LinkedIn Ad Library Change Monitor

Monitor competitor LinkedIn ads and get a clean change feed from the public LinkedIn Ad Library. Each scheduled run compares the current result set with the previous snapshot and returns only what changed: new ads, disappeared ads, and advertisers never seen before.

This is a deterministic LinkedIn advertising monitor for competitive intelligence, campaign tracking, lead-generation research, and daily or weekly alerts. It uses no login, cookies, AI, or external Actor.

At a glance

Capability	Details
Data source	Public LinkedIn Ad Library, logged out
Search targets	Advertiser, payer, keyword, or direct Ad Library URL
Input	One company or a list of monitored inputs
State	Previous snapshot in the Actor key-value store
Change feed	New ads, disappeared ads, and new advertisers
Reference data	Complete current snapshot per monitor
Scheduling	Designed for daily or weekly runs
Authentication	None required
AI enrichment	None; deterministic normalization and set comparison

What this Actor does

• Tracks one company or a list of competitors in one run.
• Searches by advertiser, payer, keyword, or a direct LinkedIn Ad Library URL.
• Detects new LinkedIn ads and ads that disappeared since the previous complete run.
• Flags a new advertiser appearing in the monitored results.
• Preserves a full current snapshot for audit and historical comparison.
• Calculates active-ad count, ads first seen in the period, average observed longevity, format mix, and payer-to-advertiser mapping.
• Keeps state isolated by monitorId, so separate competitors, users, and schedules do not share baselines.

Search phrases this Actor answers

• track competitor LinkedIn ads
• monitor LinkedIn Ad Library
• get alerts on new LinkedIn ads
• detect when competitor ads disappear
• see which companies advertise on LinkedIn
• track LinkedIn advertiser and payer activity
• compare competitor ad campaigns over time
• export LinkedIn ad change events to a dataset

Why the change feed is useful

Most ad-library scrapers return a flat dump that must be compared manually. This Actor does the set comparison for you. The first run creates a baseline and intentionally emits no new alerts. Later complete runs emit only differences, so the changes dataset is suitable for schedules, downstream automations, and daily review.

Results are conservative: if LinkedIn truncates the page at maxResults, returns a challenge/block page, or produces an unparseable empty response, the previous snapshot is not replaced and false disappearance alerts are avoided.

Event semantics

Situation	Output
First run for a new monitorId and scope	Baseline only; no change alerts
Complete run with an ad not in the previous snapshot	new
Complete run with a previous ad no longer present	disappeared
Advertiser never seen in this monitor's history	new-advertiser
Result set truncated at maxResults	Change alerts are suppressed
LinkedIn challenge, block, or parser failure	Previous snapshot is preserved

This Actor vs similar LinkedIn Actors

Capability	This Actor	SolidCode LinkedIn Ads Scraper	Jaybird LinkedIn Ad Library Scraper
Primary job	Monitor changes between scheduled runs	Extract LinkedIn ads in bulk	Extract LinkedIn ads and optional details
Output	Change events plus full snapshot	Flat ad rows	Flat ad rows with basic/enriched modes
Stateful baseline	Yes, isolated by monitorId	Not the core workflow	Not the core workflow
Alerts	New, disappeared, new advertiser	Consumer compares results separately	Consumer compares results separately
Search	Advertiser, payer, keyword, direct URL	Keyword, advertiser, direct URL	Company, payer, keyword, direct URL
Public/no login	Yes	Yes	Yes
Indicative pricing	$0.50 / 1,000 tracked ads + change events	$0.50 / 1,000 basic; $0.90 / 1,000 enriched	$0.35 / 1,000 basic; $1.50 / 1,000 enriched

The positioning is intentionally different: those Actors are optimized for extracting ad data, while this Actor is optimized for recurring monitoring and a ready-to-use change feed. Competitor prices are observed Store prices and can change.

Other Actors from the same publisher

Use these complementary Actors for a broader monitoring workflow:

Actor	Best for	Main output
Telegram Keyword Search & Channel Scraper	Public Telegram research and keyword discovery	Matching posts and channel data
Google Shopping Price Tracker & Seller Monitor	Product prices, offers, and seller monitoring	Changed offers and product snapshot

Output datasets

The default dataset contains a run manifest with links to two monitor-specific datasets:

• LinkedIn Ad Change Events & Metrics (changes): event rows for new, disappeared, and new-advertiser, plus per-company aggregate metrics.
• LinkedIn Ad Library Current Snapshot (snapshot): every normalized ad observed in the latest complete result set.

Each normalized ad has a stable ID derived from the LinkedIn Ad Library detail URL. Snapshot state is stored in the Actor key-value store and updated only after both output datasets are written successfully.

Input example

{
  "monitorId": "acme-competitors-weekly",
  "advertisers": ["OpenAI", "Anthropic"],
  "country": "IT",
  "dateRange": "30d",
  "searchType": "advertiser",
  "maxResults": 100
}

Use the same monitorId and filter scope on recurring runs. Changing the scope intentionally starts a new baseline instead of creating false changes.

Indicative launch pricing

The planned pay-per-event structure stays close to low-cost LinkedIn ad scrapers while charging a small premium for change detection:

Event	Indicative price
actor-start	$0.00005 per run
ad-tracked	$0.0005 per normalized ad ($0.50 / 1,000)
change-detected	$0.003 per emitted change

These prices are indicative until PPE charging is enabled and confirmed in the Apify Store. Dataset summary and snapshot rows should not create additional billable events.

Reliability and limitations

The source is LinkedIn's public Ad Library, so its availability, pagination, markup, and fields can change. No login or private LinkedIn data is accessed. Run a weekly smoke test and verify that both named datasets receive records before relying on alerts in production.

Billing event names are defined in the Actor code as actor-start, ad-tracked (one per normalized ad), and change-detected (one per emitted change). Store pricing can be configured separately after publication.