The Search Console Performance report is a powerful tool to analyze organic search traffic, but finding
the exact data you need can take more time than you’d like. Today, we’re excited to announce an experimental
feature in the Performance report designed to reduce the effort it takes for you to select, filter, and
compare your data: AI-powered configuration.
https://i0.wp.com/dubadosolutions.com/wp-content/uploads/2021/12/web-design-creative-services.jpg?fit=1500%2C600&ssl=16001500http://dubadosolutions.com/wp-content/uploads/2017/05/dubado-logo-1.png2025-12-04 05:00:002025-12-04 05:00:00Streamline your Search Console analysis with the new AI-powered configuration
If your marketing still treats everyone the same, you’re falling behind.
Audience segmentation is what turns generic campaigns into personalized, high-performing ones. Segmented email campaigns can generate a 760 percent increase in revenue compared to non-segmented ones.
That same principle applies across paid ads, social content, product messaging, and just about any other marketing channel you can think of.
Without segmentation, you’re guessing what your audience wants. That leads to wasted ad spend, and low engagement.
Segmentation gives you an edge. It helps you deliver the right message, to the right people, at the right time.
In this guide, you’ll learn what audience segmentation is, how the different types work, and how to apply them to drive better results across your funnel.
Key Takeaways
Audience segmentation is the process of dividing your broader audience into smaller, more specific groups.
Segmentation helps improve engagement, click-through rates, and conversions across every channel.
There are five core types: demographic, geographic, psychographic, behavioral, and firmographic (which is specifically for B2B).
Good segmentation starts with real data, not assumptions, and improves over time.
The most effective marketing strategies use segmentation to deliver more personalized and relevant messaging.
What Is Audience Segmentation?
Audience segmentation is the process of dividing your broader audience into smaller, more specific groups based on shared characteristics. These characteristics can be demographic, geographic, behavioral, or even psychographic.
The goal is simple: understand your audience better so you can speak to them more effectively.
Think of it like this: you wouldn’t send the same message to a first-time visitor and a loyal customer. And you wouldn’t talk to a 23-year-old in the same way you’d market to a 65-year-old. Segmentation helps you avoid that one-size-fits-none approach.
This isn’t just a tactic for email marketers, either. It’s a core part of building relevant campaigns across paid ads, landing pages, SMS, product marketing, and more.
Here’s what segmentation unlocks:
More personalized content and offers
Smarter ad targeting
Higher engagement rates
Better alignment across your marketing funnel
Audience segmentation often gets confused with defining your target audience. But while defining a target audience helps you understand who you’re going after at a high level, segmentation helps you break that audience down into actionable groups for more precise messaging.
Most marketers aren’t struggling with a lack of data. The challenge is turning that data into action.
That’s where customer and audience segmentation creates real value. When you group your audience based on shared traits or behaviors, you can tailor your messaging, timing, and channels to what actually resonates.
Brands that use segmentation typically see:
Higher open and click-through rates
Increased customer lifetime value
Lower cost per acquisition (CPA)
More efficient use of ad budgets
65 percent of consumers expect personalization in their customer experience. And it’s not limited to email. Whether you’re running Google Ads, building a product launch campaign, or personalizing a homepage—segmentation improves performance across the board.
It also allows you to meet customers where they are in their journey. Someone new to your brand might need education. A returning customer may be ready for an upsell. With segmentation, you can deliver the right message at the right moment.
Types of Audience Segmentation
There are several ways to segment your audience. Each type gives you a different lens into what drives your customers’ behavior. The best strategies use a mix of these, depending on your goals, product, and data.
Here are the five most common types of audience segmentation:
Demographic Segmentation
This is the most straightforward method. You segment based on traits like:
Age
Gender
Income level
Education
Marital status
Example: A clothing brand might promote its premium line to high-income professionals while marketing basics to students or entry-level workers.
Geographic Segmentation
Here, you group users by physical location:
Country or region
Climate
City size
Urban vs. rural
Example: A food delivery app might market lunch deals to users in busy cities while promoting family meals in suburban areas.
Psychographic Segmentation
This method looks at the “why” behind your customer’s actions:
Personality traits
Interests and hobbies
Lifestyle choices
Core values
Example: A fitness brand might market high-performance gear to athletes and eco-friendly materials to sustainability-minded shoppers.
Behavioral Segmentation
Segment based on how people interact with your brand:
Purchase history
Engagement level
Brand loyalty
Product usage
Example: A SaaS company might send upgrade offers to heavy users and reactivation emails to inactive accounts.
Firmographic Segmentation (B2B Only)
This is the B2B version of demographic segmentation:
Company size
Industry
Revenue
Location
Decision-maker role
Example: A software vendor might offer enterprise features to large corporations and budget-friendly plans to startups.
Real-World Segmentation Examples Across Channels
Segmentation works across every channel you’re using. The tactics change, but the principle stays the same: send the right message to the right person.
Email Marketing: New subscribers get your welcome series. Inactive customers (90+ days) get a win-back offer with a discount. Same list, different messages based on engagement level.
Paid Advertising:Cart abandoners see retargeting ads featuring the exact product they left behind. Cold audiences see brand awareness content and educational posts. Match the ad creative to where they are in the funnel.
Content Personalization: SaaS visitors see automation guides and workflow content. E-commerce brands see conversion optimization and retention posts. Your CMS can handle this with simple behavioral tags based on past visits.
Product Rollouts: Power users get early beta access to new features. Light users get the stable release later with more documentation. This reduces your support burden and makes heavy users feel valued.
SMS Marketing: Previous buyers in specific zip codes get flash sale alerts for local stores. First-time visitors get a welcome discount. High intent plus geographic relevance equals higher conversion rates.
The channel doesn’t matter. What matters is matching the message to the person and where they are in their journey.
How To Segment Your Audience, Step-By-Step
Getting started with segmentation doesn’t have to be complex. Here’s a simple process you can use to organize your audience into actionable groups.
1. Start With Data You Already Have
Look at what’s in your CRM, email platform, or analytics tool. Useful data often includes location, purchase history, on-site behavior, and sign-up source.
2. Define Your Most Important Attributes
Based on your goals, decide which traits matter most. For an e-commerce brand, it could be past purchase behavior. For a SaaS company, it might be usage level or company size.
3. Build Initial Segments
Group your audience using filters like:
“Has purchased in last 30 days”
“Visited pricing page but didn’t convert”
“Signed up from Facebook campaign”
Start simple. You can get more granular later.
4. Map Each Segment to the Customer Journey
Think about where each group is in their decision-making process. Someone early in the funnel needs education. A returning visitor might need an incentive.
If you haven’t done this yet, use customer journey mapping to connect segments to meaningful actions.
5. Test, Learn, and Refine
Segmentation isn’t one-and-done. Use A/B testing to refine your messaging, offers, and timing by segment. Drop what doesn’t work. Scale what does.
Best Practices for Audience Segmentation (That Actually Work)
Anyone can slice up an email list but effective segmentation goes beyond basic filters. Here are a few proven tips to get better results without overcomplicating your strategy.
Use Real Data, Not Assumptions
Avoid guessing what people care about. Use actual behavior, survey responses, or analytics to guide how you group your audience.
Keep Segments Useful, Not Just Accurate
A perfect audience profile is useless if it’s too small to act on. Prioritize segments that tie directly to your business goals—like conversions, upsells, or retention.
Don’t Over-Personalize
Over-segmentation can create unnecessary complexity. You don’t need 30 different versions of the same email. Focus on meaningful variations that actually move metrics.
Update Your Segments Regularly
Customer behavior changes. Segments should too. Review and refresh your data often to avoid targeting stale or irrelevant groups.
Align Segments With Personas
Your audience groups should reflect the same needs and motivations as your core buyer personas. If you don’t have a clear set, start with this guide to building an accurate customer persona.
I see the same mistakes over and over. Avoid these pitfalls to get better results from your segmentation strategy.
Segmenting too early. You need data before you can segment effectively. If you’re working with a brand-new list or product, focus on collecting behavioral data first. Premature segmentation based on assumptions will waste time and money.
Creating too many micro-segments. A segment with 47 people isn’t actionable. Keep your segments large enough to matter. If a group is too small to justify custom creative or messaging, fold it into a larger segment.
Using outdated data. Someone who bought six months ago isn’t in the same segment as someone who bought yesterday. Refresh your segments quarterly at minimum. Monthly is better for fast-moving businesses.
Segmenting but not personalizing. Building segments means nothing if you send the same message to everyone. Each segment should get tailored copy, offers, or creative. Otherwise, you’re just organizing your list for no reason.
Ignoring overlap between segments. People can belong to multiple groups. A high-value customer might also be geographically close to your store. Think about how segments intersect and prioritize which message matters most.
Not testing segment performance. Track metrics by segment. If one group consistently underperforms, either refine the segment definition or adjust your messaging. Segmentation without measurement is guesswork.
FAQs
What is audience segmentation?
Audience segmentation is the process of dividing your broader audience into smaller groups based on traits like behavior, interests, demographics, or location. It helps you deliver more targeted and relevant marketing.
What are the types of audience segmentation?
The most common types include demographic, geographic, psychographic, behavioral, and firmographic segmentation. Each one gives you a different way to understand and connect with your audience.
How do you segment your audience effectively?
Start with data you already have—like purchase history or engagement. Then group users based on shared traits, align segments to the customer journey, and continuously refine based on performance.
Conclusion
Audience segmentation isn’t a tactic you add later. It’s where effective marketing starts.
By breaking your audience into meaningful groups, you gain the ability to tailor messages, prioritize the right channels, and improve your results across the board. Whether you’re building email campaigns, running paid ads, or planning content, segmentation keeps your strategy focused and relevant.
Start with the data you already have. Pick one or two segments that align with your goals. Then test, learn, and scale.
The more precise your segmentation, the more personal your marketing will feel and the better it will perform.
Need help building a segmentation strategy that actually drives results? Check out my consulting services for hands-on support.
AI chat is the number one source B2B buyers use to shortlist software.
Not review sites. Not vendor websites. Not salespeople. AI chat.
G2’s 2025 survey of 1,000+ decision makers found that 87% say AI tools like ChatGPT, Perplexity, and Gemini are changing how they research software.
Half of SaaS buyers now start in AI chat instead of Google Search.
They’re “one-shotting” their research with prompts like “Give me CRM solutions for a large gym that work on iPads.”
What used to take hours of “Google —> right-click —> open new tab” is condensed to minutes.
If your product doesn’t show up when buyers ask AI to recommend solutions in your category, you’re losing deals before they begin.
This guide shows you exactly how to change that.
I’ll walk you through:
How AI visibility works for SaaS
Why some brands dominate AI answers
What you can do to make sure AI recommends you
Side note: The data in this article comes from Semrush’s AI Visibility Index (August 2025), focusing on the Digital Tech and Software category.
The 3 Types of AI Visibility for SaaS Brands
There are three ways your brand can show up in AI search:
Brand mentions
Citations
Recommendations
Type 1: Brand Mentions
Brand mentions mean your brand appears in the AI’s answer.
It’s not always an endorsement. It’s simply the AI recognizing your brand as relevant to the topic.
For example, I asked ChatGPT:
“How can remote teams stay aligned on projects?”
ChatGPT outlined a few tactics and listed several tools, naming specific brands as examples with no extra context about any of them.
At this level, how AI talks about your brand is super important. AKA: brand sentiment.
A positive tone builds early trust while a negative one sets bad expectations.
Let me show you what I mean.
I asked ChatGPT:
“What do marketers on Reddit say about top reporting dashboards.”
ChatGPT summarized Reddit’s discussions, listed a few tools, and included criticisms about some products.
If I were evaluating dashboards, the negative details about AgencyAnalytics and Looker Studio would create a subtle bias that would follow me as I continued my research.
That’s no bueno.
So make sure sentiment around your mentions leans positive.
Just go to “AI Visibility” > “Perception” and you’ll see key sentiment drivers surrounding your brand. The tool will show you Brand Strength Factors (positive influence on sentiment) and Areas for Improvement (negative sentiment factors).
Type 2: Citations
Citations are instances of AI using your content as a source.
It’s a strong signal that the AI trusts your brand and is using your content to build its answer.
In Google AI Mode, citations show up as clickable links on the right-hand side of the response.
In ChatGPT, they appear as footnotes or small inline links.
Citations come with two complications.
First, they’re not as visible as brand mentions.
The footnote-style links are easy to miss, which means you probably won’t get meaningful traffic from these citations.
The AI can use your content, but not mention your brand.
Semrush’s AI Visibility Index report calls this the “Zapier Paradox.”
In the Google AI Mode dataset, Zapier was the most-cited domain in the entire software category. It appeared in around 21% of the analyzed prompts.
Yet it ranked only #44 for brand mentions.
That means the AI trusts Zapier’s content enough to use it constantly.
But that trust hasn’t translated into more visibility for the brand itself.
That doesn’t mean citations are useless. Far from it, since they’re still the only method of sending users directly from AI search to your website.
But if you’re cited for an answer that recommends other brands (like Zapier often is), the citation isn’t super useful for your brand.
That’s why you want the third type of AI visibility.
Type 3: Product Recommendations
Product recommendations are where the AI moves from “here are some options” to “here’s what you should choose.”
To get recommended, your brand typically needs two things working in your favor:
Positive sentiment
Enough verified facts for the AI to feel confident putting your name forward
For example, when I asked:
“Which CRM is best for small businesses?”
ChatGPT recommended six CRM platforms.
Each one came with a breakdown of strengths.
That’s the AI directly influencing my consideration set.
And when the AI wraps up the answer with the top three CRMs, these three brands stay top of mind.
As the reader, I’m thinking:
“Alrighty. These are the tools I should probably compare.”
That’s the power of SaaS product recommendations in AI search.
The AI isn’t just helping me explore the category. It’s shaping the shortlist I walk away with.
How AI Models Choose Which SaaS Brands to Surface
When AI answers a query, it cross-checks sources.
It compares what you say about your product with its training data. Along with what the rest of the internet says about you.
If the details line up, you’ve got consensus and consistency: two forces that drive visibility in AI search.
Consensus
Consensus happens when many credible places describe your product in the same way.
In practice, the AI is looking for alignment across sources like:
Review sites (G2, Capterra, TrustRadius)
Industry blogs and SaaS publishers
Expert posts on LinkedIn or in public newsletters
User communities like Reddit and Quora
Your own website and documentation
Basically: anywhere your product is being talked about in a credible context.
Take Asana, for example.
It routinely appears in AI answers about project management tools.
And you can see why when you look at its footprint online.
Across multiple places, you’ll find the same core description repeated from their website to Capterra to Reddit.
All of these brand mentions alone help boost Asana’s potential visibility.
But when they also all point to the same story, that’s consensus. This helps AI feel confident surfacing the brand repeatedly.
Consistency
Consistency means the details match everywhere they appear.
When AI scans the web, it’s looking for verifiable facts. If those specifics line up, it trusts them.
But, if those signals don’t match, the model becomes unsure.
(Just like you would if five people gave you five different versions of the same “fact.”)
For example, let’s say:
Your pricing page says your Standard plan includes unlimited reports
Your help center says Standard users get 50 reports a month
Recent reviews say they hit limits after a week
Now you’ve got three conflicting stories.
When the AI sees that, it can’t tell which one is true. It might use the right one, or it might use the wrong one. Or it might not use any of them.
That’s why data hygiene matters in AI search.
The key facts about your brand should be consistent everywhere your brand is described.
The Content That Dominates SaaS AI Search
Not all content carries the same weight in SaaS AI search.
Some formats show up repeatedly because they help models verify what’s true about a product.
Review Platforms
Review platforms are some of the most heavily cited sources in SaaS AI search.
These sites, including G2, Capterra, and TrustRadius, give AI unfiltered, third-party proof about your product.
The platforms help the model validate:
Who you are
What your product actually does
How reliable it is
How users feel about it
In other words, this is where AI goes to separate your claims from real user experience.
And the data shows how influential they are.
According to Semrush’s AI Visibility Index, G2 is the 4th most-cited source for ChatGPT and 6th for Google AI Mode across the entire tech and SaaS category.
That tells us that:
Review platforms aren’t just buyer research hubs
They’re part of an AI’s verification layer
What people say about you in these places becomes part of the material the AI uses when describing your brand.
Best-of listicles and tool roundups give LLMs structured, pre-sorted information that they can easily digest.
These articles hand the AI a ready-made map of a category, including:
Who the key players are
How the tools differ
Which products consistently show up together
The AI regularly pulls from a mix of major publishers, niche SaaS blogs, and established industry media.
For example, when I asked for the top AI SEO tools, Google AI Mode’s citations included a bunch of best lists.
Every roundup, comparison post, or “best tools for X” mention becomes one more anchor AI tools can grab when they’re trying to answer a question about your category.
Pro tip: Don’t ignore your own media. AI models also use company-owned content as reference material. So create your own well-structured roundups and comparison pages in the niches where your product plays.
For example, when I asked ChatGPT whether Omnisend or Mailchimp is better for ecommerce, one of the citations was Omnisend’s own blog post comparing the two tools.
In other words: their own content helped shape the AI’s narrative.
Documentation & Product Knowledge Bases
AI also uses your product documentation to understand how your product works: what it does, who it’s for, and what its technical capabilities are.
For example, when I asked Google AI Mode, “Is Semrush good for enterprise?” the model pulled from several Semrush-owned pages:
The Enterprise landing page
A press release on the enterprise platform
A blog on “What Is Enterprise SEO”
An enterprise client case study
Together, those pages gave the model context to understand Semrush’s enterprise offering.
One more thing:
Make sure your content is well-structured, clear, and complete.
If it’s vague or lacks key details, the AI might look elsewhere to fill the gaps.
The Semrush study shows this clearly with pricing.
When SaaS brands don’t publish transparent pricing, AI models fill the blanks using community speculation. This speculation is often tied to negative sentiment.
So, how do you structure your content for better AI visibility?
Use:
Clear, explicit content using conversational language
Clean formatting that makes details easy to extract
Tables, charts, and Q&A blocks that package information neatly
Headings that signal hierarchy
Want the full breakdown? Our article on how to rank in AI search walks you through the full process.
Video Content
Text may fuel most AI answers, but video (especially YouTube) has become a meaningful signal, too.
In fact, YouTube is the 10th most-cited source in Google AI Mode for SaaS-related prompts.
This means AI isn’t just reading the web. It’s also learning from what people show and say on camera.
For SaaS brands, that’s a real visibility lever.
If your product appears in YouTube reviews, tutorials, comparisons, or walkthroughs, the AI can pull those details straight into its explanations.
For example, when I asked Google AI Mode whether the paid version of HubSpot is worth it, one of the citations was a YouTube review.
If you don’t have a YouTube presence yet, it’s worth planning for.
Start by getting your product included in other creators’ reviews and tutorials.
Then build out your own YouTube channel to control the narrative long-term.
What This Shift Means for Your SaaS Brand
If you’ve already put in the work on your SaaS SEO basics, you’re already in a good position.
But AI search adds a new layer, and it requires a few more steps to stay visible.
Make AI Visibility a Company-Wide Effort
AI search visibility isn’t something marketing can brute-force on its own since consensus and consistency play such a major part.
Multiple teams should keep their corners of the internet aligned in your brand story.
This means:
Marketing keeps claims factual and up to date
Product Marketing ensures documentation, changelogs, and feature pages match what’s actually live
Customer Success helps maintain accurate review-site profiles
PR/Comms monitors media mentions so nothing drifts off-message
To make that doable, create a simple internal “source of truth” every team can follow.
This doesn’t need to be a 100-page brand bible.
Start with:
Exact product names, tier names, and feature labels
The approved value props and phrasing you want repeated everywhere
Performance claims or metrics that should stay consistent across your site, docs, and press
Integration names and technical terms written the same way across all surfaces
Example of a Brand That’s Winning in AI Search (Slack)
Slack ranks ninth overall in the Digital Technology/Software category for AI visibility.
That visibility isn’t tied to one use case or category, as Slack shows up everywhere for various queries.
From prompts about remote work to team communication and the best tools for small businesses.
Here’s what they’re doing that you can steal:
Slack Owns Their Category (Not Just Brand-Specific Prompts)
Slack doesn’t only show up when someone searches for “Slack.”
They show up for everything inside their category, in prompts about:
Use cases: “team chat for remote work”
Features: “tools with shared channels”
Problems: “how to align remote teams”
Price: “team communication tools”
Showing up in these various category prompts builds early recognition.
This then affects what happens next as the user goes deeper into their buying journey.
For example, a user might start an AI conversation with:
“Which is better, Slack or Teams?”
Slack shows up in the citations because they’ve published content that answers that question.
Now, let’s say the user sees a drawback in the AI’s answer.
The user might follow up with:
“What are Slack’s security concerns?”
And Slack again shows up in the citations, this time through their own blog content.
Slack is actively shaping the conversation.
As the user moves from comparison to evaluation to decision, Slack’s content keeps appearing in the AI’s reasoning.
In short: Slack gets to influence the story at every step of the buyer journey.
Slack’s Messaging Is Clear
One thing Slack absolutely nails is message consistency.
Everywhere you look — their website, their docs, their review profiles, their blog — you get the same story about what Slack does and who it’s for.
Go to their site and you’ll see pages laying out features, use cases, and integrations. All in plain, straightforward language.
Even their blog posts break down new features in that same accessible tone.
That clarity matters because it makes it incredibly easy for AI to learn what’s what.
When your content follows a simple structure of “Here’s the feature, here’s what it does, here’s how it works,” the model can easily classify information.
But Slack doesn’t just do this on their site.
Jump over to their review profiles and you’ll find the exact same messaging — the same features, same categories, same positioning.
That consistency is a big plus.
When your messaging stays the same across every channel, you give the AI reliable information to work with.
Slack Is Present Everywhere LLMs Go for Answers
Slack has a footprint across every layer that large language models pull from.
The community layer: Reddit threads, Quora discussions, and YouTube reviews:
The expert layer: SaaS tutorials, niche SaaS blogs, and trusted industry publishers:
The verification layer: G2, Capterra, and TrustRadius:
This breadth matters because it helps LLMs find patterns.
When Slack’s value prop, features, and positioning appear the same way across all three layers, the AI treats that agreement as “high-confidence” information.
This gives the AI zero doubts about what Slack does and what it offers — and therefore what kinds of queries the AI should recommend Slack for.
Help AI Find and Feature Your SaaS Brand
For SaaS AI search, the game is simple:
Show up everywhere the AI looks.
For software companies, that means being intentional about what you publish, how you structure it, and where you show up across the web.
You don’t just need to “write more content.”
You need to create the right content, in the right places, in the right formats that AI models rely on.
http://dubadosolutions.com/wp-content/uploads/2017/05/dubado-logo-1.png00http://dubadosolutions.com/wp-content/uploads/2017/05/dubado-logo-1.png2025-12-03 17:28:222025-12-03 17:28:22SaaS in AI Search: Who’s Ranking (+ How to Steal Their Spot)
AI shopping assistants like ChatGPT, Perplexity, and Google’s generative search are influencing purchase decisions before customers ever reach your product […]
http://dubadosolutions.com/wp-content/uploads/2017/05/dubado-logo-1.png00http://dubadosolutions.com/wp-content/uploads/2017/05/dubado-logo-1.png2025-12-03 13:50:292025-12-03 13:50:298 Best E-Commerce GEO Agencies in 2025
http://dubadosolutions.com/wp-content/uploads/2017/05/dubado-logo-1.png00http://dubadosolutions.com/wp-content/uploads/2017/05/dubado-logo-1.png2025-12-03 13:43:102025-12-03 13:43:10Top 4 Perplexity SEO Agencies in 2025
http://dubadosolutions.com/wp-content/uploads/2017/05/dubado-logo-1.png00http://dubadosolutions.com/wp-content/uploads/2017/05/dubado-logo-1.png2025-12-03 13:36:412025-12-03 13:36:41Top 5 Best ChatGPT SEO Agencies in 2025
Today, we’re rolling out an improvement to Yoast AI Brand Insights, part of the Yoast SEO AI+ package. You can now scan how your brand appears in answers generated by Perplexity, in addition to ChatGPT at no extra cost. This builds on our mission to help marketers, bloggers, and business owners understand how their brand is represented across major AI platforms.
AI powered answers are fast becoming a new gateway for discovery. People increasingly turn to AI tools to research, compare, and choose products or services. Those answers often mention brands as recommendations or sources. When someone asks a question in your niche, you should be able to see if your brand is part of the conversation.
This update makes that possible across more platforms.
AI Brand Insights now lets you see when and how your brand appears in AI generated answers for relevant search style queries. You can track sentiment, and compare your visibility to competitors. By adding support for Perplexity, you get a broader view of how AI systems describe your brand and which sources they rely on, helping you stay visible and confidently represented in AI driven discovery
What’s new
You can now:
Run brand visibility scans in Perplexity
Compare how ChatGPT and Perplexity talk about your brand
Track mentions, sentiment, and citations across both platforms
Monitor changes over time in your AI Visibility Index
Nothing else changes in your workflow. The next time you log in, you’ll see a visual notification guiding you to run your first Perplexity scan.
Why this matters
Understanding how AI answers present your brand helps you move beyond guesswork and see the tone, accuracy, and sources AI chooses when mentioning you. With more customers relying on AI powered explanations than ever, visibility in these answers is now an important part of brand discovery and trust building.
How to try it
Log in through MyYoast, open AI Brand Insights, and run your next scan. Your dashboard now includes results from Perplexity alongside ChatGPT. This gives you a fuller, more accurate view of your brand’s presence in AI generated answers.
If you’re already using Yoast SEO AI+, this enhancement is available to you immediately. If you’re not, upgrading gives you access to this feature along with a complete set of tools for brand visibility, AI insights, and on page SEO.
http://dubadosolutions.com/wp-content/uploads/2017/05/dubado-logo-1.png00http://dubadosolutions.com/wp-content/uploads/2017/05/dubado-logo-1.png2025-12-03 09:07:182025-12-03 09:07:18New to AI Brand Insights: Scan your brand visibility in Perplexity
http://dubadosolutions.com/wp-content/uploads/2017/05/dubado-logo-1.png00http://dubadosolutions.com/wp-content/uploads/2017/05/dubado-logo-1.png2025-12-02 21:30:062025-12-02 21:30:06How to Boost Your AI Search Visibility: 7 Key Factors
http://dubadosolutions.com/wp-content/uploads/2017/05/dubado-logo-1.png00http://dubadosolutions.com/wp-content/uploads/2017/05/dubado-logo-1.png2025-12-02 21:21:572025-12-02 21:21:57LLM-Friendly Content: 12 Tips to Get Cited in AI Answers
