What is Answer Engine Optimization (AEO)?

Search isn’t what it used to be. 

What began as keyword-matching across blue links has transformed into real-time, AI-generated conversations. 

Tools like ChatGPT, Gemini, and Perplexity don’t just link you to answers, they give you the answer right there in a conversational interface. If it’s not precise enough, you ask a follow up question with more details, and it gives you a better answer. Maybe you’ll click a source or two. Maybe not. 

This marks a fundamental shift in how people discover, research, and choose brands.

This change is seismic for marketers, what we’ve lovely called The New Frontier of organic growth. It means the traditional SEO game (ranking #1 for a high-volume keyword) no longer guarantees attention nor influence nor conversion. The query isn’t a simple query anymore. It’s a conversation. 

The playing field has changed, and so has the scorecard.

The Emergence of Answer Engine Optimization (AEO)

Enter Answer Engine Optimization (AEO). 

This isn’t just a buzzword at this point (though it does go by a few names, none universally agreed upon – generative engine optimization, or GEO, is a strong contender). It’s a strategic necessity and a shift in our existing paradigm. 

AEO is about ensuring your brand becomes part of the answer in conversational search and generative outputs. 

Sometimes the model gives citations. Sometimes not. Sometimes your brand is mentioned. Often, it isn’t. And that’s the point: visibility today isn’t earned just through rankings (though perhaps confusingly, sometimes rankings do correlate with visibility), it’s earned through presence across the ecosystem where answers are formed.

As more and more users adopt AI tools, and as massive platforms like Google roll out AI products like AI Overviews and AI Mode to the masses, this will become the emergent and largest surface area for information and brand discovery. Well respected agencies like Omniscient Digital, Growth Plays, OGM, and iPullRank are currently helping brands capture this opportunity and drive visibility and revenue through LLMs.

Defining Answer Engine Optimization (AEO)

What is AEO?

Answer Engine Optimization (AEO) is the process of making your brand, content, and message visible in the answer layer of AI-powered tools and conversational interfaces. 

Unlike traditional SEO that competes for rankings in search engine result pages (SERPs), AEO competes for mindshare inside generative model responses.

Imagine a query like “best SEO agencies.” In the past paradigm, you’d compete for the number one spot, almost always beneath several paid placements, and you’d have a finite and predictable number of clicks, conversions, and business from this query:

And you could sort of game this with enough on-page SEO expertise and backlink operations.

Not as simple in AI answers, as they aggregate information across a ton of training data as well as sources (using retrieval augmented generation), which doesn’t rely on backlinks as a proxy for authority, and highly specific answer delivery, which begets personalized content and answers as opposed to thorough and comprehensive pages like in the past SEO world. 

Compare this with a query in ChatGPT, which often resembles a long tail and highly personalized confession (as opposed to a 2-3 word head keyword). Instead, someone may write, “I’m looking for the best SEO agencies,” but then follow up with more information about their company size, needs, and decision criteria. See below:

You can see there’s myriad sources and each link is likely a predictive variable given the prompt and context, as well as a summary of sorts of the compiled sources. Omnipresence, or ubiquity, within a category (as well as specific messaging) is more important than a single data point of ranking a page. 

The Importance of AEO

LLMs are changing how discovery happens. Whether it’s a consumer asking ChatGPT about the best CRM or a VP of Marketing browsing Perplexity for product alternatives, the goal is the same: be the trusted answer.

If you want to show up, you need:

• Specific, expert-backed content
• Frequent and credible brand mentions across authoritative sources
• Structure and clarity that LLMs can easily digest
  

AEO vs. Traditional SEO

Key Differences

Traditional SEO	Answer Engine Optimization (AEO)
Ranks pages in search results	Inserts answers directly into model outputs
Click-through is the goal	Presence and citation are the goal
Relies on backlinks and keywords	Relies on mentions, context, and citation patterns
Content designed for human readers and bots	Content designed for humans, bots, and LLMs

Complementary Strategies

Traditional SEO isn’t dead. 

In fact, it often complements AEO. Strong SEO infrastructure (site speed, structured data, on-page clarity) feeds LLMs the clean inputs they need. 

But you must layer AEO on top, thinking beyond your domain and into the full ecosystem where people seek answers.

The Rise of Answer Engines

Understanding Answer Engines

Answer engines are AI-powered systems that retrieve, summarize, and synthesize responses in real time. Some are static (trained on historical data), while others like RAG systems fetch fresh content from the web.

Examples

• ChatGPT
• Claude
• Perplexity
• Google AI Overviews (and AI Mode)
• Voice assistants (Siri, Alexa, Google Assistant)

These tools are shaping discovery. The engine itself might not be the final step in the journey, but it sets the path, and often shapes perception before someone ever visits your website or clicks “request a demo.” 

Impact on User Behavior

Users expect immediate, accurate, credible answers. The days of hopping between 10 tabs are giving way to getting a confident response from one trusted source. If your brand isn’t in that first answer, you may be invisible. And we all know how important it is to be present in the day 1 consideration set. 

Why AEO Matters for Marketing Leaders

From Surround Sound SEO to AEO

Before we had a term like Answer Engine Optimization, we had a concept rooted in behavior: Surround Sound SEO. 

Born out of performance experiments at HubSpot, the idea was simple: appear in every credible place your audience checks during the research phase. When someone googled “best CRM software,” they weren’t looking for one blog post. They were building a mental shortlist.

If your brand showed up once, maybe they gave you a look. Showed up twice? Now you’re familiar. Showed up in every review, listicle, forum, podcast, and aggregator? You became the obvious choice.

That approach became a system. We deployed it repeatedly at Omniscient, with consistent success. It was never about SEO hacks. It was about salience. Credibility. Omnipresence.

And as the locus of discovery shifts from search engines to answer engines, the concept evolves but the principle remains: to be chosen, you must be seen, repeatedly and credibly, where people (and models) go to make decisions.

Mentions > Links

In traditional SEO, backlinks were the coin of the realm. Today, especially with LLMs, the more influential currency is brand mentions, specifically on sources these models trust and index heavily. Think:

• Reddit
• G2
• TrustRadius
• YouTube
• Podcasts
• Hacker News
• Wikipedia
• High-authority editorial sites

Mentions in these environments, especially when repeated, consistent, and credible, build the connective tissue that tells a language model, “this brand matters.”

You no longer need to rank #1. You need to show up in the answer layer. Not just once, but across the full surface area of influence. This is the new digital salience. And it’s won through credibility, not contrivance.

Changing Consumer Expectations

AI tools are rewiring behavior. 

Buyers are more informed, more impatient, and more conversational. 

They’re asking rich, contextual questions like, “What’s the best project management tool for a 12-person remote design agency that needs Notion integration and hates Gantt charts?”

If your content doesn’t speak that language (the long tail, descriptive, messy language of real prospects and customers), you’re losing opportunities. 

Generic content no longer has marginal value in a world where consensus can be summarized and delivered instantly. 

Enhanced Brand Visibility

AEO is about omnipresence. 

The more often your brand appears across third-party sites, forums, podcasts, Reddit threads, comparison articles, and review platforms, the more likely you’ll be included in an AI-generated answer. Ubiquity creates credibility. 

This stuff is hard to fake. A good, simple rule of thumb is that if people aren’t recommending you naturally, it’s going to be an uphill battle to get LLMs to recommend you (not that there aren’t strategies and tactics). Ultimately, the fundamentals of product quality, product / market fit, product marketing and messaging, and brand marketing apply here. 

Competitive Advantage

Most brands are still playing the 2021 SEO game with 2025 rules. 

They’re chasing search volume instead of relevance. They’re still stack ranking keyword lists from Ahrefs by search volume and using Clearscope to produce median value content with no differentiation. 

AEO is still an underexploited frontier: first movers have the chance to build durable, compounding visibility.

The best time to start on this is today. 

Implementing AEO Strategies

Understand How LLMs Find and Present Information

Before you optimize, you need to grasp how LLMs work. Most either pull from their training data or actively retrieve content from the live web. If you’re not present in one of those datasets, or not mentioned in the right context, you’re not getting surfaced.

Key takeaway? Presence and precision matter. Especially on:

• High-authority domains (Wikipedia, Reddit, G2, YouTube, podcasts, etc.)
• Sources with semantic similarity to your target queries

You can identify commonly cited sources using one of the several dozen GEO tools to launch the past few months, like Peec.ai or Geostar. 

Identify High-Context Questions Your ICP Is Asking

Forget chasing broad, high-volume keywords. AEO is about precision. Mine voice-of-customer data, customer calls, forums, and social media to surface the real questions your audience asks, rich with context, urgency, and specificity.

Examples:

• “What’s the best project management tool for remote agencies that hate Gantt charts?”
• “Which CRMs have the best Notion integrations and strong email support?”

These aren’t traditional search queries. They’re conversation starters. Your content should speak directly to them.

Get on a call with your customers. Do traditional customer research. It’s more important than ever. 

Create Expert-Led, High-Fidelity Content

Generic content won’t cut it. LLMs reward content that is:

• Expert-authored or cited
• Rich in proprietary data or real examples
• Written clearly and fluently

Research in 2024 came out that showed exactly these things worked to move the needle on visibility in LLMs. Basically, highly credible, well structured content that answered specific questions. 

Think less “Ultimate Guide,” more “field note from someone who’s done it.” That’s what makes your content citation-worthy.

Build Presence Where It Matters

Use tools like Peec.ai or Profound to audit your visibility and find the sources LLMs already cite. If you’re not on those domains, get there. Guest posts, PR, influencer collaborations, product reviews – heck, possibly even acquire a content site that is heavily present in your topic surface area – treat these mentions like the new backlinks.

Remember: you don’t need to rank #1 in LLM land (though it obviously still helps in SEO land, which is not dead, and is still a massive business driver). 

You need to show up where the conversation happens.

Optimize Site Structure and Metadata

AEO still respects good technical hygiene:

• Use structured data/schema to clarify context
• Write clean, readable content with clear H1s, summaries, and FAQs
• Ensure your site is crawlable and fast

ChatGPT can’t read javascript, so there are some technical GEO aspects that matter, but mostly on the margin. LLMs.txt is a new tactic that seems to be popping up, but through a few small experiments, we’ve not seen much of an impact. 

Treat your website like a book, not a brochure. It should have logical chapters, intuitive navigation, and thematic depth.

Measuring AEO Success

Embrace the Imperfection

Here’s the truth: measuring AEO isn’t as cut-and-dried as traditional SEO. We don’t have clear query volumes, keyword positions, or predictable click-through rates. But that doesn’t mean you can’t track progress. It just requires a new mental model.

As with any emerging paradigm, it’s about triangulating multiple signals, not obsessing over a single number.

A Three-Layer Visibility Framework

1. Self-Reported Attribution
   
   • Ask directly: “Where did you hear about us?”
   • Look for language like “saw you in ChatGPT,” “Perplexity mentioned you,” or even just “someone recommended you.”
   • Follow up on sales calls to validate patterns.

Currently, we find self reported attribution to be the highest signal for actual value created and captured from these channels and we recommend the majority of our clients implement it.

2. Referral Traffic from AI Engines
   
   • While imperfect, GA4 and Looker Studio can still show you:
     • Incoming traffic from sites like Perplexity.ai, phind.com, or links embedded in ChatGPT Plus (via Bing).
     • Platform-specific dashboards (e.g., Peec.ai) that provide visibility snapshots.

These charts are functionally very simple to set up and show a good story with rising LLM traffic trends:

3. Prompt-Based Audits
   
   • Use tools like Peec.ai or Otterly to track visibility against high-intent prompts.
   • Prioritize prompts that match your ICP’s language.
   • Reverse-engineer the citations. If you’re not included, which source is?

Conversion Rate as a Signal

Generative AI visitors often convert at higher rates. They’re already informed. They’re high-intent. One client’s data showed LLM visitors converting at nearly 3x the rate of traditional search. That’s not coincidence, it’s because they are doing their own qualification via context and conversation, away from the traditional telemetry of website clicks.

Don’t Overlook Downstream Metrics

Track what happens after the visit:

• Time on site
• Pages viewed
• Form submissions
• Pipeline attribution

If AI is the front door, your site is still the living room. Make sure visitors want to stay.

Watch for Early Warning Signs

• Drops in AI visibility may precede traffic (or lead) declines
• Shifts in prompt relevance could signal competitive messaging changes
• Frequent hallucinations might mean your content isn’t credible or specific enough, or it isn’t appropriately consistent and consolidated across cited sources. Say hello to your product marketing and brand teams! 

Build for the Long Run

Avoid the temptation to game the models. Hacks like prompt-stuffing or reinforcement-learning tricks are ephemeral. Models update. Contrivance fades. But credibility, earned media, and useful content? That sticks.

As Taleb might say: build for antifragility.

Challenges and Considerations with AEO

The Playbook Is Evolving in Real Time

Let’s just get this out of the way: no one has it all figured out. Not you. Not me. Not even the loudest “experts” on LinkedIn.

The smartest folks in the room are working from first principles, running small experiments, iterating fast, and staying humble. AEO isn’t static. LLMs are not only opaque, they’re constantly evolving. Their interfaces, retrieval mechanisms, reinforcement training, and weighting of sources change without notice.

What worked last month might not work today. That doesn’t mean you stop. It means you lean on first principles and logical thinking, early patterns and data, and experimentations. And adapt.

The Credibility Conundrum

We’ve entered the “Revenge of the Long Tail” era, where specificity trumps scale. Generic content dies in this environment.

What shows up in LLM outputs?

• Citable sources
• Independent brand mentions
• Podcasts, Reddit threads, YouTube reviews
• Expert opinions, proprietary data, firsthand narratives
  

Hacks and contrived content might get short-term wins, but they don’t last. One brand we know tried prompt-engineering its name into ChatGPT outputs, attempting to hack the reinforcement learning component of ChatGPT. It worked… until the next model update wiped them off the map.

It may be easier now to simply BE credible than to try to fake it and hack it. 

The Attribution Problem

Measuring AEO is messy. Not all value can be tracked, and that’s okay. If your mindset is, “We won’t do it unless we can measure it precisely,” you’ll always be trailing the pack.

Instead:

• Lean on proxy signals (mentions, visibility snapshots, self-reported data)
• Combine quant with qual (GA4 data meets sales call anecdotes)
• Focus on patterns, not perfect causality

Hallucinations, Bias, and Model Limitations

Even the best models still hallucinate. They invent sources, fabricate features, and miss nuance. LLMs aren’t arbiters of truth, they’re reflectors of available information and are predictive in nature. If your brand doesn’t show up, it’s not because you’re irrelevant, it’s because the models haven’t seen enough consistent signals.

There’s also bias. Models are shaped by training data, which means well-funded, frequently mentioned brands often dominate visibility. David-vs-Goliath is still possible, but it takes hustle, precision, and omnipresence.

The Temptation to Game the System

There will always be shortcuts. Prompt-hacking. LLMs.txt. Reinforcement learning feedback loops. You can manipulate the system…for a while. But you’re building sandcastles.

The brands that win in the long term are the ones doing the hard stuff:

• Building signal-rich ecosystems
• Becoming part of the conversation across credible platforms
• Earning citations through value, not manipulation

Embrace the Chaos (and the Opportunity)

Every tectonic shift in marketing creates opportunity. AEO is no different. We’re not just optimizing content for an A+ on Clearscope, we’re architecting presence in an entirely new discovery layer.

You don’t need to chase every trend or wait for perfect data. Start by being useful. Be specific. Be credible. Show up where your audience already looks for answers, and where LLMs look to build them.

The old rules are fading. The new ones are still being written. That’s where the leverage is.

Conclusion

Answer Engine Optimization isn’t just a new acronym. It’s a new mindset. One that reflects the evolving nature of how people search, how machines synthesize, and how brands must adapt.

We’re moving from optimizing for rankings to optimizing for relevance. From chasing keywords to earning mentions. From trying to reverse-engineer algorithms to building a credible, omnipresent brand that’s too useful, too cited, too real to ignore.

And while the tactics are still forming, the principles are timeless:

• Show up in the conversations that matter
• Be cited across the platforms that feed the models
• Create specific, high-fidelity content that reflects actual expertise

If you’re a marketing leader, here’s your call to action:

• Audit your presence across trusted, LLM-indexed sources
• Identify the high-context prompts your audience is actually asking
  Build a system that favors long-term credibility over short-term hacks
• Track what matters, even if it’s imperfect
• Stay humble, stay curious, and stay in motion

This is your opportunity to get ahead of the curve, to shape how your brand appears in the answer layer of the internet, and to win in a world that favors substance, not shortcuts.

So here’s to doing the real work.

Onward.