LinkedIn Ads Scraper

This Apify Actor is designed to scrape advertisement data from LinkedIn. It retrieves detailed information about ads, including advertiser details, ad content, media, impressions, and more.

How to Use

1. Input Configuration: The Actor requires the following input parameters:

   • companyOrAdvertiserName (string, required): The name of the company or advertiser to search for ads, e.g., Nike.
   • keywords (string, optional): Keywords to filter ads by content.
   • countries (string, optional): Country codes to filter ads, comma-separated (e.g., US,GB,CA) or ALL for all countries. Default is ALL.
   • dateOption (string, optional): The date range to filter ads. Options:
     • last-30-days: Ads from the last 30 days.
     • current-year: Ads from the current year.
     • last-year: Ads from the last year.
     • custom-date-range: Specify a custom date range.
   • customDateRange (object, optional): Used only if dateOption is set to custom-date-range. Includes:
     • startDate (string, required): Start date in YYYY-MM-DD format.
     • endDate (string, required): End date in YYYY-MM-DD format.
   • size (integer, optional): The maximum number of ads to scrape. Default is 10.

2. Run the Actor: You can run the Actor on the Apify platform or locally using the Apify SDK. Provide the required input parameters in the following format:

   {
       "companyOrAdvertiserName": "Nike",
       "keywords": "shoes",
       "countries": "US,GB",
       "dateOption": "last-30-days",
       "size": 20
   }
   

3. Output: The Actor will return a JSON array containing the scraped ad data. Each ad includes fields such as:

   • id: The unique ID of the ad.
   • ad_url: The URL of the ad details page.
   • ad_text: The content of the ad.
   • ad_media_type: The type of media in the ad (e.g., image, video, text, job, doc).
   • ad_image_url: The URL of the ad image (if available).
   • ad_video_urls: The URLs of the ad video (if available).
   • ad_destination: The destination of the ad.
     • url: The external link associated with the ad.
     • title: The title of the destination link.
     • description: A brief description of the destination link.
     • other_description: Additional description if available.
   • ad_active_dates_raw: The raw text of the ad's active date range.
   • ad_start_date: The start date of the ad.
   • ad_end_date: The end date of the ad.
   • job_info: An object containing job-related information (if applicable, ad_media_type='job'):
     • title: The job title.
     • avatar: The URL of the job posting's logo.
   • doc_info: An object containing document-related information (if applicable, ad_media_type='doc'):
     • title: The document title.
     • subTitle: The document subtitle.
     • coverPages: A list of URLs for the document's cover pages.
   • advertiser: An object containing advertiser details:
     • name: The name of the advertiser.
     • linkedin_url: The LinkedIn profile URL of the advertiser.
     • avatar: The URL of the advertiser's logo.
     • industry: The industry of the advertiser.
     • generic_entity: Additional information about the advertiser.
   • impressions: An object containing impression metrics:
     • total_impressions: The total number of impressions for the ad.
     • impression_name: The name of the impression metric.
     • impression_values: A list of impression metrics, including names and values.

4. Example Output:

   [
       {
           "id": "732489586",
           "ad_url": "https://www.linkedin.com/ad-library/detail/732489586",
           "ad_text": "Check out our latest running shoes!",
           "ad_media_type": "image",
           "ad_image_url": "https://example.com/ad-image.png",
           "ad_video_urls": null,
           "ad_destination": {
               "url": "https://www.nike.com",
               "title": "Nike - Official Site",
               "description": "Shop the latest Nike shoes, clothing, and gear."
           },
           "ad_active_dates_raw": "Ran from Jan 1, 2023 to Jan 31, 2023",
           "ad_start_date": "2023-01-01",
           "ad_end_date": "2023-01-31",
           "advertiser": {
               "name": "Nike",
               "linkedin_url": "https://www.linkedin.com/company/nike",
               "avatar": "https://example.com/logo.png",
               "industry": "Sportswear",
               "generic_entity": "Global Brand"
           },
           "impressions": {
               "total_impressions": "50k-100k",
               "impression_name": "Country",
               "impression_values": [
                   {
                       "name": "Sweden",
                       "value": "99%"
                   },
                   {
                       "name": "United States",
                       "value": "1%"
                   }
               ]
           }
       }
   ]
   

Use Cases

• Analyze LinkedIn advertisements for market research.
• Collect data on competitors' ad campaigns.
• Evaluate ad performance metrics such as impressions and media types.