Every term in our pricing page, our audit reports, and our doctrine — defined plainly, with how Toutmark uses each one. Bookmark this page and link to specific terms with the anchors.
The practice of structuring your content, identity, and brand signals so AI engines (ChatGPT, Claude, Gemini, Perplexity) cite your brand when users ask questions in your category. SEO optimizes for ranking in Google's blue links; AI citation optimizes for being cited inside an AI-generated answer. The signals overlap (good content, schema, brand authority) but the surfaces and metrics differ.
AEO (Answer Engine Optimization) and GEO (Generative Engine Optimization) are the industry's interchangeable acronyms for the same goal: getting cited in generative AI answers. GEO is slightly more popular in 2024–2025 academic literature; AEO is more common among practitioners. Both describe what this page calls AI citation.
An AI system that gives users a single direct answer rather than a list of links. ChatGPT, Claude, Perplexity, Gemini, and increasingly Google's AI Overviews are all answer engines. They synthesize from multiple sources but typically cite only a handful in the visible response.
When an answer engine references your brand, your URL, or your content in its response. Citations can be explicit (clickable source link), partial (mentioned by name with no link), or implicit (paraphrased without attribution). Explicit citations carry the most value because they drive direct traffic; partial mentions still establish authority for future queries.
Structured data added to web pages in a format search engines and AI engines can parse without ambiguity. Tells the engine "this is a product," "this is a FAQ entry," "this is a person," etc. Schema.org is the shared vocabulary all major engines understand. Without schema, engines have to infer your page structure from prose; with schema, the structure is explicit.
The format we use to deliver schema markup. Stands for "JavaScript Object Notation for Linked Data." Looks like a JSON object embedded in a <script type="application/ld+json"> tag. Preferred over the older microdata format because it's invisible to users, easy to update, and doesn't pollute your HTML structure.
A specific type of JSON-LD schema that explicitly marks up question/answer pairs on a page. AI engines love FAQPage schema because it's the cleanest possible signal of "here's a question, here's the matching answer." Pages with FAQPage schema get cited at much higher rates than equivalent prose pages.
A canonical text file at your site root (yourdomain.com/llms.txt) that tells AI engines what your site is about, what your canonical URLs are, and what facts you want them to know. Inspired by robots.txt but for LLMs instead of crawlers. Not yet a universal standard, but increasingly recognized by Anthropic, Perplexity, and others.
A JSON file at /brand-facts.json that carries canonical truths about your business — legal name, founding date, headquarters, services offered, banned phrases, sources we cite from. Like a structured "about us" that AI engines and our own agents can read directly without parsing your prose.
The structured-data backbone behind Wikipedia. A free, collaboratively-edited knowledge graph where every entity (your company, your founders, your products) gets a Q-number and a set of properties (industry, founded date, headquarters, etc.). AI engines train on Wikidata and reach for it when answering identity questions.
Your unique identifier on Wikidata — a string like Q12345678. Every notable entity on Wikidata has one. Companies that don't have a Q-entity (or have one with sparse properties) are systematically harder for AI engines to identify and cite consistently.
How often your brand is mentioned across high-authority sources for queries in your category. AI engines weight density: a brand that appears 50 times across credible sources for a topic gets cited more often than a brand mentioned twice. HARO pitches, press releases, podcast appearances, and review platform listings all contribute.
The 5–15 specific questions you want to win in AI answers. "Best AI citation platform for B2B SaaS," "How to optimize for ChatGPT," "Toutmark vs competitor X" (well, not the last one — see anchor-gate). Picked at signup, edited any time, the spine of your AI citation program.
Editor's hard rule that every customer-facing draft has to be anchored to one of the customer's target queries. If a draft can't be tied back to a target query, it's rejected before it hits your queue. Prevents agents from generating off-strategy content that wouldn't move citations.
checkAnchorGate(). Editor agent enforces. The gate also prevents direct-competitor comparisons since none of our customers' target queries should reference a named competitor.The core content unit Toutmark ships. We take a paragraph from your existing site and restructure it for AI crawlers — leading with the answer, adding entity references, tightening claim density, removing fluff. Customer's brand voice preserved per Brand Facts. Reviewed by Editor; queued for your approval; published on accept.
A 0–100 score measuring your AI citation posture across seven components: schema (0–20), Wikidata identity (0–15), brand-facts freshness (0–10), FAQ coverage (0–15), llms.txt presence (0–5), citation density (0–25), brand-profile completeness (0–10). Recomputed weekly. Target ranges: 60+ is competitive, 80+ is category-leading.
/app/aeo-score with per-component breakdown and a "how to improve" recommendation per component.The compliance layer Toutmark applies to financial services, legal, healthcare, accounting, insurance, and similar regulated customers. Adds two-layer compliance review, 7-year audit retention, CCO approval queue, custom disclaimer template, license + jurisdiction tracking, FAQ category gating, no cold solicitation, and securities preview-and-accept gate. Included on the Scale tier at no upcharge.
The center of the customer dashboard. Every draft Toutmark generates — paragraph rewrites, FAQ entries, schema specs, blog posts, HARO pitches, press releases, Wikidata edits, review responses — lands here as a queued item with Accept / Edit / Remake / Reject actions. Auto-publish is opt-in per feature; nothing publishes until you approve (or you've explicitly enabled auto-publish for that specific feature).
A daily newsletter where journalists request expert quotes for stories. Pitches that match your expertise become opportunities to be cited in major publications, which in turn lifts your citation density and identity authority for AI engines.
EIN Presswire distribution — a paid wire service that pushes press releases to a network of news outlets, aggregators, and AI training-data sources. One quarterly release on Scale. Always queued for your approval before submit. Used for genuine news (product launches, partnerships, milestones) — never for fluff.
A reply to a review on G2, Capterra, or Google Business Profile. AI engines crawl review platforms and treat both the review and the company's response as ranking signals. Thoughtful approved replies to good and bad reviews demonstrate brand attention and lift citation rate.
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