-impact efforts and reduce accidental duplication of work.

Map outlets to objectives and target KPIs to determine ownership.

Every time you meet, review results from the last period. Prioritize more of what’s working and cut what isn’t.

Further reading: Journalist Outreach: 9 Steps to Earn High-Authority Links

Step 5: Report on PR and SEO Performance Together

PR and SEO usually track different metrics, like mentions and outlet quality vs. rankings and organic traffic.

The fix isn’t merging into a single dashboard.

It’s building a shared lens for evaluating what each asset actually did, no matter which team owns it.

Britt recommends that both teams agree on a shared set of questions to evaluate each asset:

• Did it get any attention?
• Did it get picked up by reliable sources?
• Did it help with search goals?
• Did it contribute to conversions?
• Did it have results that lasted longer than a short-term spike?

As Britt puts it:

The best shared work usually helps with more than one thing at a time, like visibility, authority, discoverability, and brand credibility.

Visibility: Did We Show Up in the Right Places?

Getting in front of your audience more often — and in the places they care about — is one of the main advantages of having PR and SEO collaborate.

Track these metrics to see if it’s working:

• Quality mentions in relevant outlets: Not raw mention count. A placement in a niche newsletter your buyers trust outweighs 10 mentions on unrelated blogs. PR likely already has a media monitoring tool for this.
• Recurring format mentions: Listicles, comparison posts, and “best of” roundups will continue to earn backlinks and AI citations over time. They also show how your brand is positioned relative to competitors. Track these separately in your media monitoring tool or a shared spreadsheet.
• Share of voice in category coverage: Report on the percentage of category coverage that mentions your brand vs. competitors. Free tools like Google Alerts and Mention’s share of voice calculator give you a general sense of how you’re doing. But paid media monitoring tools let you dig into specific platforms, outlet types, and topics.

For AI specifically, track how often your brand appears in AI answers for queries you care about.

You can manually check your top questions and prompts in LLMs to see if your brand is mentioned, but this gets tedious at scale.

The AI Visibility Toolkit is helpful here. It automates tracking so you’re not manually checking every LLM for every query.

You get an overall AI Visibility score for your brand, which measures how often you’re mentioned in AI systems compared to other brands.

The Competitor Research tool shows how your AI visibility stacks up against competitors, which is one of the clearest ways to show leadership whether you’re gaining or losing ground.

It also tracks your Share of Voice across AI platforms, a single metric that reflects the combined impact of your PR and SEO efforts.

Authority: Did We Become More Credible?

This is where you show if your brand is becoming a trusted source online.

Start by tracking new referring domains.

New backlinks matter too, but new domains are more meaningful because they represent more unique sources vouching for your brand.

Reporting on your website authority is also helpful. This is a third-party estimate of the level of trust search engines are likely to assign to your domain, based on your backlink profile and other signals.

Different SEO tools calculate it differently (and call it different things).

So, focus less on the score and more on the direction it moves over time.

Note: Meaningful changes to your Authority Score can take 3-6 months to appear.

The AI Visibility Toolkit tracks your mentions, citations, and cited pages over time, and tells you percentage increases and decreases.

When your authority score and AI mentions are both climbing, you’ll know your PR and SEO work is paying off.

Expert commentary placements, direct requests from journalists, and new journalist relationships are also worth tracking.

Increases in any of those areas are a strong signal that you’re gaining trust.

Google Alerts can catch mentions to help you track expert commentary placements, but a tool like Semrush’s Brand Monitoring gives you a more comprehensive picture.

It lets you track any query (SME names or other keywords) and provides:

• Total mentions
• Estimated reach
• Traffic
• Mentions with backlinks
• Sources (Social media, news, and blogs)

Demand: Did It Help People Take the Next Step?

Did improving visibility and authority have any impact on your business goals and revenue?

PR and SEO sometimes sit at the top of the funnel, so this can be tricky to answer.

Start with these metrics to prove demand:

• Referral traffic
• Assisted conversions
• Branded search lift

Track your referral traffic to show the number of visitors who visit your site directly from media coverage.

Even if numbers are low, they’ll tell you which topics make your audience want to know more about you. Then you can publish more on those in the future.

Tracking assisted conversions shows you conversions where organic search or referral traffic appeared somewhere in the buyer’s journey, but not necessarily as the last click.

PR and SEO content may not convert on the first visit, but it still influences the buyer’s journey.

This metric captures that concept.

Find this in GA4 under Advertising > Key event attribution paths, and switch to “Source/Medium” to see which specific outlets have the most impact.

As AI search has decreased click-through rates, branded search queries have become one of the clearest signals that your PR and SEO efforts are building real awareness.

It’s a metric Britt prioritizes for exactly this reason:

I track branded search lift because it’s a sign that coverage or visibility made someone curious enough to go look up the company by name. That matters to me because not every asset will result in direct clicks.

The metric is also important to Rola:

Branded search lift connects awareness and intent, showing how media exposure actually drives people to seek out your brand.

Google Search Console tells you how often people search for your brand by name and how many of those searches result in a click to your site.

Look for spikes around major coverage dates to directly tie increases to your PR and SEO efforts.

Turn PR and SEO Into an Always-On Authority Engine

The brands earning the most trust right now aren’t doing it with PR or SEO in siloes.

They’re showing up consistently across media, blogs, review sites, search engines, and AI because all of those channels feed the same authority signals.

That takes more than a “quick sync” before campaigns. It takes an always-on partnership.

You don’t need to overhaul everything at once.

Start small:

• Co-create one high-impact asset (and keep AEO best practices in mind)
• Merge your source lists
• Plan 3 pitches using our PR and SEO Joint Outreach Strategy Template

When you’re ready to go deeper on how to optimize your brand’s presence in AI, check out our complete guide to AI optimization.

The post PR and SEO: How to Build More Authority Together (5 Steps) appeared first on Backlinko.

When a buyer reads an AI answer that mentions your competitor, or scrolls through a Reddit thread where your brand doesn’t appear, that’s lost visibility. And it won’t show up anywhere in your traffic data.

Share of voice (SoV) captures what traffic metrics can’t.

It measures your brand’s visibility against competitors across channels where buyers actually research and make decisions.

While SoV spans social, PR, and paid media, search is where most brands should start. It’s the channel where buyers with the strongest purchase intent show up, and it’s the easiest to measure competitively. That’s what this guide focuses on.

I’ll walk you through four steps to measure your share of voice in organic and AI search. Then, I’ll show you how to turn that data into decisions that move the needle where it matters.

What Is Share of Voice?

Share of voice measures your brand’s visibility relative to competitors across multiple marketing channels.

That includes organic and AI search, social media, review sites, communities, and more.

Traditionally, brands used SoV to track their share of ad spend in a market.

Now it’s evolved into something even more valuable. It can measure your brand’s presence across every touchpoint where buyers research and make decisions.

In simple terms: SoV tells you what percentage of the conversation you own in your category, compared to competitors.

This guide focuses on search SoV — both organic and AI — because that’s where buyer discovery is shifting fastest and where the measurement tools have matured enough to give you actionable data.

I find that search SoV also tends to be the foundation: once you understand your visibility in organic and AI results, layering in other channels becomes much simpler.

What Counts as a “Good” Share of Voice?

While there’s no universal benchmark for SoV, establishing one for your brand comes down to:

• Market position: Market leaders have a higher share of voice since they own the conversation. Challengers aim for a mid-range SoV when competing against players with decades of brand equity.
• Competitive context: In a fragmented market with 20+ active competitors, 8% SoV could put you in the top five. But in a three-player market, anything below 30% could mean you’re behind the leader.

Beyond these two factors, look at the broader market shifts within your category.

High SoV in a declining market can be a vanity metric. The real win is growing your share as the category grows.

How SoV Works in Traditional vs AI Search

Both SEO and AI SoV answer the same question: What percentage of category demand does your brand own?

But they measure different search contexts.

SEO SoV calculates your slice of traditional organic search traffic.

You track 100 target keywords. Those keywords generate 50,000 total monthly visits across all ranking sites. You capture 15,000 of those visits.

That’s 30% organic share of voice.

AI SoV measures brand mentions in LLM responses from ChatGPT, Perplexity, Google AI Mode, and similar tools.

For example, you test 100 category-related prompts. Your brand is mentioned in 45 responses and cited in 15. Your competitor shows up in 30 responses with 10 mentions.

An AI visibility tool can calculate your weighted AI SoV based on mentions and citations.

Try now: Curious to know how often your brand shows up in AI responses? Try our free AI visibility checker to find out.

Why Is Share of Voice So Important, Especially Now?

Here are three reasons why share of voice should be your core KPI when visibility is scattered across platforms.

Track Visibility Beyond Traditional Traffic Data

Your organic traffic data reveals only half the story.

And with zero-click searches on the rise, that half is shrinking fast.

When users get their answers directly from AI Overviews and featured snippets, a huge chunk of your visibility is never captured in Google Analytics.

This makes traffic a lagging indicator of visibility.

Share of voice is a better metric because it measures how visible you are in the consideration set, even when users don’t click your site.

Think of it this way:

A user searches for the “best project management software for remote teams.”

They see an AI Overview listing five tools, including yours. The user reads it, takes no action, and later signs up for a product demo on your site.

Traditional traffic data would show this as “direct traffic” since the person went straight to the website. It wouldn’t capture the discovery that occurred in Google.

But SoV reveals that your brand appeared in the consideration set for this high-intent query.

Work Toward One North Star Metric

Your marketing team might be operating in silos.

The SEO team wants more website visits. PR wants more media mentions. The social team wants better engagement.

Each team tracks its own KPIs and optimizes for different outcomes.

But the long-term power of SoV is that it can become the one metric every team rallies around.

When everyone sees how their work contributes to the same visibility percentage, it changes how teams collaborate.

Here’s what this looks like in practice:

• SEO team targets specific keywords to boost traffic and visibility via content
• PR secures features in industry publications through expert quotes
• Social drives brand conversations on Reddit and LinkedIn
• Product wins better reviews on G2 and Capterra

This full picture takes time to build.

Start with the foundation by measuring your SoV in organic and AI search.

Once you have that baseline, you can layer in other channels over time.

Read more: How to Rank Higher (& Get More Visibility) on Google in 2026

How to Measure Share of Voice in 4 Steps

Let’s see how you can strategically calculate share of voice in four steps.

I’ll use a fictional project management software example to show how each step translates into business insights.

Step 1: Define Your Industry Landscape

Start by outlining the specific competitors and keywords you’ll track for SoV.

Without clear boundaries, you’ll either miss critical gaps or drown in too much noise.

To map your competitive terrain, pick topic clusters tied to revenue.

For a project management software, I picked these clusters:

• Category fundamentals (like “project management 101” and “project management for freelancers”)
• Use cases (like “agile project management” and “remote team collaboration”)
• Industry-specific (like “construction project management” and “marketing project management”)

Pro tip: Don’t pick these topics solely based on search volume. Choose clusters where gaining visibility directly impacts your bottom line.

One way to assess a topic’s revenue potential is to map it to funnel stages.

Categorize your clusters into three stages:

• Awareness: Where people are learning and researching, like how to manage projects
• Consideration: Where they’re exploring solutions, like the best project management software
• Decision: Where they’re comparing options and ready to buy, like Software A vs Software B

Your SoV at each stage tells you where you’re winning and losing in the buyer journey.

This allows you to allocate resources for maximum business impact.

Let’s say this project management software segments the SoV by funnel stage.

It reveals that most of the brand’s visibility is concentrated at the top with almost none at the decision stage.

That’s a problem.

They’re educating the market, but invisible when prospects are actually comparing options and reaching for their wallets.

Strategic takeaway: They need to prioritize comparison pages and case studies to shift visibility toward the decision stage.

Now, define who you’re measuring against.

In search, you’re competing for visibility against two key players:

• Direct competitors: Companies selling similar solutions like Asana, ClickUp, Notion, and Trello
• Indirect competitors: Review sites capturing the voice of the customer like G2 and industry publishers ranking for your keywords but not competing for customers like HubSpot and Zoho

Tracking them gives you the complete picture of who controls visibility in your market and where you can break through.

Step 2: Build Your Keyword & Prompt Libraries

Create a library of 200-500 queries that capture how people search in your category.

You need both keywords (what people search) and prompts (what people ask LLMs). Together, they reveal your search visibility spectrum.

Pull SEO Data First

Collect queries where you’re already visible to your audience.

Google Search Console (GSC) is a good starting point for this since it captures actual visibility through impressions.

Impressions show every time your brand appears in results, even when users don’t click.

Go to the “Queries” tab in the “Performance” report.

Click the “Impressions” column header to sort in descending order, and export this list of keywords.

And if you’re running Google Ads, export your PPC keyword list and filter for terms with conversions or high CTR.

You can also repeat this process with tools like Semrush.

Open your Semrush Position Tracking project (or create one for your domain).

Scroll down to the “Top Keywords” section and click the “View all” button.

Adjust the timeline to your preferred range before clicking “Export” to download the full keyword list.

Pro tip: Export all tracked keywords, not just the top money terms. A keyword with 20 monthly searches might seem irrelevant in isolation. But 50 of these collectively represent meaningful category visibility that SoV captures.

Layer in Competitor Intelligence

Besides your own data, track where competitors show up.

This tells you where to compete directly and where to claim ground that they’ve overlooked.

You can use Semrush’s Keyword Gap tool to find these opportunities.

Add your domain along with up to four competitors, then hit “Compare.”

Filter to the “Missing” section to find keywords with proven search demand that competitors have validated.

You need to build visibility for these terms.

For example, this project management tool could target keywords like “Gantt chart” and “project management software” to boost its SoV.

Dig deeper: How to Run a Competitor Traffic Analysis (9 Steps)

Build Your AI Prompt Library

After sourcing keywords, look at how people search for your category in AI tools.

Since AI search queries tend to be more conversational, they often mirror how people talk in community spaces.

Browse Reddit, Facebook groups, and Slack communities to see how your audience phrases their needs and pain points.

For example, this post reveals that agencies want project management tools that aren’t “too corporate or complex for creative teams.”

A question like that can translate directly into an AI prompt: “What’s the most user-friendly project management tool for small creative agencies?”

For decision-stage prompts, review sites G2 and Capterra (or those relevant to your industry) offer a lot of insights.

G2, for instance, lists popular alternatives for every tool.

This is a ready-made list of “[You] vs [Competitor]” and “alternative to [Competitor]” queries your buyers are likely running in AI search.

You can dig deeper with Semrush AI Visibility Toolkit to find prompts where competitors show up in AI answers, but you don’t.

Go to “Prompt Research” and add any of your core topics, like “agile project management.”

Click “Analyze” to get started.

The tool lists real prompts that generate AI responses for your category, such as “best productivity app” and “companies that use agile software development.”

Jot down the prompts relevant to your primary cluster.

Then, repeat for each of your 3-5 clusters.

Document Your Metadata

Finally, organize everything in a master spreadsheet with columns for:

• Keyword/Prompt
• Topic Cluster
• Funnel Stage
• Source (SEO/AI)

Once you’re done measuring SoV, this metadata will become your strategic lens.

Use it to decide which clusters to prioritize, which funnel stages are weak, and where SEO and AI visibility diverge.

Here’s what this looks like for the project management software:

Step 3: Calculate Your SoV

Your SoV equals your estimated traffic divided by the total traffic for all tracked brands, multiplied by 100.

Track both SEO and AI SoV to see the full picture of your brand’s visibility.

Calculate SEO Share of Voice

Start by checking your rankings for all the keywords in your tracking list. Track your competitors’ rankings for the same keyword set.

Each ranking position gets an average share of clicks, like position 1 getting roughly 27%.

This will help in estimating the traffic share per keyword.

Note: These benchmarks for organic search CTR shift over time. It’s also crucial to mention that organic CTRs have been declining as AI-generated answers absorb more clicks before users ever reach the results.

Multiply each keyword’s monthly search volume by the click-through rate for your ranking position to estimate your traffic for that duration.

Then, run the same calculation for each competitor.

Use this data to calculate your SoV.

Add up the estimated traffic across all keywords for each brand. Divide your total by the combined total for all tracked brands and multiply by 100.

This manual approach can be time-intensive, especially when tracking hundreds of keywords across multiple competitors.

Semrush handles this math automatically once you set up tracking correctly.

Go to Semrush Position Tracking and click “Create project.”

Enter your domain, target search engine, device type, and location.

The location setting matters for SoV tracking because search results vary by location.

If you set the location to the United States, but most of your customers are in New York, your SoV might look different than reality.

Pro tip: Start with country-level tracking to establish your baseline. Only segment by region later if local variations impact your business.

Then, click “Continue to Keywords” to manually add or import your keyword list.

Upload the CSV you made in Step 2 to preserve the data by cluster and funnel-stage categorization.

Then, press “Add keywords to campaign.”

Finally, click “Start Tracking” to begin data collection.

Once this setup is complete, Semrush starts collecting daily ranking data for every target keyword.

Check out the results in the “Share of Voice” tab under “Overview” in the Position Tracking dashboard.

You can also add up to four domains to see how you fare against others in the market.

Semrush tracks every brand’s rankings for your keyword set to aggregate the data into SoV percentages.

Important: While SoV is inherently relative and compares your visibility against others, who you choose as competitors shapes how you interpret your SoV.

Calculate AI Share of Voice

Your AI SoV shows how often LLMs cite your brand when answering questions in your category.

There’s no standardized way to manually measure AI SoV yet, but this two-step process gets you close:

• Step 1: Run each prompt from your library through your AI tools of choice, such as ChatGPT, Claude, Google AI Mode, and any other AI tools your audience uses
• Step 2: For each response, document every brand that appears — yours and your tracked competitors. Record whether each brand was mentioned, cited as a source, and whether the sentiment was positive, neutral, or negative.

Once you’ve tested all prompts, count how many times each brand appeared across all responses.

Divide each brand’s total mentions by the total number of prompts tested, and multiply by 100.

Keep in mind: This calculation gives you a directional read instead of a live metric. AI responses vary by session, phrasing, location, and platform. That’s why it’s important to test regularly and track trends over time.

Measuring AI SoV manually for 20 prompts across three platforms is doable. Doing it for hundreds of prompts while tracking how recommendations shift week over week isn’t.

That’s what Semrush’s AI Visibility Toolkit is built for.

Go to the Brand Performance report in Semrush’s AI Visibility Toolkit.

Enter your domain and click “Analyze.”

Pick an AI platform between ChatGPT, Google AI Mode, or Perplexity.

Switch among these tools to identify any significant gaps in platform-specific LLM visibility.

Once the report is generated, you’ll see a pie chart visualizing the distribution of SoV for your competitors.

The tool tests hundreds of prompts related to your category across ChatGPT, Google AI Mode, and Perplexity to measure your AI SoV.

For each prompt, it analyzes AI responses for:

• Brand mentions: How often your brand appears in the answer
• Citations: Whether the AI links to your content as a source
• Context: Whether mentions are positive, neutral, or negative

It aggregates this data across all tested prompts to calculate your percentage of total visibility.

You’ll also find a section comparing each competitor against a set of business drivers specific to your industry.

These drivers are the most frequently mentioned topics for your category.

Use this data to identify clusters where you’re stronger and weaker than your competitors.

Interpreting SEO vs AI Share of Voice

SEO share of voice measures organic traffic while AI share of voice tracks LLM mentions and citations.

These might not always align.

You can have a strong organic share of voice (ranking on top for many keywords) but a weak AI SoV if LLMs don’t find your content credible.

And brands with more credible content can win a bigger slice of AI SoV even without much visibility in organic search.

Here’s a simple matrix to understand your data:

Dig deeper: Learn more about building visibility in AI search with LLM seeding.

Step 4: Establish Your Baseline and Track Trends

The final step is turning your SoV numbers into an ongoing tracking system that informs decisions.

Create a baseline dashboard to capture three levels of detail:

• Overall metrics: Are you gaining or losing ground overall?
• Topic cluster performance: Which topics need more investment?
• Funnel stage breakdown: Where in the buyer journey are you least visible?

Here’s what this could look like for the project management software:

Once your baseline is locked in, set your tracking cadence strategically.

A monthly frequency allows you to spot trends without the need for reacting to noise.

With quarterly deep dives, you can:

• Analyze cluster-specific performance in detail
• Correlate SoV changes with past campaigns
• Adjust resource allocation based on what’s working

This rhythm prevents you from chasing short-term variations and missing critical shifts that impact your category.

Pro tip: Set up notifications in Semrush Position Tracking to get real-time alerts. You’re notified when SoV drops more than a certain threshold in any core cluster.

How to Improve Share of Voice

Not every fluctuation in your SoV requires action.

Here’s how to strategically diagnose gaps in your SoV and prioritize the right tactics to fix them.

1. Close Visibility Gaps

Clusters with <10% SoV mean you’re almost invisible.

This is especially damaging in decision-stage queries.

If you have less than 10% visibility when buyers search “best project management software,” you’re not in their consideration set.

At the same time, look for opportunities where competitors dominate, but you can compete.

For example, if your project management tool serves creative agencies but you have zero visibility for “project management for creative teams,” that’s your opening.

Potential Solutions

Diagnose the cause:

• Search your weak clusters and compare what ranks against what you have
• Check if you lack topic coverage, content depth, or basic optimization
• Look at which competitors dominate and what formats they use

Build topical authority for major business themes.

Create one pillar page with multiple supporting articles.

Build backlinks to your pillar content to establish visibility across every query in that cluster.

For example, if we learn that the project management software needs to gain decision-stage visibility, we could prioritize comparison content.

Build pages targeting “[Your Brand] vs [Competitor]” and category buyer’s guides.

2. Solve Efficiency Problems

Compare your SoV to actual traffic.

A cluster like “what is project management” might give you a high SoV.

But if only 1% of that traffic converts, you’re likely burning money on the wrong audience.

You’re winning visibility in areas that don’t drive business outcomes. And competitors are capturing high-intent buyers.

Potential Solutions

Diagnose the cause:

• Check if you’re ranking for awareness content when you need decision-stage visibility
• Look at your traffic-to-conversion ratio by cluster
• Identify if your content attracts the wrong audience (students vs. buyers)

Reallocate resources to high-intent clusters.

Instead of producing more awareness content, shift the budget to bottom-of-funnel content.

This includes comparison pages, case studies, and ROI calculators that target buyers ready to evaluate solutions.

Update existing comparison pages with current data and competitive intelligence.

3. Address Competitive Threats

Keep tabs on competitors gaining ground in your strong clusters.

If a competitor gains over 5% SoV in your strong clusters, it’s an early sign that they’re targeting your territory.

That gap can widen unless you respond to maintain your market share.

Diagnose the cause:

• Analyze what new content or tactics they launched
• Check if they’re winning on review sites, community platforms, or organic search
• Identify if they’re capturing a format you’re missing (video, podcasts, tools)

The fix depends on where your competitors are winning.

If competitors actively feature on review sites, optimize your profiles. Run campaigns to source reviews from happy customers.

If they’re visible on community platforms, proactively engage in communities like Reddit and Slack.

Prioritize Based on Effort vs. Impact

Not all gaps matter equally.

Focus on opportunities that will actually move your revenue pipeline.

Start with high-impact, low-effort wins. Then invest in high-effort moves that compound over time.

Making SoV Your 2026 North Star

Share of voice captures how often you show up across the fragmented platforms where buyers make decisions.

Get started by measuring your current SoV across SEO and AI search with the steps in this guide.

Pick the gap that costs you the most revenue, and strategize the best ways to close it.

Next step: Build your AI optimization gameplan to capture visibility in the fastest-growing search channel.

The post How to Calculate Share of Voice (+ Why it Matters for SEO) appeared first on Backlinko.