Ad Activity Tracker — Companies Running Ads & Ad Volume

If a company suddenly has 40 live ads where it had four, something changed inside that company. A new budget, a new growth lead, a launch, a funding round being spent. Public ad libraries will tell you that a company has ads. They will not tell you how many, on which platforms, since when, or whether that number is going up — which is the part that makes it a reason to call.

This Actor answers all of it, as one row per company: how many ads are live right now, on which platforms, how long they have been running, what the ads say, where they point — and what changed since your last run.

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Who it is for

• Outbound teams — "ramping ads" is a warm trigger: the budget is moving and the growth lead is under pressure to make it work. Every row tells you who to call and gives you the opening line.
• AI / GTM agents — one call, a flat dataset, no login and no key. activeAdCount, momentum, momentumTrend, signalTags, sellTo, whyNow are all on the row.
• Competitive intelligence — track rivals' ad volume, creatives and landing pages week over week.
• Agencies — prove a prospect is spending (and on what) before the first call; spot the accounts that just switched paid off.
• Investors and analysts — paid-media volume as a demand-side indicator across a portfolio or a market.

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What makes it different

	Typical ad-library scraper	This Actor
Row shape	one row per ad	one row per company
The number	you count the rows yourself	activeAdCount — the library's own total for that advertiser
Change over time	none — every run is a fresh dump	momentum, momentumPct, momentumTrend, platforms added/dropped
Platform coverage	whatever that one library shows	live ads plus every ad platform the company's own site is tagged for
Output	creatives	creatives plus the signal: tags, who to sell to, why now, a 0–100 score

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What you get per company

{
  "company": "Ramp",
  "domain": "ramp.com",
  "isAdvertising": true,
  "activeAdCount": 209,
  "platforms": ["meta", "google-ads", "linkedin"],
  "platformsWithLiveAds": ["meta"],
  "platformsOnSite": ["google-ads", "linkedin"],
  "momentum": 43,
  "momentumPct": 26,
  "momentumTrend": "ramping",
  "previousActiveAdCount": 166,
  "newPlatformsSinceLastRun": ["linkedin"],
  "adsStartedLast7d": 12,
  "adTenureDays": 207,
  "sampleCreatives": [{ "title": "…", "body": "…", "cta": "Sign up", "landingPage": "https://ramp.com/…" }],
  "landingPages": ["https://ramp.com/pricing", "…"],
  "signalScore": 83,
  "signalTags": ["running-ads", "high-volume-advertiser", "ramping-ads", "multi-platform-advertiser",
                 "added-linkedin", "testing-new-creatives"],
  "sellTo": ["Head of Performance Marketing", "Head of Growth", "VP Marketing", "CMO"],
  "whyNow": "Active ads went from 166 to 209 (+26%) since the previous check — they are putting money behind Meta right now."
}

Three dataset views are built in: Ad activity by company, What changed (the delta) and Creatives & landing pages.

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Use it in three ways

1 · Watch your target accounts or competitors.

{ "companies": ["gong.io", "ramp.com", "clay.com"], "countries": ["US"] }

Domains work best — an ad that sends traffic to the company's own site proves which advertiser page belongs to it. Brand names work too, and you can paste a Meta page id as page:1234567890.

2 · Discover who is advertising in your category. Leave the company list empty and give keywords:

{ "keywords": ["AI note taker", "project management software"], "countries": ["US", "GB"] }

You get the companies buying ads against those words, ranked by how much they are spending attention on it.

3 · A scheduled feed of what changed. Set a watchId and schedule it daily or weekly. The first run stores the baseline; from then on every row carries momentum, momentumTrend and the platforms added or dropped. Filter on ramping-ads, new-to-paid or paused-ads and you have a trigger feed.

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How the signal is built

• Count, don't sample. The row reports the advertiser's own total from the public library, not the number of ads that happened to fit on one page. activeAdCountIsMinimum tells you on the rare occasion it is a floor instead.
• Two kinds of evidence. Live ads prove volume; a live conversion tag on the company's own site proves they buy on platforms no library counts (Google Ads, LinkedIn, TikTok, Microsoft, Reddit and more). Most companies load those through a tag manager, so the container is read as well — which is how a site that looks untagged turns out to be running six platforms.
• Remember, then diff. Each watch keeps a private memory of every advertiser's ad count and platforms. Ramping, slowing, paused, resumed and new-to-paid all come from that, and small wobbles are deliberately reported as steady rather than as fake movement.

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Chain it

Then run	To get
Decision-Maker Finder	the actual people in sellTo at each advertiser, with work e-mails
Recently Funded Companies	the raise that paid for the ad ramp
Hiring Intent Scraper	whether they are also hiring the team to run it
Technology Lookup	the rest of their stack

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Notes

• No login, no cookies, no API key, and no other paid Actor is ever started.
• Ad libraries report per country — the same advertiser can have 200 live ads in one country and none in another. The country list is part of the question you are asking.
• A company with no live ads in the library still gets a row: "not advertising here" is usually the answer you wanted, and the site tags often show they buy elsewhere.
• Apify residential proxy is the default and is strongly recommended; ad libraries rate-limit datacenter ranges hard.

Pricing

Pay per event: you pay per company checked and delivered. See PRICING.md.