# Google Ads Transparency Scraper - AI Competitor Ad Intelligence (`webdatalabs/google-ads-transparency-intel`) Actor Scrape any advertiser's live ads from Google's Ads Transparency Center and get an AI read of each creative: angle, messaging themes, offer, and CTA. Search by advertiser, domain, or name. Flat output, scheduled monitoring. - **URL**: https://apify.com/webdatalabs/google-ads-transparency-intel.md - **Developed by:** [WebDataLabs](https://apify.com/webdatalabs) (community) - **Categories:** AI, Developer tools, Automation - **Stats:** 3 total users, 2 monthly users, 82.4% runs succeeded, 0 bookmarks - **User rating**: 5.00 out of 5 stars ## Pricing from $3.00 / 1,000 creative scrapeds This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events. Since this Actor supports Apify Store discounts, the price gets lower the higher subscription plan you have. 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 ## Google Ads Transparency Scraper - AI Competitor Ad Intelligence **See every ad a competitor is running on Google — and get an AI read of each creative.** Scrape Google's public [Ads Transparency Center](https://adstransparency.google.com) by advertiser, domain, or name, and receive flat, structured records with the **creative angle, messaging themes, offer, and CTA** extracted by AI vision. No browser, no login, fast and cheap. > The Google ad-spy space is dominated by raw scrapers that hand you image URLs and dates. This actor is the only one that **reads the creative for you** — turning a wall of competitor ads into an analyzable strategy map. ### Why Choose This Actor? - **AI creative analysis (the differentiator)** — every image creative is read by GPT-4o-mini vision: angle, themes, offer, CTA. - **Three ways in** — search by advertiser name, by domain (covers every advertiser running that domain), or by Google advertiser ID. - **Built for monitoring** — schedule it with monitor mode to get only *what's new since last run*. - **Fast & cheap** — pure HTTP, datacenter proxies, ~40 creatives/second. No browser overhead. - **Honest data** — we tell you exactly what the Transparency Center does and doesn't expose (see below). ### Key Features | Feature | Description | |---------|-------------| | Advertiser / domain / name lookup | Auto-detected; paste any of the three | | AI creative intelligence | `creativeAngle`, `messagingThemes`, `offer`, `cta` per image | | Monitor mode | Cross-run dedupe + a `whatsNewThisWeek` diff | | Webhook delivery | POST run summary + new creatives to n8n / Zapier / Make | | Flat output | One clean record per creative — Sheets/BigQuery ready | | Format detection | image · display · text | ### Use Cases - **Media buyers & agencies** — spot which angles a competitor doubles down on; filter `creativeAngle` to study their proven winners. - **DTC & brand teams** — track a rival's offers and CTAs week over week with monitor mode. - **Ad-spy & market research** — pull an advertiser's full active creative set in one run, flat and ready for analysis. ### Quick Start 1. **Input** a competitor — an advertiser name (`Nike`), a domain (`nike.com`), or an advertiser ID (`AR…`). 2. **Run** — set `maxResults` and leave **AI creative analysis** on. 3. **Export** CSV / JSON / Excel, or POST to a webhook. ### Input | Field | Type | Description | |-------|------|-------------| | `query` | string | Advertiser name, domain, or advertiser ID (required) | | `mode` | select | `searchQuery` · `advertiser` · `domain` (auto-detected) | | `maxResults` | integer | Creatives per advertiser (Google caps ~1,000) | | `enableAiAnalysis` | boolean | AI vision read of each image creative (default on) | | `monitorMode` | boolean | Only emit creatives new since last run | | `region`, `creativeFormat`, `dateFrom`, `dateTo`, `webhookUrl` | — | Advanced filters | ### Output — what you get One flat record per creative. **Bold = the AI differentiator.** ```json { "advertiserName": "Nike, Inc.", "advertiserId": "AR16735076323512287233", "payerName": "Nike, Inc.", "advertiserVerified": true, "format": "image", "imageUrl": "https://tpc.googlesyndication.com/archive/simgad/6852044362810907552", "firstShown": "2023-11-16", "lastShown": "2026-06-30", "previewUrl": "https://adstransparency.google.com/advertiser/AR16735076323512287233/creative/CR06146323222502572033?region=US", "creativeAngle": "Brand / lifestyle", "messagingThemes": ["performance", "new release"], "offer": "None", "cta": "Shop Now", "aiAnalyzed": true, "isNew": false, "scrapedAt": "2026-06-30T13:12:04.590Z" } ```` Example: filter to `creativeAngle = "Limited-time discount"` to isolate a competitor's promo creatives, or sort by `lastShown` to find what they're running *right now*. ### Pricing (pay per event) - **$0.004** per creative scraped - **+ AI analysis** event for each image creative read by the vision model (only when AI is on) - Scheduled monitor-mode runs only pay for what's new A 100-creative run with AI is roughly **$0.40–0.90** depending on how many are images. ### Change Tracking & Monitoring Turn on **Monitor mode** and schedule the actor. Each run skips creatives it has already seen and writes the new ones to the key-value store as `whatsNewThisWeek` (and includes them in the webhook). A ready-made "what changed this week" feed for any competitor. ### Integration Examples - **n8n / Zapier / Make** — set `webhookUrl` to receive `{ stats, whatsNewThisWeek, creatives }` on completion. - **Google Sheets / BigQuery** — flat records import directly, no flattening needed. - **Apify API** — `apify call webdatalabs/google-ads-transparency-intel` from any language. ### What this does and does NOT return (read this) - ✅ Creative **visuals** (image URL), formats, first/last-shown dates, advertiser & payer, and an **AI read** of each image. - ❌ **No ad spend, impressions, clicks, or targeting keywords.** Google's Transparency Center does not publish these for commercial (non-political) ads — no tool can. Be wary of any that claim to. - ❌ **No raw headline/description text.** Google serves creatives as rendered images/HTML, not text. Instead of guessing, we run AI **vision** over the actual creative and return the angle, themes, offer, and CTA — usually more useful than raw copy. - ℹ️ **Region** scopes the lookup and tags output; Google does not geo-filter the creative set, so this is not an "all ads in country X" export. - ℹ️ **`display` / `text` creatives** carry no static image, so they have a `previewUrl` (view it on Google) but no `imageUrl` or AI fields. Set `creativeFormat: ["image"]` for an AI-only run. - ℹ️ **`advertiserName` is the legal entity, not the marketing brand** — e.g. HelloFresh appears as "Grocery Delivery E-Services USA Inc.", and large brands may span several regional entities (Nike's US/Japan/Singapore arms). This is Google's registered advertiser identity, as shown on the Transparency Center. - ℹ️ **Domain lookup returns every advertiser Google links to that domain** (~85% precision) — occasionally including a resellers/unrelated advertiser. Filter by `advertiserName` if you need exactly one advertiser. ### FAQ - **Is this legal?** It reads Google's public Transparency Center — commercial ad creatives, which are non-personal data. Use it for competitive research, not to harvest political-ad payer identities. - **Do I need proxies?** Datacenter proxies (the default) are enough. - **Do I need an OpenAI key?** Only for the AI layer — set it as the `OPENAI_API_KEY` secret. Without it you still get all creative metadata. - **Can I schedule it?** Yes — combine a schedule with monitor mode for change tracking. - **What if my competitor runs thousands of ads?** Google caps a single advertiser at ~1,000 creatives; set `maxResults` accordingly. ### 🔗 Explore More of Our Actors | Actor | Description | |-------|-------------| | [Google Ads Intelligence Pro](https://apify.com/webdatalabs/google-ads-intelligence-pro) | Competitor ad copy from live Google **Search** results, by keyword | | [Facebook Ad Intelligence](https://apify.com/webdatalabs/facebook-ad-intelligence-pro) | AI ad-copy analysis & winning-ad predictor for Meta ads | | [Reddit Scraper Pro](https://apify.com/webdatalabs/reddit-scraper-pro) | Monitor subreddits and track keywords with sentiment analysis | | [Shopify Scraper Pro](https://apify.com/webdatalabs/shopify-scraper-pro) | Extract complete Shopify product data with variants and sales estimates | ### 📬 Custom Solutions & Enterprise Need a custom scraper, a private build, or higher volume? Reach out via the Apify Store contact form on our profile. ### 🏷️ SEO Keywords Google Ads scraper, Google Ads Transparency Center scraper, Google ad library scraper, competitor ad research, ad spy tool, AI ad analysis, ad creative analysis, Google ads competitor analysis, ad intelligence, ad monitoring, creative angle analysis, messaging theme detection, ad CTA extraction, advertiser lookup, domain ad lookup, Google ads API, ad transparency API, competitive advertising research, ad creative scraper, n8n Google ads, Zapier Google ads, GPT-4o ad analysis ### Leave a review Is this actor saving you time? A quick review on the Store helps other people find it — and tells us which fields to add next. **[Rate this actor →](https://apify.com/webdatalabs/google-ads-transparency-intel)** ### Legal Disclaimer This actor accesses publicly available data from Google's Ads Transparency Center, which publishes commercial (non-personal) ad creatives. Use it in compliance with Google's terms and applicable law, for legitimate competitive research. It does not collect personal data and is not intended for scraping political-ad payer identities. # Actor input Schema ## `query` (type: `string`): What to look up: an advertiser name (e.g. "Nike"), a domain (e.g. "nike.com"), or a Google advertiser ID (e.g. "AR16735076323512287233"). Any format works. ## `mode` (type: `string`): How to interpret the value above. Auto-detection handles most cases; set this if a name and a domain are ambiguous. ## `maxResults` (type: `integer`): How many creatives to fetch per advertiser. Google caps any single advertiser at ~1,000. ## `enableAiAnalysis` (type: `boolean`): Use AI vision to read each ad image and return its creative angle, messaging themes, offer, and CTA. This is the headline feature. ## `monitorMode` (type: `boolean`): On repeat/scheduled runs, skip creatives already seen and emit only what's new since last run (saved to the key-value store as "whatsNewThisWeek"). ## `region` (type: `string`): ISO country code (US, GB, DE, ...). Scopes the advertiser lookup and tags output. NOTE: Google does not geo-filter creatives, so this does NOT return "all ads shown in country X". ## `creativeFormat` (type: `array`): Keep only these formats. Leave empty for all. ## `dateFrom` (type: `string`): Keep creatives last shown on/after this date (YYYY-MM-DD). Google retains ~13 months. ## `dateTo` (type: `string`): Keep creatives first shown on/before this date (YYYY-MM-DD). ## `webhookUrl` (type: `string`): POST the run summary + what's-new diff here on completion (n8n / Zapier / Make). Leave empty to skip. ## `proxyConfiguration` (type: `object`): Apify proxy. Datacenter is sufficient for this endpoint. ## Actor input object example ```json { "query": "Nike", "mode": "searchQuery", "maxResults": 100, "enableAiAnalysis": true, "monitorMode": false, "region": "US", "creativeFormat": [], "proxyConfiguration": { "useApifyProxy": true } } ``` # Actor output Schema ## `overview` (type: `string`): No description ## `new_this_run` (type: `string`): No description ## `full` (type: `string`): No description # 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 = { "query": "Nike" }; // Run the Actor and wait for it to finish const run = await client.actor("webdatalabs/google-ads-transparency-intel").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 = { "query": "Nike" } # Run the Actor and wait for it to finish run = client.actor("webdatalabs/google-ads-transparency-intel").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 '{ "query": "Nike" }' | apify call webdatalabs/google-ads-transparency-intel --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=webdatalabs/google-ads-transparency-intel", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Google Ads Transparency Scraper - AI Competitor Ad Intelligence", "description": "Scrape any advertiser's live ads from Google's Ads Transparency Center and get an AI read of each creative: angle, messaging themes, offer, and CTA. Search by advertiser, domain, or name. Flat output, scheduled monitoring.", "version": "1.0", "x-build-id": "zCETo6Mt0ekrjrUZ7" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/webdatalabs~google-ads-transparency-intel/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-webdatalabs-google-ads-transparency-intel", "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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/webdatalabs~google-ads-transparency-intel/runs": { "post": { "operationId": "runs-sync-webdatalabs-google-ads-transparency-intel", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/webdatalabs~google-ads-transparency-intel/run-sync": { "post": { "operationId": "run-sync-webdatalabs-google-ads-transparency-intel", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": [ "query" ], "properties": { "query": { "title": "Advertiser, domain, or name", "type": "string", "description": "What to look up: an advertiser name (e.g. \"Nike\"), a domain (e.g. \"nike.com\"), or a Google advertiser ID (e.g. \"AR16735076323512287233\"). Any format works." }, "mode": { "title": "Lookup mode", "enum": [ "searchQuery", "advertiser", "domain" ], "type": "string", "description": "How to interpret the value above. Auto-detection handles most cases; set this if a name and a domain are ambiguous.", "default": "searchQuery" }, "maxResults": { "title": "Max creatives", "minimum": 1, "maximum": 1000, "type": "integer", "description": "How many creatives to fetch per advertiser. Google caps any single advertiser at ~1,000.", "default": 100 }, "enableAiAnalysis": { "title": "AI creative analysis", "type": "boolean", "description": "Use AI vision to read each ad image and return its creative angle, messaging themes, offer, and CTA. This is the headline feature.", "default": true }, "monitorMode": { "title": "Monitor mode (scheduled runs)", "type": "boolean", "description": "On repeat/scheduled runs, skip creatives already seen and emit only what's new since last run (saved to the key-value store as \"whatsNewThisWeek\").", "default": false }, "region": { "title": "Region", "type": "string", "description": "ISO country code (US, GB, DE, ...). Scopes the advertiser lookup and tags output. NOTE: Google does not geo-filter creatives, so this does NOT return \"all ads shown in country X\".", "default": "US" }, "creativeFormat": { "title": "Creative formats", "type": "array", "description": "Keep only these formats. Leave empty for all.", "items": { "type": "string", "enum": [ "image", "display", "text" ], "enumTitles": [ "Image", "Display / HTML", "Text / Search" ] }, "default": [] }, "dateFrom": { "title": "Active on/after", "type": "string", "description": "Keep creatives last shown on/after this date (YYYY-MM-DD). Google retains ~13 months." }, "dateTo": { "title": "Active on/before", "type": "string", "description": "Keep creatives first shown on/before this date (YYYY-MM-DD)." }, "webhookUrl": { "title": "Webhook URL", "type": "string", "description": "POST the run summary + what's-new diff here on completion (n8n / Zapier / Make). Leave empty to skip." }, "proxyConfiguration": { "title": "Proxy", "type": "object", "description": "Apify proxy. Datacenter is sufficient for this endpoint.", "default": { "useApifyProxy": true } } } }, "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 } } } } } } } } } } ```