Generative engine optimization is the practice of building the authority and mention footprint that makes large language models name your brand when they generate an answer. Our GEO services combine content that gets quoted, mentions on sources LLMs actually read, and prompt-share tracking so you see the impact every week. GEO is where SEO meets brand, measured in the answers the model gives.
A GEO agency builds the third-party signal LLMs rely on to decide which brand to name. That means mentions on Reddit, Wikipedia, industry publications and expert forums, plus original data and quotes the model can lift. According to a Profound study published April 2025, Reddit was the single most cited source across ChatGPT, Perplexity and Google AI Overviews for consumer research queries. We operate inside the sources LLMs read, ethically, and track how often your brand is named in the answers your customers actually see.
We run 250 real customer prompts through ChatGPT, Claude, Gemini and Perplexity, log which brands each model names, and map the sources each answer cites.
You need to know the starting line. The audit shows which competitors already own the answer, which sources the model trusts in your category, and where your brand is either absent or misrepresented.
Our operators are real subject-matter experts in threads AI reads. We seed useful answers, defend brand mentions, and correct misinformation, always disclosed, never spammed.
Per Similarweb data from January 2025, Reddit traffic from Google grew 603 percent year over year after the February 2024 $60M Google-Reddit deal made Reddit content a first-class training and retrieval source.
We publish original research, benchmarks and expert commentary that LLMs and journalists lift, with clean HTML, named authors and unambiguous stats.
LLMs prefer sources with specific, dated numbers and named authors. Generic listicles get skipped. Content built around one hard number a model can quote gets named as the source.
You get a dashboard showing your brand share of voice across a 200-to-1000 prompt panel, updated weekly, per engine.
Share of voice in AI answers is the new share of shelf. If ChatGPT names three competitors and never you, your pipeline shrinks even when your Google rankings hold steady.
We construct and refine your brand footprint on Wikidata and Wikipedia to establish unquestionable authority. Our team drafts schema compliant submissions, aligns your references with trusted external databases, and resolves conflicting entity data. This ensures large language models identify your executive team, proprietary assets, and core brand definitions as verified, highly trustworthy cryptographic facts.
Generative engines rely on knowledge graphs to verify claims. By securing a clean, linked data presence on Wikidata, you provide the foundational anchor that AI models use to validate your brand authority, directly increasing your inclusion rate in structured AI summaries.
We systematically extract the exact sources, directories, and academic papers that AI engines cite when recommending your competitors. Our proprietary scrapers analyze Perplexity, Gemini, and Copilot references to map these citation networks daily. You receive a prioritized roadmap to secure placements on those identical high-influence domains, neutralizing your competitors' visibility advantages.
Large language models do not search the web in real time for every query; they pull from pre-compiled indexes of trusted reference sites. Securing placements on the exact domains your competitors occupy is the fastest way to insert your brand into existing generative answer loops.
average increase in branded mentions per 100 prompts
250 real buyer prompts across four engines, mapping which competitors get named, which sources each model cites, and where your brand is absent.
We identify the exact sources each engine trusts in your category, from Reddit and Wikipedia to industry publications and niche forums, and build an earn-mention plan for each.
Original research, benchmarks, expert commentary and named-author articles with hard numbers LLMs prefer to quote over generic listicles.
Real subject-matter experts, real accounts, disclosed mentions, no stealth marketing. Slower than spam, and it does not get purged.
Weekly dashboard of your share of voice per engine, per prompt cluster, plus the sources the model cited in each answer.
SEO earns a ranked position in the ten blue links. AEO earns a citation inside an AI-generated answer by structuring your own site so the engine can lift it. GEO earns the mention by building third-party authority the engine trusts more than any single page you own. All three matter, and the split of budget depends on your category. In consumer-research categories, GEO drives the largest share of pipeline because LLMs weight Reddit, Wikipedia and community forums heavily. In transactional local categories, SEO still moves more revenue. In B2B categories where buyers ask ChatGPT to shortlist vendors, AEO and GEO combined outweigh classic SEO by month six.
By being useful, disclosed and never spammy. Our operators are real subject-matter experts who hold long-standing accounts in the subreddits your buyers read. They answer questions on their merits, disclose affiliation when they mention a client, and never post the same link across threads. Reddit's rules bar undisclosed promotion and mass posting, and their moderation is fast and unforgiving. A single disclosed helpful comment in a high-traffic thread beats fifty stealth mentions that get removed within 24 hours. Per a Profound study published April 2025, Reddit was the single most cited source across ChatGPT, Perplexity and Google AI Overviews for consumer research queries, which is why we treat it as core distribution, not a side channel.
With a prompt-share panel. We define 200 to 1000 prompts that mirror how your buyers actually query LLMs, then run them weekly through ChatGPT, Claude, Gemini and Perplexity via API. We log every brand named, every source cited, sentiment when the model has an opinion, and week-over-week movement. The result is a single number you can move: your share of voice inside the answer, per engine. That number correlates with pipeline in a way vanity impressions never did, because the prompt panel is built from your real funnel questions, not generic keyword volume.
Enterprise software, fintech, professional services. Your buyers ask ChatGPT to shortlist vendors before they ever hit your site.
High-trust categories where LLMs lean hardest on named authors, Wikipedia entities and cited publications. GEO decides who gets recommended.
Skincare, home goods, supplements, travel. Reddit and community forums drive most AI citations. GEO is how you show up inside those threads.
Last updated: 2026-07-15
AEO is on-page: schema, structure and content the engine can lift. GEO is off-page: mentions, authority and third-party signal that make the engine choose your brand over a competitor. Serious programs run both.
There is overlap. Traditional PR earns coverage in publications people read. GEO earns coverage in sources LLMs read, which include Reddit, Wikipedia, Substack and niche forums that no traditional PR firm targets.
Weekly prompt-share reports across ChatGPT, Claude, Gemini and Perplexity. You see what percentage of relevant prompts name your brand, which competitors take the rest, and which sources the model cited in each answer.
We operate as an advanced technical layer, not a replacement for your current staff. Your PR team continues to secure brand mentions, while your SEO team manages standard organic rankings. We translate those raw assets into LLM-friendly formats by injecting nested schema markup, securing Wikidata entity nodes, and auditing your press releases to ensure they contain the precise semantic patterns and keywords that generative engine crawlers look for.
We see the highest yield in high-consideration sectors where consumers conduct extensive research before purchasing. This includes enterprise B2B software, specialized healthcare, legal services, fintech, and high-ticket niche manufacturing. If your buyers ask complex questions, compare multiple vendors, or require deep technical proof before converting, generative search Engines are actively shaping their final decisions.
If you pause, your existing entity foundations on Wikidata and static schema markup remain active, but you quickly lose ground to active competitors. Model training cycles update constantly, meaning the corpus of web data the LLMs ingest changes weekly. Without continuous citation acquisition, semantic content updates, and prompt-share monitoring, newer competitor data will displace your brand in daily generative answers.