Black Friday Strategy for the Power 30 Days of Q4

Luke Austin (0:00)

There's these core moments over the next two months that every brand should have some moment constructed around, that I would contend is the table stakes baseline. So starting in sequence from that, you have early November, that's gonna be the start of the month, maybe end of October, the first week or two of November.

This is the first reason that you're giving customers a reason to buy, right?

Richard Gaffin (0:26)

Every few years, a new platform earns its place at the top of every smart advertiser's media plan. AppLovin just had the most remarkable run in ad tech history, and now they've opened that engine to e-commerce. AppLovin gives brands another way to reach more than a billion daily users through full screen ads in the mobile games they already love. With Q4 around the corner, smart data-seek brands are moving fast. Dr. Squatch, Ridge and Tumble all made AppLovin part of their strategy to reach their Q4 growth targets last year. It's super easy to launch, and brands have been able to scale to 100K per day in spend within days.

Q4 waits for no one. AppLovin is offering 5K in ad credit when you spend 5K. Just go to applovin.com/ctc to set up your first campaign.

Hey, folks, welcome to the Ecommerce Playbook Podcast. I'm your host, Richard Gaffin, Director of Digital Product Strategy here at Common Thread Collective. And I mean that literally this time because I am here in the studio with our president, Mr. Luke Austin, sitting right across from me. And obviously this is exciting for me because it's the first time I think I've done it. I think I did one with Tony maybe a little while ago. But just being a person, it's a good vibe and we're ready to talk about Q4 here with you all. But Luke, how are you doing, man?

Luke Austin (1:36)

I'm doing great. Yeah.

Fresh off a little midday HiRox workout. We're nine weeks out from HiRox A&IM. So the group of us participating in that, the stakes are high.

Got my ProMix protein shake here as an after-workout recovery.

Richard Gaffin (1:53)

Of course.

Luke Austin (1:54)

Thinking about Black Friday, Cyber Monday, Q4. I mean, it's all kind of working.

Richard Gaffin (2:00)

It's all kind of working right now. I do want to clarify for the audience that I'm not one of the people training for HiRox coming up in nine weeks or whatever. So I'm not going to sort of steal that thunder there. But yeah, let's go ahead and roll into it. So what we're talking about today is what we call the Power 30 And the Power 30 are the 30 most important days of the calendar for every brand. So here's the key stat kind of for this, which is that 55% of Q4 website revenue comes in the Power 30, which for this year will be November the 17th through December the 16th. So I guess we could characterize that as like a couple weeks before and a couple weeks after Black Friday.

So that represents 32.6% of the Q4 calendar, but of course accounts for 55% of that revenue. So what we want to talk about today, I think, is obviously the why of it, but maybe more specifically, what the brands that really won this Power 30 span did that other brands didn't do, and Luke's going to break that down for us. But let's, yeah, I'll throw it over to you, Luke. Like what, talk to me a little bit more about this 30 day period and how the best brands take advantage of it.

Luke Austin (3:01)

Yeah, so I think there's two, I think there's sort of two ways to think about this conversation and this sort of sequence. And one is like, what is the basic shape of the next two months, really, that we're headed into, November and December? What are the core moments that are like the table stakes, right? Like the scaffolding that brands should build around. And then from there, the second sequence is, okay, what is within that sort of scaffolding and general structure, what are all the ways that brands are taking that to the next level, right? And then adding it, making the home really their own and improving on it. So, and it's interesting, the interesting thing about the seat that we sit in at CTC and our data set of hundreds of brands and billions of dollars in GMV is naturally larger data sets tend to, when you look at the averages across larger data sets, it tends to sort of like smooth out the anomalies, right? When you sort of like get this like cluster and the 80 percentile in the middle, that's like, oh, like generally brands do these things, right?