Documentation
Improving visibility via external publications and mentions
How the command center turns the source-domain map into a plan for external placements: the main recommendation is the "outlet × topic" pair, and the content plan serves as a brief for the editorial team
Contents
- 01 External publications: where the brand needs to appear beyond its own site
- 02 Publication plan: the order in which outlets deliver the most visibility
- 03 Publication ideas and article generation
- 04 Knowledge base: verified facts for generation
- 05 Marketing campaigns: tracking the effect of publications
1.External publications: where the brand needs to appear beyond its own site
The "External publications" tab in the command center collects recommendations on where the brand needs to appear outside its own website. For most commercial queries, AI engines cite external sources — media, directories, communities, expert domains — far more often than brand sites themselves, so presence there directly decides whether the brand makes it into the answer.
- The recommendations grow straight out of monitoring. The system takes the prompts and providers where brand visibility sags — a low "Response coverage" — and looks at which sources the engines lean on in the answers to those exact queries. All of it is visible in the prompt card: the metrics on top and the "Sources" tab with the domains that made it into the answer. Those domains are what becomes the outlets in the recommendations
- The tab sits second in the command center — next to "Site changes" and "Publication plan" — with a recommendation counter, an outlet-type filter, and a "Pending / Completed" switch
- Recommendations are grouped by outlet type — "Publications", "Directories", "Reviews", "Authority". The group header shows how many sources it holds, how many queries they surface on, how many citations they produced, and on which engines
- One outlet, one card. The header carries the linked domain, a type badge ("Community", "Editorial placement", "Directory", "Reviews", "Authority link"), the number of queries, citations, and articles, plus provider icons. Below it a line explains why this outlet type works — detailed community answers, for instance, get cited by LLMs as "lived experience"
- Inside the card sit the outlet's specific materials, each expandable on its own: "What to do" (for example: "Perplexity and Alice AI already rely on dtf.ru in answers to your brand's queries. The brand is barely present there"), "Why it matters", "Affected queries" with coverage percentages, and "Citation examples" — the real URLs the engines already cite
- The recommendations aren't abstract: GEO Scout takes the domains AI already cites for your queries (the same ones in the "Sources" section) and suggests strengthening presence where the model already looks for confirmation — not wherever "it would be nice to be published"
- The "Generate ideas" button launches an AI agent: it studies the outlet's format, pulls brand facts from the knowledge base, and proposes several publication topics with an article outline. Next to it: "Done", snooze, hide the card, and flag the recommendation
- Each type is its own workstream: editorial placements go to PR, directories to marketing, communities to the community manager, reviews to support. For directories and review sites the job is simpler — check that the brand's listing exists and its data is current
Don't treat external publications as an add-on to on-site work. For many niches this channel lifts citations faster than anything you change on your own site: AI already trusts these sources, you just need to be inside the right material. Editorial placements are the strongest — one article on an outlet the model already cites quickly raises the brand's share of mentions.
2.Publication plan: the order in which outlets deliver the most visibility
"Publication plan" is the most important tab in the command center. It takes the same external-outlet recommendations and lines them up by impact on visibility: step 1 is the publication that closes the most queries where the brand is missing; step 2 adds the most on top of the first, and so on. Instead of a list of "places it'd be nice to be published", you get an order of work in which every next step yields less than the previous one.
- The plan's unit of measure is the "query × AI provider" pair. The same topic can be answered differently in ChatGPT and in Alice, so coverage is counted per pair rather than per query — that's how the real visibility gap shows up instead of an average
- The header answers the main question in one line: how many publications close how many unique queries (out of all monitored ones) across how many AI providers. Next to it, a coverage bar by plan step shows each step's contribution as its own segment
- The order is built on marginal coverage: each next publication closes the maximum of still-uncovered pairs. Steps are numbered, outlets influencing different providers don't crowd each other out, and an "N shared queries with step" badge honestly flags overlap with an earlier step. Every step states how many new queries it adds and how many pairs are closed cumulatively — "after this step, X of Y are closed"
- A step reads as a task: "You need a mention or your own content similar to …" — followed by the specific outlet material the engines already cite — with an effort estimate, per-query coverage percentages, and citation examples the engines already use. A step can have alternative outlets, paged through as "Alternative 2 of 6 — if the primary outlet isn't available": if one editorial team says no, you take a replacement without losing the step's coverage
- Only the top steps are shown — the ones carrying most of the coverage; beyond them each publication's return drops noticeably. Nothing is deleted: "Show all" expands the full list and "Collapse to top steps" brings the short version back
- Below the plan sits the "No query data" block: recommendations with no link to prompts, which therefore can't be ranked by visibility gain. They aren't discarded — they simply stay aside so the queue isn't diluted
- The work closes the loop right there: "Generate ideas" on a step produces topics and outlines for future materials, marking it "Done" moves the step to the "Completed" tab, and the publication's effect later shows up in marketing campaigns
Work strictly top to bottom and don't try to close the whole list. The first few steps deliver most of the gain — spending effort on the tail before the top is done isn't worth it. And don't rank steps by how prestigious an outlet feels: the plan is already sorted by how much new visibility each publication brings.
3.Publication ideas and article generation
From an external-publication card (or a plan step) GEO Scout assembles publication ideas with one button, and turns each idea into a finished article. The logic isn't "write some text" but to lean on what the engines already cite: the agent studies the format that works on that outlet and builds briefs for it.
- "Generate ideas" launches the agent right inside the card, and its steps are visible live: analyze the recommendation → visit the outlet and study its format → gather brand facts → prepare topics and article outlines → save. Usually 1–2 minutes; the credit cost is shown before the run
- The result is a set of publication ideas in the content studio. Each idea has a title, a priority (High / Medium / Low), and a format: "Listicle", "Comparison", "Guide", "How-to", "FAQ", "News". One topic can be covered by several ideas from different angles — that's how you catch more of the phrasings the engines search on
- "Target prompts" — the queries the content must answer. These are the same monitoring prompts the outlet already gets cited on, so the article is written against a specific visibility gap rather than "the topic in general"
- "Article outline" — the skeleton of the future piece: sections with their key points, and citable claims already distributed across sections. A brief like this can go to a copywriter or the outlet's editors as is
- "Citable claims" — what AI providers can quote: concrete numbers and wording about the brand pulled from the knowledge base rather than the model's general knowledge. Next to it, "FAQ questions" — the block engines are especially eager to break down into answers
- "Recommended placements" — where to take the piece. An idea grown from an external-publication card carries a single placement: the very outlet the recommendation came from. Next to it sit its type (editorial placement, community, directory) and a note on what the suggestion rests on — "Confirmed in AI responses" or "Signal-based suggestion"
- The article-generation button delivers the finished piece in 30–60 seconds: it opens in a panel with "Article" and "Schemas" tabs, the generation timestamp, and exports — "Copy article", "Download", "Copy schemas" (the JSON-LD markup for the piece)
An article from an idea is a starting point, not a publish-ready piece. Fact-check the claims and figures and adapt the text to the outlet's requirements before sending it to editors. And the fuller the brand knowledge base, the less the model has to improvise — fill it in before the first generation.
4.Knowledge base: verified facts for generation
The knowledge base lives in the content studio — the "Knowledge base" tab next to "Drafts", "Published", and "Campaigns". It holds the verified sources that briefs and articles rely on: site pages, links, and uploaded files. Facts for the content come from here rather than being invented: you index your brand materials once, and every generation then draws on them.
- The summary at the top shows the state of the base: how many sources are indexed, how many chunks there are in total, and when the base was last updated. It also restates the cost — indexing and re-indexing take 1 credit per source
- Three source types: "Add link" (any page by URL), "Add site pages" (pick from the brand's sitemap), and "Upload files" (a deck, a guide, a price list). Everything important about the brand lives in one place
- Each source is split into chunks the model later uses to find exact facts. The table shows the source title and address, the status, the chunk count, and the update date; columns are sortable, and the source search helps once the list grows
- Statuses run "Not indexed" → "Queued" → "Indexing" → "Indexed". "Failed" means the page couldn't be read (blocked, redirected, empty), "Stale" means the source changed and is worth re-indexing. Tick rows with the checkboxes to index or re-index them in bulk
- Indexed sources are blended into brief and article generation as verified brand facts. These are the "Citable facts" from the content plan — numbers and wording come from your materials, not from the model's general knowledge
- Example: the brand site states "over 322,000 stores and services accept payments with YooKassa". Once indexed, that fact lands in the generated article verbatim and correctly — no risk of the model inventing a different number
- The fuller the knowledge base, the more accurate and convincing the content: the model doesn't hallucinate but assembles the material from confirmed facts about your brand — which directly raises the chance of being cited and the trust in the publication
Load the key facts up front — numbers, pricing, advantages, differences from competitors — and re-index a source whenever the page's data changes. Then every generated article speaks about the brand with the same accuracy, and you won't have to fix facts by hand after each generation.
5.Marketing campaigns: tracking the effect of publications
Once a piece is live — on an external outlet or on your own site — add its URL to "Marketing campaigns" (a content studio tab) and track how the engines react: how often it lands in answers, which prompts it works on, and whether the brand is actually named where the piece is cited. This is where the loop closes: recommendation → publication → measurable effect.
- The "Add URL" button takes both external placements (an article on an outlet, a directory listing, a community thread) and pages of your own site. A campaign groups placements within one release, PR wave, or quarterly plan
- Four campaign KPI cards: "Citations" — how many times the URLs landed in AI answers; "Citation rate" — what share of answers on the monitored prompts contains them; "Prompts" — how many distinct queries AI used the material on; "Brand mentions in citing responses" — in what share of citing answers the brand is actually named
- That last metric is the most underrated: an engine can link to your article without naming the brand. 100% means every citation works on recognition; a low share signals the brand is mentioned too much in passing inside the material
- "Citation dynamics" — a daily chart broken down by provider: you can see when ChatGPT picked the piece up, when Alice AI did, and where a provider ignores it. The point tooltip breaks the day down per provider
- The "URL sources" tab is a table of tracked links grouped by domain: citations, share of answers, and prompt count. A domain row expands to the individual URLs — showing which material actually earns citations and which sits idle
- The "Prompts" and "Responses" tabs show which queries cite the placement and what the answers themselves look like. If the piece closes priority prompts, the loop is complete; if it lands on irrelevant ones, that's a signal to rework the content or the topic
This is the metric that makes GEO measurable: recommendation → publication → URL in a campaign → citations in the next monitoring cycle. Mind the lag: it takes 2–3 weeks on average (depending on the outlet) before a piece starts being cited — the engines need time to index it and pull it into their sources. If a URL still gains no citations after that, rework the material or try a different outlet.