Generative Engine Optimization Case Studies

• Go Fish Digital reports that a three-month GEO strategy produced a 43% rise in monthly AI-driven traffic from ChatGPT and other referral sources, plus an 83.33% lift in monthly conversions from AI…
• An AI mention is a brand name that appears inside a generated answer.
• Answer-first sections, explicit entity names, comparison pages, short summaries near the top, author attribution, and third-party mentions are the tactics most often named in these case studies.
• Published GEO case studies carry several biases.
• Case studies report results from ChatGPT, Perplexity, Google AI Overviews, Google AI Mode, Gemini, and Copilot, but they rarely disclose the prompts or sampling used.

Go Fish Digital reports that a three-month GEO strategy produced a 43% rise in monthly AI-driven traffic from ChatGPT and other referral sources, plus an 83.33% lift in monthly conversions from AI referrals (Go Fish Digital). The same firm says AI-driven leads converted at 25 times the rate of traditional search leads. Those are useful numbers, but they come from one agency's own client work, with no published control group. Other case studies report AI Overview counts, mentions, or sales-qualified leads on different timelines. Treat each figure as a claim by its author, scoped to that author's client set and window, rather than as a general benchmark.

Each row is the author's own reported result. None of the three publishes a control group.

An AI mention is a brand name that appears inside a generated answer. A citation is a link or source attribution that points to a specific URL. A recommendation is an answer that tells a user to choose a particular brand. An AI referral is a session that arrives in analytics from an answer engine domain. These four layers can move independently of one another. For example, a brand can be mentioned in an answer without being linked, and a page can be cited without producing a single referral visit. Case studies that blend these layers into one headline metric make cross-study comparison impossible. Specifically, each layer needs its own tracking:

• its own prompt set
• its own log source
• its own reporting line

Tracking each layer separately gives teams a clearer picture of which outcome their content actually produced.

No. According to Copylume, Ahrefs found that only 12% of URLs cited by ChatGPT, Gemini, and Copilot also ranked in Google's top 10 for the original prompt (Copylume). However, that gap means classic rankings and AI citations are partly separate outcomes.

Google states there are no special technical requirements for appearing in AI Overviews or AI Mode beyond normal Search eligibility and SEO fundamentals (Google Search Central). For example, a page can be indexable and well ranked yet still absent from answers, while a page outside the top 10 can still be cited. Measure citations directly rather than inferring them from rank.

Answer-first sections, explicit entity names, comparison pages, short summaries near the top, author attribution, and third-party mentions are the tactics most often named in these case studies. Go Fish Digital describes four levers:

• Prompt mapping
• Benchmarking with GA4 regex filters and log-file analysis
• Fact-dense content production
• Query fan-out expansion

According to Go Fish Digital's GEO case study, a three-month GEO strategy produced +43% growth in monthly AI-driven traffic from ChatGPT and other referral sources, and an +83.33% lift in monthly conversions from AI referrals. According to Relevance, its SmartSource case achieved 65% more traffic from LLMs and a 32% increase in Google AI Mode presence. However, because each study bundles several tactics together, none of them isolates which change caused the result.

Published GEO case studies carry several biases. They are usually written by the agency that performed the work, which means they may select favourable clients and windows. Baselines are often short, and a 12 to 13 week window can capture seasonal or product changes unrelated to GEO. However, according to the Princeton, Georgia Tech, and IIT Delhi study 'GEO: Generative Engine Optimization' (arXiv 2311.09735), websites applying GEO strategies saw AI-generated citation visibility improve by up to 40% compared to baseline content.

That is a controlled research result, not an agency's live client revenue report. Weight controlled research above self-reported client figures. Ask each vendor for its baseline, window, and raw counts.

Case studies report results from ChatGPT, Perplexity, Google AI Overviews, Google AI Mode, Gemini, and Copilot, but they rarely disclose the prompts or sampling used. Each platform retrieves and cites differently, so a gain on one does not transfer to another.

Google's documentation states that AI Overviews and AI Mode follow standard Search eligibility rules (Google Search Central). For example, OpenAI publishes crawler documentation for GPTBot, and Anthropic does the same for ClaudeBot, which lets you verify whether an AI crawler visited a page at all (OpenAI). Break results out by platform, and log crawler visits alongside referrals.

GEO results typically take several months to show measurable change, though reported timelines vary widely. Go Fish Digital's case used a three-month strategy window. According to Maximus Labs, Smart Rent saw a 32% increase in sales-qualified leads within six weeks of an AI-native SEO approach, while its Google rankings barely moved (Maximus Labs). Backlinko's 2025 analysis, as cited by Maximus Labs, reports an 800% year-over-year rise in LLM traffic for businesses running systematic GEO frameworks between Q2 2024 and Q2 2025. However, short windows can show early movement but cannot separate durable gains from noise. Set a fixed baseline before publishing, then compare matched periods.