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Prompt Tracking: How to Find (and Fix) Your AI Visibility Gaps

August 13, 2026/0 Comments/in Web Design News/by Dubado Solutions

Your brand could be ranking #1 on Google, but still be invisible to AI.

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Or worse, showing up inaccurately, with outdated or incorrect information that’ll hurt your sales.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

Visibility Overview – Gong – AI Visibility

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.

Best B2B software – BOFU, MOFU, and TOFU

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.

Competitor Research – Gong – Weak topics

This tells Gong two things:

Their audience isn’t aware of their lead generation use case
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:

Prompts worth tracking	Prompts not worth tracking
“How does Hootsuite compare to [competitor]?” (Comparison)	“What is social media management?” (Pure definition — won’t convert)
“Which social media management platforms integrate with Salesforce?” (Evaluation)	“Is Hootsuite a good company?” (Vanity — brand mention is baked in, nothing actionable)

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.

Keyword Magic Tool – Sales enablement software

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.

Visibility Overview – Gong – Your performing topics

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:

Project management	Task management	Workflow automation	Team reporting
Best project management software for marketing teams (Evaluation)	Best task tracking tools for cross-functional teams (Evaluation)	Best workflow automation software for ops teams (Evaluation)	Best project reporting tools for enterprise teams (Evaluation)
Asana vs. Monday.com for project management (Comparison)	Does Asana actually improve team productivity? (Reputation)	Asana vs. ClickUp for workflow automation (Comparison)	Is Asana’s reporting good enough for large teams? (Reputation)
Project management software with Slack integration (Evaluation)	Best task management software for small teams (Gap)	Asana vs. Notion for managing marketing workflows (Comparison)	Asana vs. Smartsheet for project visibility (Comparison)

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.

Prompt Tracking Template – Citation rate

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.

Visibility Overview – Gong – Topics & Sources

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.”

Visibility Overview – Gong – Prompt 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).

Visibility Overview – Gong – Cited sources

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.

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Audience-First SEO: How to Rank by Putting Readers First

August 12, 2026/0 Comments/in Web Design/by Dubado Solutions

Key Takeaways

Audience-first SEO builds your keyword and content strategy around a specific, high-value audience instead of a broad topic or category.
The tactics stay familiar (keyword research, content gap analysis, TAM (total addressable market) analysis), but the organizing principle behind all three changes.
Programs using this approach see growth concentrated among the audiences that actually drive revenue, not just a bump in overall traffic.
Applying it starts with defining your priority audience before you ever look at keyword volume.
Integrated agencies have a built-in advantage here, since paid audience research already exists internally and can inform SEO strategy directly.
Audience-first SEO also sets up your Digital PR targeting, since the same research tells you where that audience already spends its time.

Paid media has always started with the audience. Every campaign begins with who you’re trying to reach before it gets to what you’re going to say. Paid teams buy audiences, not channels.

SEO has worked the opposite way for years. Programs get organized around topics and keyword clusters first, then hope the right people show up once the content ranks. Audience-first SEO closes that gap by building your organic program the same way paid media already builds its targeting.

That gap matters more now than it used to. Search is fragmented across traditional results, AI-generated answers, and social, and attention is split thin across all of it. The brands winning right now are the ones cutting through to the specific audiences that move their business.

This isn’t a new set of tactics so much as a shift in starting point, one the strongest SEO programs are already using, often without a name attached to it. This piece names that instinct and lays out how to apply it on purpose.

What Audience-First SEO Actually Means

Traditional SEO is organized around topics and categories. A single topic can serve audiences with very different needs, intent levels, and business value, and that ambiguity is where a lot of traffic volume hides the fact that the wrong people are showing up.

Audience-first SEO flips that starting point. You define the specific audience you want to reach, usually the audience most valuable to the business rather than the largest one, and you run keyword research, content gap analysis, and TAM analysis through that lens.

The tactics themselves are the same ones you already run. What changes is the organizing principle behind them. Instead of asking which topics carry the most search volume, you ask which audiences matter most to the business, then find the keywords and prompts tied to them.

Paid media has operated this way for years. Every campaign starts with defining who you’re trying to reach before any decision gets made about creative or messaging. Audience-first SEO borrows that discipline and applies it to organic, with the same rigor paid teams bring to targeting, segmentation, and qualification.

The distinction between audience and topic shows up quickly once you look for it. A topic like wealth management could serve a first-generation saver building an emergency fund, a business owner preparing for an exit, or an ultra-affluent family managing a multi-generational estate. Content written to serve all of them tends to serve none of them particularly well, because their questions and buying triggers don’t overlap much.

This is where user personas for SEO earn their keep. Once you know which audience segment you’re writing for, keyword targets get sharper and content gets easier to write, because you’re solving one person’s problem instead of hedging for several readers at once.

The same logic applies to how you think about audience size. A larger audience isn’t automatically the right one to chase. Weighing audience size vs. revenue potential is often what separates a program that grows traffic from one that grows the business, and audience-first SEO forces that comparison earlier in the process instead of leaving it as an afterthought once the content is already live.

What It Looks Like When It’s Working

Plenty of programs succeeding with SEO right now are already running a version of audience-first SEO, even if nobody on the team has put a name to it. They’ve made deliberate calls about which audiences to prioritize, run their keyword and content work through that lens, and the results compound in ways topic-first strategies rarely do.

In one case, NP Digital was working with a financial services brand competing in a crowded search category with significant total addressable volume. Rather than chasing the broadest possible traffic, the SEO team built TAM analysis and content gap work around specific high-value audience segments, prioritizing the individuals and families most valuable to the business over the segment with the largest raw search volume. That decision started with the kind of audience segmentation work most brands skip, ranking each segment by demand, competitive difficulty, and long-term business value before a single piece of content got written.

Within six months, organic leads from the client’s highest-value segment, ultra-affluent individuals and families, had already surpassed the client’s full prior fiscal year total, hitting nearly 114% of the previous year’s volume before the year was even half over. Aflluent leads followed close behind at close to 90% of the prior year’s total, and the estimated pipeline impact tied to that lead volume grew from $1.46 billion for the full prior year to $2.13 billion year-to-date.

Alt text: Chart showing organic lead growth by audience segment (EW, HNW, UHNW) from January 2025 through May 2026

Table comparing FY 2025 totals to YTD 2026 actuals by segment.

Keyword rankings still played a role here, but only not focusing on casting the widest net possible. Total organic lead volume across the whole program sat at roughly 71% of the prior year’s pace over the same six-month window, well behind the pace of the priority segments. The gap between those two numbers is the point: audience-first SEO deliberately trades some volume in lower-value segments for outsized gains in the ones that matter most to the business.

The insight from that program: when you build SEO strategy around a specific audience instead of a broad category, you make sharper calls about which keywords to pursue and which content gaps to close first. Raw traffic volume becomes a far less useful signal. Audience quality becomes the measure that matters.

How to Apply Audience-First SEO in Practice

Getting audience-first SEO right does not require a new toolset. It requires changing the order of operations, and that shift plays out in three practical moves.

Start with audience definition, not keyword volume. Before opening a keyword tool, decide which audience the business needs most. This usually means ranking segments by value to the business rather than by size, since the segment with the most search volume is rarely the one with the most revenue potential. A brand serving both mass-market and high-net-worth customers, for example, might find that general wealth management searches carry the most volume, while a much smaller audience of high-net-worth individuals and families carries far more business value per lead.

Run TAM analysis by audience segment. Rather than sizing the total addressable market around a single blended topic, break it out by persona. Score each segment on search demand, ranking difficulty, and business value, then map where those three overlap. That mapping tends to surface a small number of segments where the opportunity is real: enough search volume to matter, low enough difficulty to be attainable, and high enough value to justify the investment. It’s also important to do deeper research here on these audiences you find most important. This can range from using specialized tools to looking at information sources like Reddit or customer interviews.

Build content gap analysis around audience needs, not topic coverage. Once you know your priority segments, look at where your content already ranks for those specific audiences and where it doesn’t, rather than running a generic gap analysis against a topic list. A gap analysis run this way often turns up a surprising amount of untapped opportunity sitting several pages deep in the rankings, simply because it was never built with a specific audience in mind.

Put together, these three moves turn audience-first SEO from a concept into a repeatable process your team can run quarter over quarter, and each one gets easier once the audience definition from the first step is locked in.

Example segment distribution in Semrush.

Source

Where Integrated Agencies Have an Advantage

Paid media teams have always treated audience research as a starting point, not an afterthought. Tools like Reddit Ads and GWI (Global Web Index) give paid strategists a detailed picture of who an audience is, what they care about, where they consume content, and how they talk about their own needs. Google Ads’ Audience Insights and Insights Finder tools add another layer of that same intelligence, surfacing which segments actually convert and what related interests and trends they share. That research is directly applicable to SEO strategy, and brands running SEO and paid in separate silos are rarely putting it to use that way.

In an integrated agency, that audience intelligence flows into SEO from day one. Keyword strategy gets informed by what paid research already knows about the audience, and content positioning reflects how that audience actually talks about their problems rather than just how they type their searches.

Tools like Ubersuggest and AnswerThePublic add a further layer, surfacing the specific questions and language patterns an audience uses at different points in their journey. Combined with paid audience research, they help build a content strategy that is both search-optimized and genuinely useful to the people you’re trying to reach.

The audience opportunity matrix is one of the clearest outputs of this integrated approach. Mapping audience segments by search demand, keyword difficulty, and business value shows exactly where the strongest opportunities sit, and just as importantly, where they don’t.

Scatter plot mapping audience segments by monthly search volume and competition, with a table scoring each persona on demand, competition, and AUM potential.

That same audience-first lens applies to sizing the opportunity. A TAM analysis broken out by segment, rather than blended across an entire category, shows which audiences carry the most untapped search volume relative to their ranking difficulty and business value, giving the team a clear place to focus first.

Table showing total addressable market by audience segment, including monthly search volume, average keyword difficulty, average CPC, and estimated number of TAM topics per segment.

Audience-First SEO and Digital PR: Publishing Where Your Audience Already Goes

Traditional link building is organized around domain authority and topical relevance. Audience-first Digital PR is organized around presence: where does this specific audience actually go for information, and are you showing up there? Those questions are related, but they lead to different outreach lists.

Social metrics across net worth segments.

When audience research is done well, you already have that answer. Paid audience research tools, combined with SEO audience data, surface the publications, communities, and platforms where your target audience spends its time. That becomes the actual targeting brief for Digital PR outreach, rather than a generic list of high-authority sites in your industry vertical.

AI insight tools add one more layer here, showing which content is already getting cited for prompts relevant to your audience, so you know where AI-driven visibility is concentrated too.

This connection also strengthens the SEO program directly. Earned coverage on the sites your audience trusts builds authority signals that are harder to manufacture and more durable than links acquired through broad outreach. It also creates touchpoints with your audience outside of search, which builds brand recognition that shapes how they engage once they do find you organically. A reader who saw your brand mentioned on a site they already trust arrives at your organic content with a head start on credibility that a first-time visitor doesn’t have.

The integrated play here: audience research informs SEO content strategy and Digital PR targeting at the same time. One brief drives two channel strategies, both built around the same specific people, which also means the two teams stop duplicating research that already exists somewhere else in the building.

The Complement to Search Everywhere Optimization

Search Everywhere Optimization is the right ambition for brands with the resources to pursue visibility across every surface their audience uses: traditional search, AI-generated results, social, video, and beyond. Audience-first SEO answers the question that has to come first: which of those surfaces matter most for the specific audience you’re trying to reach, and what do they need to see from you there?

For brands that can’t optimize everywhere at once, audience-first SEO becomes the prioritization framework. Instead of spreading effort across broad topic coverage, you concentrate on the overlap between audience need, search opportunity, and business value. That’s a more defensible use of SEO budget and a much clearer brief for the team running the program.

The two approaches work together rather than against each other. Audience-first SEO sharpens the who and the where. Search Everywhere Optimization expands the how. A brand with clarity on its priority audiences is better positioned to pursue visibility across surfaces, because it already knows what those audiences need and where they’re looking for it. It’s also worth noting that Google Search Console now surfaces how some of your social content performs on Google, giving audience-first teams one more data point for connecting the dots across surfaces.

Source

For a marketing leader deciding where to invest next quarter, that ordering matters. Trying to run Search Everywhere Optimization without a clear audience definition underneath it usually means spreading budget across surfaces evenly instead of weighting it toward the ones your priority audience actually uses, which is a slower and more expensive way to get to the same result.

FAQs

How do I identify my target audience for SEO?

Rank your existing customer segments by business value, not by search volume, then check which of those segments has real search demand behind it. From there, build out SEO audience personas for the segments that clear both bars.

How does SEO engage an audience?

SEO engages an audience when the keywords, content, and site experience all reflect what a specific group of people needs, rather than serving a broad topic to whoever happens to land on the page.

How do I target an audience in SEO?

Run your keyword research, content gap analysis, and TAM analysis through an audience lens instead of a topic lens, and let that definition shape which keywords and content gaps you prioritize.

Conclusion

The best SEO programs are already doing some version of audience-first SEO. The question is whether your team is doing it on purpose or backing into it by accident.

Naming the approach matters because it makes the process repeatable. Define your priority audience, run your TAM and content gap analysis through that lens, and let audience quality, not raw traffic, tell you whether the program is working. Start with finding your target audience if that first step still feels undefined, and build out from there.

That’s the kind of program NP Digital builds and runs for clients every day, connecting audience research from paid media into SEO strategy so organic traffic starts working harder for the people who actually matter to your business.

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12 things Reddit needs to make its ad platform more competitive

August 11, 2026/0 Comments/in Search Engine Land, Web Design News/by Dubado Solutions

Channels outside of Google and Meta have struggled to get recent headlines in the paid advertising world. But my agency’s performance marketing team has seen one under-the-radar channel — Reddit — introduce a ton of new features and ad types in 2026, making it more viable for our clients.

Between new ad types and AI-powered functions, powerful integrations for shopping, video ad enhancements from late in 2025, and Reddit’s AEO and SEO clout making marketers more aware of the need to engage on the platform, we’ve got more clients active on, or curious about, Reddit than I’ve ever seen.

That said, Reddit’s ad platform — though much further along than it was a couple of years ago — still needs more features and improvements to existing ones to draw a bigger share of advertising budgets.

My Reddit targeting and audience wishlist

A huge part of Reddit’s influence comes from the extremely candid and opinionated content its users provide — and users are enabled to be exactly that, in large part, because accounts use usernames rather than real names.

Redditors can be as anonymous as they want, and I don’t wish to change that. Instead, I’d like Reddit to offer the following.

1. Expand reach without sacrificing privacy

Better identity targeting for anonymous or logged-out users in a privacy-safe way would expand our targetable reach, which is a big deal given Reddit’s niche status compared to Google and Meta.

See exactly how your competitors win.

Uncover the keywords, ads, landing pages, and strategies driving your competitors’ paid search success—and find your next opportunity to outperform them.

Analyze your competitors

2. Bring B2B intent to Reddit

B2B and firmographic targeting that includes:

Job title, function, and seniority.
Industry and company size.
Named-company and account-list targeting.
Tech usage and/or professional-interest segments.
Decision-maker and buying-committee audiences.

Reddit offers communities, interests, keywords, customer lists, and lookalikes. Adding privacy-safe firmographic data would make the platform more competitive with LinkedIn while preserving Reddit’s differentiated behavioral signals.

3. Make purchase intent easier to target

Reddit should turn its strongest advantage — people actively researching and discussing decisions — into understandable, scalable “in-market” and journey-stage audiences, including:

Recently researched a category.
Asked a question about a product or problem.
Engaged with comparison or recommendation threads.
Evaluated alternatives.
Repeated recent engagement.

4. Make existing audience signals more reliable

As for what we can do on Reddit with the reach we have, I’d like to request stronger retargeting depth, lookalike audiences, CRM integrations, and cross-subreddit behavioral signals. Reddit introduced all those targeting options, but they’re still patchy and unreliable, further eroding scale and performance.

5. Give advertisers more control over who they reach

Reddit advertisers need greater confidence that their strategies are hitting the right people. Adding exclusions would help ensure we can eliminate some irrelevant eyeballs, so I’d like to ask for:

Negative keyword and community exclusions.
Current-customer and existing-lead suppression.
Clear control over AND versus OR targeting logic.

6. Make audience planning more predictable

Last in the audience and targeting category, advertisers need better audience planning and forecasting. Before spending budget, they need to see:

Realistic audience sizes (Reddit currently has ranges that can seem wildly unrealistic).
Demographic and device composition.
Top associated communities and topics.
Estimated CPM, conversion volume, and audience saturation based on budget.

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See terms.

My Reddit measurement and attribution wishlist

With the releases of Brand Lift, Conversion Lift, and CAPI, Reddit measurement took a huge step forward in 2023.

Today, Reddit’s role in the user research and consideration phase is increasingly important as AI search minimizes clicks and pushes performance marketers to focus further up the funnel.

That means Reddit’s value is increasingly measured through analyses like MMM and MTA rather than through a persistent reliance on last-click attribution.

All of that is to say that it’s easier to measure Reddit ads’ impact than it was a few years ago. Yet, indicative of a platform that’s still more of a challenger than a powerhouse, it’s falling short on some basics.

There’s one specific (and persistent) gap that should be table stakes for a serious ad platform: more third-party integrations for dynamic UTM tracking. Beyond that, I’d love to see Reddit introduce the following.

7. Prove incremental value without leaving the platform

Reddit is generally considered a test channel, so self-serve incrementality testing — which larger competitors offer — would help demonstrate the incremental value it drives. Specifically, I’d like to see Reddit provide:

Conversion-lift studies.
Randomized audience holdouts.
Geo experiments.
Self-serve brand-lift studies.
Incremental reach and frequency measurement.

In aggregate, these tests would help Reddit advertisers defend upper- and mid-funnel investment when last-click reporting underrepresents its influence.

8. Connect ad delivery to revenue outcomes

Reddit has Pixel, CAPI, and omnichannel attribution capabilities. The larger opportunity is to make it easier to pull in offline data from CRMs and other sources, so advertisers can lean into down-funnel and revenue-based optimization.

Native HubSpot, Salesforce, and other CRM integrations would be particularly valuable. Advertisers need to tell Reddit which leads became valuable customers, then allow its delivery system to find more people with similar signals.

My Reddit ad formats and creatives wishlist

More than on most platforms, it’s critical to make sure your ads appear as native as possible to their context. Redditors turn up their noses at anything inauthentic.

In 2024, Reddit made some updates to Conversation ads that gave advertisers a useful option in a native setting, but there are many more native formats they could introduce. I’ll list some of my recommendations below.

9. Give advertisers more ways to fit into the conversation

Polls, product carousels, and Q&A ad units designed to fit within the Reddit environment would all be good formats for advertisers to test.

10. Bring short-form video up to speed

Another area of opportunity for Reddit is more competitive short-form video. Yes, they do have short-form video, but introducing vertical formats and optimizing for autoplay would make that format a lot more viable for advertisers (this is kind of in the “table stakes” category).

11. Put ads where high-intent Reddit research happens

Reddit Answers was integrated into the broader Reddit search experience in May 2026. Reddit Answers ads in high-intent searches and recommendation questions, with clear sponsorship labeling and strict relevance requirements, would give advertisers another way to reach users close to the purchase decision.

12. Let advertisers learn from past campaigns

The last big item on my creative list is an ad library that expands to show historical ads, much like Meta’s, where you can see both paused and active ads. That kind of archival reference would be super helpful to have on the back end.

Every click they win is a customer you lose.

See where competitors are investing, which keywords drive their results, and how to capture more of the market.

See who’s stealing your traffic

Reddit could earn more of the ad budget

If it’s not obvious, Reddit has taken some significant strides forward over the last few years, to the point where it can be surprising when it hasn’t checked some of the more basic boxes.

These requests shouldn’t be considered pipe dreams, either. The above list was compiled from situations where my team and I have butted up against limits when running real Reddit campaigns.

Given the way AI search engines have eaten into clicks and made awareness more of a paid media play, and given Google’s heavy-handed move away from control and toward mass automation, we’re very willing to divert budget to Reddit if we can make a solid business case for it.

Reddit’s unique community and research signals would be powerful if the platform figured out how to turn them into targetable audiences using ad formats that enable real conversations throughout the buying journey.

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SEO Tips and Strategies for Franchises: A Guide for 2026

August 10, 2026/0 Comments/in Web Design/by Dubado Solutions

Key Takeaways

Franchise SEO is the practice of optimizing your online presence so each franchise location ranks higher in search engine results and AI Overviews.
SEO for franchises requires balancing brand consistency across locations with the need for each branch to stand out independently in its local market.
Core tactics include targeting local keywords, creating unique location pages, setting up a Google Business Profile for every branch, and maintaining accurate name, address, phone number (NAP) citations.
AI Overviews now influence a majority of local searches, and thin or duplicate location pages tend to get filtered out. That means each page needs unique content and visible experience, expertise, authoritativeness, and trustworthiness (E-E-A-T) signals.
SEO is a long-term play. Pair it with a solid technical audit and a franchise pay-per-click (PPC) strategy to cover ground that organic search alone can’t quickly reach.

Operating a franchise is a fantastic way to start a business.

Not only are people already aware of your brand, but you get the support and backing of a well-established organization and a pre-existing customer base ready to buy.

However, consistent effort is essential for long-term success.

Franchise SEO is essential for ranking in search engine results and AI Overviews, increasing your reach to new customers. About 60 percent of searches result in zero clicks due to the growing appearance of AI Overviews. Franchisees need to understand both traditional and modern SEO tactics to truly expand their audience.

In this article, I’ll explain SEO for franchise businesses, how it differs from standard SEO, and up-to-date strategies to help your franchise stand out.

What Is Franchise SEO?

The Subway franchisee’s hours of operation and contact information for the location at 19 Moosehead Trail in Newport, ME.

Franchise search engine optimization (SEO) is when you optimize your online presence to make your franchise business stand out in search engines like Google, Bing, and Yahoo, as well as in AI search tools like ChatGPT, Google’s AI Overviews, and Perplexity.

Key franchise SEO tips include:

Optimizing your website for local keywords
Creating website content to appeal to customers and localizing the content when relevant
Getting backlinks from relevant local websites
Encouraging customers to submit reviews of your business
Ensuring your website loads quickly and is mobile responsive (52.3 percent of global website traffic comes from mobile devices)

With franchises, there’s a lot of competition. You’re not only up against other brands but potentially competing branches in the same franchise.

Given that almost three-quarters of people use Google to find local business information, the higher you can rank in the search engine results, the better.

Whether you run one franchise or 20, implementing effective SEO for your franchise website means more organic traffic. That, in turn, leads to more store visits, sales, and profits.

Franchise SEO vs. Regular SEO: What’s the Difference?

Standard SEO focuses on keywords and content for a single website or a company as a whole.

Local SEO for franchises is a specialized form of SEO that focuses on optimizing each franchise location. Local SEO is typically a large part of this strategy. That includes making sure that each site contains the correct information, such as address and contact details, and is formatted correctly.

SEO for franchise websites can be tricky, as you need to optimize each location independently.

If you manage multiple franchise locations, you also need to consider your website’s structure and how all your location pages work together. After all, you don’t want to promote one location at the expense of another.

With franchise SEO, people tend to search for more niche, location-specific keywords. You need to consider their search intent to optimize your website properly.

Challenges With Franchise SEO

While effective franchise SEO is rewarding, it presents unique challenges.

Here’s what to watch for:

The risk of duplicate content. Franchise locations often use similar content across their websites, which can lead to duplicate content issues in the search results. It’s essential to keep duplicate content to a minimum.
Building local content. With SEO for your franchise, you need to balance standard SEO with local SEO. You have to make each location stand out for its own area while keeping every site within brand guidelines.
Brand inconsistency. Franchises need to have a cohesive look and feel. While it’s important for your stores to rank as high as possible, they also need to share a consistent brand identity.
AI Overview visibility. With AI Overviews appearing for 57 percent of local searches. To be cited in these results, each location needs unique, credible content rather than boilerplate copied across sites.

Use These SEO Strategies for Your Franchise

Now that we understand the differences between standard and franchise SEO, let’s look deeper into some strategies to help your franchise succeed.

1. Identify the Most Important Keywords Related to Your Business

The first step is to identify and research the keywords most relevant to your franchise.

Consider:

Your target audience. What keywords are they most likely to use?
Your location. You want to target local keywords and terms.
Your competitors. What keywords do they rank for?
Search intent. Are customers looking for information, or are they ready to buy?

Plenty of tools can help you find and research the right keywords for your franchise.

Ubersuggest, for instance, shows you what’s already working for others in your market, so you can borrow those ideas and refine them.

In the example below, the term “best mattresses near me” has an SEO difficulty of 55. This tells you that ranking highly is doable, but landing the top spot will take some work.

An AI Keyword Overview for “best mattresses near me,” showing an SEO Difficulty of 55 and a monthly Keyword Search Volume of 1,000.

However, “best mattress stores near me” has an SEO difficulty of 75, meaning there’s much more competition and you’ll have a harder time clinching the top spot.

Alt txt: An Ubersuggest AI Keyword Overview report for “best mattress stores near me,” showing an SEO Difficulty of 75 and a monthly Keyword Search Volume of 1,900.

Another valuable free tool for franchise SEO is Google Keyword Planner.

While it’s designed for use with Google Ads, it can suggest a wealth of relevant keywords based on a seed phrase or your website URL.

Google Keyword Planner results for “mattress stores.”

2. Localize Your Keywords

Localizing your keywords makes sure you target the right customers in the right areas.

If you have multiple locations, it is especially important to localize your keywords to reach customers in each area.

Let’s say you run a car maintenance franchise in Broward County, Florida. Strong localized keywords might include:

“Car repairs in Fort Lauderdale”
“Car servicing in Pembroke Pines”
“Car mechanic in Hollywood”

Hyperlocal SEO takes it a step further, targeting specific geographic areas, like neighborhoods or streets, to maximize visibility. For example: “Car mechanic on Ocean Drive.”

3. Localize Your Website

Jiffy Lube’s business listing for a franchise location on Riverside St. in Portland, Maine.

Localizing your website is a great way to optimize for local SEO and promote your individual franchise locations.

Create dedicated pages for each franchise location with a clear address, phone number, and other relevant information. You’ll also need to include unique content on each location page, as pages with thin content don’t compete in AI Overviews or Local Packs.

Creating a proper local page for each location helps you rank for local keywords and increases your NAP (name, address, phone number) citations, which I’ll discuss later.

It also helps to include a map of the area with each franchise’s location marked. This makes your website more search-engine-friendly and helps customers find the nearest location.

Franchises often use multiple domains. The main corporate domain serves as the central hub for the franchise brand, providing high-level information, while individual franchise locations use separate domains to target local audiences more effectively. In this case, linking all the domains together will help search engines understand that they are related.

4. Optimize Your Individual Businesses on Google Business Profile and Other Directories

One of the best ways to enhance your franchise’s search engine presence is to set up Google Business Profiles (GBPs) for each location.

A GBP provides additional context about your franchise locations, including your address, phone number, hours, and products or services you provide.

Google Places results for mattress stores in New York City.

Having a Google Business Profile also increases the chance of your franchise appearing in the Local Pack map at the top of the search results.

Additionally, regularly publishing posts like offers, events, and updates, and actively managing the Q&A section, signals to Google that the profile is active and maintained. That can improve AI Overview and Local Pack eligibility.

Try to complete as many fields as possible and keep everything current, so searchers always get the most accurate information about your business.

Beyond Google, signing up for other directories can widen your franchise’s visibility, build additional NAP citations, and generate backlinks to your website. Just be sure to choose directories that are relevant and authoritative. Low-quality, spammy ones can hurt your online presence.

Sites like Yelp, Foursquare, and Yellow Pages (YP) are good starting points. I’d also suggest checking with your local chamber of commerce, which can often point you to directories worth listing on.

5. Make Sure Your Brand Is Consistent

McDonald’s is one of the largest franchised businesses in the world. It has a massive marketing “bible” that helps enforce brand consistency, telling franchisees everything from what colors to use to which words to avoid.

Online McDonald’s Ad displaying their uniform creative standards for franchisees.

Source: https://www.itsnicethat.com/articles/turner-duckworth-redesign-mcdonalds-branding-visual-identity-graphic-design-250719

As a result, McDonald’s has remarkable brand uniformity, and customers can expect the same experience wherever they are in the world.

You don’t need a guide as extensive as McDonald’s, but you do need a cohesive look and brand voice. This helps customers trust you, and it helps search engines and AI systems recognize you as a legitimate business.

That means keeping your brand messaging, logo, visuals, and fonts consistent across all platforms, including your website, Google Business Profile, and social media accounts.

The easiest way to manage this is with a style guide and regular audits to keep all your digital marketing assets aligned.

6. Audit Your Technical SEO

Your franchise’s content can’t rank if search engines can’t properly access and understand your site. That’s where technical SEO comes in.

Here’s where to focus:

Mobile-friendliness: Google indexes mobile-first, so your franchise site needs to look and function well on smaller screens.
Page speed: Slow-loading pages frustrate users and can hurt rankings. Use PageSpeed Insights to help pinpoint the culprits, whether that’s oversized images or a slow server response.
Crawlability: Make sure search engines can easily navigate your site by maintaining a clean sitemap, fixing broken links, and reviewing your robots.txt file.

Once you’ve reviewed those areas, run a site crawl using a tool like Screaming Frog or Semrush to uncover hidden issues with duplicate content or missing meta tags.

For larger franchise operations managing hundreds of locations, our guide to enterprise SEO digs deeper into scaling these technical fixes.

7. Target and Remove Duplicate Content

When you have a website with multiple location pages that are very similar, you risk confusing the search engines.

Infographic showing how pieces of duplicate content can confuse search engine and AI crawlers.

Source: https://moz.com/learn/seo/duplicate-content

If a search engine sees several pages with duplicate content, it has to decide which one to rank. It uses several factors to work this out, but there is a chance it gets the answer wrong.

Fortunately, you can see which pages are being indexed and which aren’t by using Google Search Console’s “Crawled – currently not indexed” filter. From there, you can take steps to make sure search engines aren’t showing the wrong location page to the wrong person.

Contrary to popular belief, duplicate content won’t automatically tank your search engine rankings, though it might if you’re using it deceptively. Either way, it’s best to minimize duplicate content across your site where you can.

Let’s say you operate a chain of restaurants and have the same menu at each. Rather than having an identical menu on each location page, use a stand-alone menu page and link to it instead.

You can also steer crawlbots toward what you want them to see and guide them away from pages you don’t. Implementing a “rel=canonical” tag makes sure you can consolidate rankings to the intended URL.

8. Have a Local Link-Building Strategy

Link building is the practice of getting other websites to link back to your site.

When you get links from relevant, high-quality sites, it shows search engines that your website is trustworthy and reliable, leading to a boost in search results.

Link building is one of the trickiest aspects of franchise SEO because the results are beyond your control. There’s no guarantee that other websites will link to you. Plus, you need backlinks for all your locations to optimize your search engine presence. However, get your strategy right, and it’s worth the effort.

Here are some ways you can get links for your franchises:

Befriend local journalists, and they’ll give you a heads-up when they need a quote for a story.
Partner with related local businesses. For example, if you run a coffee shop, join forces with a bakery.
Hold special events, sponsor local sports teams, or run a competition to get links in the local press.
Use tools like Ubersuggest to identify the backlinks your competitors have. You can then approach the same websites to see if they’ll link to your franchise as well.

9. Ensure NAP Consistency

Kumon Math and Reading Center’s San Francisco page displaying a “Schedule Today” CTA for a child’s free assessment.

A NAP (or NAP citation) is a mention of your franchise’s name, address, and phone number on a website.

This can be your own website, a directory, a social media profile, or another company’s site.

NAP citations are significant to local SEO success. They show the search engines that your business is active and legitimate.

It’s important to make sure your franchise name, address, and phone number are accurate and consistent across all platforms to maximize visibility. Accurate citations across the internet increase your authority. Similarly, accurate information helps potential customers find you more easily.

10. Optimize E-E-A-T on Local Pages

Infographic explaining the four components of Google’s E-E-A-T ranking signals: Expertise, Experience, Authoritativeness, and Trustworthiness.

E-E-A-T stands for “experience, expertise, authoritativeness, and trustworthiness.”

Google wants to prioritize the most credible and reliable websites in the search engine results. It uses the E-E-A-T framework in its Search Quality Rater Guidelines to determine which content to promote.

E-E-A-T is especially important on your money or your life (YMYL) content. These are websites with subject matter that could affect someone’s future happiness, health, financial stability, or safety.

To optimize E-E-A-T on your franchise’s local pages, include a variety of content, such as customer reviews, product descriptions, contact information, FAQs, and informational articles.

Doing this will help build trust and credibility with search engines and customers. It can also help with AI visibility since Google’s AI Overviews strongly favor pages with visible E-E-A-T signals.

Another good way to enhance your franchise SEO is to showcase your credentials. For example, if you run a daycare franchise, telling customers about the qualifications and certifications of your employees can help build your credibility.

11. Develop a Great Content Strategy

When you operate a franchise, good content marketing is essential.

It encourages customers to stay on your website and convert while attracting backlinks and helping you rank.

The great thing about content marketing is how many forms it takes. Whatever you sell, wherever your franchise operates, and whatever your budget, you can create content that prospective customers want to engage with.

Screenshot of a blog article covering winter cleaning tip content showcasing how content should provide value first and convert customers second.

The blog above is from the Molly Maid website. It focuses on cleaning tips readers can use, so even if you end up not using their services, the content still has value.

These content types work especially well for franchise SEO, as you can focus on both local and national topics and trends:

Blog posts
Podcasts
Video content
Infographics
Social media posts

To get started with content marketing, get clear on your target market and their pain points. Then address those pain points with helpful, well-structured content. Each piece should follow an intuitive format of headings, subheadings, and short paragraphs that make the reading experience easy and informative.

From there, work in your keywords naturally, and you’ll have SEO-optimized content that answers your audience’s questions and encourages them to use your product or services.

12. Encourage Local and Online Content Reviews

More than 9 in 10 (93 percent) of customers say they read customer reviews before purchasing a product. The more positive reviews you can generate, the more likely prospective customers are to buy from you.

Image related to SEO Tips and Strategies for Franchises: A Guide for 2026

An in-depth customer review about a dine-in brunch restaurant covering their parking, dietary restrictions, and wheelchair accessibility.

Having lots of reviews builds trust and entices customers to use your products or services, all while supporting local SEO. Reviews posted on platforms like Google Business Profile can include keywords customers naturally use, which helps improve your relevance in local search results.

While these keywords may not directly boost your website’s rankings, they can enhance visibility on the review platform itself, making it easier for potential customers to find your business. Additionally, positive reviews serve as powerful social proof, showing future customers that others trust and value your business, which can drive more conversions.

The easiest way to get reviews is just to ask. Send an email to customers after they use your services and ask them to leave a review, whether on your Google Business Profile, your Facebook page, or a review platform like Tripadvisor.

Be sure to respond to all reviews, whether they’re positive or negative.

According to BrightLocal, 80 percent of consumers say they’re likely to use a business that takes the time to respond to all its reviews.

13. Consider Franchise PPC to Complement Your SEO

SEO is a long game. It builds durable, compounding visibility, but it can take months for a new franchise location to start pulling meaningful organic traffic. That’s where paid advertising comes in.

Using franchise pay-per-click (PPC) tactics can put your franchise at the top of search results right away, which is especially useful when opening a new branch or trying to stay visible during high-competition seasons.

A few things to keep in mind:

Geographic targeting matters as much as it does for SEO. Structure your campaigns by location so individual branches aren’t bidding against each other and driving up costs.
Protect your branded terms. Searches like “[Franchise Name] near me” signal high intent, and competitors can bid on your brand name even when your organic rankings are solid. Running paid ads on those keywords keeps that traffic where it belongs.

Franchise SEO Tools

Running franchise SEO without the right tools gets tough fast, especially as you add locations to your portfolio. These will help keep your campaigns effective, whether you manage one location or 100:

Ubersuggest: This is my go-to for keyword research, competitor backlink analysis, and surfacing the local search terms your franchise should be ranking for. It’s especially handy when you need to compare how individual locations stack up against nearby competitors.
Google Business Profile Manager: If you’re managing more than a handful of GBP listings, the bulk location management features save serious time. You can update hours, services, and descriptions across multiple branches in one go.
Screaming Frog or Ahrefs Site Audit: Both crawl your site at scale and flag duplicate content, canonical tag issues, and thin location pages. This is critical when you have dozens (or hundreds) of near-identical templated pages.
BrightLocal or Whitespark: These are built specifically for local SEO. Use them to audit NAP citations and track rankings location by location.
Google Search Console: It’s free, and it’s still one of the most powerful tools out there. Monitor indexation, Core Web Vitals, and per-location performance straight from the source.

FAQs

What is franchise SEO?

SEO for franchises is the practice of optimizing your website (or websites) so you rank as high as possible in the search engine results for all locations you operate in.

How do start building an SEO program for a franchise?

Focus on three things: a strong corporate site, optimized local landing pages for each location, and a fully built-out Google Business Profile for every branch. Consistent NAP citations and local reviews do the heavy lifting from there.

Should franchises have separate URLs for local SEO?

Yes. Each location should live on its own URL, typically as a subfolder (yoursite.com/chicago). This lets you target city-specific keywords, build local backlinks, and rank in the right geographic SERPs without competing against your other branches.

How do you jumpstart local SEO for new franchise locations?

Claim the GBP listings, publish the location pages, and pursue local citations and reviews immediately. Prioritize getting your first 10 to 15 reviews within the opening month, since fresh listings with active engagement tend to climb the Local Pack faster.

How do local events and sponsorships boost franchise SEO?

They earn local backlinks and brand mentions from community sites. Sponsoring a youth sports team or charity 5K race often gets your franchise listed on organizer pages, news outlets, and event recaps, which are exactly the kinds of locally relevant signals Google rewards.

Conclusion

Franchise SEO is essential for driving web traffic, building trust, and building customer loyalty.

Plus, the best part is that it works whether you sell sandwiches, smoothies, or software solutions.

Remember that when it comes to SEO for franchises, you’ve got to be consistent.

Make sure your information appears the same across all platforms and that each of your location pages uses the same branding and tone of voice. This also means optimizing your content and online presence for AI Overviews, as they’re quickly becoming the new frontier for local visibility.

Get these moves right, and prospective customers are sure to fall in love with your franchise.

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SEO Guide for SaaS Companies

August 7, 2026/0 Comments/in Web Design/by Dubado Solutions

Key Takeaways

SaaS SEO requires a strategy built for long sales cycles and global competition.
Map your content to every stage of the buyer journey, from awareness-stage blog posts to decision-stage case studies and comparison pages.
AI search has reshaped how buyers research software, with 51 percent of B2B software buyers now starting with an AI chatbot more often than Google. That means optimizing as much for AI citations as search rankings.
Build authority through technical SEO, high-quality content, digital PR, and a strong presence on third-party review sites like G2 and Capterra.

There are few better traffic sources for software-as-a-service (SaaS) companies than organic search.

Recent data shows that B2B SaaS companies see a 702 percent return on investment (ROI) from their SEO efforts. That’s a huge number, and it makes a ton of sense.

With the right SaaS SEO campaign, you can acquire users for free and at scale. Best of all, many of those users arrive intending to make a purchase.

So, how do you get your website to dominate the search engine results pages (SERPs)? And how do you keep those visitors on your site and convert them to customers?

SEO for SaaS companies has to account for the unique features of the industry. SaaS brands have a very different target market and customer journey than, say, a local business or a law firm. Your SaaS SEO strategy needs to reflect this.

In this SaaS SEO guide, I’ll show you how to build a strategy that checks all the right boxes. We’ll cover the benefits of generating organic traffic for SaaS businesses and walk through actionable steps you can use to improve your SEO positioning today.

What Is SaaS SEO?

SaaS SEO is search engine optimization that helps software-as-a-service brands rank higher in Google. It covers the activities that drive search engine traffic, including:

Keyword research
Content creation
On-page SEO
Link building

The difference is how you approach each one.

Google’s ranking factors are the same across industries, but SaaS brings its own opportunities and challenges.

The SaaS Industry and What Makes It Unique for SEO

The SaaS industry has its own quirks, and you’ll want to keep them in mind when building your SEO strategy.

For one, competition is fierce. Plenty of businesses offer similar services, and some are working with much larger marketing budgets. Comparison sites like Capterra and G2 pile on, too. Their domain authority is strong enough that they regularly outrank individual SaaS brands for product-related queries.

Oh, and your competition is worldwide, not local, which means global SEO considerations come into play from the start.

AI search has reshaped how SaaS buyers research and discover tools. ChatGPT, Perplexity, and Google’s AI Overviews now answer many top-of-funnel questions directly in the results.

That means fewer informational clicks reach your site. According to GrowthSRC, Google’s average click-through rate (CTR) for the No. 1 ranking position dropped 32 percent year-over-year, falling from 28 percent in 2024 to 19 percent in 2025 after the AI Overviews rollout.

For SaaS marketers, the goal is now to rank in traditional search results and be cited in the AI answers that show up in front of your buyers.

The SaaS Buyer Journey

The SaaS customer journey often involves weeks or months of research and decision-making.

That means your focus should be on long-term SEO strategies, such as content marketing and technical optimization. A “quick fix” approach won’t be as effective.

You’ll also need content for every stage of the journey. It’s not enough to create top-of-the-funnel content to attract people and hope they convert. You need product-focused content to show readers why they should choose your tool over a competitor’s.

You probably won’t get a conversion the first time someone visits your site, as the image below from Salespanel shows. Your SEO plan needs to build sustained authority in your space over time. That’s how you stay visible in search results and keep attracting potential customers to your site.

The Salespanel graphic maps the full lifecycle (awareness, consideration, acquisition, service, and loyalty). For SEO planning, though, marketers will more likely work from a simpler model focused on where content does the heavy lifting.

HubSpot’s three-stage framework is a good starting point:

Awareness: Educational blog posts and guides that answer the problem your tool solves.
Consideration: Comparison pages, alternative roundups, and integration content that helps buyers shortlist you.
Decision: Case studies, ROI calculators, and product-led landing pages that close the gap between interest and signup.

Source: https://blog.hubspot.com/marketing/content-for-every-funnel-stage

It’s not just new customers you have to think about, though.

Because SaaS brands use a subscription-based business model, you need to be constantly thinking about how to retain customers. Your B2B SaaS SEO strategy will need to reflect this by creating content that simultaneously attracts new users, educates existing customers, and showcases your authority.

Benefits of SEO for SaaS Businesses

Done well, SEO supports SaaS marketing efforts. It puts you in front of potential customers who are actively seeking what you sell.

The global SaaS market reached $315.7 billion in 2025, is projected to hit $375.6 billion in 2026, and could reach nearly $1.5 trillion by 2034. Capturing even a sliver of that growth means investing in SEO.

If you’re not sold yet, here are more benefits of SEO for SaaS brands:

Increased brand visibility and credibility. The more your content appears in the search, the more reputable your brand will become. This can be a deciding factor when potential customers are choosing between you and a competitor.
Scalable traffic. There is a huge compounding factor with SEO. The more content you create and the more links you build, the more your month-on-month traffic will grow.
Lower-cost acquisition. Putting more effort into your SEO reduces your dependence on paid marketing. As is the case in an industry with high ad costs, anything to alleviate some of that spend will be helpful for SaaS companies.
Increased product awareness. The more your product shows up in search engines, the easier it will be for your sales team to talk about your product because customers will have probably seen it before.
Helps to convert prospects from other channels. The SEO content you create is multipurpose and can be used by sales teams to convert prospects from other marketing channels, such as social media and pay-per-click (PPC) ads.
Improve your user experience. Many SEO tasks also improve user experience, such as optimizing for speed, navigation, and readability. This helps ensure that potential customers stay on your website longer and are more likely to convert.
Stronger brand health. Organic search data can flag early signs of shifting brand trust or product satisfaction, giving SaaS teams a real-time read on how the market perceives them and a chance to course-correct before issues show up in churn or pipeline.

Regular SEO work also helps you hold on to the rankings you’ve earned. Search engines constantly update their algorithms, so refreshing content and earning new links will keep you ahead of the game.

More and more buyers are searching online for products, too. More than two-thirds (67 percent) of B2B buyers now prefer a rep-free buying experience, and 45 percent say they used AI during a recent purchase. That means you need to appear in search engines and AI Overviews if you want your product on your audience’s shortlist.

SEO also plays well with the B2B industry’s long sales cycles. A single paid ad isn’t going to be enough to keep your prospects on the hook. You need a regular stream of content that showcases your authority and keeps your prospects in your funnel if you want to succeed. Only SEO can achieve that.

Best Practices for Improving Your SaaS SEO Strategy

SEO for SaaS companies takes more than publishing a few blogs and hoping for the best. It succeeds when keyword research, on-page optimization, technical SEO, and off-page authority all work together.

Here’s how to approach each one.

Best Practices for SaaS Keyword Research

Before optimizing your website for SEO, it’s important to do keyword research to identify the terms and phrases potential customers use when searching for your SaaS tool.

Start by creating a list of relevant keywords related to your business and the products or services that you offer. This can include words and phrases related to your software’s features and general topics in your industry.

You’ll also want to choose keywords that map to each phase of the buyer journey. That’s even more important now that AI search favors content that closely matches user intent.

Think beyond the keyword itself. Ask what the searcher is trying to accomplish, then create content that answers that need. The better your content matches intent, the more likely it is to rank in search results and appear in AI-generated answers.

Once you have a shortlist of keywords, use a tool like Ubersuggest to compare their search volume and competition. That will help you prioritize the opportunities with the greatest potential.

For example, searching for “customer data management platform” shows you how often people search for the term and which related keywords are worth exploring next.

Ubersuggest Keyword Summary for “customer data management platform.

Don’t worry if your initial keyword list is short. SaaS companies often operate in highly specialized, competitive markets where obvious keyword opportunities are limited.

That doesn’t mean the opportunity isn’t there.

First, don’t get hung up on search volume. A keyword that brings in even a dozen visits per month can result in a sale that delivers a return on your investment.

Second, focus on your product’s features and the problems they solve for customers. These kinds of queries may be hyper-specific, but they also tend to have strong purchase intent. You can also create vs. pages that compare your product with your competitors.

Again, these bottom-of-the-funnel keywords are great at driving high-intent traffic.

An example of a comparison article that would be a great bottom-of-funnel piece to help your customers during the Decision phase of their buyer’s journey.

Source: https://www.rock.so/blog/asana-vs-monday

Third, look at what your competitors are ranking for. Use a tool like Ubersuggest to mine your competitors’ websites and find relevant keywords you can rank for, too.

The more you understand your competitors’ content strategies, the easier it will be to identify gaps you can fill with better, more useful content.

Strong keyword research lays the foundation for every other part of your SaaS SEO strategy.

Best Practices for On-Page SaaS SEO

On-page SEO involves optimizing the pages on your website so they’re easy for both search engines and people to understand.

To improve on-page SEO, start with the fundamentals. Write descriptive page titles and meta descriptions, organize your content with clear headings, optimize your images with descriptive alt text, and add internal links that guide readers to related resources. These elements help search engines understand your content while making it easier for visitors to navigate your site.

The more relevant information you provide on a single page, the better your chances of ranking in the SERPs.

Great on-page SEO, however, starts with the quality of your content. If your page doesn’t answer a searcher’s question better than what’s already ranking, no amount of optimization will make up the difference.

So, what separates great content from average content?

First, it fully addresses the reader’s problem. It goes beyond the basics and answers the follow-up questions they’re likely to have instead of forcing them back to the search results.

Second, it provides an exceptional user experience. It’s well-structured and easy to read, broken into sections with headings, lists, images, and other elements to help users scan and digest information quickly.

This blog post from ClickUp is a good example of clear structure and strong formatting.

An example blog from ClickUp showing on-page SEO best practices like header structure, formatting, and readability.

Best Practices for Technical SaaS SEO

Technical SEO involves making changes to your website’s back end that are not visible to users but can still have a major impact on search engine visibility.

To optimize your technical SEO, start by optimizing site speed so your pages load quickly. Next, create an XML sitemap and submit it to search engines so they can easily crawl and index your pages.

Infographic explaining how Google’s web crawler uses your XML Sitemap to index your website’s pages.

Also, make sure to set up structured data, such as schema markup, to better understand the content on your page and help improve Google rankings. This helps search engines determine what each page is about, which in turn helps them return more relevant results for user queries.

It’s also important that your website is mobile-friendly and works properly on all devices. This will improve the user experience and enhance your chances of ranking in SERPs.

Best Practices for Off-Page SaaS SEO

Off-page SEO builds your website’s authority beyond your own domain. The biggest ranking signal is still high-quality backlinks from trusted, relevant websites that show search engines your content is worth recommending.

Below is an example of Twilio backlinking to SpotHero’s website.

A Twilio blog article showcasing an example of a backlink to their customer, SpotHero.

Source: https://www.twilio.com/en-us/blog/insights/data/customer-data-platform-roi

How do you find SaaS link-building opportunities?

One of the easiest ways to find link-building opportunities is to analyze your competitors’ backlink profiles. Tools like Ubersuggest can show you which websites already link to competing SaaS companies, giving you a shortlist of publications and blogs worth targeting.

Here’s an example using Twilio.com:

Note: If you click the orange “one link per domain” button, it will remove repeat domains and give you a much more manageable list.

You don’t have to rely on outreach alone, though. Original research, industry surveys, reports, free tools, and useful resources naturally attract links because people want to reference them. Building relationships with industry publications and influencers can amplify that effect even further.

The goal is to earn links from websites your audience already trusts. Those links strengthen your authority and drive qualified referral traffic at the same time.

Creating Your SaaS Strategy: Step By Step

Now that we’ve covered the core pillars of SaaS SEO, it’s time to put them into action. Use the framework below to build a content-based SEO strategy that attracts qualified traffic and supports long-term growth.

Graphic displaying the steps of a content strategy.

This process breaks down into eight steps:

1. Set Goals and KPIs

Start by defining measurable goals for your SaaS SEO strategy. SaaS companies typically focus on attracting prospective buyers, driving traffic to free demos and converting them into paid users, and educating and retaining current users.

Next, choose the key performance indicators (KPIs) you’ll use to measure success. Track metrics like organic search visibility, keyword rankings, website traffic, and lead generation rate. That way, you’ll know what’s working and where to adjust your strategy as you go.

2. Identify Your Target Audience

Next, determine your target audience. Are they engineers? Marketing operations leaders? Business owners? Knowing who you are targeting helps you create content tailored to their needs.

3. Identify Their Pain Points

Once you know your target audience, focus on their needs and the kind of content they want. Identify topics that are relevant to them and create content that offers value, solves their problems, and answers their questions.

4. Analyze Best-Fitting Keywords

Now it’s time to put your keyword research into action. Use the terms you’ve identified to build content that matches search intent and supports each stage of the buyer journey. Then optimize your titles, headings, body copy, and URLs so search engines can clearly understand what each page is about.

In the example below, Gartner targets the keyword “customer data management platform” consistently across the title, meta description, and URL, reinforcing the page’s relevance for that search.

Google search results for “customer data management platform,” showing how Gartner’s use of that keyword in their title and meta description helped land them Position 1 in the SERPs.

5. Set Campaign Goals and Tracking Abilities

Now that you’re ready to start creating content, you’ll need to revisit goal-setting on the campaign level. Set measurable goals for each campaign to track performance. You should also establish a tracking system (Use my SEO templates if you’re not sure where to start) to measure the success of each piece of content you produce and make changes accordingly.

6. Produce Content

Create high-quality content that matches search intent and gives readers a reason to choose your page over the competition. Use clear headings, visuals, examples, and other formatting elements to make complex topics easier to scan and understand.

7. Distribute Content

Publishing is only the beginning. Promote your content through your website, email newsletters, social media, and other marketing channels to maximize its reach. Then monitor its performance and refine your approach based on what’s driving traffic and conversions.

8. Monitor Results and Optimize Based on Findings

Your job isn’t over once your content goes live. Regularly optimizing your content based on analytics data can significantly improve your organic search visibility and get closer to achieving your SaaS SEO goals.

Once a year is a good baseline timeframe for content review and refreshing, but ultimately, you should review your traffic and make adjustments based on what’s being read and what’s not.

Successful SaaS SEO Strategies

Looking for inspiration? Here are a few SaaS brands that have built strong organic visibility and the SEO strategies that helped them get there.

Adobe XD

To grow awareness of Adobe XD, its interface design and prototyping software, Adobe created a content-focused community targeting design professionals.

Source: https://www.adobe.com/subscription/xdideasnewsletter.html

With the help of my agency, Adobe created an intent-based content strategy, backed by in-depth keyword, competitive, and content gap research. We also incorporated technical best practices, optimizing page speed, schema markup, and internal linking.

The results? A 648 percent increase in page one rankings and over 25,000 downloads in the first six months, with just under half of all traffic coming from search engines.

Canva

If you want an example of how to improve your SaaS SEO through backlinks, look no further than Canva.

The design platform has created hundreds of backlink magnets through its template pages. Covering everything from letterheads and invoices to coupons and invitations, these pages give users everything they need to create a great-looking design. And this means that websites provide a lot of value to their readers by linking to them.

Screenshot of Canva’s library of poster template

Source: https://www.canva.com/posters/templates/

As a result, Canva has acquired backlinks from highly authoritative domains such as The Next Web, Yahoo, and Thrillist.

But it doesn’t just wait for the links to roll in. Canva engages in personalized outreach to win those backlinks from target websites.

The result?

They have over 25 million backlinks from 280,000 domains and rank for over 5 million keywords, according to Ahrefs.

Smartlook

Product analytics and insights tool Smartlook used a product-focused keyword research strategy to break into the U.S. market and take on established goliaths like Hotjar.

They achieved this via several strategies.

The first was to improve existing landing pages that targeted competitor-style keywords like “Hotjar alternative.” While these pages were well-designed, they lacked sufficient depth of content to rank well on Google. Smartlook added much more information to these pages to better meet searcher intent and created new pages that comprehensively covered each topic.

Cisco has since acquired Smartlook and continues to operate as part of its portfolio, but the SEO strategy remains just as relevant today. Building comprehensive comparison pages around high-intent keywords is still an effective way for SaaS companies to capture buyers evaluating their options.

Verint

A clear example of what a strong SaaS SEO strategy can achieve is our work with Verint, a customer experience software company serving more than 9,800 brands across 175 countries.

As Verint prepared for a major website migration, including multiple blog and acquired business unit migrations, the challenge was preserving existing rankings while growing non-branded organic traffic in a highly competitive market.

We partnered with Verint’s product and marketing teams to build an SEO strategy around the migration. That included technical fixes for Core Web Vitals, mapping redirects, and content audits using our 6Rs framework to determine what content should be reformatted, repurposed, refreshed, retired, redirected, or simply remain as is.

The broader strategy also incorporated localization for global markets and a digital PR initiative to strengthen domain authority.

Source: https://www.verint.com/blog/

Within 30 days of launch, Verint achieved a:

210 percent increase in non-branded organic search clicks year over year
33 percent increase in keywords ranking in positions one through 10
32 percent increase in total organic search clicks year-over-year

The results show what’s possible with a coordinated SaaS SEO program.

SaaS and AI Search

AI search has become a fixture in the SaaS buyer journey. Prospects who used to start with a Google search are now asking ChatGPT to compare tools, prompting Perplexity for vendor shortlists or scanning Google’s AI Overviews before clicking anywhere.

According to G2’s 2026 AI Search Insight Report, 51 percent of B2B software buyers now start their software research with an AI chatbot more often than with Google, and 71 percent rely on AI chatbots somewhere in the research process.

For SaaS marketers, this changes what visibility means. Ranking on page one still matters, but getting cited inside an AI answer matters, too.

If a buyer asks ChatGPT for the best project management tool for remote teams and your product isn’t mentioned, you’ve lost the discovery moment entirely. The same G2 research found that 69 percent of buyers reported AI chatbots surfaced information that led them to choose a different vendor than expected.

To keep your audience engaged, your SaaS SEO strategy should now account for:

Clear, well-structured content that LLMs can parse and pull from with confidence.
Strong E-E-A-T signals like author bylines, original data, and expert quotes that build trust with both search engines and AI tools.
Presence on trusted third-party sites such as G2, Capterra, and respected industry publications. A recent SE Ranking study found that sites with profiles on review platforms like G2, Capterra, and Trustpilot were three times more likely to be cited by ChatGPT.
Branded content that defines your category so your name surfaces when buyers ask about the problem you solve.

FAQs

What is SaaS SEO?

SaaS SEO is the practice of optimizing a software-as-a-service company’s website to rank higher in search engines for keywords that matter to its buyers. It accounts for the industry’s specific nuances, such as long sales cycles and a subscription-based revenue model.

How important is SEO in a SaaS business?

SEO is one of the highest-leverage growth channels available to SaaS companies. It compounds over time, lowers your dependence on paid acquisition, and meets buyers where they’re already researching solutions. With B2B’s stretched-out sales cycles, a steady stream of search-visible content can keep prospects engaged from first touch to close.

How SaaS companies improve their SEO?

Start with a technical audit to fix page speed and indexing issues. Then build topic clusters that map to each stage of the buyer journey, target bottom-funnel terms like comparisons and alternatives, and earn authority through digital PR and third-party reviews on G2 and Capterra.

What’s more important, a SaaS content strategy or SEO strategy?

They aren’t competing approaches. Your content strategy defines what you publish and why, and your SEO strategy ensures that content gets found. The strongest SaaS programs treat them as a single integrated effort, where keyword research informs content topics, and content quality drives rankings and conversions.

How do I combine SEO and PPC for SaaS lead generation?

Use PPC to capture high-intent commercial queries while SEO builds long-term authority on informational and comparison terms. Share keyword data between teams to identify which paid terms convert well enough to warrant organic investment, and use retargeting to re-engage organic visitors who didn’t convert on the first visit.

Conclusion

SaaS SEO is one of the most effective ways to attract qualified buyers throughout the customer journey. The stronger your strategy, the more opportunities you’ll have to build awareness and convert prospects into long-term customers.

Optimizing your SaaS website starts with a content strategy tailored to your target audience. That means researching relevant keywords and creating high-quality content that appeals to both users and search engines.

While your industry may be more technical than others, following the advice in this SaaS SEO guide will help you achieve better organic search visibility and get closer to your goals.

At the same time, search itself is changing.

AI tools like ChatGPT and Claude are changing how buyers discover software, while Google’s AI Overviews are reshaping what visibility looks like on the SERP.

The SaaS brands that win going forward will be the ones building content for both traditional search and AI answers, while mapping every piece to a real stage in the buyer journey

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LinkedIn Is Cracking Down on AI Slop. Here’s What That Means for Your Strategy

August 5, 2026/0 Comments/in Web Design/by Dubado Solutions

Key Takeaways

LinkedIn announced algorithm changes on May 20, 2026, targeting low-quality AI-generated posts, comments, and automation tools.
Content flagged as AI slop will not be removed but will be suppressed beyond a user’s immediate network, limiting reach significantly.
LinkedIn’s detection systems claim 94 percent accuracy in identifying generic AI content, though false-positive data has not been disclosed.
Content creation on the platform is up 14 percent year over year, driven largely by AI-assisted creation.
AI-assisted content is still welcome if it contains original perspective, expertise, or meaningful contribution.
Brands that combine AI efficiency with authentic subject matter expertise will gain a competitive distribution advantage as the algorithm matures.

LinkedIn has a problem, and it is one the platform created for itself.

After years of integrating AI writing tools directly into its product, LinkedIn is now fighting to contain the flood of low-quality AI-generated content those tools helped produce. The result is a content algorithm that is actively suppressing posts it identifies as “AI slop”: polished-sounding, generic, and hollow.

For brands and marketers who have been using AI to scale their LinkedIn presence, this is a signal worth taking seriously.

What LinkedIn Is Actually Doing

LinkedIn VP of Product Laura Lorenzetti announced the changes in a May 20 blog post. Three types of content are in scope: generic AI-generated posts that lack original perspective, bot-generated and generic AI comments, and automation tools that create AI content at scale.

A post from LinkedIn VP of Product Laura Lorenzetti.

Posts flagged by LinkedIn’s detection systems will not be removed, but their distribution will be suppressed. They will remain visible to a user’s direct connections and followers, but the broader recommendation engine will not amplify them. In practice, this means the platform reach that makes LinkedIn valuable for brand awareness and thought leadership becomes inaccessible to content that fails the originality check.

LinkedIn built its detection capability using an “AI solving AI” approach. Human editors annotated thousands of posts as either generic or original, those examples trained machine learning models to identify patterns at scale, and the system now runs on the feed continuously. The 94 percent accuracy figure comes from LinkedIn’s own testing, which means false positive rates are unknown. Some legitimate content will likely be caught in the net.

The business logic behind the crackdown is straightforward. LinkedIn sells premium subscriptions and advertising on the promise of a high-value professional audience. A feed filled with content nobody wrote undermines that promise, reduces engagement, pushes premium members out, and eventually costs advertisers. Protecting content quality is protecting the revenue model.

What Gets Flagged and What Does Not

LinkedIn has been specific about what it is targeting. Posts that feel generic or repetitive, even if they appear polished on the surface. Comments that simply summarize the post they are replying to without adding anything. Content created through bulk automation tools. Posts that use construction patterns associated with AI assembly, including phrasing like “it’s not X, it’s Y.”

What is explicitly not being targeted is AI-assisted content that contains original thinking. LinkedIn has been careful to draw this line. If a writer uses AI to research, structure, or polish a post built around a real professional insight, that post is welcome. What is not welcome is a post where AI is doing all of the intellectual work.

The practical distinction is whether the content contains something that only the author or their organization could provide. A post built around a first-party data point, a client case study, an executive’s direct experience, or a genuinely specific industry observation has something AI cannot fabricate. A post built around generic claims about industry trends or leadership principles, however well-written, has nothing that differentiates it from the thousands of similar posts already in the feed.

A Linkedin article post from NP Digital.

Why This Changes the Distribution Math

For teams that have been using AI to increase posting frequency on LinkedIn, the suppression mechanism changes the math significantly. Volume without quality now actively works against reach. A suppressed post still consumes the posting slot without delivering the visibility that made posting worthwhile in the first place.

The brands and individuals who will gain distribution advantage as this algorithm matures are the ones that understand what LinkedIn’s algorithm actually measures. The system does not detect AI-written text directly. It detects whether anyone cared enough to stop scrolling. Near-zero dwell time, no saves, and no meaningful comments are the behavioral signals that reduce distribution. Content without a specific professional insight at its core produces exactly those outcomes.

What Content Actually Passes LinkedIn’s Test

The behavioral signal LinkedIn’s algorithm reads is whether people engaged with the content meaningfully: dwell time, saves, substantive comments, and shares. These behaviors correlate strongly with one thing: whether the post contains something specific that only the author or their organization could provide.

A post built around a generic observation about industry trends, however well-written, will produce near-zero dwell time because it says nothing the reader has not already seen. A post built around a specific client outcome, a first-party data point, or a direct professional experience produces engagement because it contains information that does not exist elsewhere in exactly that form.

LinkedIn’s detection system cannot read AI-generated text as such. What it can detect is whether the behavioral signals suggest anyone cared enough to read past the first two lines. That is the actual test. The brands and individuals who will outperform in this environment are the ones producing posts that earn saves and real comments because they contain something worth returning to.

The practical audit for any LinkedIn content program is simple: read the last ten posts and ask, for each one, what specific information does this contain that only our brand could provide? If the answer is “nothing,” the content is at suppression risk regardless of how it was produced.

What to Do Now

Continue using AI as a production tool, not a thinking tool. Research, drafting, editing, formatting, and refinement are all appropriate uses of AI in the LinkedIn content workflow. The step AI cannot replace is identifying the specific professional insight that makes the post worth reading.

Prioritize writing LinkedIn articles with executive thought leadership and first-party perspectives. Our guide to covers how to build that kind of content at scale.

An example of a Linkedin article from NP Digital.

These are the content types most resistant to AI suppression because they contain information that genuinely cannot be replicated at scale. An executive’s direct experience with a business problem, a client outcome with specific context, or an internal data point with genuine industry relevance will consistently outperform generic posts on the same topic.

Audit your current LinkedIn content mix. If a meaningful percentage of recent posts would pass for content from any other company in your category, that is a suppression risk worth addressing. The fix is not less AI. It is more raw material from the people and experiences that are actually specific to your brand.

FAQs

Will LinkedIn remove AI-generated posts entirely?

No. Posts identified as AI slop will be suppressed in the recommendation feed but remain visible to a user’s direct connections and followers. Removal is not currently part of the announced changes.

How does LinkedIn detect AI slop?

LinkedIn uses a machine learning system trained on human-annotated examples of generic versus original content. The system identifies patterns in language, structure, and engagement behavior. It claims 94 percent accuracy, though false-positive data has not been disclosed.

Is AI-assisted writing still allowed?

Yes, explicitly. LinkedIn has drawn a clear line between AI-generated content that lacks original perspective and AI-assisted content that uses AI tools to support human thinking. The latter is welcome. The former is what the suppression system targets.

Does this affect LinkedIn ads as well as organic content?

The announced changes target the organic recommendation feed. LinkedIn’s paid advertising products operate separately and are not currently in scope for these content quality restrictions.

Conclusion

LinkedIn’s crackdown on AI slop is a predictable consequence of the content inflation that AI writing tools have produced on every major platform. The platforms that survive on professional audience quality will protect that quality, even when it means limiting the reach of content created using their own tools.

For brands, the competitive advantage in this environment goes to those who treat AI as a production accelerator for content that starts with genuine expertise. The brands already doing this will benefit from the suppression of lower-quality content filling the same feeds. The brands relying on AI as a substitute for original thinking face a meaningful distribution penalty.

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The Page 2 Podcast: What SEOs must know to get chosen by AI

August 5, 2026/0 Comments/in Web Design News, Yoast SEO/by Dubado Solutions

The Page 2 Podcast: What SEOs must know to get chosen by AI

Took place on
27 July 2026

Hosts & Guests

Alex Moss

Principal SEO

Jon Clark

The Page 2 Podcast Host

As AI agents reshape how people discover and buy products, SEO is evolving beyond rankings and clicks. In the latest episode of The Page 2 Podcast, Yoast Principal SEO Alex Moss joined Jon Clark and Joe DeVita to explore what it takes for brands to be selected by AI agents, from structured data and entity relationships to markdown, llms.txt, and creating a machine-readable source of truth.

In this episode, you’ll learn:

What it means to optimize for AI agents instead of search clicks
Why markdown can outperform HTML for LLMs
Whether llms.txt is worth implementing today
How entity maps and structured data help AI understand your content
What businesses should prioritize to prepare for the next generation of AI-powered search and commerce

Whether you’re just starting to explore AI search or already experimenting with new optimization standards, this conversation offers practical insights into where SEO is headed and how to prepare for what’s next. Give it a listen to future-proof your SEO strategy for the age of AI.

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25 August 2026

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Principal SEO

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Principal SEO

The SEO Update by Yoast – August 2026

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How AI visibility adds context to PPC performance

August 4, 2026/0 Comments/in Search Engine Land, Web Design News/by Dubado Solutions

How AI visibility explains PPC performance

AI visibility metrics help uncover pre-click influences that might not be obvious from search terms, conversion tracking, landing page analysis, or other conventional data points. They add context that helps explain why campaigns attract the right customers, the wrong customers, or no customers at all.

Performance marketers are paid to find the most valuable customers with the most efficient spend. The baseline is understanding what happened after someone searched, clicked, or converted. But focusing exclusively on cleaning up existing demand is a short-sighted goal.

AI experiences (and what goes into serving them) are just as important to performance workflows because AI can shape what customers know, which brands they consider, and the language they use before they ever reach an ad or website.

What AI visibility metrics reveal

AI visibility metrics help answer two questions:

What information did an AI system retrieve to support its response?
Was your brand part of the information that shaped that response?

Three signals are especially useful:

Grounding queries show the retrieval searches AI systems use to gather supporting information and the broader topics your brand appears in.
Citations show when your content is referenced in an AI-generated response.
Share of authority shows how much citation activity belongs to your domain compared with other cited domains for the same topic or query set.

See exactly how your competitors win.

Uncover the keywords, ads, landing pages, and strategies driving your competitors’ paid search success—and find your next opportunity to outperform them.

Analyze your competitors

How to put AI visibility to work

Grounding queries show how AI interprets human intent

Search terms show what a person typed. Grounding queries show the information an AI system retrieved to help answer that person’s question.

A single prompt can generate several grounding queries covering comparisons, pricing, reviews, product details, availability, implementation questions, or other supporting topics. Those queries show how AI translates a human need into retrievable information.

It gives you another way to evaluate whether landing pages, product descriptions, and campaign messaging communicate the right value.

If AI systems consistently associate your brand with services you don’t offer, audiences you don’t want, or use cases that don’t convert well, that mismatch may eventually show up in paid campaigns as traffic that looks relevant but performs poorly.

For example, a B2B company offering executive coaching may not want to be interpreted the same way as a company offering tactical sales training. Both ideas may be semantically similar, but they can attract different buyers, budgets, expectations, and conversion paths.

If grounding queries consistently associate the company with lower-value training searches instead of higher-value advisory or coaching needs, that’s a signal worth investigating.

The useful signal isn’t whether one phrase is universally better than another. It’s whether grounding queries, search terms, landing page behavior, and conversion quality point to the same interpretation of the same offer.

What to do with this insight

If you see a lot of relevant grounding queries, that can be a strong opportunity to test AI-powered query matching with Performance Max, AI Max, or other AI-supported campaign types.

At minimum, grounding queries can inform keyword testing, search themes, creative ideas, and landing page updates. The key is to treat grounding queries as inputs, not instructions.

A grounding query isn’t the same as a keyword. It’s a clue about how AI systems interpret intent. Before acting on it, ask:

Does this query reflect a product or service we actually want to sell?
Does it match the customers we want more of?
Do we have a landing page that supports this intent?
Would this work better as a keyword, search theme, creative test, or content update?
Can we measure whether the test improves conversion quality?

If grounding queries and search terms overlap in valuable ways, that may validate that AI systems and customers are interpreting your offer similarly

If they don’t overlap, investigate before changing bids or budgets. The issue may be messaging, landing page clarity, or content gaps rather than campaign settings.

Dig deeper: SEO vs. PPC vs. AI: The visibility dilemma

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See terms.

Citations and topics help you preview how AI understands your brand

A citation doesn’t mean you won the customer, the final answer, or the conversion. It means your content helped shape the AI experience. That matters because consideration can happen before a measurable click.

If your brand is cited for topics that align with your paid campaigns, your content and campaign messaging may reinforce each other. If your brand is cited for topics that don’t match what you sell, who you serve, or where you win, that may explain why some campaign traffic looks relevant on the surface but doesn’t convert well.

Topics add another layer by showing the themes, attributes, and categories AI systems associate with your brand. That can be especially useful when you’re trying to understand whether AI systems accurately represent your brand.

For example, if a cybersecurity platform wants to be known for enterprise identity protection but AI visibility reporting consistently associates it with small-business antivirus comparisons, that mismatch could be leading to lower-quality “conversions” that translate into bad data for the ad platform. What looks like a campaign settings or targeting issue could actually be a phrasing or content problem.

This is why landing page content matters. AI-powered campaign features such as final URL expansion, asset optimization, and broader matching systems also rely on how your brand, products, services, and pages are interpreted.

If AI visibility data shows that AI systems misunderstand your brand, there’s a reasonable chance campaign automation could inherit some of that confusion.

What to do with this insight

If citations and topics are misaligned, audit your landing page content before assuming the issue is bidding, budget, or audience targeting.

Look at how your priority pages describe:

The problems you solve and whether you attempt to tackle more than one.
The proof points that support the claims made in your advertising.
The customer types you want more of based on how you describe your services.

Then compare that language with the topics where AI systems cite or associate your brand.

If AI systems are pulling your brand into the wrong topics, tighten the content. Make the product category, audience, proof points, and next step easier to understand. If the right topics appear but your citations are weak, look for places where your content may be too thin, too generic, or missing the evidence needed to be useful.

Better content can strengthen paid media campaigns because AI-powered campaign tools are increasingly tasked with interpreting pages, assets, and customer context. The clearer your landing pages and content are, the easier it is for those systems to understand where your offer is relevant.

Dig deeper: 4 CRO strategies that work for humans and AI

Share of authority reveals where competitors are beating you in AI recommendations

Citations show whether your content is referenced in a given grounding query.

Share of authority shows how much citation activity belongs to your domain compared with other cited domains for the same topic or grounding query. This can be a useful competitive signal because it shows where other brands may be influencing the customer’s research journey before a search, click, or conversion happens.

If competitors are cited more often on a priority topic, they may be doing a better job answering the questions customers ask before they convert. This might mean:

More accessible landing pages.
Better proof points, such as reviews and awards.
More useful product information that aligns with their feed.

Fundamentally, ask:

Are competitors doing a better job proving their value in the places AI systems use to shape recommendations?

If the answer is yes, the issue may not be that your campaigns are broken. Your content may not be giving AI systems enough clear, useful, or verifiable information to understand why your brand belongs in the recommendation set.

What to do with this insight

Use share of authority to identify where competitors are outperforming you on topics that matter to the business. Then invest in the content and landing page experiences that prove your value.

That might mean:

Building new landing pages for high-value use cases.
Expanding product or service details to include ideas mentioned in grounding queries.
Adding clearer proof points, such as reviews and awards.
Updating creative and messaging to reflect what customers and AI systems are already asking about.

Not every share-of-authority gap deserves action. If you’re underrepresented on a topic that doesn’t matter to your business, that may be fine.

But if you’re underrepresented on a high-value category, core product, branded initiative, or use case that your paid campaigns depend on, that gap deserves attention.

The performance question isn’t: “How do we become visible everywhere?” A better question is: “Where do we need stronger evidence so qualified customers are more likely to consider us?”

Every click they win is a customer you lose.

See where competitors are investing, which keywords drive their results, and how to capture more of the market.

See who’s stealing your traffic

What AI visibility adds to PPC reporting

AI visibility reporting isn’t a replacement for conversion reports, bidding reports, placement reports, or behavioral analytics. Those tools still tell you whether campaigns are working and where performance is coming from.

AI visibility adds a different perspective. It helps explain how customers, AI systems, and competitors interact with information before traditional performance metrics exist.

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Microsoft Clarity adds branded and non-branded AI queries

August 3, 2026/0 Comments/in Search Engine Land, Web Design News/by Dubado Solutions

Microsoft has updated its analytics tool, Clarity, to add branded and non-branded breakdowns to the AI Citations dashboard and AI reports. Clarity lets you filter branded versus non-branded information across query analysis and filtering.

What Microsoft said. “To make that analysis easier, Microsoft Clarity now adds branded query segmentation to the AI Citations dashboard,” Microsoft wrote. “You can now distinguish branded and non-branded grounding queries AI systems use to look up supporting information for a response,” Microsoft added.

What it looks like. Here is a screenshot from the Microsoft Clarity blog of these new updates:

What is new. Microsoft added branded vs. non-branded view across query analysis and filtering to the Clarity reports including:

Branded labels in the queries card: Individual queries are now clearly marked as branded in the queries view, so you can quickly identify brand-specific queries and understand what the AI systems looked up at a glance.
Share of Authority breakdown by query type: The Share of Authority card now breaks out results by branded and non-branded queries, giving you a clearer view of where your authority is strongest: queries that mention your brand versus more general queries.
Branded and non-branded filters: Filter dashboard data by branded or non-branded queries to compare how your visibility performs when an AI system looks up your brand directly versus broader, more general topics.
More precise citation analysis: By separating brand-led demand from generic discovery, you can better assess brand strength, identify discovery and consideration opportunities, and interpret changes in citation performance with greater confidence.

Branded labels in the queries card: Individual queries are now clearly marked as branded in the queries view, so you can quickly identify brand-specific queries and understand what the AI systems looked up at a glance.
Share of Authority breakdown by query type: The Share of Authority card now breaks out results by branded and non-branded queries, giving you a clearer view of where your authority is strongest: queries that mention your brand versus more general queries.
Branded and non-branded filters: Filter dashboard data by branded or non-branded queries to compare how your visibility performs when an AI system looks up your brand directly versus broader, more general topics.
More precise citation analysis: By separating brand-led demand from generic discovery, you can better assess brand strength, identify discovery and consideration opportunities, and interpret changes in citation performance with greater confidence.

Why we care. Being able to break down and filter your analytics reports by branded and non-branded queries can help you zone in to the data that matters to you. Having more clarity on how people find your content through AI search and chat experiences are important and useful. This update gives you a little more information to work with when it comes to understanding your AI visibility.

Be the brand AI recommends.

See where your brand appears in AI search, where competitors are winning, and what it takes to become the answer AI recommends.

See your AI visibility

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AI Search Data Is Now in Google Search Console: Here’s What You Need to Know

August 3, 2026/0 Comments/in Web Design/by Dubado Solutions

Key Takeaways

Google launched dedicated Generative AI performance reports in Search Console on June 3, 2026, initially rolled out to a subset of UK-based sites.
The report tracks impressions across AI Overviews, AI Mode, and AI features in Discover, broken down by pages, countries, devices, and dates.
Data begins from May 18, 2026; there is no historical backfill.
Click data is not included in the current version, which is the most significant limitation.
Google also introduced an opt-out toggle allowing sites to block content from AI features without affecting traditional organic rankings.
AI visibility and traditional organic visibility are now two distinct, separately measurable channels.

For two years, AI search performance has operated as a black box. Brands could see that AI Overviews were growing, that click-through rates were falling, and that something had changed in how Google surfaced content. But first-party data on what was actually happening inside AI features was not available.

Google changed that on June 3, 2026.

What Google Actually Launched

Google’s Search Generative AI performance reports give site owners a dedicated view inside Search Console showing how their content appears within generative AI features. Previously, any traffic or impressions from AI Overviews and AI Mode were folded into the standard Performance report with no way to isolate them. That separation is now possible.

GSC's Search Generative AI performance reports.

Source

The report covers five dimensions: impressions (how often your URLs appeared in AI features), pages (which specific URLs were cited), countries (geographic breakdown of AI visibility), devices (for Search results), and dates (with hourly through monthly granularity).

The rollout launched June 3, 2026, initially for a subset of UK-based site owners. This is a direct response to the UK Competition and Markets Authority mandate, which requires Google to share this data under the Digital Markets Act. A global rollout is planned but no timeline has been confirmed. If your Search Console does not yet show the report, it is coming.

Alongside the reporting launch, Google introduced an opt-out toggle that allows site owners to exclude their content from AI Overviews, AI Mode, and Discover AI features entirely. Critically, opting out carries no organic ranking penalty. Google has confirmed the toggle will not be used as a ranking signal for traditional search results. The toggle takes effect from June 17, 2026.

Source

What the Data Does and Does Not Tell You

The most significant limitation of the current report is that it tracks impressions only. There is no click data, no CTR, no average position, and no query-level breakdown. You can see that your content appeared in an AI feature, but not whether anyone clicked through to your site as a result.

For performance marketers accustomed to building decisions around clicks and conversion, this creates a measurement gap. AI systems are designed to answer questions directly, which means click rates from AI features are likely structurally lower than click rates from traditional results. An impression inside an AI Overview does not confirm a visit, and given how AI Overviews behave, it may not produce one at all.

The right way to read this data, at least in its current form, is as a resonance signal. A page that earns high AI impressions is content the model finds worth citing. Cross-reference AI impressions against the organic clicks that same URL earns in the standard Performance report, and you get a genuinely useful picture: pages that perform strongly in both channels are your highest-value content assets. As one analysis put it, high AI impressions and high organic clicks on the same page is the clearest signal of what non-commodity content actually looks like. For a deeper look at how to interpret and act on AI brand visibility data, see our recent breakdown.

The data also starts from May 18, 2026, which sits inside the May 2026 core update window. Early trend interpretation should account for that overlap, since ranking shifts from the update will be mixed into the initial AI impression patterns.

Reading AI Impressions as a Strategy Signal

The absence of click data in the current report does not make AI impressions useless. It changes how they should be read.

An impression inside an AI Overview or AI Mode response means Google’s system selected your content as a grounding source for its answer. That selection reflects the same quality signals that drive strong traditional rankings: factual accuracy, topical authority, clear structure, and relevance to the specific question being answered. Pages that consistently earn AI impressions are your content assets that the model finds most citable.

AI impressions in Google Search Console.

Cross-referencing AI impressions with organic clicks from the standard Performance report creates a genuinely useful diagnostic. Pages with high organic clicks and high AI impressions are performing in both paradigms simultaneously.

These are your non-commodity pages: content that earns traffic from users who click through and citation from AI systems answering related questions. Pages with high AI impressions but low organic clicks may indicate content that answers queries well enough to be cited but does not generate sufficient click intent on its own. These are worth examining for conversion optimization. Pages with low AI impressions and high organic clicks may represent ranking-driven traffic that is increasingly vulnerable as AI Overviews expand into their query categories.

Should You Opt Out of AI Features?

Almost certainly not, for most brands.

The business case for opting out is narrow. Publishers with content-licensing models, paywalled material, or specific legal reasons to restrict AI citation may have legitimate reasons to consider it. For the vast majority of brands, opting out means losing a growing visibility channel, with no ranking benefit to offset it.

The opt-out toggle is most useful as a signal that Google has acknowledged the tension between feeding AI systems with publisher content and compensating those publishers for it. Having the control is meaningful. Using it defensively, without a clear strategic rationale, is not recommended.

What to Do Now

Even before your Search Console account gains access, prepare the reporting infrastructure now.

Define how AI impressions will feed into your performance reporting. AI visibility and traditional organic visibility are now distinct channels, and they need separate measurement frameworks. A page ranking well in traditional search is not the same as a page earning AI citations, even though both matter.

Identify which pages are likely candidates for AI citation in your current content mix. Content that directly answers specific questions, uses clear structure, and is factually accurate and current is more likely to surface in AI features. Those pages should be audited for completeness and optimized before the report gives you data to react to.

Set a baseline as soon as access arrives. The report currently has no historical data before May 18, 2026, which means the earlier you establish your first benchmarks, the more useful comparative data you will have going forward.

FAQs

When will I get access to the new AI report in Search Console?

The current rollout is limited to a subset of UK-based site owners. Google has said a global rollout is planned but has given no specific timeline. Monitor your Search Console account for the Generative AI section to appear.

Can I see which queries trigger AI impressions for my content?

Not in the current version. The report does not include query-level data. This is one of the most significant gaps and may be addressed in future updates.

Does opting out of AI features help my rankings?

No. Google has confirmed that the opt-out setting will not be used as a ranking signal for traditional organic search. Opting out affects AI Overviews, AI Mode, and Discover AI features only.

Should I treat AI impressions the same as organic impressions?

No. AI impressions indicate your content was cited inside a generative feature, not that a user was shown your link in a traditional results format. The downstream behavior is different, click rates from AI features are likely lower, and your measurement framework should reflect that distinction.

Conclusion

AI search visibility has been growing for two years with no way to measure it directly. The new GSC Generative AI performance report closes that gap, partially. Impressions data without clicks is an incomplete picture, but it is a meaningful start. The brands that build reporting frameworks around this data now, before a global rollout makes it standard practice, will be better positioned to interpret performance and make decisions as the reporting matures.

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