The bottom line: While AI-driven traffic currently represents less than 1% of overall website traffic, its quality and conversion potential are unprecedented. SEO software leader Ahrefs reports that despite accounting for less than 1% of their total traffic, visitors from AI platforms are their highest converting channel—with a conversion rate exceeding 10%. This document outlines a strategic framework to capitalize on this shift, moving beyond volume metrics to capture highly qualified, high-intent users at the final stages of their decision-making process.
Every marketing team I speak to has heard of Answer Engine Optimization (AEO), but most have no idea how to approach it strategically. They’re stuck in the same mindset that got them ranking in Google—and that’s a problem.
As Klaus-M. Schremser, co-founder of Otterly.AI, puts it:
“Today’s AI-search engines are answering machines rather than search engines. We have to take that into account in our optimization strategies for LLMs and GenAI.”
I wanted to develop this AEO strategy document to give marketing teams a clear, repeatable process for optimizing their brand’s presence within AI answer engines—not just for visibility, but for active recommendation and high-intent traffic.
Table of Contents
Why AEO Matters: The ROI Question
Let’s face it. You have limited marketing budget and a lot of channels competing for it. So why should AEO be a priority?
The TLDR version: AI traffic converts at rates that blow traditional channels out of the water.
While the volume is still small, the quality is unmatched. Here’s what we’re seeing:
- Ahrefs reports AI traffic as their highest converting channel, despite being less than 1% of total traffic, with conversion rates exceeding 10%.
- Users who click through from AI are more informed, have done their research, and are ready to make decisions.
- Early movers have a significant advantage—over 40% of AI professionals are exploring ways to optimize generative AI outputs, but most don’t have a strategy yet.
The shift is already happening. A study by Siege Media found that as AI answers more general questions, traffic to traditional “guide” and “how-to” content has plummeted by -34.7% and -88.3% respectively. AI is eating the top of the funnel. What’s left? High-intent, bottom-of-funnel traffic that’s ready to convert.
Understanding the Landscape: Mentions vs. Citations
Before we dive into strategy, it’s critical to understand the two primary forms of AI visibility—because they represent fundamentally different outcomes and require distinct optimization approaches.
Getting mentioned in LLMs
Mentions occur when a brand, product, or service is named in an AI-generated response without a direct, clickable link. This is a measure of brand recognition and recommendation by the AI itself.
Getting cited in LLMs
Citations, by contrast, are direct, clickable links to a webpage that the AI used as a source for its answer. Citations represent the new currency for driving high-intent traffic from AI.
Here’s the thing: mentions matter more than citations.
Research from BrightEdge shows that ChatGPT mentions brands 3.2 times more often than it cites them. From a user behavior perspective, users are guaranteed to read the AI’s direct answer (where mentions occur) but may not look at or click on the citations, which are often hidden or less prominent. Furthermore, mentions are more stable and less volatile than citations, providing a more consistent signal of brand trust and authority within the AI model.
What Drives Mentions and Citations?
Commercial queries are the primary drivers of both. The same BrightEdge study found that queries with commercial intent—using words like “best,” “deals,” “vs,” “alternatives”—drive 4-8 times more mentions than purely informational queries.
This insight is critical for content strategy. It reinforces the importance of bottom-of-funnel (BOFU) content in the AEO landscape—the same content types we’ve been pushing for years in our SEO-driven content marketing approach.
The 3-Pillar AEO Framework: Our Repeatable Process
At Digital Elevator, we’ve developed a proprietary, outcome-oriented 3-step process for building a defensible AEO strategy. The framework is built around the three fundamental ways that AI models determine brand visibility: through owned content, earned validation, and amplified authority signals.
We call it the 3 P’s: Presence, Prominence, and Propagation.
Pillar 1: Presence (Owned Media Strategy)
Goal: Establish your website as the definitive, authoritative source of truth for your products, services, and market category—directly influencing the information LLMs use.
Why Owned Content Matters
For factual, objective questions, AI models show a strong preference for first-party content. A Yext study of 6.8 million citations found that brand websites were the dominant source (over 40%) for all major AI models when answering objective, unbranded queries.
But here’s where it gets interesting: traditional SEO fundamentals still matter for AEO.
A recent study by Seer Interactive demonstrated a strong correlation (0.65) between organic search ranking and LLM mentions. This means that traditional SEO factors—particularly organic visibility—directly influence AI visibility. Backlinks, however, were found to be relatively neutral and not as relevant.
The Bottom-of-Funnel (BOFU) Shift
AI is accelerating a market shift away from broad, top-of-funnel content. The Siege Media study I mentioned earlier found that as AI answers more general questions, traffic to traditional “guide” and “how-to” content has plummeted. Users who click through are now more informed and have specific, high-intent, BOFU questions.
This is exactly the type of content we’ve been creating for our clients for years—”best,” “vs,” “pricing,” “alternatives” content mixed with strong UI and clear calls-to-action.
Actionable Steps for Pillar 1:
1. Build Your Brand Authority Repository
Create a centralized, internally-validated repository of all critical information about your brand. This serves as the single source of truth that informs all content creation and ensures consistency across platforms.
This repository must include:
- Detailed product/service capabilities and key differentiators
- Crucially, a focus on BOFU content: Pricing, detailed comparisons (“vs”), alternatives, integrations, compliance, and support details
- Ideal Customer Profile (ICP) fit and specific, niche use cases
- Proprietary data, case studies, and unique insights that cannot be replicated by AI summaries
2. Execute a BOFU-Centric Content Strategy
Based on the principles from the Graphite guide and the OtterlyAI research, create dedicated pages or enhance existing ones to target clusters of high-intent questions. Here are six key optimization principles for owned content:
- Deliver Meaningful Value, Not Fluff: Prioritize expertise and specificity. Add unique insights, original research, or frameworks. Support content with data and credible sources.
- Answer Search Intent Quickly and Clearly: Use summary boxes or TL;DR sections. Provide direct answers to common questions. Avoid burying key insights below the fold.
- Structure Content for Semantic Parsing: Use clear headings (H2/H3) to delineate sections. Follow logical, hierarchical content flow. Include lists, tables, and callouts to break up text.
- Align Content to Natural Language Queries: Use headings that match user questions (e.g., “What is [Product] pricing?”). Embed concise, relevant answers right below. Avoid keyword stuffing—focus on relevance and clarity.
- Increase Originality and Authority: Cite your own data or case studies. Include expert commentary or author bios. Build domain authority with internal linking and topical consistency.
- Optimize Existing Content at Scale: Refresh outdated information. Add missing sections that answer emerging queries. Consolidate thin pages into robust, evergreen resources.
Prioritize “Product Questions”—queries that are likely to result in a product recommendation. Structure content to directly answer these questions in a clear, concise, and easily parsable format for LLMs. Go beyond simple summaries and provide expert-level detail, proprietary data, and unique workflows that an AI cannot replicate.
3. Implement Foundational Technical Best Practices
While extensive technical AEO is not recommended, ensure content is easily crawlable, structured, and semantically rich. Use schema markup where appropriate to clearly define entities and relationships. Maintain strong traditional SEO fundamentals, as organic ranking directly correlates with LLM mentions.
4. Leverage E-E-A-T Signals
AI systems like ChatGPT and Google’s Search Generative Experience (SGE) rely on citations and authority signals to curate trustworthy results. Google has made clear that Experience, Expertise, Authoritativeness, and Trust (E-E-A-T) continue to influence content ranking—now also in the generative layer.
Content that is well-linked internally and externally, features clear authorship and expertise, and provides up-to-date, comprehensive answers is far more likely to be quoted or recommended by AI systems.
Pillar 2: Prominence (Earned Media Strategy)
Goal: Ensure your brand is prominently featured and validated by the third-party sources that AI models trust for subjective and opinion-based queries.
Why Third-Party Validation Matters
When queries become subjective (e.g., “What is the best…?”), AI models shift their reliance to third-party directories and industry-specific sources to gauge consensus and authority.
Understanding where LLMs get their training data helps inform where to focus earned media efforts. Large language models are trained on vast datasets that include Common Crawl (60%), WebText2 (22%), Books (16%), and Wikipedia (3%). Additionally, OpenAI has partnerships with news sites and has licensed Reddit’s user-generated content for LLM training.
Actionable Steps for Pillar 2:
1. Master General Directories
For subjective queries on OpenAI’s ChatGPT, third-party directories are a primary source, peaking at 46.3% for branded subjective questions. Ensure profiles on major platforms are complete, accurate, and consistent with your brand’s authority repository. This includes maintaining up-to-date information on pricing, features, integrations, and customer reviews.
2. Dominate Industry-Specific Platforms
For models like Perplexity, industry-specific directories are key. These niche platforms account for 24% of citations for unbranded subjective queries. Identify and optimize presence on the most authoritative review sites and platforms in your vertical. Actively manage reviews and engage with user feedback to signal ongoing authority and responsiveness.
3. Execute Citation Optimization
Identify the most frequently cited URLs for your target AEO topics and develop a strategy to get your brand mentioned within that content. This is the core of an “earned” AEO strategy.
Use tools that analyze citation sources (based on Perplexity’s “Sources” tab, Google’s SGE snippets, or ChatGPT’s browsing references) to reverse-engineer visibility. This approach allows you to:
- Identify content currently cited in AI results
- Spot thematic or structural patterns across cited pages
- Compare converting vs. non-converting content from AI-driven traffic
- Map gaps and opportunities for content creation and optimization
4. Secure Wikipedia Presence
Wikipedia is not only a 5x boosted source in LLM training data, but it is also frequently cited by AI models for factual information. For brands that meet Wikipedia’s notability guidelines, establishing and maintaining a well-sourced Wikipedia page is a high-value earned media tactic.
Pillar 3: Propagation (Off-Page Amplification)
Goal: Amplify the signals of trust and authority around owned and earned assets, creating a feedback loop that reinforces your brand’s position within the AI ecosystem.
While direct content is crucial, AI models also weigh broader signals of authority and public discourse. This pillar focuses on influencing the wider web to reinforce the narratives established in Pillars 1 and 2.
Actionable Steps for Pillar 3:
1. Strategic Public Relations
Target PR efforts to secure mentions and links from high-authority news outlets and publications that are frequently cited by AI models. Given that OpenAI has partnerships with news sites and that news content is part of LLM training data, securing coverage in these outlets has a dual benefit: immediate visibility and long-term influence on model training.
2. Community Marketing and Social Validation
Foster conversations and user-generated content on social platforms that validate your brand’s key differentiators and market position. While forums like Reddit account for a small percentage of citations in location-based queries (~2%), they are still valuable for brand commentary and narrative shaping.
Importantly, Reddit’s user-generated content has been licensed for LLM training, making authentic community engagement a long-term investment in AI visibility. Encourage forum participation and thought leadership in relevant online communities. The goal is not just immediate visibility, but to influence the broader corpus of content that AI models learn from.
3. Targeted Advertising
Use paid channels to amplify your best-performing BOFU content, driving user engagement and signaling to AI models that this content is valuable and relevant. While advertising does not directly influence LLM training, it can drive traffic and engagement signals that indirectly boost content authority and visibility.
Next Steps: How to Get Started with AEO
The transition to an AEO-centric world is inevitable, and early movers have a significant advantage. Research shows that over 40% of AI professionals are currently exploring ways to optimize generative AI outputs, but most don’t have a strategy yet.
The strategic imperative is to act now to build a defensible position before the space becomes saturated.
Here’s how to get started:
1. Audit Your Current AEO Footprint
Begin by identifying the most important “Product Questions” and commercial-intent queries for your brand. Use tools that analyze citation sources to understand where your brand currently appears (or doesn’t) in AI-generated responses.
2. Initiate the Brand Authority Repository
Assemble the cross-functional team required to build and validate this central repository of information. This should include product, marketing, sales, and customer success teams to ensure comprehensive and accurate information.
3. Prioritize BOFU Content Creation
Analyze existing content for gaps and create a roadmap for developing the high-intent, comparison, and detail-oriented content that succeeds in the AEO landscape. Focus on content that provides a level of detail and expertise that a general AI summary cannot replicate.
4. Strengthen SEO Fundamentals
Given the strong correlation between organic ranking and LLM mentions, ensure that traditional SEO best practices are in place. This includes technical SEO, on-page optimization, and building domain authority through internal linking and topical consistency.
5. Reverse-Engineer Competitor Visibility
Analyze which competitors are being cited or mentioned in AI responses for target queries. Identify the patterns and sources that drive their visibility, and develop a strategy to match or exceed their presence.
Should You Go In-House or Use an Agency for AEO?
The decision of whether to handle your AEO strategy in-house or hire an agency is a complex one. There are a number of factors to consider, such as your budget, your in-house expertise, and your desired level of control.
If you have a large budget and a team of experienced SEO and content professionals who understand the nuances of AI optimization, you may be able to handle your AEO in-house. However, if you have a limited budget or in-house expertise, you may want to consider hiring an agency for AEO services.
An agency can provide you with several benefits, such as access to expert AEO professionals, access to specialized tools and resources, and a proven track record of success in both traditional SEO and emerging AI channels.
There’s also an opportunity cost to consider. The time it takes to get something to market matters. If an agency can take your AEO strategy to market in half the time it takes an in-house team, consider the impact that can have on your business. Those potentially untapped leads will be further along your sales cycle, and the ROI from investing in an agency will have a significant business impact compared to trying to save money using an in-house team that has a different focus.
As you plan ahead or are getting AEO budgets together, consider the opportunity cost of not launching campaigns quickly and effectively.
References
Graphite. (2025). Ultimate Guide to AEO (Answer Engine Optimization). https://graphite.io/five-percent/aeo-is-the-new-seo
Ahrefs. (2025). AI Traffic Has Increased 9.7x in the Past Year. https://ahrefs.com/blog/ai-traffic-increase/
Yext. (2025). AI Citations, User Locations, & Query Context. https://www.yext.com/research/article/ai-citations-user-locations-query-context#introduction
Conductor. (2025). AI Search Explained: Citations, Mentions & SEO Impact. https://www.conductor.com/academy/ai-search/
BrightEdge. (2025). ChatGPT Brand Mentions vs. Citations: What Triggers Visibility. https://www.brightedge.com/resources/weekly-ai-search-insights/chatgpt-brand-mentions-vs-citations-what-triggers-visibility
Siege Media. (2025). The Clear, Accelerating Shift Toward Bottom-of-Funnel Content. https://www.siegemedia.com/research/blog-ai-content-shift
Seer Interactive (2025). STUDY: What Drives Brand Mentions in AI Answers?
https://www.seerinteractive.com/insights/what-drives-brand-mentions-in-ai-answers
Otterly.AI. (2025). Generative Engine Optimization (GEO) Guide: How to Win in AI Search. https://otterly.ai
