With increased competition, stricter Google guidelines, and the rise of AI-powered search, standing out online is more challenging than ever.
For multi-location brands, this task is even harder as they must maintain a unified brand presence across all locations, yet fulfill consumers’ desire for personalized, local engagement.
Rallio isn’t just another scheduling platform, it’s the next generation of AI-powered tools revolutionizing how multi-location businesses stand out online.
AI-powered insights: Rallio’s AI Assistant operates 24/7, analyzing your data to uncover your strengths and growth opportunities. It also compares your performance against competitors, providing actionable strategies to outperform them.
AI-generated posts: Rallio’s AI instantly generates social media posts tailored to your brand’s style and messaging. Fresh, approved content is just a click away. It can also generate captions and hashtags from any image in your media library, saving time while boosting engagement.
AI-generated captions: Rallio makes creating compelling captions easy. With a simple prompt, it crafts engaging captions complete with relevant emojis and hashtags, driving interactions with your audience.
AI playbook: With the Rallio AI Playbook, you are able to customize your own AI engine that powers your brand from top to bottom throughout the platform. Your Playbook captures your brand voice, tone, and content preferences – everything the AI needs to create effective on-brand, tailored posts just for you.
Reputation management: Rallio simplifies managing reviews across multiple locations by consolidating all reviews into a single dashboard. Its AI generates personalized responses based on review context, saving time and ensuring consistency.
Employee advocacy: Rallio’s mobile app empowers your team to contribute authentic, hyper-local content by submitting photos and videos. This employee-driven content boosts engagement and local relevance, which are key for improving local SEO.
REVV – review acceleration: Positive reviews are crucial for visibility in search results, especially in Google’s Map Pack. Rallio’s REVV platform helps businesses collect and manage reviews through smart surveys, driving up review volume and improving online reputation.
By automating content creation, enhancing employee engagement, and streamlining review management, Rallio helps multi-location businesses build authentic relationships with local audiences while strengthening their national presence. Watch our free demo to see it in action.
How Rallio helps brands gain visibility in AI-powered search
Savvy marketers are focusing on generative engine optimization (GEO) to gain visibility in AI-powered search engines like ChatGPT, Perplexity, and more. A principle of GEO is to prioritize relevance, engagement, and authority, and that’s precisely how Rallio helps boost visibility.
Social signals: Rallio generates content that drives likes, shares, and comments, increasing engagement with your brand.
Local SEO: By focusing on localized posts and employee-driven content, Rallio boosts visibility in local search results and Google’s Map Pack.
Authority: Rallio ensures consistent, high-quality content across platforms, which signals trust and authority to search engines.
Reputation: Managing and responding to reviews effectively enhances local SEO and reinforces brand credibility.
If your brand is leveraging GEO strategies, Rallio can be your secret weapon to boost engagement, relevance, and authority, helping you stand out in search results.
Ready to see Rallio in action? Get instant access to our free demo
Take the first step toward transforming your brand’s online presence with Rallio. Get instant access to our free demo video here.
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Google Ads rolled out a beta feature that lets app marketers apply Seasonality Adjustments to Smart Bidding, giving advertisers more control during short, high-impact events like flash sales or product launches.
Why we care. App campaigns often see sharp conversion swings during promotions, but Smart Bidding typically learns reactively. This beta gives them the ability to proactively boost bids during predictable conversion spikes, ensuring they capture maximum value from short-term promotions and avoid leaving revenue on the table.
How it works:
Works across all App campaign bid strategies.
Best for short, intense periods (1–7 days).
Not meant for minor fluctuations (Smart Bidding already accounts for those).
Bottom line. Advertisers now have a lever to prevent missed opportunities during critical promotional windows, making Smart Bidding more predictable when the stakes are highest.
First seen. This was announced by Qais Haddad, senior app growth manager at Google, on LinkedIn.
Google’s documentation says advertisers can only add 5,000 keywords to a campaign-level negative keyword list. But one advertiser has reported successfully adding more – raising questions about whether this is a glitch or an unannounced update.
Why we care. Negative keyword lists are critical for advertisers, helping them cut wasted spend and prevent ads from showing on irrelevant searches. A higher limit could be a welcome change for large accounts managing thousands of exclusions – but only if Google confirms it’s intentional.
Driving the news. Stan Oppenheimer, paid search specialist at Dallas SEO Dogs, spotted a search campaign with more than 5,000 negatives (i.e. the published limit).
Oppenheimer flagged the issue to Google, asking for clarification and for the official help docs to be updated.
Between the lines. If this is more than a glitch, it could be part of Google’s broader push to standardize campaign limits across formats. But the lack of clarity leaves advertisers unsure whether they can rely on the higher cap.
What’s next. Until Google confirms, advertisers should proceed cautiously – and assume the official 5,000-word cap still applies to search campaigns.
What are Google saying. “The threshold remains 5,000 keywords per negative keyword list, but there may be some cases in which lists a bit over the limit are accepted.” Ginny Marvin, Google Ads Liaison, confirmed on X:
A trial many expected to fizzle has delivered a bombshell: Judge Leonie Brinkema ruled Google illegally monopolized digital advertising, setting up a remedies phase that could force major changes to its ad tech stack. But with Google already losing ground in ad tech and the web fragmenting into retail media, walled gardens, and AI-native platforms, the remedies may feel like too little, too late.
Why we care. The DOJ wants to unwind Google’s dominance by weakening its ad exchange (AdX) and prying open its auction logic. Publishers and advertisers argue this could level the playing field. If auction logic is opened up and interoperability enforced, advertisers may see more competition, better pricing, and greater transparency. But if the remedies stall or prove symbolic, the status quo remains – while spend continues shifting toward walled gardens and retail media networks.
Zoom in:
The DOJ’s asks. Strip AdX from DFP, open-source auction logic, and revisit divestiture if competition doesn’t improve.
Google’s counter. Interoperability with rival ad servers, no “first look” or “last look” privileges, and scrapping unified pricing rules—without divestiture.
Witnesses. Executives from DailyMail.com, AWS, PubMatic, and Index Exchange will testify against Google, while Google leans on its own engineers and Columbia University experts.
Between the lines. Even if the court forces remedies, Google’s grip on display ads has already slipped as advertisers shift spend into walled gardens and AI-driven platforms. The ruling could end up more symbolic than transformative.
What’s next.Testimony runs Sept. 22–30, with a ruling expected in 2026. Until then, the ad industry is bracing for a decision that could either shake up—or barely dent—the future of the open web.
For years, backlinks have been the gold standard for building authority, driving link juice, and climbing up the SERPs. But with the rise of Generative AI, the search landscape is shifting. Instead of chasing endless links, visibility now also depends on something more intelligent: AI citations. This evolution means your brand can show up in front of wider audiences, even without a massive backlink profile.
The question is, when it comes to AI citations versus backlinks, how do they differ, and does one outweigh the other? In this blog, we’ll break down both, explore their role in building authority, and uncover whether AI citations are the future of digital visibility or just another layer to your SEO strategy.
What are backlinks?
Backlinks are simply links from one website to another. Think of them as digital recommendations: when a reputable site links to your content, it signals to search engines that your page is trustworthy and valuable.
For example, below is a screenshot from a Zapier blog post that links to the Yoast SEO plugin landing page in the blog.
Zapier blog post has linked to the Yoast SEO plugin page
Backlinks aren’t new; they’ve been around for more than two decades. In fact, links were introduced back in 1998 as part of Google’s original PageRank algorithm, making them one of the oldest forms of online citations. Since then, they’ve remained a core ranking factor, shaping how websites compete for visibility.
The PageRank Citation Ranking research paper
Today, backlinks are still considered one of the strongest signals for building authority. Many brands invest in link-building strategies to secure high-quality backlinks, from being cited in well-written pieces to building relationships that earn natural mentions.
Why backlinks matter?
Backlinks are not just about search rankings, but they influence almost every aspect of your website’s visibility and growth. Here’s why they remain essential:
Improve rankings by acting as one of Google’s most important signals, especially when they come from authoritative domains
Drive referral traffic that is often highly targeted and more likely to engage with your content
Boost authority and credibility by showing search engines that trusted sites vouch for your content
Help with faster indexing by guiding search engine crawlers to discover and prioritize your pages
Provide semantic understanding by giving Google context through anchor text and linking page content
What types of backlinks work best?
Not all backlinks are equal, and the ones that matter most usually have these traits:
They come from trusted and authoritative websites
They include your target keyword or a variation of the target keywords in your anchor text
They are topically relevant to your niche
They are ‘dofollow’ links that pass link equity
Backlinks remain important for SEO, but as search evolves, they’re no longer the only way to build authority. This is where AI citations enter the picture.
AI citations are references, attributions, or direct links to your content, brand, or product that appear within AI-generated answers. Unlike traditional backlinks that live inside web content, AI citations are shown within AI search results or summaries. They often appear as clickable source cards, numbered footnotes, or links listed below an AI overview.
For example, when Google AI Overviews quotes websites in the AI search box, it cites the original sources that provided the information.
Some other examples of AI citations are:
ChatGPT cites your brand or content as part of its generated answer
Bing Copilot highlights your product as a recommended solution to a user’s query, even if it doesn’t include a direct link
Perplexity.ai lists your research as a supporting source beneath its summarized response
Why AI citations matter for visibility?
AI citations are becoming critical for brand exposure because they align with how people now consume information online:
Search is becoming prompt-driven, which means users type questions or prompts instead of keywords. If AI picks your content to cite, you’re instantly visible to that audience
Discovery is moving from clicks to context. Users may not always visit your website, but being cited ensures your brand becomes part of the answer itself
AI is becoming your audience’s first impression. In many cases, people see the AI summary before they see the actual search results. Appearing as a cited source makes your brand part of that first interaction
Citations boost credibility and authority. When an AI tool references your content, it signals to users that your site is trustworthy enough to be part of the response
Types of AI citations that influence brand visibility
Not all AI citations look the same. Here are the key forms that shape how your brand is discovered:
Name-drop mentions drive brand visibility
When AI directly mentions your brand or product in its response, such as in a recommendation or ‘best of list, you gain instant visibility in front of users without them needing to click further.
Source references build credibility signals
These citations work like the ‘works cited’ section in AI outputs. Tools like Gemini, Perplexity, or Google AI Overviews may display your URL in the list of sources at the bottom of the response. Even if you’re not in the main summary, you benefit from the authority signal.
Quoted passages establish expert authority
When AI pulls exact wording from your content and attributes it to you, it elevates your position as an expert. This type of citation places you in prime digital real estate, signalling leadership in your niche.
Synthesized mentions shape brand narrative
Sometimes AI blends your insights into its summary without naming or linking back to you. While harder to measure, your content still influences the narrative and reinforces brand authority in indirect ways.
AI citations are already reshaping how visibility works in search. Just as backlinks defined SEO two decades ago, citations in AI search are now shaping brand perception by influencing what users see, trust, and remember about your business.
How are AI citations and backlinks different?
So, now that we have an overview of AI citations and backlinks, let’s see how backlinks and LLM citations differ from each other -`
Aspect
Backlinks
AI/LLM Citations
What they are
Hyperlinks from one website to another, long used as a ranking factor in SEO
Mentions, attributions, or references included in AI-generated answers, sometimes with clickable links
Visibility
Usually embedded within web content and not always visible to the average reader
Front-facing and displayed in AI overviews, chatbots, or search snapshots, making them highly visible to users
Trust impact
Boosts site authority indirectly through improved rankings and referral signals
Builds direct credibility by being presented as a trusted source in AI answers or summaries
Selection factors
Determined by domain authority, anchor text, and contextual relevance
Google AI Overviews, citing your blog
Examples
A news site links to your product page in an article
Link building strategies, such as outreach, partnerships, and content marketing, to earn quality backlinks
SEO focus
Link building strategies, such as outreach, partnerships, and content marketing, to earn quality backlinks
Creating structured, high-quality, and easily digestible content that AI systems can cite
Effect
Improves rankings and drives referral traffic over time
Enhances brand visibility, authority, and recall directly in AI-powered search experiences
How to earn both?
Earning backlinks and AI citations doesn’t have to be two separate strategies. With the right approach, the same efforts that build traditional authority also make your content LLM crawler-friendly.
Here’s how to do it:
Create deep, original, and useful content
Go beyond rewriting what’s already ranking. Publish original research, case studies, interviews, or unique perspectives that others can’t find elsewhere. AI models pull from fresh, problem-solving content, and so do journalists and bloggers who link naturally.
Write for real questions, not just keywords
Search is shifting from keywords to prompts. Pay attention to what your audience is actually asking on forums, social media, and other platforms. Create conversational, direct answers to those questions. If your content aligns with user prompts, it’s far more likely to be both cited by AI and linked by humans.
Leverage structured data
Use schema markup (FAQ, HowTo, Article, Product) to help AI and search engines clearly understand your content. Proper attribution of authors and sources also increases your chance of being recognized as a credible reference. Structured, transparent content is ‘citation ready.’
Build relationships for natural backlinks
Backlinks remain relationship-driven. Connect with journalists, bloggers, and industry peers through guest posts, expert roundups, or collaborations. AI often mirrors human trust signals, so if authoritative voices link to you, AI is more likely to cite you too.
Focus on clarity and quotability
Make your content easy to lift and reuse. Use short, memorable statements, stats, or definitions that can be quoted word-for-word. Structured layouts like subheadings, lists, and bullet points make content easier to reference by both humans and AI.
Monitor, analyze, and adapt
Don’t just publish; instead, track performance. Use SEO tools for backlinks and platforms to monitor AI citations and understand AI brand perception. If competitors are cited for prompts you should own, study their structure and improve on it. Adjusting based on data helps you stay ahead.
The takeaway: With the right strategies, you don’t need separate plans for backlinks and AI citations. Clear, authoritative, and trustworthy content earns both and multiplies your visibility across search engines and AI-powered platforms.
Exploring Yoast’s AI features
Applying the right strategies for earning backlinks and AI citations is easier when you have the right tools. Yoast’s AI features combine SEO best practices with AI-powered enhancements to make your content clearer, more discoverable, and more effective.
Here’s how they can support your workflow:
Yoast AI Generate
Quickly create multiple, tailored titles and meta descriptions for your pages or blog posts. This ensures your content attracts clicks and stands out in search results. You can select from different options, tweak them to fit your brand voice, and preview how they’ll appear in SERPs.
Yoast AI Summarize
Turn long-form content into scannable, bullet-point takeaways in seconds. This may also help reduce bounce rates by giving readers immediate clarity on what your page delivers. It also makes your content easier for AI systems and Google’s AI Overviews to interpret correctly.
Yoast AI Optimize
Get AI-powered suggestions to improve SEO signals such as keyphrase distribution, sentence length, and readability. You can review, apply, or dismiss recommendations with one click, ensuring that optimization never comes at the cost of your unique editorial voice.
Together, these AI-powered features help you save time, improve clarity, and boost both human and AI-driven visibility, laying the foundation for stronger backlinks and more consistent AI citations.
Backlinks or citations: What truly matters for visibility?
Backlinks have been the backbone of SEO for more than two decades, helping websites climb rankings, build authority, and attract referral traffic. But the rise of AI citations is reshaping how visibility works. When AI systems like Google’s AI Overviews or ChatGPT cite your content, they place your brand directly in front of users at the moment of discovery.
The truth is, it’s not a choice between backlinks and AI citations. Both matter, but in different ways. Backlinks remain critical for SEO growth and authority, while AI citations are quickly becoming the new gatekeepers of brand perception and visibility. The winning strategy is to create content that earns both.
http://dubadosolutions.com/wp-content/uploads/2017/05/dubado-logo-1.png00http://dubadosolutions.com/wp-content/uploads/2017/05/dubado-logo-1.png2025-09-19 13:52:122025-09-19 13:52:12Everything you need to know about AI citations vs backlinks
Your SEO and PPC teams probably don’t share data. That’s problematic.
Organic traffic is slipping. CPCs are climbing.
And conversions aren’t keeping pace.
It’s not just the LLMs — the SERP itself has changed. In 2025, every query is a blended battlefield of ads, AI overviews, videos, shopping units, map packs, and organic links.
Yet, most teams operate with SEO and PPC in silos.
That doesn’t work anymore.
Because to users, there’s no “organic vs. paid search.” They just click what’s useful. And “useful” now shows up in more places than ever.
If you don’t align your channels, you end up with duplication, cannibalization, and wasted spend.
This guide will show you eight ways to bring SEO and PPC together — from sharing keyword data to sharpening targeting. So you can cut costs, capture more clicks, and drive higher ROI.
Let’s start with an often-overlooked but powerful way to combine your PPC and SEO efforts: spotting intent mismatches.
1. Analyze the SERP to Fix Poor PPC Ad Performance
When your PPC ads fail to convert, the problem might not be your targeting or creative — it could be that you’re bidding on the wrong intent entirely.
If the SERP is dominated by videos, tutorials, or how to guides, it signals that users are still researching — not necessarily ready to buy your product.
Without analyzing the SERP, you risk wasting ad spend on queries that will never convert.
Let’s use Squarespace as an example.
If they’re bidding on “website design” and conversions are weak, a quick SERP check would explain it:
Google surfaces a local pack of agencies for this term, which signals service-seeking intent — not DIY website builders.
Knowing that, they could cut the term and redirect spend to higher-intent queries.
2. Stop Wasting PPC Budget on Customer Support Terms
One of the most common (and costly) PPC mistakes is bidding on customer support queries.
Searches like “[YourProduct] login problems” or “[YourProduct] forum” signal that someone is already a customer trying to troubleshoot — not a prospect considering a free trial or demo.
Yet, many companies spend thousands every month sending these clicks to sales pages that rarely convert.
For example, if Squarespace analyzed their rankings for a term like “Squarespace login,” they’d see they already rank #1.
And those visitors almost never convert for one vital reason — they’re already customers.
Luckily, there’s an easy fix: Squarespace can exclude this and other support terms from its PPC campaigns.
Here’s how to do this for your own ad campaigns:
Start by finding support-related queries for your brand using a keyword research tool.
Enter your brand’s name in the top search bar and your brand’s URL in the purple search bar to personalize the data to your domain.
Click “Search.”
Manually scan the list (or use the “Include keywords” filter) to find support-related terms like “login,” “pricing,” “free trial,” “templates,” “support,” and “forum.”
Then, view the number highlighted in blue to the right of each term — that’s your current ranking.
Already ranking #1–3 for your most commonly searched support terms?
Organic SEO is doing its job, which means you can remove these terms from your PPC campaigns.
In other words, the closer the page matches what a searcher actually wants, the less you pay for each click.
Conducting keyword research can help you understand where you need a separate landing page. To start, use a keyword research tool to group organic keywords into clusters.
Then, map each keyword cluster to a dedicated PPC landing page.
This way, your ads always point to content that matches the searcher’s intent, while your Quality Score (and budget efficiency) benefits from the added relevance.
Squarespace is a good example of this.
Instead of sending every “website builder” query to one broad page, they build dedicated landing pages around different intents.
For example, a search for “portfolio website” leads to a page showcasing portfolio-specific templates, not a generic product overview.
4. Unify PPC and SEO Data to Decide When to Bid on Your Brand
Brand bidding is one of the biggest friction points between SEO and PPC teams.
The debate isn’t whether to bid on your brand — it’s when. Without unified data, teams make this decision based on assumptions rather than evidence.
The truth is somewhere in the middle — and the right decision depends on context.
So, instead of separating PPC advertising and SEO data, combine them to make a more informed decision.
Start by checking whether competitors are bidding on your brand with a manual search for your branded keywords.
For instance, a search for “Squarespace website builder” shows that Wix is also bidding on the term.
Want to automate this process?
Use a tool like Semrush’s Keyword Gap that lets you assess your site and your competitors’ sites for the top shared keywords (paid and organic) they use.
If you see your competitors bidding on your branded keywords, it makes sense to run ads to defend those clicks.
But if your competitors aren’t bidding, it’s time to check your organic coverage.
Do you already own most of page one organically for your branded terms?
If the answer is no, ads help fill the gaps.
If yes, you can safely test pausing.
Turn off your ads for branded keywords and see what happens.
Pro tip: If cutting ads also cuts traffic by [40%, they’re adding value. If drops hit 80%+, you’re just paying for what you’d get anyway.
Finally, consider the messaging value of your ads.
Even if you’re getting organic coverage, brand ads give you space to promote new features, discounts, or free trials.
So it might still be worth paying for them.
For example, Squarespace uses its paid ads on the term “Squarespace website builder” to promote its new AI website builder tools.
5. Prioritize High-ROI SEO Keywords by Analyzing PPC Data
A common SEO challenge is figuring out which keywords actually matter.
Ranking for broad terms might bring traffic, but not necessarily signups or revenue.
Without conversion data, it’s hard to know where to focus.
This is where PPC comes in. Paid campaigns don’t just generate leads — they generate fast, reliable data.
You can see which headlines win clicks, which keywords drive conversions, and what each click is worth.
Take the phrase “website platform for small businesses.”
If PPC data shows it converts four times better than the broader “website platform,” that’s the angle worth prioritizing in your SEO titles, H1s, and content strategy.
PPC metrics can even help you prove the business value of SEO — something every stakeholder loves.
Once you know a keyword’s conversion rate and customer value from paid campaigns, you can model the value of ranking for it:
SEO ROI = (Organic clicks gained × PPC conversion rate × Customer value) − SEO cost
Say a keyword costs $30K/month in ads, but ranking organically would capture roughly a third of that traffic.
That’s about $9K in “free” conversions every single month.
That’s the kind of math that gets buy-in from leadership.
You can use this same logic to estimate the value of refreshing existing content. Sometimes a simple update is worth tens of thousands in equivalent ad spend.
The takeaway?
PPC data gives you the proof points and the playbook to double down on the SEO opportunities that will actually pay off.
Algorithm shakeups create openings you can exploit if you move fast.
If a competitor drops from page one, don’t wait.
Publish or refresh your content to take over those keywords. At the same time, increase your PPC bids on the same terms while auction pressure is temporarily lower.
That one-two punch lets you capture traffic your rivals just lost before they even know what hit them.
Many stakeholders still think of SEO and PPC as competing, not complementary.
While leadership may be nervous to try a new, silo-free approach to search engine marketing, you can convince them in a couple of ways.
First, show them how SERPs have evolved.
AI Overviews, rich features, and rising CPCs mean the old “paid vs. organic” split doesn’t exist anymore.
Then, use this powerful three-step storytelling framework to convince execs to act.
Step 1: Explain what’s happening by describing the external shift. Example: “AI Overviews and rising CPCs are changing how people find us in search.”
Step 2: Show how it’s impacting you by tying the shift to your company’s results. Example: “Our paid CPCs are up 22%, and organic traffic for branded queries is down.”
Step 3: Highlight what you can do about it by presenting alignment as the solution. Example: “By aligning SEO and PPC, we can cut wasted spend on brand terms and reinvest in high-converting queries.”
Start small. Don’t push for a full overhaul on day one.
Instead, prove ROI by aligning on a single initiative — like deciding when to bid (or not) on branded keywords.
Once you’ve shown early results, it’s easier to get everyone aligned on their responsibilities.
Next, work with SEO and PPC teams to establish next steps for each team member to achieve closer alignment.
Here’s a role-based plan for what your teams should start doing now:
SEO/PPC Team Role
Primary Responsibilities
Action Steps to Drive SEO + PPC Alignment
SEO Specialists
Mine PPC data for ROI
Request PPC data to see which paid keywords actually drive results
Use that data to identify low-CPC, high-ROI terms worth pursuing in organic search
Share blog content and resources that PPC teams can repurpose for retargeting campaigns
PPC Teams
Flag costs and align content
Flag high-CPC keywords that SEO should try to rank for long-term to reduce reliance on paid
Align PPC landing page messaging with existing SEO pages so users get a consistent story
Promote educational content to cold audiences instead of conversion-focused ads
CMOs & Leaders
Measure blended performance
Set shared KPIs (e.g., revenue per SERP, blended CAC)
Merge data sources so SEO and PPC teams both have access to the same performance insights
Break down silos by running regular joint syncs between paid and organic teams
Agencies & Consultants
Prove value with unified reporting
Deliver blended strategy reporting that shows paid and organic results in one view
Use unified insights to demonstrate ROI and strengthen client retention or upsell
Educate clients on how the SERPs are changing and how alignment helps them adapt
Boost Your ROI with a Shared SEO and PPC Strategy
It doesn’t make any sense not to have SEO and PPC work together.
Keep the teams siloed, and you’ll waste budget, lose traffic, and fall behind as search evolves.
For your first move, start with a shared SERP review.
Map where you’re strong, where you overlap, and where the gaps are for the quickest path to better ROI from both channels.
Want to dig deeper?
Explore our guide to the best PPC tools to uncover the advanced data and insights you need to align SEO and PPC, cut wasted spend, and boost ROI.
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When shoppers are online, knowing which store to buy from can be a tough decision. The new store widget powered by Google
brings valuable information directly to a merchant’s website, which can turn shopper hesitation
into sales. It addresses two fundamental challenges ecommerce retailers face: boosting visibility
and establishing legitimacy. The widget helps you attract customers and encourage them to make a
purchase. Businesses using the store widget on their websites saw up to 8% higher sales
within 90 days compared to similar businesses without it.
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Answer Engine Optimization (AEO) is one of the most important topics in search right now.
It’s about making sure your brand shows up inside AI-generated answers — not just on traditional SERPs.
As large language models (LLMs) like ChatGPT, Gemini, and Perplexity reshape discovery, AEO ensures your content gets mentioned and cited where buyers are asking questions.
But here’s the bigger truth: AEO is just one piece of a larger shift.
We’re entering the era of Search Everywhere.
Discovery no longer happens in a single Google results page.
It’s happening across AI chat, overviews, forums, video, and social.
And new data shows just how fast this shift is accelerating.
New research from Semrush predicts that LLM traffic will overtake traditional Google search by the end of 2027.
And our own data suggests that’s likely to be true.
In just the past three months, we’ve seen an 800% year-over-year increase in referrals from LLMs.
We’re seeing tens of millions of additional impressions in Google Search Console as AI Overviews reshape how Google displays answers.
If your brand isn’t adapting, you risk disappearing from the channels your audience is already using.
In this guide, I’ll explain:
What AEO is and how it differs from SEO
Why your existing SEO foundation still matters (and what to evolve)
Practical steps to optimize for answer engines and drive measurable results
What Is AEO and Why Does It Matter?
Answer Engine Optimization (AEO) is the practice of structuring and publishing content so that AI systems — like Google AI Overviews, AI Mode, ChatGPT, and Perplexity — pull your brand directly into their answers.
But AEO goes beyond tweaking a few pages. It’s about making your brand part of the conversation when people ask questions.
That requires three things:
Publishing content in the right places where AI tools actively crawl and cite
Earning brand mentions across the web (even without a link)
Ensuring technical accessibility so AI crawlers can actually parse your content
These engines don’t rank “10 blue links.” They generate answers.
Sometimes they cite sources. Sometimes they don’t. Either way, the goal is to give the searcher everything they need without leaving the interface.
That changes your job. With AEO, you’re not only optimizing for a click — you’re optimizing to shape the answer itself.
Why AEO Matters Now
Traditional search is still a traffic driver. That won’t change overnight.
But discovery is moving fast:
Success used to mean ranking #1.
Soon there may be no “#1 spot” at all.
The win condition is becoming the recommended solution — the brand AI platforms trust enough to include.
The data tells the story:
ChatGPT reached 100 million users faster than any app in history. And as of February 2025, it now has more than 400 million weekly users.
Google’s AI Overviews now appear on billions of searches every month — at least 13% of all SERPs.
And they appear for more than half of the keywords we track at Backlinko:
Answer engines are influencing YOUR audience too. So it makes sense to start optimizing for them now.
How AEO and SEO Work Together
Let’s clear up the biggest question:
“Isn’t this just SEO with a new name?”
In many ways, yes. But there’s a reason everyone is talking about AEO right now.
If you’ve been confused by all the acronyms — AEO, GEO (Generative Engine Optimization), AIO (AI Optimization) — here’s the point:
They all reflect the same shift. Search is no longer only about rankings. It’s about visibility in AI-powered answers.
Terms like AEO, GEO (Generative Engine Optimization), and AIO (AI Optimization) have exploded in interest — because they reflect a real shift.
And with all the acronyms flying around, it can be tough to know who to listen to.
We’re not saying AEO replaces SEO.
But it does help reframe your strategy for how discovery works now — across AI tools, social platforms, and new surfaces beyond traditional search.
From Traditional SEO to Search Everywhere
Evolving From
Evolving To
SEO = Google Search
SEO = multi-surface visibility (Search, AI/LLMs, social)
Success = ranking for keywords
Success = being found across Search + Chat
SEO is a siloed function
SEO is cross-functional + connected to product, brand, PR, and social
Keyword-first content planning
Intent and entity-driven topic planning with semantic structure
Backlinks to pass PageRank
Traditional backlinks plus more focus on brand mentions and co-citations
Traffic as a core KPI
Visibility, influence, and conversions across touchpoints as core KPIs
Technical SEO as the foundation
Technical SEO as the foundation (with additional focus on JavaScript compatibility)
That means there’s good news:
If you’ve invested in good SEO, you’re already a lot of the way there.
AEO builds on the foundation of great SEO:
Creating high-quality content for your specific audience
Making it easy for search engines to access and understand
Earning credible mentions across the web
These same elements help AI engines decide which brands to reference.
But here’s the difference:
AI engines don’t work exactly like Google.
That means some of your tactics (and what you track) need to evolve.
So let’s walk through how to do that.
7-Step AEO Action Plan
We’re still in the early days of understanding exactly how AI engines pull and prioritize content.
But one thing is clear:
You need to adapt or reprioritize some traditional SEO tactics for Answer Engine Optimization.
The first three steps below cover overarching best practices for AEO.
Steps 4-7 cover optimizing content for answer engines specifically (and how to track your results).
Step 1. Nail the Basics of SEO
As I said earlier, good AEO is also generally good SEO. But not everything you do as part of your wider SEO strategy is as important for answer engine optimization.
Let’s focus on what really matters for answer engines.
Make Your Site Easy to Read (for Bots)
Crawlable and indexable: If AI tools can’t access your pages, you won’t show up in answers
Fast and mobile-friendly: Slow, clunky sites hurt UX — and your chances of getting cited
Secure (HTTPS): This is now table stakes, and it builds trust with users and AI systems
Server-side rendering: Some AI crawlers still struggle with JavaScript, so use server-side rendering as opposed to client-side rendering where you can
Show You’re Worth Trusting (E-E-A-T)
AI wants trustworthy sources. That means showing E-E-A-T:
Experience: Share real results, personal use, or firsthand knowledge
Expertise: Stick to topics you truly know — and go deep
Authority: Get quoted, guest post, or contribute to well-known sites
Trust: Use real author bios, cite sources, and include reviews or testimonials
Note: We’re not suggesting these AI tools have any sort of “system” built into them that aligns with what we call E-E-A-T. But it makes sense that they’ll prefer to cite content from reputable sources with expertise. This provides a better user experience and makes the AI tools themselves more reliable. Also, download our Free Template: E-E-A-T Evaluation Guide: 46-Point Audit
Step 2. Build Mentions and Co-Citations
AI systems don’t just look at backlinks to understand your authority. They pay attention to every mention of your brand across the web, even when those mentions don’t include a clickable link.
Backlinks are still important. But this changes how you should think about building your wider online presence.
Audit Your Current Mentions
Start by auditing where you’re currently mentioned. Search for your brand name, product names, and key team members across Google, social media, and industry forums.
Take note of what people are saying and where those conversations are happening.
You’ll probably find mentions you didn’t know existed. Some will be positive, others neutral, and a few might need your attention.
Also run your brand name and related terms through the AI tools themselves.
Does Google’s AI Mode cite your brand as a source for relevant terms?
Does ChatGPT know who your team members are?
What kind of sentiment do the answers have when you just plainly ask the tools about your brand?
It’ll let you track your LLM visibility (a by-product of good AEO) in top tools compared to your rivals:
The tool compares your brand to your rivals in terms of AI visibility, market share, and sentiment:
And it’ll show you where your brand strengths are and where you can improve:
Want to track your brand’s AI visibility? Get a free interactive demo of Semrush’s AI SEO Toolkit to see how you can compare to competitors across ChatGPT, Claude, and other AI platforms.
Keep Building Quality Backlinks
Just because mentions are more important than before with AEO, it doesn’t mean you should abandon traditional link building. Backlinks still matter for SEO, and they often lead to the kind of authoritative mentions that AI systems value.
There are a few different definitions out there of co-citation and co-occurence.
I’ll be honest: the definitions don’t matter as much as the implications. I’ve seen one source define co-citations as the exact thing another source calls co-occurence. So for this section, I’m just going to talk about what these are and why they matter, without getting bogged down in definitions.
The first important way to think of co-citations/co-occurences is simply the mention of one thing alongside another.
In the case of AEO, we’re usually talking about your brand or website being mentioned alongside a different website or topic/concept on another website.
For example, if your brand is Monday.com, you’ll pick up co-citations involving:
Your competitors (ClickUp, Asana etc.)
Key terms or categories associated with your business (like “project management software”)
Specific concepts or questions related to what you do (e.g., “kanban boards” and “how to automate workflows”)
In Monday’s case, there are hundreds of pages out there that mention it alongside ClickUp and Asana in the context of “project management tools”:
This suggests to Google and other AI tools that Monday and ClickUp are both related to the term “project management tools” and are both popular providers of this kind of software.
The other common way to think about co-citations is mentions of your brand across different, often unrelated websites. For example, Monday being mentioned on Forbes and Zapier would be a co-citation involving them.
To sum it up:
If two (or more) brands/websites are often mentioned alongside each other, AI tools will assume they are related (i.e., they’re competitors)
If a brand is often mentioned in the context of a particular topic, concept, or industry, AI tools will assume the brand is related to those things (i.e., what you offer)
If lots of different websites mention a particular brand, the AI tools will assume that brand is worth talking about (i.e., probably trustworthy)
Obviously, there’s a lot more to it, but this is a fairly basic overview of what’s going on.
How to Put This into Action
To build citations, co-citations, and co-occurences:
Look for opportunities to get mentioned alongside your competitors. When publications write comparison articles or industry roundups, you want your name in that list. These co-citations help AI systems understand where you fit in your market.
Participate in industry surveys and research studies. When analysts publish reports about your sector, being included gives you credibility (and any backlinks are a bonus).
Get involved in relevant online communities. Answer questions on Reddit, contribute to LinkedIn discussions, and join industry-specific forums. These interactions create mentions in places where AI systems often look for authentic, community-driven insights.
The goal is to become a recognized voice in your space. The more often your brand appears in relevant contexts across the web, the more likely AI systems are to include you in their responses.
Step 3. Go Multi-Platform
Going beyond Google is something top SEOs have been telling us to do for a long time. But AI has made this an absolute must.
Platforms like Reddit, YouTube, and other user-generated content sites appear frequently in AI outputs.
So, a strong brand presence on these platforms could help you show up more often.
The benefits here are (at least) three-fold:
Being active on multiple platforms lets you reach your audience where they are. This helps you boost engagement, brand awareness, and, of course, drive more conversions.
AI tools don’t just look at Google search results. They pull from forums, social media, YouTube, and lots of other places beyond traditional SERPs.
Being active on multiple platforms means you’re less exposed to one particular algorithm or audience. Diversification is just good practice for a business.
Brian Dean did an excellent job of this when he was running Backlinko. That’s why you’ll see his videos appear in Google SERPs for ultra-competitive keywords like “how to do SEO”:
We’re taking our own advice here. In fact, it’s a big part of why we launched the Backlinko YouTube channel:
Here’s some quick-fire guidance for putting this into practice:
People go to YouTube to learn how to do things, research products, and find solutions to their problems. This makes product reviews, tool comparisons, and in-depth tutorials great candidates for YouTube content.
Podcast content and transcripts are beginning to surface in AI results (especially in Gemini). Building a presence here is a great opportunity to grab some AI visibility.
TikTok and Instagram Reels reach younger audiences who increasingly use these apps for search. Short-form videos that answer common questions in your industry can drive discovery, and AI tools can also cite these in their responses to user questions.
AI tools LOVE to cite Reddit as a source of user-generated answers (especially Google’s AI Overviews and AI Mode). To grow your presence on the platform, find subreddits where your target audience hangs out and share genuinely helpful advice when people ask questions related to your expertise. Don’t promote your business directly — focus on being useful first.
LinkedIn works similarly to Reddit for B2B topics. Publish thoughtful posts and engage in relevant discussions to help establish your voice in professional circles. These interactions can then get picked up by AI systems looking for expert perspectives.
Step 4. Find Out What AI Platforms Are Citing for Your Niche
What’s a powerful way to understand both what to create and what topics to target?
To simply learn what AI tools are likely to include in their responses to questions that are relevant to your business.
Start by directly testing whether/how your content appears in AI tools right now. Go to ChatGPT, Claude, or Perplexity and ask questions that your content should answer.
In the example below, Backlinko is mentioned (great), but there’s also a YouTube video front and center. And forums are appearing too. These are places we might want to consider creating content or engaging with conversations.
As you do this for your brand, pay attention to the sources they cite:
Are they commonly mentioning your competitors?
What platforms do they tend to cite? (Reddit, YouTube etc.)
What’s the sentiment of mentions of both your brand and your competitors?
As you do this, try different variations of the same question.
For example, you could ask “What’s the best email marketing software?”
Then try “Which email marketing tool should I use for my small business?”
Notice how the answers change and which sources get mentioned consistently.
In the example above, the first prompt mentioned MailerLite, which was absent in the list for small businesses. But the second prompt pushed Mailchimp to the top and mentioned three new options (Constant Contact, Brevo, and ActiveCampaign).
If you were MailerLite and trying to reach small businesses, you’d want to understand why you’re not being cited for that particular prompt.
Pro tip: Try it with different tools as well. They each have their own preferences when it comes to citing sources, so it’s a good idea to test a couple of them.
You can automate this process with tools like Profound or Peec AI. These platforms run prompts at scale, helping you understand how and where your brand appears. But they can be pricey.
That’s why I recommend you spend some time running these prompts manually at first.
By the way:
This isn’t just important for “big brands” or those selling products. You can (and should) do this if you run a blog, local business website, or even a personal portfolio.
For example, consultants and freelancers will find these tools often cite marketplaces like Upwork and Dribbble. If you don’t have a profile on there, you’ll likely struggle to get much AI visibility.
And if you’re a local business owner, you’ll often find specific service and location pages appear in AI responses:
This is useful for understanding the types of content you should be focusing on for AEO. Now it’s time to decide what topics to focus on in your content.
Step 5. Answer Your Audience’s Questions
The way people search with AI tools is fundamentally different from how we use traditional Google search. This changes how you should plan your content.
Traditional SEO taught you to target specific keywords. You’d create a page optimized for “healthy meal prep ideas” and try to rank for that phrase.
But what happens when people are instead searching for “what to cook for dinner when I’m trying to lose weight”?
The answer might involve healthy meal prep as a solution, but it’s a completely different prompt (not a search) that gets to that answer (not a SERP).
When you run these queries through Google’s AI Mode, you see two totally different sets of sources and content types.
For the “healthy meal prep ideas” query (which is a perfectly valid and searchable term), the focus is listicles, single recipes, and YouTube videos. And the format is categories (bowls, wraps, and sandwiches etc.) with specific recipes:
But for “what to cook for dinner when I’m trying to lose weight,” the sources are primarily lists, forum results, or articles specifically around weight loss.
In this case, the format of the answer is largely broad tips for cooking healthily and then some general cooking styles or meal types, rather than specific recipes:
As more users realize they can use conversational language to make their searches, longer queries will become more common. This makes this kind of intent analysis critical.
These longer, more specific queries represent huge opportunities. Most companies aren’t creating content that answers these detailed questions.
The more specific the question, the more likely you are to show up when AI systems look for authoritative answers. You want to own the long-tail queries that relate directly to your product or expertise.
But:
You obviously can’t reasonably expect to create content for every single long-tail query out there. So how do you approach this in an efficient way?
How to Choose the Questions to Answer
Start by listening to the actual questions your customers ask.
Check your customer support tickets, sales calls, and user feedback. These real questions from real people often make the best content topics — because they’re the same kinds of questions people will ask these AI tools.
Don’t have any customers? No problem.
Use community platforms to find these conversational queries. Reddit, Quora, and industry forums are goldmines for discovering how people actually talk about problems in your space.
Step 6. Structure Your Content for Answer Engines
AI systems process information differently than humans do. They break content into chunks and analyze how those pieces relate to each other.
Think of it like featured snippets but more granular, and for much more than just direct questions.
This means the way you structure your content directly impacts whether AI systems can understand and cite it effectively.
Note: A lot of what I say below is just good writing practice. So while this stuff isn’t necessarily “revolutionary,” these techniques are going to become more important as you focus on AEO
.
One Idea per Paragraph
Keep your paragraphs short and focused on one main idea.
When you stuff multiple concepts into a single paragraph, you make it harder for AI systems to extract the specific information they need.
Also avoid burying important information in the middle of long sentences or paragraphs. Front-load your key points so they’re easy to find and extract.
And guess what?
It also makes it easier for your human readers to understand too. So it’s a win-win.
Use Clear Headings
Use clear headings and subheadings to organize your content logically.
Think of these as signposts that help both readers and LLMs navigate your information. And make sure your content immediately under the headings logically ties to the heading itself.
For example, look at the headings in this section. Then read the first sentence under each one.
Notice how they’re all clearly linked?
This is a common technique when trying to rank for featured snippets. You’d have an H2 with some content that immediately answers the question…
…and this would rank for the featured snippet for that query:
This is still a valid strategy for traditional search. But for AEO, you need to have this mindset throughout your content.
Don’t make every H2 be a question (this will quickly end up looking over-optimized). But do make sure the content that follows your (logical) headings is clearly linked to the heading itself.
Break Up Complex Topics into Digestible Sections
If you’re explaining a complex or multi-step process, use numbered steps and clear transitions between each part.
This makes it easier for AI systems to pull out individual steps when someone asks for specific instructions. And it’ll make it much easier for your readers to follow.
Also write clear, concise summaries for complex topics. AI systems often look for these kinds of digestible explanations when they need to quickly convey information to users.
Include Quotes and Clear Statements
Include direct quotes and clear statements that AI systems can easily extract.
Why is this worth your time?
Because pages with quotes or statistics have been shown to have 30-40% higher visibility in AI answers.
So instead of saying “Email marketing could be an effective channel for your business,” write “Email marketing generates an average ROI of $42 for every dollar spent.”
Note: Don’t just flood your content with quotes and stats. Only include them when they actually add value to your content and are useful for your readers.
Use Schema Markup
Schema markup gives you another way to structure information for machines. This code helps systems understand what type of content you’re presenting.
For example, FAQ schema tells algorithms that you’re answering common questions. HowTo schema identifies step-by-step instructions.
You don’t need to be a developer to add schema markup. Many content management systems (like WordPress) have plugins that handle this automatically.
Make It Scannable
Use formatting like bold text to highlight important facts or conclusions and make it easier for readers to skim your content. This helps both human readers and AI systems identify the most important information quickly.
This has always been a big focus of content on Backlinko. We use lots of images to convey our most important points and add clarity through visualizations:
And we use clear headings to make our articles easy to follow:
The goal is to make your content as accessible as possible to both humans and machines. Well-structured content performs better across all types of search and discovery.
And if your content is enjoyable to engage with, it’s probably going to do a better job of converting users into customers as well.
Step 7. Track Your Visibility in LLMs
How often are tools like ChatGPT, Perplexity, or Gemini mentioning your brand?
If you’re not tracking this yet — you should be.
Tracking your visibility in AI-generated responses helps you understand what’s working and where you need to focus your efforts.
But where do you start? And what should you track?
Manual Testing as a Starting Point
Start with manual testing. This is the simplest way to see how you’re performing right now.
Ask the same questions across different AI platforms, like ChatGPT, Claude, Perplexity, and Google (both AI Mode and AI Overviews). Take screenshots of the responses and note which sources get cited.
Do this regularly, and you’ll start to see patterns in which types of content get mentioned and how your visibility changes over time.
Honestly though: you’re going to struggle to get a lot of meaningful data doing this manually. And it’s not scalable. Plus, so much of what an AI tool outputs to a user depends on the previous context, like:
Past conversations
Previous prompts within the same conversation
Project or chat settings
This makes it challenging to get truly accurate data by yourself. This is really more of a “feel” test that, in the absence of dedicated tools, can provide a very rough idea of how answer engines perceive your brand.
Use LLM Tracking Tools
For more comprehensive tracking, dedicated tools can automate this process.
Platforms like Semrush Enterprise AIO help you track your brand’s visibility across AI platforms like ChatGPT, Claude, and Google’s AI Overviews.
It shows you exactly where you stand against competitors and gives you actionable steps to improve.
Competitive Rankings is my favorite feature. Instead of guessing why competitors might rank better in AI responses, you get actual data showing mention frequency and context.
Another option is Ziptie.dev. It’s not the most polished tool yet, but they’re doing some really interesting work — especially around surfacing unlinked mentions across AI outputs.
If you already have Semrush, then the Organic Research report within the SEO Toolkit does provide some tracking for Google AI Overviews specifically.
You can track which keywords you (or your competitors) rank for that have an AI Overview on the SERP. If you don’t currently appear in the overview, that’s a keyword worth targeting.
Tracking the keywords you do rank for in these AIOs over time can help you gauge the performance of your AEO strategy.
Why Talk to Your Boss (or Clients) About AEO?
You’ve seen the steps. Now you need a story.
AEO isn’t just a tactical shift — it’s a way to explain what’s changing in search without resorting to hype.
AEO helps you frame those changes clearly:
Traditional SEO still works
Your past investments are still paying off
But the bar is higher now
Visibility means more than rankings
Your brand needs to be mentioned, cited, and trusted across every channel
AEO gives you the framework to explain what’s changing and how to stay ahead of it.
You Need to Start Now to Stay Visible
This space is evolving fast. New capabilities are rolling out monthly.
The key is to start tracking now so that you can benchmark where you are and spot new opportunities as AI search matures.
Grow your presence by adding a AEO approach on top of your SEO efforts:
Continue optimizing for strong rankings and authority (AI still leans on this)
But now, prioritize content and signals that AI engines are more likely to reference directly
Want to learn more about where the world of search is heading? Check out our video with Backlinko’s founder Brian Dean. We dive into how search habits are changing and how you can build a resilient, multi-channel brand.
http://dubadosolutions.com/wp-content/uploads/2017/05/dubado-logo-1.png00http://dubadosolutions.com/wp-content/uploads/2017/05/dubado-logo-1.png2025-09-15 14:01:542025-09-15 14:01:54Answer Engine Optimization (AEO): How to Win in AI Search
We’ve all asked a chatbot about a company’s services and seen it respond inaccurately, right? These errors aren’t just annoying; they can seriously hurt a business. AI misrepresentation is real. LLMs could provide users with outdated information, or a virtual assistant might provide false information in your name. Your brand could be at stake. Find out how AI misrepresents brands and what you can do to prevent them.
AI misrepresentation occurs when chatbots and large language models distort a brand’s message or identity. This could happen when these AI systems find and use outdated or incomplete data. As a result, they show incorrect information, which leads to errors and confusion.
It’s not hard to imagine a virtual assistant providing incorrect product details because it was trained on old data. It might seem like a minor issue, but incidents like this can quickly lead to reputation issues.
Many factors lead to these inaccuracies. Of course, the most important one is outdated information. AI systems use data that might not always reflect the latest changes in a business’s offerings or policy changes. When systems use that old data and return it to potential customers, it can lead to a serious disconnect between the two. Such incidents frustrate customers.
It’s not just outdated data; a lack of structured data on sites also plays a role. Search engines and AI technology like clear, easy-to-find, and understandable information that supports brands. Without solid data, an AI might misrepresent brands or fail to keep up with changes. Schema markup is one option to help systems understand content and ensure it is properly represented.
Next up is consistency in branding. If your brand messaging is all over the place, this could confuse AI systems. The clearer you are, the better. Inconsistent messaging confuses AI and your customers, so it’s important to be consistent with your brand message on various platforms and outlets.
Different AI brand challenges
There are various ways AI failures can impact brands. AI tools and large language models collect information from sources and present it to build a representation of your brand. That means they can misrepresent your brand when the information they use is outdated or plain wrong. These errors can lead to a real disconnect between reality and what users see in the LLMs. It could also be that your brand doesn’t appear in AI search engines or LLMs for the terms you need to appear.
It would hurt the ASICS brand if it weren’t mentioned in results like this
At the other end, chatbots and virtual assistants talk to users directly. This is a different risk. If a chatbot gives inaccurate answers, this could lead to serious issues with users and the outside world. Since chatbots interact directly with users, inaccurate responses can quickly damage trust and harm a brand’s reputation.
Real-world examples
AI misrepresenting brands is not some far-off theory because it has an impact now. We’ve collected some real-world cases that show brands being affected by AI errors.
All of these cases show how various types of AI technology, from chatbots to LLMs, can misrepresent and thus hurt brands. The stakes can be high, ranging from misleading customers to ruining reputations. It’s good to read these examples to get a sense of how widespread these issues are. It might help you avoid similar mistakes and set up better strategies to manage your brand.
You read stories like this every week
Case 1: Air Canada’s chatbot dilemma
Case summary: Air Canada faced a significant issue when its AI chatbot misinformed a customer regarding bereavement fare policies. The chatbot, intended to streamline customer service, instead created confusion by providing outdated information.
Consequences: This erroneous advice led to the customer taking action against the airline, and a tribunal eventually ruled that Air Canada was liable for negligent misrepresentation. This case emphasized the importance of maintaining accurate, up-to-date databases for AI systems to draw upon, illustrating a major AI error in alignment between marketing and customer service that could be costly in terms of both reputation and finances.
Case 2: Meta & Character.AI’s deceptive AI therapists
Case summary: In Texas, AI chatbots, including those accessible via Meta and Character.AI, were marketed as competent therapists or psychologists, offering generic advice to children. This situation arose from AI errors in marketing and implementation.
Consequences: Authorities investigated the practice because they were concerned about privacy breaches and the ethical implications of promoting such sensitive services without proper oversight. The case highlights how AI can overpromise and underdeliver, causing legal challenges and reputational damage.
Sources: Details of the investigation can be found in The Times.
Case 3: FTC’s action on deceptive AI claims
Case summary: An online business was found to have falsely claimed its AI tools could enable users to earn substantial income, leading to significant financial deception.
Consequences: The fraudulent claims defrauded consumers by at least $25 million. This prompted legal action by the FTC and served as a stark example of how deceptive AI marketing practices can have severe legal and financial repercussions.
Sources: The full press release from the FTC can be found here.
Case 4: Unauthorized AI chatbots mimicking real people
Case summary: Character.AI faced criticism for deploying AI chatbots that mimicked real people, including deceased individuals, without consent.
Consequences: These actions caused emotional distress and sparked ethical debates regarding privacy violations and the boundaries of AI-driven mimicry.
Case 5: LLMs generating misleading financial predictions
Case summary: Large Language Models (LLMs) have occasionally produced misleading financial predictions, influencing potentially harmful investment decisions.
Consequences: Such errors highlight the importance of critical evaluation of AI-generated content in financial contexts, where inaccurate predictions can have wide-reaching economic impacts.
Sources: Find further discussion on these issues in the Promptfoo blog.
Case 6: Cursor’s AI customer support glitch
Case summary: Cursor, an AI-driven coding assistant by Anysphere, encountered issues when its customer support AI gave incorrect information. Users were logged out unexpectedly, and the AI incorrectly claimed it was due to a new login policy that didn’t exist. This is one of those famous hallucinations by AI.
Consequences: The misleading response led to cancellations and user unrest. The company’s co-founder admitted to the error on Reddit, citing a glitch. This case highlights the risks of excessive dependence on AI for customer support, stressing the need for human oversight and transparent communication.
Sources: For more details, see the Fortune article.
All of these cases show what AI misrepresentation can do to your brand. There is a real need to properly manage and monitor AI systems. Each example shows that it can have a big impact, from huge financial loss to spoiled reputations. Stories like these show how important it is to monitor what AI says about your brand and what it does in your name.
How to correct AI misrepresentation
It’s not easy to fix complex issues with your brand being misrepresented by AI chatbots or LLMs. If a chatbot tells a customer to do something nasty, you could be in big trouble. Legal protection should be a given, of course. Other than that, try these tips:
Use AI brand monitoring tools
Find and start using tools that monitor your brand in AI and LLMs. These tools can help you study how AI describes your brand across various platforms. They can identify inconsistencies and offer suggestions for corrections, so your brand message remains consistent and accurate at all times.
One example is Yoast SEO AI Brand Insights, which is a great tool for monitoring brand mentions in AI search engines and large language models like ChatGPT. Enter your brand name, and it will automatically run an audit. After that, you’ll get information on brand sentiment, keyword usage, and competitor performance. Yoast’s AI Visibility Score combines mentions, citations, sentiment, and rankings to form a reliable overview of your brand’s visibility in AI.
See how visible your brand is in AI search
Track mentions, sentiment, and AI visibility. With Yoast AI Brand Insights, you can start monitoring and growing your brand.
Optimize your content for inclusion in LLMs. Performing well in search engines is not a guarantee that you will also perform well in large language models. Make sure that your content is easy to read and accessible for AI bots. Build up your citations and mentions online. We’ve collected more tips on how to optimize for LLMs, including using the proposed llms.txt standard.
Get professional help
If nothing else, get professional help. Like we said, if you are dealing with complex brand issues or widespread misrepresentation, you should consult with professionals. Brand consultants and SEO experts can help fix misrepresentations and strengthen your brand’s online presence. Your legal team should also be kept in the loop.
Use SEO monitoring tools
Last but not least, don’t forget to use SEO monitoring tools. It goes without saying, but you should be using SEO tools like Moz, Semrush, or Ahrefs to track how well your brand is performing in search results. These tools provide analytics on your brand’s visibility and can help identify areas where AI might need better information or where structured data might enhance search performance.
Businesses of all types should actively manage how their brand is represented in AI systems. Carefully implementing these strategies helps minimize the risks of misrepresentation. In addition, it keeps a brand’s online presence consistent and helps build a more reliable reputation online and offline.
Conclusion to AI misrepresentation
AI misrepresentation is a real challenge for brands and businesses. It could harm your reputation and lead to serious financial and legal consequences. We’ve discussed a number of options brands have to fix how they appear in AI search engines and LLMs. Brands should start by proactively monitoring how they are represented in AI.
For one, that means regularly auditing your content to prevent errors from appearing in AI. Also, you should use tools like brand monitor platforms to manage and improve how your brand appears. If something goes wrong or you need instant help, consult with a specialist or outside experts. Last but not least, always make sure that your structured data is correct and aligns with the latest changes your brand has made.
Taking these steps reduces the risks of misrepresentation and enhances your brand’s overall visibility and trustworthiness. AI is moving ever more into our lives, so it’s important to ensure your brand is represented accurately and authentically. Accuracy is very important.
Keep a close eye on your brand. Use the strategies we’ve discussed to protect it from AI misrepresentation. This will ensure that your message comes across loud and clear.
http://dubadosolutions.com/wp-content/uploads/2017/05/dubado-logo-1.png00http://dubadosolutions.com/wp-content/uploads/2017/05/dubado-logo-1.png2025-09-15 08:46:152025-09-15 08:46:15When AI gets your brand wrong: Real examples and how to fix it