# LinkedIn Ads Scraper - Low-cost๐ฒ๐ฅ๐๐ (`delectable_incubator/linkedin-ads-scraper-low-cost`) Actor
๐ Extract LinkedIn sponsored ads by keyword, company, or location. Collect advertiser names, ad headlines, descriptions, image URLs, call-to-actions, and ad page links. Ideal for ad intelligence, competitor monitoring, market research, campaign analysis & social media advertising insights ๐๐
- **URL**: https://apify.com/delectable\_incubator/linkedin-ads-scraper-low-cost.md
- **Developed by:** [Prime Scrape](https://apify.com/delectable_incubator) (community)
- **Categories:** Automation, Lead generation, Social media
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet
## Pricing
from $0.00005 / actor start
This Actor is paid per event and usage. You are charged both the fixed price for specific events and for Apify platform usage.
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
---
## ๐ฏ๐ LinkedIn Ads Scraper | Bulk Ad Intelligence Scraper | Apify Actor
### ๐ Extract LinkedIn Ads Data in Seconds (No Code)
The **LinkedIn Ads Scraper (Apify Actor)** is a powerful, scalable and **SEO-optimized advertising intelligence tool** designed to extract **LinkedIn sponsored advertisements in bulk**.
It allows you to collect ad creatives, advertiser information, marketing messages, campaign trends, images, and engagement-related data for **competitor analysis, ad intelligence, market research, lead generation, media monitoring, AI datasets, and marketing optimization.**
---
### ๐ฅ Why This LinkedIn Ads Scraper?
โ Best LinkedIn Ads scraper on Apify
โ Supports **bulk keyword scraping (multi-search)**
โ Extract LinkedIn sponsored ads instantly
โ Analyze competitors' advertising strategies
โ Structured JSON / CSV / Excel output
โ Perfect for marketing intelligence
โ Ideal for ad research workflows
โ No coding required
---
### ๐ฏ What This Scraper Does (LinkedIn Ads Data Extraction)
This Apify Actor extracts **real-time sponsored ads from LinkedIn Ad Library search results.**
#### ๐ Core Features
โ
Scrape LinkedIn sponsored advertisements
โ
Bulk keyword scraping support
โ
Company filtering support
โ
Country targeting support
โ
Date range filtering
โ
Extract advertiser information
โ
Extract headlines and descriptions
โ
Extract ad creatives and images
โ
Extract ad detail URLs
โ
Automatic pagination handling
โ
High-speed extraction engine
โ
Export-ready structured datasets
---
### โก Input Configuration (Simple & Powerful)
#### ๐ฅ BULK KEYWORD MODE (SEO BOOST ๐)
````
{
"searches": \[
{
"keyword": "AI",
"company": "NVIDIA",
"country": "All",
"date": "Any"
},
{
"keyword": "Marketing",
"company": "HubSpot",
"country": "United States",
"date": "Last 30 Days"
}
],
"maxItems": 500
}
```
---
### ๐ Supported Countries
Target LinkedIn advertisements by country:
* United States
* United Kingdom
* Canada
* Germany
* France
* Spain
* Italy
* Australia
* India
* All Countries
and many more...
---
### ๐ Extracted Ads Data (Structured Output)
| Field | Description |
| -------------- | ---------------------------- |
| advertiserName | Advertiser company name |
| advertiserLogo | Advertiser logo URL |
| creativeType | Ad creative format |
| headline | Ad headline |
| description | Ad description |
| commentary | Main ad text |
| imageUrl | Ad image URL |
| imageAlt | Ad image description |
| sponsoredText | Sponsored label |
| eventDate | Event date if available |
| contentType | Image, video, carousel, etc. |
| detailsLink | Direct LinkedIn ad URL |
| keyword | Search keyword used |
| country | Selected country |
---
### ๐ก Use Cases (High Demand SEO Keywords)
This LinkedIn Ads scraper is commonly used for:
๐ฏ LinkedIn ads scraping
๐ Ad intelligence
๐ข Competitor advertising analysis
๐ Marketing research
๐ Lead generation research
๐ก Advertising monitoring
๐ค AI training datasets
๐ต๏ธ Competitor campaign tracking
๐ผ B2B marketing intelligence
๐ข Creative inspiration research
โก Bulk advertising data extraction
---
### ๐ Key Features (Apify SEO Optimized)
โก Bulk keyword scraping
๐ฏ Ad library extraction
๐ข Company filtering
๐ Country targeting
๐
Date filtering
๐ Smart pagination system
๐ง Clean structured output
๐ High-speed scraping engine
๐ Auto retry & stability system
๐พ Export-ready datasets
โ๏ธ Scalable cloud execution
---
### ๐ค Output Formats Supported
โ JSON (API ready)
โ CSV (Excel compatible)
โ Excel XLSX
โ XML
โ HTML
---
### ๐ฆ Example Output
```
{
"advertiserName": "NVIDIA",
"creativeType": "SPONSORED\_STATUS\_UPDATE",
"headline": "Must Attend AI Business Strategy Talks",
"description": "March 17-21",
"commentary": "See how executives across industries are creating real-world impact with AI.",
"imageUrl": "https://...",
"eventDate": "March 17-21",
"detailsLink": "https://www.linkedin.com/ad-library/detail/627715666",
"contentType": "image",
"keyword": "AI",
"country": "All"
}
````
---
### ๐ Built-in Dataset Views
#### ๐น Overview
Quick summary of advertisers, headlines, and ad formats.
#### ๐น Detailed Ad Information
Full creative details, descriptions, images, and URLs.
#### ๐น Ads by Advertiser
Group extracted ads by company.
#### ๐น Ads by Keyword
Analyze campaigns by search keyword.
#### ๐น Ads by Country
Compare advertising strategies across regions.
#### ๐น Media Gallery
Browse extracted ad creatives and images.
#### ๐น Compact List
Minimal export format for automation workflows.
---
### ๐ฅ Why This is the BEST LinkedIn Ads Scraper on Apify?
โ Optimized for Apify marketplace ranking
โ High-performance ad extraction engine
โ Bulk keyword support
โ Competitor intelligence ready
โ Marketing analytics included
โ Enterprise-ready scalability
โ Structured export-ready datasets
โ Perfect for SEO traffic & marketplace visibility
---
### ๐ธ Pricing
This scraper runs on a **pay-per-result pricing model**.
You only pay for successfully extracted records.
๐ณ **Price:** $1.48 / 1,000 results
---
### โ FAQ (SEO BOOST SECTION)
#### Can I scrape multiple keywords at once?
Yes โ bulk keyword mode is fully supported.
#### Can I analyze competitor ads?
Yes โ simply search competitor company names and keywords.
#### Can I filter by country?
Yes โ country filtering is supported.
#### Can I export data?
Yes โ JSON, CSV, Excel, XML and HTML are supported.
#### Is this scraper fast?
Yes โ optimized for high-speed extraction.
#### Is coding required?
No โ this is a fully no-code Apify Actor.
---
### โ ๏ธ Disclaimer
This tool is not affiliated with LinkedIn.
It is an independent data extraction solution built for publicly accessible information.
---
### ๐ Related Actors (PrimeScrape Ecosystem)
We are building a complete marketing intelligence suite:
๐ Facebook Ads Library Scraper
๐ LinkedIn Company Scraper
๐ LinkedIn Profile Scraper
๐ LinkedIn Jobs Scraper
๐ YouTube Ads Intelligence Tools
๐ Competitor Research Solutions
๐ More Coming Soon ๐
---
### ๐ PrimeScrape Ecosystem
Built for data scraping, automation, AI training datasets, lead generation, and market intelligence at scale.
๐ Marketing Intelligence
๐ข Competitor Research
๐ Advertising Analytics
๐ Lead Generation
๐ค AI Datasets
โ๏ธ Automation Pipelines
---
### ๐ฌ Support
โญโญโญโญโญ Leave a review if you enjoy this scraper.
๐ฉ Need a custom scraper or enterprise solution?
Contact us directly through Apify.
**PrimeScrape โ High-Performance Scraping Solutions Built for Scale ๐**
# Actor input Schema
## `keywords` (type: `array`):
List of keywords to search for in the LinkedIn Ads Library.
Examples:
โข ['ai', 'machine learning']
โข ['nvidia', 'cloud computing']
โข ['marketing', 'saas']
The scraper will process each keyword and collect up to maxItemsPerKeyword ads for each.
## `entreprise` (type: `string`):
Specify the company whose ads you want to scrape from the LinkedIn Ads Library. Example: 'NVIDIA', 'Google', etc. ๐ข
## `country` (type: `string`):
Choose the country you want to scrape LinkedIn ads from. You can pick 'All ๐' or any specific country! ๐
## `date` (type: `string`):
Choose how you want to sort ads by date! โฐโณ You can select 'Any' for all dates, or narrow it down by 'Last 30 days', 'This month', or 'This year'.
## `maxItemsPerKeyword` (type: `integer`):
Maximum number of ads to collect for EACH keyword.
The scraper will:
โข Scroll through results for each keyword
โข Stop when reaching this limit OR after 10 consecutive empty scrolls
โข Move to the next keyword automatically
## Actor input object example
```json
{
"keywords": [
"ai",
"cloud"
],
"entreprise": "nvidia",
"country": "All ๐",
"date": "Any",
"maxItemsPerKeyword": 60
}
````
# Actor output Schema
## `overview` (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 = {
"keywords": [
"ai",
"cloud"
],
"entreprise": "nvidia",
"country": "All ๐",
"date": "Any",
"maxItemsPerKeyword": 60
};
// Run the Actor and wait for it to finish
const run = await client.actor("delectable_incubator/linkedin-ads-scraper-low-cost").call(input);
// Fetch and print Actor results from the run's dataset (if any)
console.log('Results from dataset');
console.log(`๐พ 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);
});
// ๐ Want to learn more ๐? Go to โ 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 = {
"keywords": [
"ai",
"cloud",
],
"entreprise": "nvidia",
"country": "All ๐",
"date": "Any",
"maxItemsPerKeyword": 60,
}
# Run the Actor and wait for it to finish
run = client.actor("delectable_incubator/linkedin-ads-scraper-low-cost").call(run_input=run_input)
# Fetch and print Actor results from the run's dataset (if there are any)
print("๐พ Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"])
for item in client.dataset(run["defaultDatasetId"]).iterate_items():
print(item)
# ๐ Want to learn more ๐? Go to โ https://docs.apify.com/api/client/python/docs/quick-start
```
## CLI example
```bash
echo '{
"keywords": [
"ai",
"cloud"
],
"entreprise": "nvidia",
"country": "All ๐",
"date": "Any",
"maxItemsPerKeyword": 60
}' |
apify call delectable_incubator/linkedin-ads-scraper-low-cost --silent --output-dataset
```
## MCP server setup
```json
{
"mcpServers": {
"apify": {
"command": "npx",
"args": [
"mcp-remote",
"https://mcp.apify.com/?tools=delectable_incubator/linkedin-ads-scraper-low-cost",
"--header",
"Authorization: Bearer "
]
}
}
}
```
## OpenAPI specification
```json
{
"openapi": "3.0.1",
"info": {
"title": "LinkedIn Ads Scraper - Low-cost๐ฒ๐ฅ๐๐",
"description": "๐ Extract LinkedIn sponsored ads by keyword, company, or location. Collect advertiser names, ad headlines, descriptions, image URLs, call-to-actions, and ad page links. Ideal for ad intelligence, competitor monitoring, market research, campaign analysis & social media advertising insights ๐๐",
"version": "0.0",
"x-build-id": "rbFVNaJ5EiNyzeVll"
},
"servers": [
{
"url": "https://api.apify.com/v2"
}
],
"paths": {
"/acts/delectable_incubator~linkedin-ads-scraper-low-cost/run-sync-get-dataset-items": {
"post": {
"operationId": "run-sync-get-dataset-items-delectable_incubator-linkedin-ads-scraper-low-cost",
"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": {
"$ref": "#/components/schemas/inputSchema"
}
}
}
},
"parameters": [
{
"name": "token",
"in": "query",
"required": true,
"schema": {
"type": "string"
},
"description": "Enter your Apify token here"
}
],
"responses": {
"200": {
"description": "OK"
}
}
}
},
"/acts/delectable_incubator~linkedin-ads-scraper-low-cost/runs": {
"post": {
"operationId": "runs-sync-delectable_incubator-linkedin-ads-scraper-low-cost",
"x-openai-isConsequential": false,
"summary": "Executes an Actor and returns information about the initiated run in response.",
"tags": [
"Run Actor"
],
"requestBody": {
"required": true,
"content": {
"application/json": {
"schema": {
"$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": {
"$ref": "#/components/schemas/runsResponseSchema"
}
}
}
}
}
}
},
"/acts/delectable_incubator~linkedin-ads-scraper-low-cost/run-sync": {
"post": {
"operationId": "run-sync-delectable_incubator-linkedin-ads-scraper-low-cost",
"x-openai-isConsequential": false,
"summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.",
"tags": [
"Run Actor"
],
"requestBody": {
"required": true,
"content": {
"application/json": {
"schema": {
"$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": [
"keywords"
],
"properties": {
"keywords": {
"title": "โ๏ธ๐ Keywords for Scraping Ads Metadata (Bulk)",
"type": "array",
"description": "List of keywords to search for in the LinkedIn Ads Library.\n\nExamples:\nโข ['ai', 'machine learning']\nโข ['nvidia', 'cloud computing']\nโข ['marketing', 'saas']\n\nThe scraper will process each keyword and collect up to maxItemsPerKeyword ads for each.",
"default": [
"ai",
"cloud"
],
"items": {
"type": "string"
}
},
"entreprise": {
"title": "๐ข Enter the Company Name for Ads Metadata",
"type": "string",
"description": "Specify the company whose ads you want to scrape from the LinkedIn Ads Library. Example: 'NVIDIA', 'Google', etc. ๐ข",
"default": "nvidia"
},
"country": {
"title": "๐ Select the Country for Scraping Ads",
"enum": [
"All ๐",
"Albania ๐ฆ๐ฑ",
"Algeria ๐ฉ๐ฟ",
"Andorra ๐ฆ๐ฉ",
"Angola ๐ฆ๐ด",
"Antigua and Barbuda ๐ฆ๐ฌ",
"Argentina ๐ฆ๐ท",
"Armenia ๐ฆ๐ฒ",
"Australia ๐ฆ๐บ",
"Austria ๐ฆ๐น",
"Azerbaijan ๐ฆ๐ฟ",
"Bahamas ๐ง๐ธ",
"Bahrain ๐ง๐ญ",
"Bangladesh ๐ง๐ฉ",
"Barbados ๐ง๐ง",
"Belarus ๐ง๐พ",
"Belgium ๐ง๐ช",
"Belize ๐ง๐ฟ",
"Benin ๐ง๐ฏ",
"Bhutan ๐ง๐น",
"Bolivia ๐ง๐ด",
"Bosnia and Herzegovina ๐ง๐ฆ",
"Botswana ๐ง๐ผ",
"Brazil ๐ง๐ท",
"Brunei ๐ง๐ณ",
"Bulgaria ๐ง๐ฌ",
"Burkina Faso ๐ง๐ซ",
"Burundi ๐ง๐ฎ",
"Cabo Verde ๐จ๐ป",
"Cambodia ๐ฐ๐ญ",
"Cameroon ๐จ๐ฒ",
"Canada ๐จ๐ฆ",
"Central African Republic ๐จ๐ซ",
"Chad ๐น๐ฉ",
"Chile ๐จ๐ฑ",
"China ๐จ๐ณ",
"Colombia ๐จ๐ด",
"Comoros ๐ฐ๐ฒ",
"Congo ๐จ๐ฌ",
"Congo (Democratic Republic) ๐จ๐ฉ",
"Costa Rica ๐จ๐ท",
"Croatia ๐ญ๐ท",
"Cuba ๐จ๐บ",
"Cyprus ๐จ๐พ",
"Czech Republic ๐จ๐ฟ",
"Denmark ๐ฉ๐ฐ",
"Djibouti ๐ฉ๐ฏ",
"Dominica ๐ฉ๐ฒ",
"Dominican Republic ๐ฉ๐ด",
"Ecuador ๐ช๐จ",
"Egypt ๐ช๐ฌ",
"El Salvador ๐ธ๐ป",
"Equatorial Guinea ๐ฌ๐ถ",
"Eritrea ๐ช๐ท",
"Estonia ๐ช๐ช",
"Eswatini ๐ธ๐ฟ",
"Ethiopia ๐ช๐น",
"Fiji ๐ซ๐ฏ",
"Finland ๐ซ๐ฎ",
"France ๐ซ๐ท",
"Gabon ๐ฌ๐ฆ",
"Gambia ๐ฌ๐ฒ",
"Georgia ๐ฌ๐ช",
"Germany ๐ฉ๐ช",
"Ghana ๐ฌ๐ญ",
"Greece ๐ฌ๐ท",
"Grenada ๐ฌ๐ฉ",
"Guatemala ๐ฌ๐น",
"Guinea ๐ฌ๐ณ",
"Guinea-Bissau ๐ฌ๐ผ",
"Guyana ๐ฌ๐พ",
"Haiti ๐ญ๐น",
"Honduras ๐ญ๐ณ",
"Hungary ๐ญ๐บ",
"Iceland ๐ฎ๐ธ",
"India ๐ฎ๐ณ",
"Indonesia ๐ฎ๐ฉ",
"Iran ๐ฎ๐ท",
"Iraq ๐ฎ๐ถ",
"Ireland ๐ฎ๐ช",
"Italy ๐ฎ๐น",
"Jamaica ๐ฏ๐ฒ",
"Japan ๐ฏ๐ต",
"Jordan ๐ฏ๐ด",
"Kazakhstan ๐ฐ๐ฟ",
"Kenya ๐ฐ๐ช",
"Kiribati ๐ฐ๐ฎ",
"Korea (North) ๐ฐ๐ต",
"Korea (South) ๐ฐ๐ท",
"Kuwait ๐ฐ๐ผ",
"Kyrgyzstan ๐ฐ๐ฌ",
"Laos ๐ฑ๐ธ",
"Latvia ๐ฑ๐ป",
"Lebanon ๐ฑ๐ง",
"Lesotho ๐ฑ๐ธ",
"Liberia ๐ฑ๐ธ",
"Libya ๐ฑ๐พ",
"Liechtenstein ๐ฑ๐ฎ",
"Lithuania ๐ฑ๐น",
"Luxembourg ๐ฑ๐บ",
"Madagascar ๐ฒ๐ฌ",
"Malawi ๐ฒ๐ผ",
"Malaysia ๐ฒ๐พ",
"Maldives ๐ฒ๐ป",
"Mali ๐ฒ๐ฑ",
"Malta ๐ฒ๐น",
"Marshall Islands ๐ฒ๐ญ",
"Mauritania ๐ฒ๐ท",
"Mauritius ๐ฒ๐บ",
"Mexico ๐ฒ๐ฝ",
"Micronesia ๐ซ๐ฒ",
"Moldova ๐ฒ๐ฉ",
"Monaco ๐ฒ๐จ",
"Mongolia ๐ฒ๐ณ",
"Montenegro ๐ฒ๐ช",
"Morocco ๐ฒ๐ฆ",
"Mozambique ๐ฒ๐ฟ",
"Myanmar ๐ฒ๐ฒ",
"Namibia ๐ณ๐ฆ",
"Nauru ๐ณ๐ท",
"Nepal ๐ณ๐ต",
"Netherlands ๐ณ๐ฑ",
"New Zealand ๐ณ๐ฟ",
"Nicaragua ๐ณ๐ฎ",
"Niger ๐ณ๐ช",
"Nigeria ๐ณ๐ฌ",
"North Macedonia ๐ฒ๐ฐ",
"Norway ๐ณ๐ด",
"Oman ๐ด๐ฒ",
"Pakistan ๐ต๐ฐ",
"Palau ๐ต๐ผ",
"Panama ๐ต๐ฆ",
"Papua New Guinea ๐ต๐ฌ",
"Paraguay ๐ต๐พ",
"Peru ๐ต๐ช",
"Philippines ๐ต๐ญ",
"Poland ๐ต๐ฑ",
"Portugal ๐ต๐น",
"Qatar ๐ถ๐ฆ",
"Romania ๐ท๐ด",
"Russia ๐ท๐บ",
"Rwanda ๐ท๐ผ",
"Saint Kitts and Nevis ๐ฐ๐ณ",
"Saint Lucia ๐ฑ๐จ",
"Saint Vincent and the Grenadines ๐ป๐จ",
"Samoa ๐ผ๐ธ",
"San Marino ๐ธ๐ฒ",
"Sao Tome and Principe ๐ธ๐น",
"Saudi Arabia ๐ธ๐ฆ",
"Senegal ๐ธ๐ณ",
"Serbia ๐ท๐ธ",
"Seychelles ๐ธ๐จ",
"Sierra Leone ๐ธ๐ฑ",
"Singapore ๐ธ๐ฌ",
"Slovakia ๐ธ๐ฐ",
"Slovenia ๐ธ๐ฎ",
"Solomon Islands ๐ธ๐ง",
"Somalia ๐ธ๐ด",
"South Africa ๐ฟ๐ฆ",
"South Sudan ๐ธ๐ธ",
"Spain ๐ช๐ธ",
"Sri Lanka ๐ฑ๐ฐ",
"Sudan ๐ธ๐ฉ",
"Suriname ๐ธ๐ท",
"Sweden ๐ธ๐ช",
"Switzerland ๐จ๐ญ",
"Syria ๐ธ๐พ",
"Taiwan ๐น๐ผ",
"Tajikistan ๐น๐ฏ",
"Tanzania ๐น๐ฟ",
"Thailand ๐น๐ญ",
"Timor-Leste ๐น๐ฑ",
"Togo ๐น๐ฌ",
"Tonga ๐น๐ด",
"Trinidad and Tobago ๐น๐น",
"Tunisia ๐น๐ณ",
"Turkey ๐น๐ท",
"Turkmenistan ๐น๐ฒ",
"Tuvalu ๐น๐ป",
"Uganda ๐บ๐ฌ",
"Ukraine ๐บ๐ฆ",
"United Arab Emirates ๐ฆ๐ช",
"United Kingdom ๐ฌ๐ง",
"United States ๐บ๐ธ",
"Uruguay ๐บ๐พ",
"Uzbekistan ๐บ๐ฟ",
"Vanuatu ๐ป๐บ",
"Vatican City ๐ป๐ฆ",
"Venezuela ๐ป๐ช",
"Vietnam ๐ป๐ณ",
"Yemen ๐พ๐ช",
"Zambia ๐ฟ๐ฒ",
"Zimbabwe ๐ฟ๐ผ"
],
"type": "string",
"description": "Choose the country you want to scrape LinkedIn ads from. You can pick 'All ๐' or any specific country! ๐",
"default": "All ๐"
},
"date": {
"title": "๐
Choose Date Sort (When Ads Were Posted) โฐโณ",
"enum": [
"Any",
"Last 30 days",
"This month",
"This year",
"Last year"
],
"type": "string",
"description": "Choose how you want to sort ads by date! โฐโณ You can select 'Any' for all dates, or narrow it down by 'Last 30 days', 'This month', or 'This year'.",
"default": "Any"
},
"maxItemsPerKeyword": {
"title": "๐ฏ Maximum Ads Per Keyword",
"type": "integer",
"description": "Maximum number of ads to collect for EACH keyword.\n\nThe scraper will:\nโข Scroll through results for each keyword\nโข Stop when reaching this limit OR after 10 consecutive empty scrolls\nโข Move to the next keyword automatically",
"default": 60
}
}
},
"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
}
}
}
}
}
}
}
}
}
}
```