How to Avoid Getting Fired for Botching Your BFCM Campaigns
Black Friday and Cyber Monday punish guesswork. Teams that land results arrive with proof, not hopes.
Carly, CEO of Sometimes Curly, and Darlene, CRO of TubeScience, built their guidance on live data. Between them they manage large paid social programs and have visibility into outcomes at scale. TubeScience’s recent analysis covered $450 million in Meta ad spend during Oct 1 to Dec 31, 2024, with advertisers averaging $8.8 million
over the peak period. The patterns are clear enough to act on now.
The best-performing teams do not wait until November to find their winning ideas. Carly explained that testing early is what keeps brands from panic mode when performance starts to fluctuate. “Most teams wait for the BFCM brief, but by then you’re already late,” she said. “You should know which hooks and angles win long before the sale starts.”
That means running micro-tests in September and October to identify creative patterns that hold up under spend. Small data sets reveal what to scale later, and they help creative teams focus on proven concepts rather than last-minute guesses.
Complex stacks of perks confuse buyers and slow conversion. Straight percentage discounts, on the other hand, win for most eCommerce businesses. Gift with purchase works for LTV models that cannot afford deep cuts. Fifty percent off showed up on both winning lists. Darlene called it the safe bet when a team is unsure. “It is the most consistent performer across the data we study.”
Fatigue kills good work faster than many expect. Darlene’s view was precise. “You can’t rely on a single hero video. You need constant variation and daily reads on what moves.”
Two examples from recent winners illustrate the point.
Bottom funnel shoppers respond to price clarity and proof. Mid funnel needs reasons to believe that go beyond a sale tag. Top funnel needs a hook that holds attention long enough to deliver the message. Use both emotional and rational triggers so you do not leave entire buyer profiles untouched.
“Relying on one type leaves a large part of your market unpersuaded.”
AI has made production faster, but both speakers emphasized that its real value lies in acceleration, not direction. Carly describes it as an assistant that helps execute more ideas, not decide which ones matter. “AI can help with versioning or speed, but judgment still belongs to the marketer,” she said.
Darlene adds that TubeScience uses automation to expand testing volume but never outsources taste or context. “Automation is about speed, not taste,” she noted. “Our best ads always come from people who understand why the message matters.”
Used well, AI can shorten turnaround times and keep creative pipelines active without losing human intent. The danger comes when teams trust machine output more than customer insight.
Misreading performance data is one of the fastest ways to derail a campaign. Darlene cautions against overreliance on last-click attribution or surface-level platform data. “You’ll see spend patterns that make no sense in-platform but deliver real lift when you track the full cycle,” she said.
The best teams combine daily metrics with post-event reviews that account for delayed conversions. They also agree internally on what success looks like before launch. “You need one definition of success before launch,” Carly said. “Otherwise, every stakeholder ends up arguing a different truth.”
That alignment keeps analysis honest when numbers come under pressure. Teams that lack it spend more time defending results than improving them.
Carly’s closing line is a useful filter for any planning meeting. “If your workflow only works in quiet months, it is not a workflow.” BFCM will test that statement.
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