Competitor Ad Library Scraper — Google Ads Transparency + LinkedIn

Every ad your competitors run on Google (Search, Display, YouTube) and LinkedIn, pulled from the public ad-transparency libraries: advertiser, format, ad text, headline, image or video, first and last shown, days running, and the regions it ran in. Search by company name, domain or Google advertiser id. Plain HTTP: no browser, no login, no API key. $1 per 1,000 ads.

Sample output

Example: set competitors: ["hubspot.com"], sources: ["google"], googleRegion: "US" and sort the dataset by daysRunning — HubSpot's top text ad has run 1,832 days in 17 regions, and that one column tells you which competitor ads actually pay before you write a word of your own copy.

Why it is cheap

Google's Ads Transparency Center loads its results from its own JSON endpoints, and LinkedIn's Ad Library is server-rendered HTML. This Actor calls those directly, so it never starts a headless browser and never chains other Actors. One request returns up to 40 Google ads or about 24 LinkedIn ads.

What you get

Field	Source	Notes
competitor	both	The input line this row came from.
source	both	google or linkedin.
advertiser, advertiserId	both	Google's id looks like AR….
creativeId / adId	google / linkedin	Stable ad id.
format	both	Google: text · image · video. LinkedIn: e.g. Single Image Ad, Video Ad.
firstShown, lastShown, daysRunning	google	daysRunning is the quickest signal of a winning ad: advertisers stop paying for ads that lose.
regions[]	google, with details on	Each region the ad ran in and the last date it ran there.
adText, headline, adTextTruncated	linkedin	adTextFull adds the untruncated text when details are on.
imageUrl(s), previewUrl	both	Creative image, or the video preview.
adUrl	both	The ad's own page in the public library.
advertiserUrl, paidBy	linkedin, with details on	The advertiser's LinkedIn page and its "Paid for by" entity.

A real record

From a live run on 2026-10-04 (input Salesforce, LinkedIn):

{
  "competitor": "Salesforce",
  "source": "linkedin",
  "adId": "1630842716",
  "advertiser": "Salesforce",
  "format": "Single Image Ad",
  "creativeType": "SPONSORED_STATUS_UPDATE",
  "headline": "「Salesforceの営業はチーム戦。だから成長できる」。IT未経験から常務執行役員になったリーダーのキャリア論",
  "adTextTruncated": true,
  "adUrl": "https://www.linkedin.com/ad-library/detail/1630842716"
}

And a Google row from the same day (input hubspot.com, region US, details on): format text, firstShown 2026-07-31, lastShown 2026-10-04, daysRunning 66, run in 6 regions.

How to use it

• Competitor swipe file: list 5–20 competitors, run weekly, sort by daysRunning — the long-running ads are the ones that pay.
• New-campaign alert: schedule daily and diff creativeId / adId against yesterday's dataset.
• Agency pitch deck: one run per prospect's top three competitors, exported to CSV.
• n8n / Make / Zapier: call the run-sync endpoint and read the dataset.

Use cases

• Google Ads Transparency scraper: pull every ad a brand runs on Google Search, Display and YouTube — no login, no API key, no browser. The Google Ads Transparency Center is public; this Actor reads it directly.
• LinkedIn Ad Library scraper: scrape a competitor's sponsored content, video ads and single-image ads from the LinkedIn Ad Library without a browser.
• Competitor ad spy: see which creatives have been running the longest (daysRunning) — those are the ones that convert, and they are visible in the Google Ads Transparency data.
• Ad creative dataset for agencies: one run per client pitch, exported to CSV or JSON and ready to drop into a deck.
• Ad monitoring via n8n / Make / Zapier: schedule daily, diff new creativeId values against yesterday, get alerted when a competitor launches a campaign.

Inputs

Input	Default	Notes
competitors	["hubspot.com"]	One per line: a domain (hubspot.com), a company name (Salesforce) or a Google advertiser id (AR…). Up to 50.
sources	google	Add linkedin together with a RESIDENTIAL proxy (see Limits).
maxAdsPerSource	40	Caps rows and cost per competitor per library.
googleRegion	anywhere	ISO country code such as US or GB.
linkedinCountries, linkedinDateOption	all, any	LinkedIn's own filters.
linkedinExactAdvertiser	true	Keeps only ads whose advertiser name contains the competitor's name. LinkedIn's search is loose without it.
includeDetails	false	One extra request per ad: Google regions, full LinkedIn text, paid-by. Slower.
proxyConfiguration	off	Needed for LinkedIn (RESIDENTIAL group); for Google only if the log says blocked.

Pricing (pay per event)

Event	Price
Ad pushed to the dataset	$0.001 each — $1 per 1,000 ads

No start fee. Searches that fail, are blocked or find nothing are not charged. Example: 10 competitors × 40 Google ads = 400 ads = $0.40.

Limits, stated plainly

• Meta (Facebook/Instagram) is not covered. Meta's Ad Library API needs a token tied to an identity-verified Facebook account, and its web page is a JavaScript app. It is left out rather than done badly.
• LinkedIn refuses Apify's datacenter IPs. From the platform, LinkedIn answered HTTP 403 both with no proxy and with the datacenter proxy (tested 2026-10-04); from a home connection it answers normally. Use the RESIDENTIAL proxy group for LinkedIn; residential proxy traffic is billed by Apify on top of the per-ad price. A blocked LinkedIn search is logged and not charged.
• Google rate-limits by IP. Requests are paced at least 3 seconds apart per site and that cannot be changed, but Google still returns HTTP 429 to an address that has made many searches. When it does, that search is logged blocked, is not charged, and the Actor moves on. Turn on the proxy input for big runs.
• A domain search on Google returns ads that point at that domain, which can include resellers and affiliates. Search by company name or advertiser id to get only the brand's own ads.
• Both libraries can change their format without notice. Every field is read defensively (a change gives null, not a crash) and the parsers are tested against pinned fixtures from the 2026-10-04 live responses.
• These are public transparency libraries, but each platform has its own terms on reuse of the data. Check them before you resell it.

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