AI Search Visibility Tracker — AEO / GEO

Track how visible a brand is in Google's AI-era search — the layer your classic rank tracker and Search Console cannot see. Give it a list of queries and your brand identity; for every query it returns one structured, pipeable row.

Traffic arriving from AI answers converts far better than a blue-link click — the visitor has already compared options. But ~85% of brand mentions in AI search come from external domains, so the actionable question isn't "do I rank" — it's "who gets cited, and am I one of them?" This actor answers that, per query.

What you get per query

Field	Meaning
ai_overview_present	Did Google render an AI Overview for this query
ai_overview_sources	The cited source URLs + domains (the crown jewel of AEO)
brand_in_ai_overview / brand_ai_overview_via	Is your brand cited (source), named (mention), both, or absent
brand_cited_domains	Which of your domains the AI cited
competitor_domains_in_ai_overview	Everyone else the AI cited — your AEO competitive set
brand_organic_rank	Classic organic position of your domain (or null)
brand_in_featured_snippet	Do you own the featured snippet
fan_out_queries	The query fan-out — Google's own sub-questions (People-Also-Ask + related). A blueprint of the content to create
top_organic_domains	The competitive landscape
visibility_score	A deterministic 0–100 roll-up, so rows sort without any AI

Optional AI add-on (enrichWithAI)

Turn it on to add brand_sentiment, brand_prominence and a one-line brand_recommendation per row. Bring your own OpenAI key (openaiApiKey, you pay the tokens) or leave it empty for a free deterministic pass — the actor always returns the fields either way.

Why re-run it

AI answers are volatile: 40–60% of AI citations change month-to-month. A one-time snapshot goes stale fast — schedule it weekly/monthly and watch the trend. AI answers also differ by region, so set countryCode / languageCode per market.

Access & pricing

A protected target — runs through the Apify GOOGLE_SERP proxy for reliable access (proxy from the first byte). Pay per query row (PPE). Honest limit: Google AI Overview is JS-injected and does not render for every query/region; when it is absent we return ai_overview_present: false and still deliver the fan-out, organic rank, featured snippet and competitive landscape.

Usage statistics

This Actor creates a small, content-free summary at the end of each run. It is used only to monitor reliability and improve this Actor. A copy is saved as USAGE_STATS in your own Apify key-value store, so you can see the exact record created for your run.

Set disableUsageStats to true in the input to opt out. Nothing is sent then; your USAGE_STATS record only says that statistics were disabled.

Only these fields are recorded:

• schema version, Actor name and build number;
• UTC start and finish hour (not a precise timestamp);
• run duration, number of results and time to the first result, each as a coarse range;
• whether the result was empty, the end status, and an error type from a fixed list;
• memory setting and counts of charged events;
• names of the input fields you set, never their values;
• the selected option for input fields that offer a fixed list of choices (for example a sort order).

We do not collect input text, search terms, URLs, domains, usernames, email addresses, names, proxy credentials, tokens, scraped records, output items, raw error messages, stack traces, or hashes of any of those values. Records are kept for no longer than 13 months, used only as aggregated operational statistics, and never sold or shared.

Additional fields (Phase 2)

This Actor also records your Apify user ID, whether Apify marks the account as paying, the size range of list inputs, the selected country when the input offers a fixed list of countries, and one category from a fixed Actor taxonomy. We use these fields only for aggregate reliability, repeat-use and cross-Actor analysis; reports suppress any cell with fewer than five distinct users.

The same disableUsageStats: true input flag turns these fields off too. The user ID is removed after 13 months; we do not export, sell, share, or attempt to re-identify this data.

Run-outcome signals (v2)

To learn whether a run did what it was asked to do, the record also holds a few more coarse ranges and yes/no flags. None of them contains content:

• the result limit you asked for (a range, when the input has one) and what share of it was delivered;
• results delivered per input item you listed (a range);
• output quality as ranges: how fully the result fields were filled, the share of rows that look like errors, the share of duplicate rows, and how many different fields appeared. These are counted in memory while results are saved; no result content is kept;
• how the run was started (console, API, schedule, webhook, another Actor);
• how it ended: stopped by you, timed out, reached the requested limit, stopped by the charge limit, and how many times the platform moved the run;
• if this Actor reports it: how many items to process worked or failed (ranges) and one failure reason from a fixed list;
• a short code made from the names of the input fields you set, never their values.

Repeat-run fingerprint (v2)

When your Apify user ID is recorded (see above), the record also holds an 8-character one-way code made from your input (proxy settings left out) and this Actor's name. It only lets us see that the same account ran the same input again soon after an unsatisfying run; we never see the input itself. It is stored only in the database, never published, and reports use it in aggregate with the same five-user minimum. It is the one exception to the statement above that no hashes are collected, and disableUsageStats: true turns it off.