Arlen Robinson ([00:01].424)
Welcome to the eCommerce Marketing Podcast, everyone. My name is Arlen and I’m your host. And today we have a very special guest, Michael Kaminsky, who is the co-founder of a next-generation marketing mix modeling startup, Recast. He’s a statistician, entrepreneur, and marketing science researcher who loves helping companies avoid wasted marketing spend through advanced analytics. Welcome to the podcast, Michael.

Michael ([00:31].6)
Arlen, thanks for having me. I am super excited to be here.

Arlen Robinson ([00:34].352)
Yes, thank you for joining and we’re super excited to talk to you. Um, as I was saying before we started recording, this is definitely a, a great subject that we hadn’t really covered lately. Um, and, uh, I think it’s very timely because a lot of things have changed with regards to, uh, all of these different marketing platforms. How do you, um, get proper stats and things like that, because today, um, you know, we’re talking about your, we’re going to be talking about your bread and butter.

which is, you know, where do e-commerce operators go wrong in their marketing measurements and what are some of the common pitfalls that they should avoid? So I know you’re kind of knee deep in working with businesses to succeed in measuring their marketing and avoiding things. And so I think this is definitely gonna be an awesome conversation. But before we do get into all of that, why don’t you tell us a little bit more about your background and…

specifically how you got into what you’re doing today.

Michael ([01:32].103)
Yeah, so my background, not in marketing, actually. I started out as an econometrician, a research scientist, basically using historical data to try to learn things about the world. So I started out doing work in environmental economics, doing statistical analyses, publishing journal articles, then moved into health care, did a lot of work doing research on does this medical intervention work better than this other one, and how do we

run these statistical analysis in order to learn things about the world. And then from there, I moved into, into e-commerce and marketing. So I went, um, and started working as a data scientist at a company called Harry’s, uh, sort of the men’s grooming brand, one of the last generation of big e-commerce companies that then eventually became sort of a large CPG company, right, made the transition from being just e-commerce to distributing through retailers like Target and Walmart, and now sort of everywhere that

sold and it’s now a holding company that has a bunch of other brands. So a really interesting journey there. I ran the data science and analytics team and we spent a lot of time thinking about marketing measurement, both in the context of the pure e-commerce business. How do we think about that? How do we do that really well at a time, you know, five, 10 years ago when not, there just weren’t as many tools available for people who are operating in e-commerce businesses. And then also how do we do that in a world of omnichannel, right? When you’re selling on Amazon

Target,, Walmart, How do you start to think about bringing all of those pieces together? And so those challenges during my time at Harry’s and then afterwards, after starting Recast, is really what got me excited about marketing analytics and marketing science. There’s a lot of really, really hard and interesting technical problems there. And then a lot of value that can be created because the difference in terms of business performance between a business that does marketing analytics really well and one that doesn’t is just enormous. So it’s a really,

to be in and a lot of really interesting intellectually stimulating challenges to work on.

Arlen Robinson ([03:59].074)
Okay, great,

Arlen Robinson ([04:05].532)
their transition and as they were going from the various stages of it. So I’m sure that was a great learning ground for you. Um, but yeah, where I want to kind of start at. And so we’re going to kind of dive deep into marketing measurements and wanted to see in your experience, what would you say are some common mistakes that you’ve seen e-commerce operators make, you know, just measuring their marketing effectiveness, cause that’s a big thing.

Michael ([04:29].211)
Yeah, definitely. There’s a couple of different mistakes that sort of come immediately to mind. So the first one is not thinking about incrementality. So incrementality, what is it, what does that mean? When I use the word incrementality, what I mean is the causal relationship between marketing activity and sales, which is to say, okay, when we spend an additional $1,000 on

some marketing channel, how many additional sales does that actually drive? Or if we spent in a thousand dollars less on this marketing channel, how many fewer sales would we get? And incrementality is, is important because it’s the thing that we really care about as marketers, right? Which is what’s the true return on investment of the dollars that we are putting into our marketing program. And so, um, a reason, you know,

Incrementality is not the same thing as like the ROAS that you see in some marketing platform, right? You log into Facebook, you look at the reporting platform, it’s going to show you some ROAS number, that number isn’t incrementality.

A good way and easy way to think about this is like the ROAS on retargeting campaigns are often really, really high because every dollar you put into the retargeting campaign, you’re getting lots of conversions. But the question that you should be asking yourself as an operator is, would I have gotten those conversions anyway? Is that retargeting spend actually truly incremental or is it just taking credit for people who were brought into, you know, made aware of our brand via our prospecting campaigns and then retargeting is taking all the credit?

branded search campaigns work similarly. Often the in-platform ROAS for those branded search campaigns look really, really high, but that’s because people are already searching for your brand. They already became aware of you via some other advertising that you’re doing. And the question you should be asking yourself is, if I didn’t spend those dollars on branded search, would I still have gotten those conversions anyway? And so…

Michael ([06:19].303)
The idea of incrementality, I think, is the most important one that e-commerce operators need to be thinking about. And you need to be thinking about, okay, I have these metrics that I’m looking at, which probably don’t measure incrementality directly. And so how far away from them, how far away from the true concept of incrementality are those metrics? And that’s the thing that you really need to be thinking about is what am I measuring?

And then how biased or not is it away from this thing that I really care about, which is the incremental value of a dollar invested into that channel.

Arlen Robinson ([06:50].552)
Yeah, great breakdown. And you can kind of see from your explanation, I was just thinking a lot of times, especially now because of the amount of different marketing platforms that are available for businesses, if you don’t measure, like you said, the incrementality, it can be very difficult to figure out, yeah, where are you getting that boost? Because I’ve experienced this on our end as the…

you know, with our company, which is a SaaS company, and a lot of times we’re doing different marketing channels and different paid campaigns. And a lot of times when you start getting into the details of it, especially if you’re running multiple different campaigns, it can be tricky to figure out, okay, what is attributing growth? Because, you know, we’ll start to see and I know other businesses that I’ve talked to start to see growth when they’ve done a particular campaign.

but then maybe they’re doing retargeting, maybe they’re doing Facebook ads, maybe they’re doing even paid ads on Google. And it’s like, they are seeing a boost, but really, all right, where is that really coming from? Could it just be from, you’re getting a lot more brand awareness out there, people are just naturally, you know, seeing your brand exposed more, and then you’re getting your brand exposed to different companies that are in your target demographic.

and then they’re coming back to your site. So it becomes really tricky. So yeah, I can see how the incrementality is a great way to try to break it down.

Michael ([08:21].435)
Yeah, it’s definitely tricky and it’s, you know, if you’re not thinking about it and ask and being skeptical and asking the right questions, it’s easy to get misled. It’s easy to look at the ROAS report in Facebook and be like, okay, we’ve got to put all our money into retargeting or all of our money into branded search. But that’s, I think obviously the wrong answer there. And so it’s really important to be skeptical and to be thoughtful and to think hard about, you know, what are we measuring and then how are we going to use this to make the right decisions for the business as a whole.

Arlen Robinson ([08:36].508)

Arlen Robinson ([08:44].785)

Arlen Robinson ([08:48].08)
Yeah, exactly. And speaking of right decisions, it leads me to the next question. You know, a lot of times when brands are thinking of investing in different marketing campaigns, the main thing is, you know, they don’t want to waste money, they want to make sure, you know, they get a return on it. And so what would you say are some common pitfalls in measuring marketing that typically lead to wasteful spending on my brands?

Michael ([09:14].607)
Yeah, really good question. So I mean, you know, sort of layering back to the previous question, it’s not really thinking about incrementality, right? If you just blindly follow the ROAS reports, especially in platform ROAS.

you’re going to get misled and that often leads to large amounts of waste. Every advertising platform that you’re operating on is incentivized to try to claim as many conversions as they possibly can. That’s just the way the incentive structure is set up. It’s not that they’re bad people. It’s not that they’re being deliberately dishonest, but it makes sense for them to try to claim as many conversions as they possibly can.

And so if you look at those ROAS numbers in platform between Facebook and Google search and Google shopping and your streaming TV provider and whoever else it is, the numbers are going to be biased optimistically. And so if you just follow those numbers and you assume that that’s the true return that you’re getting, you’re going to overspend on all of those different marketing channels and you’re going to end up wasting a lot of dollars. So I would say, you know, the biggest thing that you can do is to not do that. And then.

Another piece of advice that I would give is that it’s important, I think, to take…

an experimentation approach to thinking about how to optimize your marketing mix. And that actually might mean wasting more dollars upfront, running experiments that don’t end up paying off, but that’s actually okay. Right. What you want to be thinking about as an operator, as a marketer in this world is how can I get the most learnings as quickly as possible about what’s working and what’s not for my brand. And that sometimes means running a deliberate experiment in order to try to get a read on is this actually generating lift for us?

Arlen Robinson ([10:33].313)
Mm-hmm. Yeah.

Michael ([10:52].157)
and then recognizing that not all experiments will pay off, right? It’s worthwhile to go and run a clear, crisp experiment in TikTok and see like, okay, do we actually see a lift when we’re running ads in this channel or doing an influencer program or whatever that is? And

The answer might be like, no, and that’s okay. It’s okay to get that learning and then say like, okay, we’re not gonna make this channel a priority going forward. But really it’s better to do that and like put a bunch of money into the channel so that you can register a Lyft or not than it is to like spend small amounts of money over a very long time period where you’re never actually getting that read. And so sometimes like wasting money in a test or an experiment can actually be a.

better overall decision for the business, rather than sort of just dipping your toe in all of these different channels and never really getting a read on what’s working or not. And so it’s important to, I think, think holistically about, okay, where are we running experiments? Where are we using, where are we getting those learnings from? And then how are we using those learnings overall that in order to make better, more optimal decisions and get to a better, more optimal market.

Arlen Robinson ([11:57].228)
Yeah, great

Arlen Robinson ([12:25].92)
and then just, you know, set it and forget it. But of course you can’t do it. When it comes to marketing, that phrase doesn’t exist. So.

Michael ([12:30].163)

Michael ([12:35].64)
Yeah, my co-founder likes to say that there’s no silver bullets only lead bullets, which is to say that like, there’s no one thing that’s just gonna, nothing is easy, right, in this world, unfortunately. And so I think getting marketing right.

Arlen Robinson ([12:40].03)

Arlen Robinson ([12:47].143)

Michael ([12:50].287)
It takes a lot of work and a lot of time, and that can feel really frustrating to business owners because it is a lot of work and a lot of time. But it’s so important, like for e-commerce businesses at scale, marketing is in general their biggest line item by far in their P&L and

Arlen Robinson ([12:58].908)

Michael ([13:06].907)
it’s really, really important to examine that and to think really hard and do whatever you can in order to optimize that as much as possible. There’s almost, you know, between that and like your production costs, there’s almost nothing that can make a bigger difference to your P&L at the end of the year. And so it’s really worth putting a lot of time and effort into thinking about, are we doing this as well as we possibly can?

Arlen Robinson ([13:28].6)
Yeah, yeah, I get that. That makes sense. And you know, from what you also said, and I’ve seen this and I’ve talked to other business owners that have campaigns in the various platforms, you definitely have to pull away from just relying on their reports and their stats. Cause like you said, they’re going to be not necessarily, like you said, deceiving or deceptive at all, but yeah, they’re the, the bottom line is yeah, they’re, they’re trying to claim all, all these conversions. Cause of course,

If you’re not getting any conversions, you’re not going to continually spend. So the, you know, things that may, you know, may be attributed to them, um, or the campaign that you’re running on those platforms, you know, you may have gotten something from it, but it may be a little bit more, let’s just say a little bit more exaggerated than you really are getting in the only way to really figure that out is just to have another third party platform, third party analytics solution that’s going to.

Um, be, I guess you could say kind of non-biased if you will. Um, so yeah, I definitely agree on, on that. Um, now as far as digging a little deeper into all of this, um, you know, when we’re talking about metrics and analytics, there’s a lot of advanced things that you can do. Um, how would you say, you know, advanced analytics, um, play a role in enhancing marketing measurements, uh, you know, for e-commerce businesses?

Michael ([14:55].615)
So I think the really important thing for operators to be thinking about here is using the right tool for the job. And it’s really gonna depend a lot depending on what stage of the business are they? Are they a big multinational operator with multiple different brands and product lines and hundreds of millions of dollars in revenue or are you just getting started and you’re in the sort of like.

single digit millions of revenue, tens of million dollars of revenue. And the tool set that you’re going to be using there is going to be very, very different. And I think this is another mistake that a lot of operators make is they’re using the wrong tool set for the stage of business that they’re at. They’re a really small company trying to do what like Procter and Gamble does, or they’re a really big company doing sort of what, you know, using the same tool sets that they used when they were a very small company. And so I think the first thing to think about is what, what are the, what are the analytics that are necessary for the stage that we’re in?

Arlen Robinson ([15:49].619)

Michael ([15:49].875)
And so for smaller companies, you don’t need to get that sophisticated. You probably don’t need a marketing mix model. You’re probably only operating in one or two or maybe three different marketing channels. And so the thing that you need to be thinking about there is…

One, like how are we going to triangulate what’s really working and what’s not based on the different pieces of information that we have. And so you can look at some of those businesses, like really all you need to look at is like overall business performance, right? Is revenue growing when we tend to increase our marketing spend or not? And you can do a really simple analysis in Excel that can point you in the right direction, at least enough to be making decisions that you need to make next month or next quarter, which is really like the timeframe that’s appropriate for a business that’s at that scale.

Arlen Robinson ([16:35].218)

Michael ([16:36].893)
you want to start adding on different ways of measuring that marketing spend in large part because the return on investment gets higher. Once you’re spending $5, $10 million a year on marketing spend, it’s worthwhile to invest in really honing in on what’s working and what’s not. And so the next thing that I generally recommend for operators is to start building an experimentation muscle. And so that can be doing things like, let’s try turning off branded search spend for two weeks and see what happens to our revenue.

right, and look at the before and after effects of turning off branded search or starting to run these more sophisticated experiments where it’s like, okay, we’re going to run, you know, this type of Facebook campaign only in half the country, but not the other half of the country, and then look at the Lyft or the Delta in overall revenue between those two different regions. That sort of experimentation is actually not that hard to do, right? It takes a little bit of…

operational care to figure out how to make it work. But the statistics aren’t very hard. It’s pretty easy to interpret the results of the test. You can do it in Excel. And it’s really, really good muscle to start building up, both for the executive team, as well as for the marketing operators in terms of being able to set up and execute the test, and then being able to interpret the results and communicate that out, and understand why the results of that test might look different from the ROAS report that you see either in Google Analytics or…

in the app platforms themselves. So that’s generally the next thing that I recommend that people start doing is thinking about how do we build this testing muscle? How do we learn how to opt?

Arlen Robinson ([18:02].512)

Michael ([18:08].663)
operate and execute these tests and then interpret the results. And then beyond that is where you start to layer on more sophisticated platforms, something like a recast that does marketing mix modeling that can help with measuring channels, you know, when you have like 10 plus different marketing channels that are all running at the same time, you have tests at different points in the year, you need to do forecasting, you need to measure the impact of, you know, different types of promotions, right? All of that sort of stuff starts to come in

to play, but it really only makes sense for these businesses that are at that next level of complexity. They’re in a lot more than just two or three digital channels. They’re really trying to do a lot of different things at once and need a tool. And it’s, you know, there’s a good ROI on investing into a sophisticated tool that can help them do it.

Arlen Robinson ([18:54].56)
Okay, gotcha. It’s good to know, you know, it’s not every business has to worry about those type of things. Well, like you said, if you’re if you’re in a lot of, you know, more than like you said, two, three, four different platforms, then it makes sense to start looking at some of these advanced things. So that’s, um, yeah, definitely good to know. So right now this podcast is being recorded at the top of 2024. We’re right in January 2, recording this. And so I guess it would make sense to

Of course, probably address the elephant in the room at this point, because I think any technology marketing, internet related technology is going to have to come to grips with it. And that’s AI. And so I wanted to see what do you think? How do you see emerging technologies like AI and machine learning, transforming marketing measurement in the commerce sector?

Michael ([19:42].827)
It’s a really good question. And I can definitely give my opinion, but because we’re here in the top of 2024, things are changing a lot really rapidly. So the opinion might change in a couple of weeks, depending on what new comes out. I think, look, there’s AI in general, and machine learning in particular, have been hugely impactful in terms of marketing measurement and optimization, right? When you think about what makes Facebook work so well as an advertising platform, it’s because they’re really, really good at machine learning and have been for a very long time.

to target people really, really efficiently. They have so much data and such good algorithms for figuring out what types of products are going to be interesting to what types of people based on their activity and what they’ve purchased in the past, that it makes them a very, very powerful platform. And I think that sort of advanced targeting is going to continue and is going to become more and more available on other platforms as well, right? Facebook was a leader in that. That’s what allowed them to create, I think, the most efficient marketing platform.

ever made, but that sort of targeting and strategy is going to come to other platforms. You know, YouTube obviously has it and it’s getting better at it. And then I think we’re going to see that rolling out also to other things like streaming TV and display platforms of how do we get better and better and better at targeting our customers on these different platforms. And that’s AI and machine learning is going to have a huge role in that. When it comes to

Marketing analytics, I actually think that it’s very much a double-edged sword because these technologies are very good at optimization and they aren’t necessarily good at what I would call causal inference, which is to say, how do we actually learn things about the world? How do we learn about what true incrementality is? Um, machine learning, there are techniques that can be used from machine learning to do causal inference, but causal inference is like a scientific matter.

Right? How can we run an experiment? How can we use scientific best practices in order to learn things about the world? And machine learning can lead you astray just as much as it can point you in the right direction when it comes to doing that. And so I think for practitioners, the thing to be thinking about is, you know, in general, I think being really skeptical, where’s the bias coming from? How do we know if it’s going to work or not? What are the…

Michael ([22:05].051)
What are the ways outside of the model that we can use to validate whether this model is pointing us in the right direction. Those are the things that I think practitioners need to really be thinking about when it comes to evaluating these new tools in the world of marketing measurement, because I mean, look in marketing measurement, snake oil has been sold for a hundred years. It will continue to be sold. Whether you slap a like machine learning or AI label onto it. You as a, as a buyer, as a practitioner just need to be really skeptical in terms of understanding.

Arlen Robinson ([22:25].032)

Michael ([22:35].005)
look, just because they’re using machine learning, it doesn’t mean that it’s more true, right? Machine learning is just like a database or software, right? It’s a tool that can help or can hurt when it comes to understanding the real truth about what’s working for us or not. And so practitioners always need to be thinking about how can I be skeptical about this? How can I make sure that this is actually working for me and I’m not just being sold snake oil?

Arlen Robinson ([22:58].78)
Yeah, yeah. Well said. And I see that across the board, not only in the marketing space, but in, you know, almost every piece of technology there, we’re constantly seeing these labels, AI, AI features being included. And you do have to take a step back and really figure out, all right, you know, okay, it has these features in it. But is that what is that really saying? What is it really doing? Is it making a difference?

And you know, I get it. These brands are trying to take advantage of, uh, this AI hype and, uh, you know, and it’s of course more than just hype. I mean, there’s some pretty advanced and amazing things that are going on now. And you know, we’re only at the very beginning. And so, you know, we get to the end of this year, um, you know, things are probably going to look drastically different than they do now. And you know, just in the span of a year and even just a few months, I’m sure, um, things are going to change a lot, but yeah, you do have to be very careful when looking at these cause, um,

You know, I get countless newsletters and blog articles about new features or AI. And yeah, you have to be careful and figure out, all right, is this really making a difference? How were these products prior to this new feature? Is it really going to change the game for my business? And I think that’s the main question we have to ask. Michael, as we get ready to wrap things up.

Aside from these emerging technologies, what would you say are some future trends in e-commerce marketing measurements that businesses should try to prepare for in the future?

Michael ([24:35].111)
Yeah, really good question. I think one of the things that…

One of the big trends, I think probably from last year and going into next year is thinking about how to expand into multiple different channels smartly as an e-commerce operator. So there’s a lot of e-commerce operators that have their DTC store on Shopify, and that works great, but then are also thinking about, okay, how do we expand into Amazon? How do we expand into some of these other online retailers in a way that makes sense for us and our brand? And then once you sort of make that decision, I think it’s really important to think about how are you going to think about marketing effectiveness

in that world. It’s really easy to sort of look at, okay, someone clicked on an ad before they came to our Shopify site, but you lose that visibility when it comes to Amazon. And so then you wanna start thinking about, okay, we’re still doing e-comm, we’re still maybe 75% direct to consumer, but 25% of our business is now coming from Amazon. And how do we think about making smart decisions in that world? And so when I think about trends for the next year, it’s becoming more omni-channel, and what does that mean

brands that grew up on Shopify to start to make decisions in a more omnichannel world and how do we deal with the implications of that. That’s one big trend and the other one is just the continued sort of changes to our visibility in terms of our ability to track people across the internet.

Arlen Robinson ([25:58].152)

Michael ([25:58].443)
that’s across device or on mobile. How do we live in that world and how do we continue to make good smart decisions when our visibility has been reduced? And so I think really smart e-commerce operators are trying to get ahead of that in terms of thinking about what does that mean for our decision-making process? What are the implications of that for the way that we measure and optimize today? And then what are we gonna, what are we doing to set ourselves up for success in the future as we know that things are changing when it comes to our ability

across the internet and therefore measure the effectiveness of our marketing programs.

Arlen Robinson ([26:33].668)
Yeah, very, very true. And those things are definitely coming down this year. Like you said, these changes in marketing or tracking visitor tracking customer tracking with these various browsers, they’ve all stated that they’re going to, you know, I guess you can say

be more on the side of the consumer, so to speak, with regards to the data and the tracking. And so as a brand, yeah, you definitely have to stay on top of that and make sure, you know, if they, these browsers and these companies shut things down and prevent, you know, let’s say all types of tracking, then yeah, what are you going to do as a brand to maintain your, you know, get, get this customer data, get your prospects data.

What type of marketing funnels do you have? Are there other ways that you’re gonna be able to capture it? So I think in a way, I think it’s kind of good in a way because I think it’s getting brands to think more about owning their customer and paying a lot more attention to their marketing funnels from beginning to end. Whereas before, you know, you relied a lot more on these cookies and these different tools that…

attracting the customer. But now, yes, I think at the end of the day, I think it’s, it’s only a good thing for brands.

Michael ([27:54].971)
I totally agree. I think it’s healthy for the industry. I think it’s healthy for marketers and for the brands to start thinking a little bit harder about where…

where is growth gonna come from? What’s the efficient way to get there? I mean, a lot of huge brands were built on the back of Facebook advertising, which was great for those brands and really exciting. But what’s happened over the last couple of years, and I think a lot of operators who are listening to this can have probably experienced this, is that a lot of the profit margin has gotten eaten away by Facebook, because there are so many different brands competing for and bidding on the same advertising inventory effectively. Like, Facebook clears a huge amount of profit, but you as an operator, your profit is going

Arlen Robinson ([28:12].701)

Michael ([28:35].781)
is shrinking because you’re having to pay Facebook so much for each additional customer that you’re acquiring. And so I think that the future is going to be brands thinking about how do we get away from that and how do we get into a world where we can actually…

Arlen Robinson ([28:41].671)

Michael ([28:51].903)
grow sustainably and profitably, not just by relying on Facebook, where our Facebook and Google search, honestly, where the profit is starting, the profit margins are getting eaten away by competitors bidding for the same eyeballs. And so what’s that next layer of growth going to look like? How are we going to achieve that? I think that that’s what, you know, again, I think it’s really good for the industry overall, although it’s gonna mean a lot of hard work and hard thinking from these brands as they figure out how to operate in that new world.

Arlen Robinson ([28:54].418)

Arlen Robinson ([29:04].349)

Arlen Robinson ([29:08].305)

Arlen Robinson ([29:14].929)

Arlen Robinson ([29:22].837)
Yeah, yeah,

Michael ([29:47].843)
Oh, good one. Oh man, I was like panicking when I had it hurt when I when you sent me the email saying that there’s gonna be a fun fact question because I can I never feel like I have anything good enough. My fun fact is going to be that I

won a talent show when I was in seventh grade with my juggling set. So I had a whole like 15 minute little juggling presentation with jokes and did a bunch of different juggling tricks. So that’s the fun fact about me.

Arlen Robinson ([30:17].388)
Okay, awesome, awesome. How many, what exactly were you juggling? What was this?

Michael ([30:23].81)
I had, it’s a good question, I now like only vaguely remember it, but I had balls and flaming torches, so I did the whole thing.

Arlen Robinson ([30:28].748)
Oh, wow. Okay. That’s yeah. Well, so you were the real deal. Okay. Yeah. Juggling is not easy. Yeah. I remember trying it when I was a kid. I may have been able to get three tennis balls briefly for like 20 seconds juggling a few times. Beyond that. Yeah, I kind of gave up. I lost patience.

Michael ([30:33].511)
That was the real deal.

Michael ([30:48].891)
Well, I think that’s probably a smart idea, because I wasted so many hours of my childhood actually learning how to juggle. And it doesn’t, it’s no good for me now.

Arlen Robinson ([30:54].642)

Arlen Robinson ([30:58].336)
Well, I don’t know. You never know. You never know. You need to juggle something. But, you know, it’s a good, a good hobby, I guess you could say. It’s a good thing to kind of keep you, your focus. And I guess as a child, I’m sure it’s great for the hand-eye coordination. So, I mean, I’m sure that Bill is great for building that. Well, that’s awesome, Michael. Thank you for sharing that. I really appreciate that. Lastly, before we do let you go, if our listeners and viewers want to reach out to you and pick your brain anymore about marketing.

Michael ([31:12].583)
That is definitely true.

Arlen Robinson ([31:28].154)
What’s the best way for them to reach you?

Michael ([31:30].919)
Yeah, definitely. So definitely check me out on LinkedIn. That’s where I post the most about marketing measurement and all of these different topics. So my name, Michael Kaminsky, you should be able to find me there. You can also find me on Twitter at Mike Kaminsky. Both of those are the other two places where I tend to be active and talking and thinking about marketing analytics.

Arlen Robinson ([31:48].948)
Okay, awesome. Great. Well, I definitely will have the link to your site, Recast, the website on our show notes. And I’ll definitely encourage people to check you out on LinkedIn or Twitter and see how you can help them out. Well, like I said, this has been an awesome conversation, Michael. I really appreciate having you on the e-commerce marketing podcast.

Michael ([32:08].159)
Thanks for having me, Arlen. This was a blast.

Arlen Robinson ([32:10].088)
Thank you.

Podcast Guest Info

Michael Kaminsky
Co-founder of Recast