Michael Kaminsky, founder of Recast, discusses how boutique retailers waste money on branded search and why marketing mix modeling helps them spend smarter. He explains incrementality and how CMOs can use data to allocate budgets where they actually move the needle.
There's a couple of questions that I want to ask you, Mike, and just kind of have a conversation around because I do think there's a bit of an endemic problem within, like, the digital marketing community around deploying spend and some of these misleading things that they've learned for so long. One is obviously branded search. So I want to talk about that, and that'll be an interesting talking point. And then the second is, like, for the multilocation boutique retailer, you know, call it in, like fashion or apparel that has like 10, 15 stores in the United States. Like, what's the best way to calibrate and set up an mmm? And the perspective I'm coming from is that they are literally siloing direct to consumer from the other parts of the business, when really they could be deploying spend in a way that is incremental for those retail locations as well as for the direct to consumer business. Now, I want you to just touch on, like, how that might be risky, like how you calibrate the MMM to include all of those different facets and how you try and, like, look at the data in a way that, like, can you have a, you know, a perfect situation or do you see cannibalization on direct consumer if you try and stretch budget in a way that is also incremental to the retail locations? This is something I'm, like, actively talking to a lot of prospects about, and they're just, they're not. No one knows really how to. What the, what the right answers are.
These are really good questions. I mean, I. I'll preview the second part. Like the 10 to 15 boutique locations. That's a really hard problem. So I'm interested in brainstorming with you, but that's a tough one.
Yeah.
Let's talk about brain search. I mean, brain search is a. It's a really easy one to reason about and like, it actually, like, I use this all the time to highlight, like, why MMM is important because it's a digital channel that is so far at the bottom of the funnel that it is going to show up looking great on any digital tracking measure. But everyone instinctively knows that it's not incremental or it's probably not as incremental for every single click.
You'd be surprised on that front too, though. Like, really, I, I got, I got off too. I mean, this is, this is very interesting, though, like, just some CMOs. And I do think the role of the CMO needs to become a little bit more like, like a data economist, almost like an, an analyst In a way. I had literally two conversations in the past couple weeks, new CMO coming on board. And they're like, yeah, we've reallocated our spend. We allocated more spend towards branded search. And I'm just like this, like, come on. Increased our marketing efficiency ratio. It's just an Emmy R. Sometimes is not the, the best, you know, the best indicator. No. So yeah, sorry to interrupt you, but I mean, you think it's obvious when you dealing in data all day and.
Talking about this stuff, it's a good reminder that I have a myopic view of the world. No, I mean I think it is, it's at least easy to like talk through this idea of look, if they are searching for your brand, they have already heard of you and they are looking interested in engaging with you more. And it's unclear if having that top spot in Google, what that actually adds, like paying Google for that click, how much does that actually add to your business? And I think, you know, it's also hard because like there are times when brand search is incremental and I've talked about this and there are a bunch of ways that if, you know, if your competitors are actively bidding on your terms and your products aren't that differentiated or you don't have that much brand loyalty, like then you might need to spend money to defend that top spot and it might be worth it for you, but it's going to depend to business. To business and but you're totally right that like coming in and being like we're going to dump a ton more money to branded search and it's going to like make our last click numbers look great. That's obviously terrible and like not a great forward step for that business. And that's where you want to push people to think about incrementality and testing and like, you know, where, where and when does this make sense for us? But again, it, as you noted, it requires a different skill set from the CMO than I think what a lot of people have been trained on. We need CMOs who can reason about that, who can think about that in order to allocate those dollars efficiently. Because it's easy to get misled and you know, buy a bunch of branded search. It's just like, you know, CMOs 10 years ago, like buying impressions, being like, I'm going to maximize impressions and then buying a bunch of garbage impressions or buying a bunch of garbage traffic that didn't actually do anything for their business. Because what you actually want to be focused on is Incrementality who is purchasing? Is. Are these dollars actually driving revenue or driving profit?
And I mean that's exactly why, you know, CMO tenure is just getting compressed in such a way because channel innovation is accelerating. How many channels can you buy on now? A lot more than what you used to be. It's not as cut and dry. There's a lot of conjecture, you know, so I think a lot of CMOs need to really kind of look at their skill sets and try and I mean if you're an aspiring cmo, like you need to really understand the data landscape. Let's go back to the boutique question. I know there's like no right answer for it. I've just been like kind of, you know, knocking my head against the wall too of like how do you. Because you can slice an MMM in so many different ways. Like you can just look at one location, you can look at all the locations, you can look at the third party commerce locations direct to consumer and yeah, I'm just curious what your take is.
Yeah, I mean this, this is like a really sticky problem because they're not like their DTC is national, they have some amount of geographic focused boutiques and that makes it makes the MMM problem much more difficult.
Difficult.
And so like, honestly in this situation, like this is a place where I would focus a little bit more on testing and because then like the benefit of their situation is that you can really do a lot of like nice geographic level isolation stuff and be like, look like if we do a Facebook campaign in the surrounding area of these two stores but not the other 12, do we see a lift and can we get a read on incrementality there? And that is actually where I would focus that business rather than doing mmm, which is going to be really complicated because of the way that they're geographically going to be located or laid out from a statistical perspective. And so I would actually focus that business a little bit more on testing because I think that's where you're going to be able to get much cleaner reads on what's working that you can then generalize ideally to the other, to the rest of the, to the rest of the program. But it is, it's a very, it's a, it's a tough problem because of exactly what you, what you stated, which is you can slice it a bunch of different ways. And you have two different marketing programs at two different levels. One geographic focus for the boutiques and then one national focus for the D2C. And so you get into this very sticky statistical problem in terms of trying to use an MMM to analyze that.
