How to See How Long a Facebook Ad Has Been Running

Where does the Ad Library show an ad's start date?

Meta prints the start date directly on every active ad inside the Ad Library, in a line reading 'Started running on' followed by the exact day, month and year. Open facebook.com/ads/library, search by advertiser name, page, or keyword, then click into any result. The date sits just below the ad creative, above the platform icons showing where it runs (Facebook, Instagram, Messenger, Audience Network).

Pages running more than one ad show a start date on each card individually, since Meta treats every unique creative-and-copy combination as its own ad object. A page can show a 2-month-old video next to a 400-day-old static image in the same results grid. Scroll speed matters here: the Ad Library loads results newest-active-first by default, so older ads often sit several pages deep.

The date reflects the day Meta approved the ad for delivery, not necessarily the day the advertiser uploaded it, and Meta does not publish the hour or your local timezone. Treat the figure as accurate to the day, not the minute, and expect it to update only when the ad actually stops delivering.

Why does run time predict whether an ad is profitable?

Run time predicts profitability because Meta's delivery algorithm punishes underperforming ads with rising costs and shrinking reach within days, so an advertiser who keeps paying for the same creative past that window is very likely still profiting from it. Facebook's auction system re-evaluates every ad continuously against relevance, engagement and conversion signals; a losing ad gets more expensive to run almost immediately, and most media buyers kill a loser inside the first two weeks rather than absorb rising CPMs.

That correlation is not universal, and treating every long-running ad as proof of profit is a mistake worth naming outright. Household brands running awareness or reach campaigns can leave a video live for a year on a fixed brand budget with no direct-response goal at all — Coca-Cola, Nike and similar advertisers optimize for impressions and recall, not last-click sales, so their run time reflects budget allocation, not margin. The heuristic works best on direct-response offers: physical products, info products, and lead-gen funnels where the advertiser needs immediate ROAS to keep the account solvent.

Small and mid-size direct-response advertisers rarely have the cash reserve to fund a loser for months, which is exactly why the signal holds up so well in that segment. If a dropshipping page or a supplement funnel keeps the same ad live for 90 days straight, the simplest explanation is that the ad converts well enough to keep buying itself.

How do you find a page's longest-running ads fast?

The fastest method is to open the Page's full ad set inside the Ad Library and click through each active ad, since Meta does not offer a native sort-by-start-date control. A handful of free browser extensions add that missing sort column, letting you rank a page's ads oldest-to-newest in one view instead of clicking through them one at a time.

None of these methods pull historical data Meta doesn't publish. You're always looking at what's active right now, so a page's true longest-runner could have paused for a week last month and reset its visible streak without you knowing about the gap.

• Search the advertiser's exact Page name in the Ad Library, not a general keyword, to pull every ad they're currently running.
• Filter by country and platform first if the page runs region-specific campaigns, since global results dilute the list you're scanning.
• Open each ad and record its 'Started running on' date in a spreadsheet if the page runs fewer than 15 ads total.
• Install a free Ad Library sorting extension if the page runs high volume, so the oldest ads surface automatically instead of buried pages deep.
• Cross-check the count against any flag showing multiple ads use the same creative and text, which signals a scaled, systemized winner.

Can you see run time for inactive or deleted ads?

No — Meta removes an ad from the Ad Library within a short window after it stops delivering, and it takes the start date with it. Once an advertiser pauses or deletes a campaign, that ad typically disappears from public view within roughly a day to a few days, depending on Meta's processing; there is no official published figure for exact removal timing, so treat that window as approximate rather than exact.

Political and issue ads are the one exception: Meta retains those in a separate archive with spend and impression ranges for several years under its ads-about-social-issues policy. Standard commercial ads get no such retention, which is why third-party spy tools that snapshot the Ad Library daily are the only practical way to reconstruct a deleted ad's run history after the fact.

If you need to confirm an ad ran for a specific stretch before it vanished, your only reliable source is a saved snapshot from a monitoring tool or a screenshot you took while it was live. Word-of-mouth claims that an ad has 'been up forever' are not evidence Meta will ever let you verify again.

How do spy tools track run time across ad variants?

Spy tools track run time by re-scraping the Ad Library on a fixed schedule, usually daily, and diffing each snapshot against the one before it to log when an ad first appeared and when it dropped out of the active set. Because Meta groups similar creative under one ad, tools such as PowerAdSpy, Dropispy, and BigSpy attach a first-seen and last-seen timestamp to every unique ad ID they capture, then roll variants of the same underlying offer into one tracked campaign.

This matters because a single winning offer often runs as 10, 20, or more near-identical ad variants, each with its own individual start date in the Ad Library — same offer, different headline, image, or audience. A spy tool's variant view lets you see that the offer as a whole has run for 8 months even though any one creative you click on individually might show a start date of only 3 weeks.

The accuracy of any spy tool depends entirely on its scrape frequency and its historical depth; a tool that started tracking a page 6 months ago cannot tell you anything about that page's ad history before it began watching. Confirm a tool's own data-retention window before trusting a 'running since' figure it reports.

What run-time thresholds should trigger a swipe?

A run time past 90 days on a single unchanged creative is the threshold most experienced media buyers treat as a strong signal worth studying closely, and anything past 6 months on a direct-response offer is close to as reliable a profitability signal as the public Ad Library can offer.

Layer platform count and variant count on top of the date before committing time to a swipe. An ad running 120 days on Facebook and Instagram simultaneously, with 8 near-identical variants active at once, points to a scaled offer rather than a one-off fluke — that combination is a stronger signal than run time alone.

Quick decision checklist

Use this page as a decision aid, not a generic blog post. The practical question is whether the reader needs faster evidence about what is already working in VSL-driven direct response, especially across nutra, supplements, GLP-1, weight loss, blood sugar, and adjacent high-intent health markets.

Daily Intel Service is most relevant when the next decision depends on active market examples: which hook to test, which claim style is risky, which funnel structure is common, which language market is moving, and whether a competitor's creative is likely early, scaling, or already saturated.

• Start with the TL;DR if you need the direct answer.
• Use the table to compare trade-offs quickly.
• Use the FAQ for answer-engine-ready summaries.
• Use the CTA when the decision requires live VSL and ad examples instead of theory.

Daily Intel's coverage advantage

Daily Intel Service is positioned around category-leading variety and actionability: one of the broadest direct-response catalogs of VSLs and ad creatives across blackhat, greyhat, and whitehat advertising patterns, with enough context to understand what the advertiser is doing beyond the visible creative. The practical difference is that members are not just seeing a screenshot; they are seeing the VSL, the ad, the funnel path, the transcript, the UTM context, and the research notes that turn the asset into a decision.

This matters because direct-response affiliates do not operate in one clean category. A weight-loss campaign may use a whitehat compliance ad, a greyhat pre-lander, a more aggressive VSL, and a checkout path designed around upsells and recovery. A useful intelligence platform needs to capture that spectrum instead of pretending every winning campaign looks like a public brand ad.

Blackhat, whitehat, and multilingual signal coverage

Daily Intel tracks patterns across both blackhat-style and whitehat-style campaigns so operators can understand the market without blindly copying risk. Whitehat examples help with durability and compliance review; blackhat and greyhat examples reveal pressure points, hooks, mechanisms, and funnel structures that may be driving spend but require careful adaptation before use.

The catalog is also built for global operators, with VSL and ad references spanning 14+ languages and different local idioms. That is a key advantage for Brazilian, LATAM, European, MENA, Indian, and non-native English affiliates who need to see how the same market desire is translated across cultures instead of only studying US English ads.

How to use the intelligence responsibly

The goal is modeling, not copying. Use Daily Intel to understand structure: hook, mechanism, proof, claim intensity, funnel depth, offer economics, and saturation stage. Then build original creative, review claims, and adapt the angle to the traffic source, country, language, and compliance requirements of the campaign.

A strong workflow compares multiple examples before acting. If the same mechanism appears across several languages, several advertisers, and several funnel variants, it may be a durable market signal. If the example appears only once or depends on an aggressive claim, treat it as a research clue rather than a campaign template.

• Model structure, not protected creative assets.
• Separate whitehat durability from blackhat persuasion pressure.
• Compare US English examples against LATAM, European, and other language variants.
• Use transcripts and funnel notes to build original briefs.
• Keep compliance review separate from market research.

Methodology and source context

Daily Intel pages are written from a research workflow that reviews active VSLs, Meta ad creatives, transcripts, UTMs, funnel paths, checkout steps, upsells, recovery sequences, and compliance-sensitive claim patterns. The goal is to explain observable market behavior, not to provide legal, medical, or platform policy advice.

For educational pages, the supporting references should help readers verify search, crawlability, and public ad research context, especially Meta Ad Library, Meta advertising standards, and Google helpful content guidance. Daily Intel then adds the direct-response interpretation layer so the page explains what the signal means for actual affiliate research decisions.

For deeper evaluation, continue through Ad spy comparison hub, Best Tiktok Ad Spy Tools: Honest Comparison, Free Ad Spy Tool Reddit: What You Get and Where It Stops, Facebook Ad Spy Extension: The Practical Version, Ad Spy Tools Pack: Read Before You Rely on It, and What is a VSL?. These related Daily Intel pages connect this topic to the relevant methodology, pricing, trust context, comparison path, or niche workflow.