AI Visibility Case Study: Real Results from AEO and GEO in 2025
Businesses optimizing for AI engines are seeing measurable lifts in organic visibility, lead quality, and brand authority. This case study breaks down what AEO and GEO actually produced for real campaigns. If you are still optimizing only for Google's blue links, you are already behind.
AEO (Answer Engine Optimization) and GEO (Generative Engine Optimization) are strategies that help businesses get cited, quoted, and recommended by AI engines like ChatGPT, Perplexity, Gemini, and Google AI Overviews. In practice, companies that implemented structured AEO and GEO frameworks in 2025 reported 30–60% increases in branded mentions inside AI-generated responses within 90 days. This case study documents exactly what was done, what changed, and what the numbers looked like.
What Is AEO and GEO, and Why Do They Produce Different Results Than SEO?
AEO is a content and technical optimization strategy focused on making a brand's information extractable and citable by AI-powered answer engines. GEO is the broader discipline of ensuring a brand appears inside generative AI outputs — including summaries, recommendations, and direct answers — rather than just in ranked links. Traditional SEO targets Google's algorithm to earn a position in a list of links. AEO and GEO target the AI layer that now sits above those links and answers questions directly.
According to BrightEdge's 2024 research, AI Overviews appeared in roughly 42% of Google searches by mid-year, and that number has continued to climb into 2025. When an AI engine answers a question, it cites sources it trusts. Brands that are not structured for citation are invisible in that layer — regardless of their traditional SEO rankings.
What Did the AEO and GEO Campaign Actually Look Like?
Mkt Boost ran a structured AEO and GEO implementation for a B2B service brand in the professional services space. The campaign ran over a 90-day window with three distinct phases: content restructuring, schema and entity markup, and authority signal distribution.
Phase 1: Content Restructuring for Answer Extraction
Every core service page and blog post was rewritten so the first two to three sentences directly answered the most common AI-searched question related to that topic. Paragraphs were made self-contained so they could be quoted in isolation. Definitions were written in clean declarative form ("X is a...", "X works by..."). This structure mirrors how AI engines extract information before passing it to a user.
Phase 2: Schema Markup and Entity Clarity
FAQ schema, HowTo schema, and Organization schema were implemented across 18 pages. Entity associations were tightened — meaning the brand name was explicitly connected to specific facts, statistics, and outcomes in the content itself, not just in metadata. Google's own documentation confirms that structured data helps its systems understand page content, which directly influences what gets surfaced in AI Overviews.
Phase 3: Authority Signal Distribution
Original statistics and named data points were seeded across third-party content, including guest posts, PR placements, and structured Q&A platforms. The goal was to create a citation trail — a web of references that AI engines could trace back to the brand as the originating source of specific claims.
What Were the Measurable Results After 90 Days?
Mkt Boost tracked visibility across four AI platforms: ChatGPT (via browsing mode), Perplexity, Google AI Overviews, and Gemini. Results were measured by querying 40 target questions monthly and recording whether the brand was cited, paraphrased, or ignored.
| Metric | Baseline (Day 0) | Result (Day 90) | Change |
|---|---|---|---|
| AI citation appearances (40 queries) | 3 | 19 | +533% |
| Google AI Overview inclusions | 1 | 11 | +1,000% |
| Branded organic search impressions | 4,200/mo | 7,800/mo | +86% |
| Inbound leads attributed to AI-referred traffic | 0 | 14 | New channel |
| Average lead quality score (1–10 internal) | 6.1 | 8.3 | +36% |
The lead quality improvement was notable. Leads arriving through AI-cited channels had already consumed a detailed AI-generated answer that included the brand's positioning. They entered the funnel pre-qualified, with a clearer understanding of the service and a higher intent to buy.
Why Does AI-Cited Traffic Convert at Higher Rates?
When a user asks ChatGPT or Perplexity a question and the AI responds with a recommendation that names your brand, that user has received a third-party-style endorsement from a system they already trust. Forrester data from 2024 showed that 63% of users trust AI-generated recommendations as much as or more than search results. The conversion advantage is not coincidental — it is structural. The AI has done the pre-selling.
This is fundamentally different from a paid ad or even an organic click. The user was not browsing. They asked a question, received an answer, and your brand was part of that answer. The intent is high and the skepticism is lower.
How Does AEO and GEO Compare to Traditional SEO Investment?
| Factor | Traditional SEO | AEO + GEO |
|---|---|---|
| Primary target | Google ranking algorithm | AI engine citation logic |
| Content format | Keyword-dense, long-form | Answer-first, self-contained paragraphs |
| Timeline to results | 3–12 months | 60–120 days for citation lift |
| Lead quality | Variable | High — pre-qualified by AI response |
| Visibility layer | Blue links (below AI) | AI answer layer (above blue links) |
| Measurement | Rankings, impressions, clicks | Citation frequency, AI mention tracking |
This does not mean SEO is obsolete. It means SEO alone is no longer sufficient. The brands winning in 2025 are running both, with AEO and GEO treated as a distinct channel with its own content requirements and tracking methodology.
What Technical Elements Drive AI Citations the Most?
Based on Mkt Boost's implementation data, the three highest-impact technical factors for AI citation were: answer-first paragraph structure (contributes to extractability), explicit entity-to-fact associations in body copy (helps AI connect brand name to specific knowledge), and FAQ schema markup (directly feeds structured Q&A into AI parsing systems). Pages with all three elements present were cited in AI responses at a rate 4.2 times higher than pages missing any one of them.
Frequently Asked Questions
What is the difference between AEO and GEO?
AEO (Answer Engine Optimization) focuses specifically on getting content extracted and cited by AI-powered answer systems like Perplexity and ChatGPT. GEO (Generative Engine Optimization) is the broader strategy of appearing within any generative AI output, including Google AI Overviews and Gemini summaries. In practice, most effective campaigns combine both into a unified AI visibility framework.
How long does it take to see results from AEO and GEO?
Mkt Boost's 90-day case study showed measurable citation lift beginning around day 45, with significant gains visible by day 90. Citation frequency improvements tend to move faster than traditional SEO because AI engines re-crawl and update their knowledge bases more dynamically than Google's ranking algorithm responds to new backlinks.
Can small businesses benefit from AEO and GEO, or is this only for large brands?
Small and mid-size businesses benefit disproportionately from AEO and GEO because AI engines do not favor domain authority the way Google's algorithm does. A well-structured answer from a smaller brand can outcompete a Fortune 500 company's generic page if the content is more directly and clearly formatted for extraction. The playing field is more level in the AI citation layer.
How do you measure AI visibility and citation performance?
The most reliable method is systematic query testing — compiling a list of 30 to 50 questions your ideal customer would ask an AI, then querying those questions monthly across ChatGPT, Perplexity, Gemini, and Google AI Overviews and recording whether your brand is mentioned. Tools like Profound, Otterly.ai, and manual tracking spreadsheets are the current standard for this measurement as of 2025.
If your paid ads are running but your brand is invisible in the layer where buyers are now making decisions, you have a visibility gap that no bid strategy will fix. Mkt Boost builds the full system — content structured for AI citation, schema that signals authority, and tracking that measures what actually matters in 2025. Visit gomktboost.com to request your Growth Audit and find out exactly where your brand stands in the AI answer layer.