How to Research Competitor Black Friday Ads
Research competitor Black Friday ads before the archive expires: launch timing, offer depth, and the evergreen ads they kept running through the sale.
Research competitor Black Friday ads before the archive expires: launch timing, offer depth, and the evergreen ads they kept running through the sale.
It is late October and the client wants a Black Friday plan by Friday. You open last year's competitor pages in the Meta Ad Library, include inactive ads, and get almost nothing. The sale ads you remember from last November are gone. Nobody deleted them. The library simply stopped showing them.
Short answer: To research competitor Black Friday ads, read three things from last year's sale: how many days before the peak the promo creative launched, how deep and how conditional the offer was, and which evergreen ads kept running straight through it. Start now, because the archive that still holds last year's sale ads is time-limited.
The takeaways
Retention depends on the library and the region, and it is shorter than most Black Friday guides assume. Meta's Ad Library tools page says ads delivered in the EU are "archived for one year upon the delivery of their last impression", and political ads stay for 7 years. Ordinary commercial ads shown only outside the EU are visible while active, and that is all.
So a US-only competitor's sale from last November is already invisible on Meta. A brand that also advertised in Germany or France is still there, but only until about a year after its sale ended. For Black Friday 2025 that lands in late November to early December 2026. TikTok's library was built for the EU's Digital Services Act and gives you a European view. Google's Transparency Center shows a last-shown date on each ad. Check each library's filters yourself before you plan around them, because these rules have changed before.
The 30-day winner rule fails on sale ads because a Black Friday ad is built to die. The rule works year-round because nobody keeps paying for a losing ad for a month. A promo ad launches a week or two before the peak, runs hard, and stops when the offer ends. Its short life says nothing about how well it sold.
It is easy to look at a nine-day sale ad and file it as a failed test. Usually it was the whole campaign.
So for this window, change the question. Skip "which ad lasted" and ask when it appeared, what it offered, and what ran next to it. Runtime still matters for one group: the ads that were never about the sale. The usual method for reading durability on a single ad applies to those.
Three details from a competitor's Black Friday ads carry over to your own plan. First, launch timing. Note the start date of the first discount creative and count the days to Black Friday. A brand that went live on the Monday before has a different theory of the season than one teasing early access three weeks out.
Second, offer depth and terms. Write down the headline discount, then the conditions: minimum order, excluded products, sitewide or one hero product, and the stated end date. The fine print tells you how much margin they were willing to give up. The offer-reading method covers this in general, and Black Friday is the week the terms move most.
Third, the sequence. Plenty of brands run one creative for the early window, another for the weekend and a "last chance" version for Cyber Monday. Log the order as well as the ads.
The real control during a sale is the evergreen ad that kept running through it. In Black Friday week an account fills up with discount creative and spend shifts toward it. An ad with no offer that the brand left on through Cyber Monday held its budget against their own promo. That is about the strongest vote of confidence the library will ever show you.
To find these ads, look for start dates weeks or months before November on ads that were still active during the sale window. Study them for angle and structure, because they work without a discount carrying them. They also show what the brand falls back on once the sale ends, which is roughly what your shared audience sees in December.
An ad library shows what ran, never what it returned. You see the creative, the dates and, for EU ads on Meta, some reach data. You do not see spend, conversions, or whether the sale made money. A brand that ran 40% off for five days may have regretted it in January.
So treat what you collect as a map of decisions made under pressure: launch timing, discount depth, the evergreen survivors. Put it next to your own numbers from last year, such as your CPMs in peak week, your conversion rate at each discount level, and the day your budget ran out. The competitor read gives you hypotheses. Your account decides which ones are worth testing.
The cleanest answer to the retention problem is to stop depending on the archive. Watch competitors during this year's window and you capture every promo ad while it is live, in every region, including the ones that vanish from Meta the day they stop. That is the job of the daily pull in Adscalr's competitor intelligence: the Meta, TikTok and Google ad libraries in one dataset, refreshed daily and sorted longest-running first. The evergreen controls sit at the top, and this week's sale creative appears as it launches. A daily refresh is fast enough for a sale that runs a week or more.
This is the thinking behind Adscalr.
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