LinkedIn Ad Library Scraper — Ads, Impressions & Targeting

Turn any LinkedIn Ad Library search into a structured stream of sponsored ads. Start from a company, keyword, payer, country, or a pasted Ad Library URL, and get full ad copy, creative links, run dates, impression ranges, per-country impression splits, and targeting parameters as clean rows.

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Why use this scraper?

• Impressions and targeting, not just creatives — impression ranges, per-country splits, and the targeting facets an advertiser used, parsed into typed fields.
• Filter before you pay — narrow by impression volume and by targeting category server-side, so you only get charged for rows you actually want.
• Many searches, one run — each entry in searches carries its own company, country, date window, and filters.
• Numeric impressions — totalImpressionsMin / totalImpressionsMax alongside the raw "5k-10k" string, so you can sort and threshold without parsing text.
• No browser — every page is fetched over plain HTTP, which is why runs are fast and cheap.
• You are not billed for failures — an ad whose detail page fails is logged and skipped, never pushed and never charged.

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Overview

The LinkedIn Ad Library publishes every sponsored ad running on LinkedIn. For ads shown to EU audiences it additionally publishes impression volumes and targeting parameters under DSA transparency rules.

This actor turns that library into a dataset: one row per ad. It's built for competitive-intelligence teams tracking a rival's creatives and spend signals, agencies auditing a category, and researchers studying commercial advertising.

Ads outside the EU still return the full creative, copy, payer, and run dates — but LinkedIn does not publish impressions or targeting for them, so those fields are absent. That's a limit of the source, not the scraper.

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Supported inputs

You can start a run four ways, and mix them freely:

1. Company, keyword, or payer

{ "companies": ["HubSpot"], "keywords": ["AI agents"], "payers": ["HubSpot, Inc."] }

2. Independent searches, each with its own filters

{
  "searches": [
    { "company": "HubSpot", "countries": ["DE"], "dateOption": "last-30-days" },
    { "keyword": "AI agents", "includedTargetingFacetCategories": ["JOB"] }
  ]
}

3. A pasted Ad Library URL — search pages or a single ad detail page

{
  "startUrls": [
    "https://www.linkedin.com/ad-library/search?accountOwner=HubSpot&countries=DE",
    "https://www.linkedin.com/ad-library/detail/1441861963"
  ]
}

4. Filters on top of any of the above — country, date window, impression range, targeting categories.

Not supported: LinkedIn feed posts, organic company posts, Campaign Manager data, ad spend in currency (LinkedIn publishes impression ranges, never cost), and any page behind a login wall.

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Use cases

Audience	What they use it for
Competitive intelligence	Track a competitor's live creatives, messaging shifts, and relative impression volume
Performance marketing	Mine winning hooks, headlines, and CTAs across a category before writing new ads
Agencies	Audit a prospect's current advertising and build the pitch deck from real data
Market research	Measure category-level advertising pressure and geographic mix over time
Policy & academic research	Study DSA-disclosed targeting parameters and impression distribution
Brand protection	Find who is running ads that name your brand, and which entity paid for them

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How it works

1. Your companies, keywords, payers, and searches entries are turned into Ad Library search URLs with your filters applied.
2. Each search page is fetched over HTTP and read directly from the server-rendered markup.
3. Pagination follows the Ad Library's own pagination endpoint until maxItems is reached, backing off automatically if LinkedIn rate-limits.
4. When scrapeAdDetails is on, each ad's detail page is fetched for payer, run dates, impressions, and targeting.
5. Rows are pushed to the dataset as they complete, ready to export as JSON, CSV, or Excel.

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Input configuration

Field	Type	Default	Description
companies	array	[]	Advertiser/company names — one search each
keywords	array	[]	Free-text keyword searches
payers	array	[]	Paying-entity names
countries	array	[]	ISO country codes, e.g. ["DE","FR"]
dateOption	string	all-time	all-time, last-30-days, current-month, current-year, last-year, custom-date-range
startDate / endDate	string	–	YYYY-MM-DD; when set they take priority over dateOption
impressionsMinValue	integer	–	Lower impression bound, combined with its unit
impressionsMinUnit	string	thousand	none, thousand, or million
impressionsMaxValue	integer	–	Upper impression bound
impressionsMaxUnit	string	thousand	none, thousand, or million
includedTargetingFacetCategories	array	[]	Ad targeting must use these: LANGUAGE, LOCATION, AUDIENCE, DEMOGRAPHIC, COMPANY, EDUCATION, JOB, INTERESTS_AND_TRAITS
excludedTargetingFacetCategories	array	[]	Ad targeting must NOT use these; same value list
searches	array	[]	Independent searches; each entry may override any filter above
startUrls	array	[]	Ad Library search or detail URLs
maxItems	integer	100	Maximum ads to return
scrapeAdDetails	boolean	true	Fetch each ad's detail page for impressions, targeting, and payer
includeEmployerBranding	boolean	false	Include employer-brand promos alongside sponsored ads
sessionCookie / sessionCookies	string / array	–	Optional li_at cookie(s) if a search returns only employer-brand results
proxy	object	Apify datacenter	Proxy configuration
maxConcurrency	integer	3	Parallel detail fetches
minDelay / maxDelay	integer	1 / 3	Delay range in seconds between requests
debug	boolean	false	Verbose per-request logging

Note on impression filters: LinkedIn requires both bounds. If you set only one, the actor fills the other in automatically so your search still runs.

Example — a competitor's German ads above 100k impressions

{
  "companies": ["HubSpot"],
  "countries": ["DE"],
  "impressionsMinValue": 100,
  "impressionsMinUnit": "thousand",
  "maxItems": 100
}

Example — two unrelated searches in one run

{
  "searches": [
    { "company": "HubSpot", "countries": ["DE"], "dateOption": "last-30-days" },
    { "keyword": "AI agents", "includedTargetingFacetCategories": ["JOB"] }
  ],
  "maxItems": 200
}

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Output overview

One row per ad. Every row carries identity (adId, adLibraryUrl), the advertiser, the creative and copy, and the CTA destination. Rows for EU-facing ads additionally carry the payer, run window, impression range, per-country impression split, and targeting facets.

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Output sample

Real row, trimmed — produced by { "companies": ["HubSpot"], "countries": ["DE"] }:

{
  "adId": "1441861963",
  "adLibraryUrl": "https://www.linkedin.com/ad-library/detail/1441861963",
  "advertiserName": "HubSpot",
  "advertiserBio": "Promoted",
  "advertiserUrl": "https://www.linkedin.com/company/68529",
  "isPromoted": true,
  "adStatus": "ACTIVE",
  "format": "VIDEO",
  "headline": "Routine-Anfragen erledigt? Gute Arbeit.",
  "body": "HubSpot's Customer Agent erledigt Routineanfragen von allein und holt dich nur dazu, wenn es zählt. …",
  "ctas": ["Mehr erfahren"],
  "clickUrl": "http://hubspot.de",
  "imageUrl": "https://media.licdn.com/dms/image/v2/D4D10AQH3o7vyy-TVcA/videocover-high/…",
  "paidBy": "HubSpot, Inc.",
  "availabilityRaw": "Ran from Jul 1, 2026 to Jul 25, 2026",
  "firstShownAt": "2026-07-01",
  "lastShownAt": "2026-07-25",
  "totalImpressionsRaw": "5k-10k",
  "totalImpressionsMin": 5000,
  "totalImpressionsMax": 10000,
  "impressionsByCountry": [{ "country": "Germany", "percentage": 100 }],
  "targeting": [
    { "category": "Language", "included": ["Targeting includes Deutsch"], "excluded": [] },
    { "category": "Job", "included": ["Member"], "excluded": [] }
  ],
  "scrapedAt": "2026-07-25T19:48:25.821Z"
}

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Key output fields

Identity — adId, adLibraryUrl, startUrl, scrapedAt

Advertiser — advertiserName, advertiserBio, advertiserUrl, advertiserLogo, paidBy, isPromoted

Creative — format (SINGLE_IMAGE, VIDEO, CAROUSEL, DOCUMENT, EVENT, TEXT), headline, body, imageUrl, imageUrls, videoUrl, videoPosterUrl, documentUrl

Destination — ctas, clickUrl, externalLinksInText

Run window — availabilityRaw, firstShownAt, lastShownAt, adStatus

Reach (EU-facing ads) — totalImpressionsRaw, totalImpressionsMin, totalImpressionsMax, impressionsByCountry[]

Targeting (EU-facing ads) — targeting[] with category, included[], excluded[], raw

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Pricing

Pay per event, tiered by your Apify plan:

Plan tier	Per ad
Free	$0.0015
Bronze	$0.0009
Silver	$0.0007
Gold and above	$0.0004

Plus $0.00005 per actor start. Ads that fail detail extraction are never pushed and never charged.

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FAQ

Do I need a LinkedIn account or cookie? No. The actor reads the public Ad Library anonymously. sessionCookie exists only as a fallback if a particular search returns nothing but employer-brand promos.

Why are impressions and targeting missing on some ads? LinkedIn publishes them only for ads shown to EU audiences, under DSA transparency rules. A US-only campaign returns creatives and run dates but no impressions. Filtering by an EU country is the reliable way to get rows that always have them.

Can I get ad spend in dollars? No. LinkedIn publishes impression ranges, never cost. Any tool claiming a spend figure is estimating it.

Why did I get fewer ads than maxItems? Either the search genuinely has fewer matches, or LinkedIn stopped serving more results. The run's status message says which, so a short result never looks like a complete one.

Can I filter by impressions with only a minimum? Yes. LinkedIn itself requires both bounds, so the actor fills the missing side in for you.

Does it scrape organic LinkedIn posts? No — sponsored ads from the Ad Library only.

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Support

Found a bug or need a field that isn't here? Open an issue on the actor's Issues tab and it will be looked at.

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Additional services

Need a tailored export, a different schema, a scheduled feed into your warehouse, or a scraper for another site? Custom work is available — get in touch through the Apify profile.

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Explore more scrapers

Browse the full collection at apify.com/memo23 — scrapers for job boards, real-estate portals, review sites, social platforms, and more.

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🤖 For AI Agents & LLM Apps

Compact reference for AI agents calling this actor via the Apify MCP server or the Apify API (actor: memo23/linkedin-ads-scraper).

Purpose: Scrapes the LinkedIn Ad Library — one row per sponsored ad, including DSA-disclosed impression ranges and targeting facets for EU-facing ads.

Minimal input:

{ "companies": ["HubSpot"], "countries": ["DE"], "maxItems": 25 }

Output: one dataset row per ad — adId, adLibraryUrl, advertiserName, advertiserBio, advertiserUrl, isPromoted, adStatus, format, headline, body, ctas[], clickUrl, externalLinksInText[], imageUrl, imageUrls[], videoUrl, documentUrl, paidBy, availabilityRaw, firstShownAt, lastShownAt, totalImpressionsRaw, totalImpressionsMin, totalImpressionsMax, impressionsByCountry[{country, percentage}], targeting[{category, included[], excluded[]}], scrapedAt.

Behaviors an agent should know:

• Always set maxItems; a broad keyword can match thousands of ads.
• impressionsMinValue requires a unit (none/thousand/million); a one-sided range is completed automatically.
• includedTargetingFacetCategories accepts only: LANGUAGE, LOCATION, AUDIENCE, DEMOGRAPHIC, COMPANY, EDUCATION, JOB, INTERESTS_AND_TRAITS.
• Impressions and targeting are absent for non-EU ads — don't treat that as a scrape failure.
• Billing is per dataset item plus a per-run start fee; failed ads are not pushed and not charged.
• Set scrapeAdDetails: false for a cheap, fast listing-only pass without impressions or targeting.

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⚠️ Disclaimer

This Actor is an independent tool and is not affiliated with, endorsed by, or sponsored by LinkedIn Corporation, Microsoft Corporation, or any of their subsidiaries. All trademarks mentioned are the property of their respective owners.

The scraper accesses only the publicly available LinkedIn Ad Library, which LinkedIn publishes for advertising transparency — no authenticated endpoints, paid features, or member content behind the linkedin.com login wall. The optional sessionCookie input is supplied by the user, applies only to those same public Ad Library pages, and is never required. Users are responsible for ensuring their use complies with LinkedIn's Terms of Service, applicable data-protection law (GDPR, CCPA, etc.), and any contractual obligations of their own organization.

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