# GEO Rank Tracker - Weekly AI Visibility Monitoring (`dltik/geo-rank-tracker`) Actor Schedule weekly to track how your brand's AI visibility changes over time. Each run computes a GEO score across ChatGPT/Claude/Gemini, then diffs vs the previous run: score trend, prompts gained/lost, competitor moves, alerts. The recurring companion to GEO Visibility Score. - **URL**: https://apify.com/dltik/geo-rank-tracker.md - **Developed by:** [dltik](https://apify.com/dltik) (community) - **Categories:** SEO tools, Marketing, AI - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, NaN bookmarks - **User rating**: No ratings yet ## Pricing from $0.00005 / actor start This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events. Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#pay-per-event ## What's an Apify Actor? Actors are a software tools running on the Apify platform, for all kinds of web data extraction and automation use cases. In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours, and optionally produces a well-defined JSON output, datasets with results, or files in key-value store. In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server. Actors are written with capital "A". ## How to integrate an Actor? If asked about integration, you help developers integrate Actors into their projects. You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready. The best way to integrate Actors is as follows. In JavaScript/TypeScript projects, use official [JavaScript/TypeScript client](https://docs.apify.com/api/client/js.md): ```bash npm install apify-client ``` In Python projects, use official [Python client library](https://docs.apify.com/api/client/python.md): ```bash pip install apify-client ``` In shell scripts, use [Apify CLI](https://docs.apify.com/cli/docs.md): ````bash # MacOS / Linux curl -fsSL https://apify.com/install-cli.sh | bash # Windows irm https://apify.com/install-cli.ps1 | iex ```bash In AI frameworks, you might use the [Apify MCP server](https://docs.apify.com/platform/integrations/mcp.md). If your project is in a different language, use the [REST API](https://docs.apify.com/api/v2.md). For usage examples, see the [API](#api) section below. For more details, see Apify documentation as [Markdown index](https://docs.apify.com/llms.txt) and [Markdown full-text](https://docs.apify.com/llms-full.txt). # README ## GEO Rank Tracker — Weekly AI Visibility Monitoring **GEO Rank Tracker** is the recurring companion to GEO Visibility Score. Instead of a one-shot snapshot, you **schedule it weekly** — each run computes your brand's GEO score across ChatGPT, Claude, and Gemini, then diffs against the previous run: score trend, prompts you gained or lost, competitor movement, and alerts on big swings. Set it once, get a brand-visibility trend that builds itself. This is GEO monitoring as it should be: continuous, not a single point in time. Know the moment you drop out of "best CRM" or a competitor starts showing up in your space. > ⭐ **Found this useful?** Click the **Bookmark** button at the top of [this page](https://apify.com/dltik/geo-rank-tracker) — it helps the actor stay visible. Then set an **Apify Scheduled run (weekly)** so your trend builds automatically. --- ### What GEO Rank Tracker monitors over time - 📈 **GEO score trend** — 0–100 score, tracked run over run (last 12 runs kept) - ➕ **Prompts gained** — queries where your brand newly appears - ➖ **Prompts lost** — queries where you dropped out (the alert that matters most) - 🥊 **Competitor movement** — new competitors entering your AI answer space - 🔔 **Alerts** — automatic flags on ±10 point swings, lost/gained prompts, new competitors - 🗓️ **Built for scheduling** — history persists across runs via a named key-value store --- ### How to set up weekly GEO tracking 1. **[Create a free Apify account](https://apify.com/sign-up)** 2. **Open [GEO Rank Tracker](https://apify.com/dltik/geo-rank-tracker)** 3. **Enter your brand + the prompts you want to rank for** (keep this list stable so deltas are meaningful) 4. **Run once** — this saves your baseline 5. **Set an Apify Schedule** → weekly. Every week you get the new score + what changed + alerts 6. **Download or pipe** the trend report (JSON / CSV / Excel) into your dashboard --- ### What data does GEO Rank Tracker output? | Field | Description | |-------|-------------| | `current.geo_score` | This run's GEO score (0–100) | | `current.mention_rate` | % of responses mentioning your brand | | `vs_previous.score_change` | Delta vs the previous run | | `vs_previous.prompts_gained` | Prompts you newly appear in | | `vs_previous.prompts_lost` | Prompts you dropped out of | | `vs_previous.competitors_new` | Competitors newly appearing | | `alerts` | Human-readable alerts for this run | | `trend` | Score + mention-rate per recorded run (last 12) | --- ### How much does GEO rank tracking cost? **$0.05 per prompt analyzed** via Apify Pay-Per-Event (includes the OpenRouter call). A weekly schedule of 10 prompts × 3 LLMs = 30 events ≈ **$1.50/week**. | Schedule | Prompts × LLMs | Weekly cost | |----------|----------------|-------------| | Light (5 × 1) | 5 | ~$0.25 | | Standard (10 × 3) | 30 | ~$1.50 | | Deep (20 × 3) | 60 | ~$3.00 | Versus $99+/mo for Semrush AI Visibility — and this one runs on your schedule. --- ### Input | Parameter | Type | Required | Default | Description | |-----------|------|----------|---------|-------------| | `brand` | string | ✅ | — | Brand to track (history is keyed by this) | | `prompts` | array | ❌ | 4 defaults | Buying-intent queries (use `{brand}`) — keep stable | | `competitors` | array | ❌ | `[]` | Competitor names to watch alongside you | | `llms` | array | ❌ | 3 models | OpenRouter model IDs | | `limit` | integer | ❌ | `10` | Max prompts per run | | `openrouterApiKey` | string | ❌ | env var | Override the default OpenRouter key | --- ### Why recurring beats one-shot A one-time GEO audit tells you where you stand today. **GEO Rank Tracker tells you which way you're moving** — and alerts you the week a competitor overtakes you, while you can still react. AI answers change constantly as models update; a single snapshot is stale within weeks. Trend > snapshot. --- ### Related GEO actors - **[GEO Visibility Score](https://apify.com/dltik/geo-visibility-score)** — the one-shot version (start here) - **[GEO Brand Sentiment](https://apify.com/dltik/geo-brand-sentiment)** — how AI describes your brand - **[GEO Citation Tracker](https://apify.com/dltik/geo-citation-tracker)** — URL/source citation detection - **[GEO Prompt Bank](https://apify.com/dltik/geo-prompt-bank)** — pre-built prompts per industry - **[GEO Site Audit](https://apify.com/dltik/geo-site-audit)** — is your site AI-crawler ready? --- > ⭐ **Bookmark this actor** at the top of [its Apify Store page](https://apify.com/dltik/geo-rank-tracker), then schedule it weekly. # Actor input Schema ## `brand` (type: `string`): Brand name to track (e.g. 'Notion', 'Stripe'). History is keyed by this — keep it stable across scheduled runs. ## `prompts` (type: `array`): The buying-intent queries you want to rank for. Use {brand} as placeholder. Keep this list stable so week-over-week deltas are meaningful. ## `competitors` (type: `array`): Competitor names to track alongside your brand in the same answers. ## `llms` (type: `array`): OpenRouter model IDs. Default: 3 cheap models (Gemini Flash, GPT-4o-mini, Claude Haiku). Keep stable across runs. ## `limit` (type: `integer`): Cap total prompts. 1 prompt x N LLMs = N charged events. ## `openrouterApiKey` (type: `string`): Override the default OpenRouter key. Get one at openrouter.ai/keys. ## Actor input object example ```json { "brand": "Notion", "prompts": [ "What's the best note-taking app in 2026?", "Best productivity tool for remote teams", "{brand} vs alternatives - which is better?", "Top tools to organize work as a freelancer" ], "competitors": [], "llms": [ "google/gemini-2.0-flash-001", "openai/gpt-4o-mini", "anthropic/claude-haiku-4.5" ], "limit": 10 } ```` # API You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup. ## JavaScript example ```javascript import { ApifyClient } from 'apify-client'; // Initialize the ApifyClient with your Apify API token // Replace the '' with your token const client = new ApifyClient({ token: '', }); // Prepare Actor input const input = { "brand": "Notion", "prompts": [ "What's the best note-taking app in 2026?", "Best productivity tool for remote teams", "{brand} vs alternatives - which is better?", "Top tools to organize work as a freelancer" ], "competitors": [] }; // Run the Actor and wait for it to finish const run = await client.actor("dltik/geo-rank-tracker").call(input); // Fetch and print Actor results from the run's dataset (if any) console.log('Results from dataset'); console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`); const { items } = await client.dataset(run.defaultDatasetId).listItems(); items.forEach((item) => { console.dir(item); }); // 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/js/docs ``` ## Python example ```python from apify_client import ApifyClient # Initialize the ApifyClient with your Apify API token # Replace '' with your token. client = ApifyClient("") # Prepare the Actor input run_input = { "brand": "Notion", "prompts": [ "What's the best note-taking app in 2026?", "Best productivity tool for remote teams", "{brand} vs alternatives - which is better?", "Top tools to organize work as a freelancer", ], "competitors": [], } # Run the Actor and wait for it to finish run = client.actor("dltik/geo-rank-tracker").call(run_input=run_input) # Fetch and print Actor results from the run's dataset (if there are any) print("💾 Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"]) for item in client.dataset(run["defaultDatasetId"]).iterate_items(): print(item) # 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start ``` ## CLI example ```bash echo '{ "brand": "Notion", "prompts": [ "What'\''s the best note-taking app in 2026?", "Best productivity tool for remote teams", "{brand} vs alternatives - which is better?", "Top tools to organize work as a freelancer" ], "competitors": [] }' | apify call dltik/geo-rank-tracker --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=dltik/geo-rank-tracker", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "GEO Rank Tracker - Weekly AI Visibility Monitoring", "description": "Schedule weekly to track how your brand's AI visibility changes over time. Each run computes a GEO score across ChatGPT/Claude/Gemini, then diffs vs the previous run: score trend, prompts gained/lost, competitor moves, alerts. The recurring companion to GEO Visibility Score.", "version": "1.0", "x-build-id": "WgEfQik7nHtdrC2yY" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/dltik~geo-rank-tracker/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-dltik-geo-rank-tracker", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for its completion, and returns Actor's dataset items in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/dltik~geo-rank-tracker/runs": { "post": { "operationId": "runs-sync-dltik-geo-rank-tracker", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/dltik~geo-rank-tracker/run-sync": { "post": { "operationId": "run-sync-dltik-geo-rank-tracker", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } } }, "components": { "schemas": { "inputSchema": { "type": "object", "required": [ "brand" ], "properties": { "brand": { "title": "Your brand", "type": "string", "description": "Brand name to track (e.g. 'Notion', 'Stripe'). History is keyed by this — keep it stable across scheduled runs." }, "prompts": { "title": "Prompts to track", "type": "array", "description": "The buying-intent queries you want to rank for. Use {brand} as placeholder. Keep this list stable so week-over-week deltas are meaningful.", "items": { "type": "string" } }, "competitors": { "title": "Competitors to watch (optional)", "type": "array", "description": "Competitor names to track alongside your brand in the same answers.", "items": { "type": "string" } }, "llms": { "title": "LLMs to query", "type": "array", "description": "OpenRouter model IDs. Default: 3 cheap models (Gemini Flash, GPT-4o-mini, Claude Haiku). Keep stable across runs.", "default": [ "google/gemini-2.0-flash-001", "openai/gpt-4o-mini", "anthropic/claude-haiku-4.5" ] }, "limit": { "title": "Max prompts per run", "minimum": 1, "maximum": 100, "type": "integer", "description": "Cap total prompts. 1 prompt x N LLMs = N charged events.", "default": 10 }, "openrouterApiKey": { "title": "Your OpenRouter API key (optional)", "type": "string", "description": "Override the default OpenRouter key. Get one at openrouter.ai/keys." } } }, "runsResponseSchema": { "type": "object", "properties": { "data": { "type": "object", "properties": { "id": { "type": "string" }, "actId": { "type": "string" }, "userId": { "type": "string" }, "startedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "finishedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "status": { "type": "string", "example": "READY" }, "meta": { "type": "object", "properties": { "origin": { "type": "string", "example": "API" }, "userAgent": { "type": "string" } } }, "stats": { "type": "object", "properties": { "inputBodyLen": { "type": "integer", "example": 2000 }, "rebootCount": { "type": "integer", "example": 0 }, "restartCount": { "type": "integer", "example": 0 }, "resurrectCount": { "type": "integer", "example": 0 }, "computeUnits": { "type": "integer", "example": 0 } } }, "options": { "type": "object", "properties": { "build": { "type": "string", "example": "latest" }, "timeoutSecs": { "type": "integer", "example": 300 }, "memoryMbytes": { "type": "integer", "example": 1024 }, "diskMbytes": { "type": "integer", "example": 2048 } } }, "buildId": { "type": "string" }, "defaultKeyValueStoreId": { "type": "string" }, "defaultDatasetId": { "type": "string" }, "defaultRequestQueueId": { "type": "string" }, "buildNumber": { "type": "string", "example": "1.0.0" }, "containerUrl": { "type": "string" }, "usage": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "integer", "example": 1 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } }, "usageTotalUsd": { "type": "number", "example": 0.00005 }, "usageUsd": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "number", "example": 0.00005 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } } } } } } } } } ```