[00:00:00] Peter Mahoney: The next CMO podcast explores topics that are on the minds of forward-thinking marketing executives from leadership and strategy to emerging technologies. And we bring these topics to life by interviewing leading expertsin their fields. The next CMO is sponsored by Plannuh makersare the world’s first AI based marketing leadership platform and hosted byme, Peter Mahoney, the former CEO of Plannuh along with my cohost Kelsey
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in this episode of the next CMO pod. I speak to Dan McGaw, the founder and CEO of mcgaw.io, an analytics and marketing technology company. Dan has spent 20 years as a marketing leader and he’s been called one of the original growth hackers. He was previously the head of marketing at Kissmetrics and the VP of growth at code school.
Dan’s also been called a living MarTech encyclopedia, and he recently released a book called build cool expletive stuff, I guess, which is a blueprint to creating a marketing technology stack. And it has a very interesting title, Dan and I discussed the importance of a data taxonomy for marketing his contrarian view on the idea of a single source of truth for data.
We bust some myths about attribution modeling and Dan even gives our listeners an opportunity to get a free copy of his book by using some cool interactive text messaging technologies. If you’re listening at home in front of the kids, you might consider using your headphones for this episode, Dan’s vocabulary is a little bit spicier than mine.
I hope you enjoy this. Hey, Dan, welcome to the next CMO podcast. We’re so excited to have you here today and to get us started, wanted to just tell your, the audience a little bit about you and all of your many initiatives that you’re involved with these days.
[00:02:15] Dan McGaw: Well, thank you very much. It’s it’s a pleasure to be here.
Thanks so much for having me. Yeah, I’m Dan McGaw the CEO founder of a company called mcgaw.io where marketing analytics at a mark. Wait, was that
[00:02:25] Peter Mahoney: coincide? That that company was the same name as your last name
[00:02:29] Dan McGaw: or was that it is, is I didn’t choose the company name, which is fascinating. It was chosen by our team.
Interesting, funny story. We used to be called effin. Amazing. That was what we started out as, and we were F amazing for five years and we just, well, six years actually, we changed our name last year. So, uh, but that was a fun pursuit to change a company name. Like how do you change a brand? How do you do all that stuff?
But the team chose Magalia, which is quite funny. We originally were going to be a muggle. Associates. But when I was looking at domains, I could only get Mugu and ass and I was like, I don’t think that’s gonna work. Um, all right. I
[00:03:03] Peter Mahoney: already got you off track, Dan. This is unbelievable. Control the conversation.
All right, come back. All right. mygov.io, set the table. What are you all about and what else are you involved in and how did you get there?
[00:03:15] Dan McGaw: Yeah. So a God that he is a marketing technology, marketing analytics agency, but we specialize in building the tech stack for organizations. So we’re really responsible for your revenue infrastructure.
How do you manage your data? How do you use your David? How do you leverage it? How do you use that to ultimately drive the business? I’ve been in this space for over 20 years. So I got my start in 1998. I was sending mass emails since, before there was even mass emails, you know, MailChimp got acquired yesterday.
I started doing mass email before MailChimp was even around. They were started in 2001. So shows you that. I, I was in tech for a little bit too, but fast forward before starting this company, I was head of marketing at Kissmetrics. I was before that head of growth@codeschool.com. So I’ve just been around the block a little bit in regards to that stuff.
And, you know, I get the most fun out of building processes and procedures and operations. Right. I just love data. I like seeing it work. I like automation. So that’s what really gets me. Well, that’s,
[00:04:04] Peter Mahoney: that’s fantastic. And so many of our listeners I know, are struggling with sort of their overall strategies when it comes to technology.
And so let’s, let’s start from the very, very top. So yeah, I’m a new CMO coming into a company. And how do I even tell what I have in whether I have the right stuff in place relative to my marketing technology stack? What are the priorities I should focus on?
[00:04:33] Dan McGaw: Yeah. You know, I think the first area that you really need to start out with is where your marketing automation tool is or where your CRM is.
You know, naturally if you’re a B2C business, your marketing automation tool many times is your CRM. If you’re a B2B business, you have the CRM connected to the marketing automation tool. So you’ve got to get a good. So how those tools are connected, but also how is data being stored? And then how am I going to measure my business off of what’s happening in those tools?
I think that’s a really, really good point of focus. I think the biggest focus that any CMO should be really having is the numbers, right? Where am I getting my reporting from? And that’s why I talk about the marketing automation tool or the CRM in many cases, that’s where the record of truth for many companies are getting their reporting from, well, it’s not the best place and hopefully you have a data warehouse and more advanced analytics.
That’s unfortunately where most people are getting their data, especially in a B2B company. The CRM is where we get most of our reporting. So I would highly recommend focusing on those types of things. But if I was going to give any CMO, a new CMO advice, and this is not a plug for me at all, because I don’t think you should hire us because I, I.
The number one thing that we have seen with new VPs of marketing new CMOs is you don’t have the time to do the true diagnosis of the team, the tools and the data that you’re really using. And it’s really, really helpful when you bring in a third party to do a diagnosis of what’s going on, because it enables you to point your finger and be a good cop on your own and have a bad cop at saying something different.
So I highly recommend to try to get a third-party that’s going to help you diagnose these things. Because you have to remember if you piss off the team that manages these tools and they leave you’re at a bad spot. But if I pissed off the team that manages those tools, that’s different. You’re not a bad spot.
You could just say I’m an asshole. So I think that’s a key thing when you’re trying to, if you’re a new CMO and you’re looking at your tech stack, your team’s not going to tell you the truth. They’re going to hide the dead bodies. They’re going to bury things. So it can be really, really helpful to bring in a consultant.
And I’m not saying, bring us, I mean, I don’t care. Go to Upwork, right? Bringing a consultant who can do a diagnosis and lay the foundation for where your architecture is and your infrastructure. And then start to move from there.
[00:06:36] Peter Mahoney: I think that’s great advice and bringing in, and especially to have a foil, you, you really need as, as, as you said someone to point the finger and blame and say that that mean guy said that this thing is broken and Hey, by the way, is it really broken?
Maybe we should look at that. So I think it makes a ton of sense. Uh, one thing it’d be helpful to understand Dan is. Help people sort of evaluate what’s going on. What are some of the most common problems that marketing teams have when it comes to their overall technology industry?
[00:07:13] Dan McGaw: Yeah. Th the largest problem that is, that is the case a hundred percent of the time is the data taxonomy.
So how are they naming their data? The nomenclature of the data and, you know, organizations three years ago, five years ago, 10 years ago, even 20 years ago. Right. We were all much, much. Silo. But now with the modern stack, we’re connecting everything together. Data’s flowing freely. The problem is, is that the taxonomy that we’re using or the nomenclature that we’re using cross departments do not match.
So when you think about taxonomy data taxonomy, to make sure everybody. You know, when you collect somebody’s first name that is called first name, some companies it’s F name, some companies it’s not right. There’s different ways that that data field is going to be tracked between Marketo or Salesforce or whatever platform it is.
You have to make sure that that data naming the data dictionary matches across departments. So we’re all calling. First name, the same thing. Now I’m using first name. Cause everybody understands first name, but this gets much, much more complicated. When you start talking about account status or lead status or pipeline management, what pipeline is?
This is this enterprise is this small business that nomenclature and data taxonomy is usually the fundamental problem inside the infrastructure, which causes all the issues later. And that’s really the big thing that you have to focus on first is what is the data taxonomy? How does that work and how do we make sure that that’s clean?
Yeah.
[00:08:31] Peter Mahoney: And I suspect that that would cause all sorts of problems these days. Of course, the data taxonomy is far more complex than it’s ever been. Because as you said, you can bring in all of these different data sources and you bring in your giant, you’ve got a CDP, you’ve got a data lake, and we’re going to ask you to define some of these weird elements that are out there these days for people, but w with all this stuff flowing in.
Right now, how, how do people manage all that? Do they even know all of the right all, did they even have a list of all the data elements that come in or is it even a bigger problem? It’s just this rat’s nest that they need to.
[00:09:11] Dan McGaw: Unfortunately, I wish I was a better answer. In many cases, it is a rat’s nest and that’s usually where a company like us gets brought in because we know where all the dead bodies are.
And we know what to look that being said. There are some really, really cool tools which are coming on the marketplace that help you find out your taxonomy across tools. There’s a product out there called sonar, which is really, really big in the Salesforce space. There’s also another. The stack Moxie, which is able to help you do some of this stuff.
And there’s more and more people coming onto the marketplace. I think data governance is becoming really, really important for companies, but it is a little bit of a rat’s nest and most companies are not organized because sales is going to have their data dictionary with their sales ops person.
Marketing’s going to have that. Person, right. Customer success doesn’t even have an ops person, so it can be a little difficult and it becomes really unwieldy. But if you prioritize clean data, the first thing you’re going to have is data taxonomy. And if you’re trying to prioritize specific outcomes, whether that be reporting personalization or automation, the end of the day, it’s all based on that data.
So bad data garbage in garbage out. So you’ve got to get that
[00:10:12] Peter Mahoney: data. Yeah. I definitely have seen a lot of bad data in my day. So if, if you’re looking at, if you’re looking at your, your entire data infrastructure, all this stuff out there, do do most companies that you encounter, do they have some kind of a centralized storage for all this data?
Or is that something that is evolving with most companies? And how should you think about that as a marketing?
[00:10:41] Dan McGaw: Yeah. You know, I think that’s definitely evolving, right? The old adage is what is our record of truth? What is our single source of truth? And I think that’s an old school of thinking. A lot of people try to shove all their data on a Salesforce or something like that.
But I think over the last five years, you know, data warehousing and business intelligence tools, people are getting a lot more. With that and trying to take all the data from all of their tools and put them into a warehouse and then run more sophisticated reports that being said, most companies aren’t even scratching the surface on that.
They don’t have a warehouse if they do it only collects it data maybe. Um, and it’s not getting all of that information in there. So I think there is a large shift that’s happening. Oh where people are starting to do that. But I think that’s also partially because you can now finally pull all the data out of all of these tools, because we have ETL tools like five Tran or stitch or a customer data platform, like a segment or an mParticle.
You finally have the ability to pull the data out and then put it somewhere else, which over the last three years has really changed. So I think people are definitely trying to get data out and put it into a warehouse and then report off of that to get it all on. That being said, I am the exact opposite of having a single source of truth in our model and our methodology.
And, you know, I will definitely talk about my book build cool shit later, we have a methodology where we believe all systems in the stack should get a replication of the data. So if you have a marketing automation tool, it should be nearly a hundred percent match for match to your CRM. But if you also have other products, you’d want to try to circulate that data as much as you can.
So all of the teams can do that. So typically Zen desk or a game site or anything in the customer success world is not integrated in to share its data with marketing or sales. And that’s really a bad idea because you need marketing to be able to access that personalized and customer centric data. So we really are a big proponent of having all of your systems get updated as much as we can, obviously within reason, but you should be constantly.
Cycling your data throughout the stack. If there’s an update in Salesforce, push at the gain site, or there’s an update in Gainsight, push it to Marquetto right. You should be trying to share that data. And that’s a really, really big component that I talk about a lot in my book.
[00:12:46] Peter Mahoney: But I think that makes a, it makes a ton of sense.
And you see a lot of this, uh, this people S stick all their data from different systems into some offsite, cold storage somewhere, and then it’s not accessible by anything. And you can’t take action. So let’s pop up, like on an, a one, two, or maybe a thousand levels here and in talk about why is even any of this stuff.
So I’m a marketing leader, trying to run my functioning, deliver better results. Why is all this data so important to me? What should I be thinking about when I’m trying to assess the priorities for data? And again, what’s, what’s the business driver for me to understand all this.
[00:13:28] Dan McGaw: Yeah. And, you know, I hate to say this old adage, again, you can’t measure, you can’t manage what you can’t measure.
Right. And if you don’t have measurement, you can’t manage that. And it becomes more of opinions. And as a CMO or any business leader, you can’t have the way that you’re reviewing your team, reviewing the company, be opinion based. You have to have it data informed the longer on their still opinion. So, you know, I think measurement is one of the largest components of course, of getting the data.
Correct. You need good measurement to do. But you also need to make sure that you know where to prioritize your team. Very commonly. When you see in marketing organizations, you know, they’re working hard on this campaign. That’s only delivering 20% of the results. If they would be focusing on that other one, that’s driving 80% of the results.
They’d be driving more revenue for the business, but because they don’t have good analytics and they’re based on opinion, you know, unfortunately, Kevin over there who really likes SEO and it’s driving traffic, but it’s not driving revenue. We get distracted by those shiny objects and those metrics. So if you have good data, you can truly manage and truly steer the team in the right direction.
So for me as a data, not as I might say, that is one of the biggest reasons, but I think when it comes down to true CMO management or leadership, People management is just 10 times easier when you can point your finger at a number compared to pointing a finger at their opinion or their emotion or their sense of reality.
So that data makes it a lot easier to manage your team as well.
[00:14:50] Peter Mahoney: Makes total sense. And I certainly agree. There’s, there’s a lot of opinion going on and, and without being backed up by some serious data, you have some, some issues. Obviously, I was going to say something that you mentioned there. Dan reminds me of a key part of my philosophy that I guess is my podcast, so I can share it that I love your opinion on only if you like it is the, the idea that.
With measurement, as you said. So of course you can’t manage what you can’t measure. There’s a really important part of marketing measurement that people don’t do that we’ve really been advocating pretty significantly. And it’s about normalizing measurement to a common denominator of what we think of as business value creation.
So today, I might measure one campaign by lead contribution one by pipeline one, by number of deals, one by clicks or opens or something like that. And we’re big believers that even ROI isn’t useful enough. I think it’s useful, but not sufficient. It’s useful because I know the relative. Return based on what I’ve spent, but I can’t tell the absolute amount of business value that it’s created.
And I can have a hundred X ROI on something that I spent 10 cents on, and it’s not going to move the needle or it can have a three X ROI on something that I’ve spent 5 million on. It is going to move the needle a lot. So this idea of normalizing data to. Marginal business value created is something that we’ve been at advocating.
So I can edit this in post, if you don’t think it’s a good idea, but I’d love your opinion on it. I
[00:16:29] Dan McGaw: totally agree. You know, I was just in a debate last week about a strategy that we were rolling out because of high conversion rates. I’m like, but you’ve got to remember like the volume here is not driving revenue, but we want to ditch all this time into this thing.
So I totally agree with you. I guess the question that I would have for you. How are you deciding what is the business driver? Is it, Hey, we’re looking at just revenue that comes from that. Are we looking at deal size? What are the metrics you’re using to do that?
[00:16:53] Peter Mahoney: Yeah, it’s a really good point. And we’ve, we’ve been spending a lot of time working on prediction algorithms to try to understand what the expected long-term business value will be.
Uh, based on an interim milestone that you might’ve hit. So as an example, you understand it at least to some level of granularity, what your funnel conversion looks like, what an average deal size is, what a lifetime of a customer value is. So you should be able to project a, with some variable accuracy based on where you are within the funnel, what the business value.
An outcome is, and that outcome could be an opportunity and a pipeline is probably reasonably predictable. Cause you may convert 25% of your pipeline with reasonable predictability at an average contract value. And yeah, I feel pretty good about that. You start to go up the stack into, uh, you know, a lead is a little bit higher, harder, but if it’s a qualified lead, you should be able to attribute value.
And then at some point, you stop because it’s just, frankly, not that useful because you know, an open and an email, uh, being worth, you know, one, 1000th of a cent is again, not very useful to, to measure because it’s not very predictable, but you can measure. And, and you can, what we found is that you can.
Project future business value based on a, an interim milestone that you’ve hit. And you can predict you can project the success of a campaign based on historical performance. Combined with where your marketing team expects it to be at a certain time in its life cycle. So those things combined give you actually some really interesting data that you can throw into a machine learning model and come up with a pretty reasonable range of outcomes that are normalized to business value.
So that’s the way that we think of.
[00:18:49] Dan McGaw: I love it, man. You’re totally speaking my language. So we’re, we’re a hundred percent on the same page. I agree with you. The business outcome is most important. So going back to you asked me the question, what is most important to a COO in their role? And I talked of course, a little bit about data taxonomy.
I talked a little bit about getting good data, you know, having that good data and focusing on the true business impact. The true outcome is always where I sit. Like, what are the true objectives and outcomes that we’re going to create and how is this going to make a meaningful impact on the business?
So I think you’re spot on with, um, all of that. Yeah. So
[00:19:18] Peter Mahoney: let’s, let’s, let’s pivot now that we’re in full agreement, let’s find some things that we can disagree about.
[00:19:23] Dan McGaw: Cause that gets spice here. Let’s get into an argument. Right? Exactly.
[00:19:27] Peter Mahoney: So let’s, let’s talk about, about attribution and measurement and in UTM.
So unbundled that for us and, and tell me, tell me what you think about all the things related to that topic club.
[00:19:42] Dan McGaw: Oh man. So attribution the most, the most famous word in marketing ever. So I’m actually pretty well versed in multitouch attribution. So I was hired by a large FinTech company a few years ago to do a, a study on all the multi-touch attribution vendors in the marketplace.
And then what should they do based upon their business? We recommended for them to roll out a custom multitouch attribution model based upon their warehouse. But attribution is extremely, extremely dense because everybody thinks it’s the holy grail. They think once I figure out my multitouch attribution, it’s going to be great.
It’s really, it’s a pipe dream in most company’s cases. Right. I just hate to say it, but you know, the reason why it’s a pipe dream is because. The data that you have in most cases is not good. And it’s because you don’t have good, uh, tracking management and you don’t have good UTM management. And just to help all the listeners understand UTM stands for urchin tracking module.
So before Google analytics was called Google analytics, it was urgent and urgent was the original company and they patented this technology that they would add a query parameter to the end of the. So that way, when somebody clicked on that URL and they hit your website, their analytics product could tell what was the campaign?
What was the source? What was the medium along with many other pieces of context? So you should be using UTM tracking on all of your links that are not on your website. So PBC, email, social media, all of those things. The problem with UTMs is that every single marketer has a different perspective on what should be created.
So let’s just say you’re doing Facebook marketing. You have a capital F from one marketer, you got a lowercase F from another. When you go to do your attribution modeling, those are two separate data points. So it breaks all of your tracking. There’s a product that we created a few years back called utm.ai, which enables you to do UTM campaign link management.
However it enables you to do across a thousand employees. Right? So rules, logic built into it. So people can’t mess it up. If you don’t have good UTM tracking. Your attribution is garbage. It’s really, really hard. It’s really, really expensive to work with. So you’ve got to make sure you have good campaign tracking, set up.
If you have a good campaign tracking, set up your multi-touch attribution and your attribution is no longer a pipe dream because you actually have good data to base it on a good day to move forward and don’t get me wrong. You can get your, your house in order and then do attribution. But first-touch attribution.
Last touch attribution. Definitely have a place in the marketplace right there. Good leading indicators to what is. However, when you truly want to know your return on ad spend, you can’t listen to Facebook. Can’t listen to Google. Can’t listen to any of the ad networks. You need to run a multi-touch attribution model.
We always recommend companies to start out with a linear touch model. So that way they, of course, for every touch point, I’m going to distribute the conversion amount. So let’s say conversion amount is a hundred bucks just to keep around number there’s two touch points will each one of those touch points is going to get $50 in revenue attributed to that touch point.
So if I spent $50 in Facebook ads, $50 in Google ads, there’s two touchpoints. I’m at a met net Eden, that’s your stereotypical easy attribution model, but in the modern tech stack and in the modern market, You have hundreds of touch points and you have all kinds of different ways. You need to measure that.
So it’s really, really important to one. If you are going to get into multi-touch attribution to understand it is going to take time. It’s not a two-week project, not a two-month project, it’s more like a six or 12-month project to really get up and going. And at the end of it, your goal is to drive optimization in your channels.
Their goal is not to do reporting. Your goal is to be able to. Set window of time that I know I made this amount of money. I spent that amount of money and I’m now going to turn these campaigns on, I’m gonna turn these campaigns off. So I that’s the basics of it, but I think a lot of people still, even after I’ve been preaching this for years, they think it’s like the holy grail.
That’s going to help them scale their business. It’s going to help you scale marketing, but you have to have good attribution or you’re going to waste all of your money. So you’ve got to get it in check.
[00:23:23] Peter Mahoney: Yeah. It’s, it’s, it’s interesting. And I completely agree that people have a. MSCI approach when it comes to sort of managing, managing an inconsistent approach when it comes to managing their, their tracking in general, in their UTM codes, especially when you’re distributed across a larger organization.
So it sounds like you’ve got some pretty compelling tools to help with that. I think the, the other point that you make is that it’s a, it’s a long-term significant investment to sort of figure that all out. The other approach. Is useful for people by the way, is to, is to pick a different level to measure performance.
So one of the problems that I think marketers are struggling with today is that we’ve completely bastardized. The term campaign. I campaign should be a long-term thematic pursuit that doesn’t last. A week or a month, it’s something that’s lasting a period of time and it may have lots and lots of underlying tactics in it.
Of course, if you go to Facebook, it says, Hey, add a campaign and you have 75 campaigns in your Facebook thing. They’re really tactics. It’s not really a campaign, but if you organize all that stuff together, you should be able to tell. And it’s one thing that we encourage CMOs to do. Is it a minimum. I should be able to take all of those things and say, I’ve got a digital top-of-the-funnel campaign that includes a bunch of different channels.
It’s got different potential outcomes. And over these three quarters, I’m going to spend $3 million on it. So in aggregate, what have I spent in an aggregate? What is the performance coming out? The other end? That’s actually a useful thing to do to understand the, you know, it’s, again, it’s about picking the low.
To understand where measurement is actually possible to get
[00:25:10] Dan McGaw: there. Yeah. And I, I agree with you. I think most companies may campaigns, the tactics, they don’t actually make the campaign, the broader campaign gates in, and our taxonomy. When we think about UTM management and campaign management, many of our campaigns are never ending.
Right. They’re ongoing. Multi-year, they’re just continue to go, but things roll up to that, but it’s, it’s a good way to structure your data. Um, so I agree with you. People are too tactic focused on the campaign. Yep.
[00:25:36] Peter Mahoney: Absolutely. So let’s, let’s do this. Let’s let’s spend a minute and talk about your book because you, you wrote a cool book that now, unfortunately, when we talk about the title is going to make me put the explicit thing on my podcast, but I guess that’s okay.
I, so tell me about the book. What motivated it and then why should we all be reading the readings? Yeah, well,
[00:25:57] Dan McGaw: I’ll call it a build. Cool shit. So, and just add the T at the end, you don’t have to add that explicitness to it. Again, another thing that I created that I did it name, but it came out. So you don’t.
When we really started talking, when we started noticing this massive switch in the modern technology stack, compared to the traditional stack, right? So modern tracking when we’re talking about, you know, Marketo and Salesforce are amazing products. You consider them traditional tech stacks, modern stack is looking at more of these customer data platforms and wildly integrated things, stacks that are not rate limited, like you would be on Marketo or Salesforce as an example.
And when we looked out there, you know, the stack was growing. I mean, at the time there was 9,000 different. Right now there’s supposedly 16,000 tools. I just got reported to me and trying to understand how do I choose a tool? Why do I choose a tool? How do we integrate all this stuff? Where do I put the data?
You know, as a, as a senior executive is dense, it’s really, really hard. And you’re dependent upon a marketing operations or a revenue operations person to help you, but you still need to have the foundation. So I specifically wrote the book to help executives understand. What is the stack? What are the key components of the stack?
And then what are the outcomes that you should be able to create in your stack using the modern stack? So we talked about data enrichment. We talk about customer data platforms. We talk about how do you do modern personalization and all that stuff in the. But it’s a really short read. Like you could knock the book out, it’s 130 pages full color, and you can knock it out in two and a half hours on a Saturday.
I knew if I wrote another big book, like everybody else, it’s 400 pages is going to take you six months. Executives wouldn’t really read it. So we tried to make it. So it was bite-sized and easy to understand and also really, really engaging. So it was a ton of fun to write. And are you, I’d love to give everybody an opportunity to get a copy of the book if you’re cool with that for free free
[00:27:42] Peter Mahoney: stuff for my listeners.
Yeah. Yeah,
[00:27:45] Dan McGaw: great podcast offering. So what I want you to do, pull out your cell phone. Okay. We’re going to have you text a word to this number and it’s going to have one of our text bots actually collect all of your information and we’ll ship you a free book. Automagically as we like to say. So the phone number is (415) 915-9011.
I’ll say the number of. 4 1 5 9 1 5 9 0 1 1. If you text the word MarTech. So M a R T E C H just texted the word MarTech. It will respond back and actually click all of your information and ship you a free copy of the book. So sell for 22 bucks. Shipping is about seven. I’m going to give it to you all for free because you’re on this amazing CML podcast, but I promise you this.
It will change your perspective on how a stack is built and how the modern stack is really changing compared to the way it was five years ago, or even two years.
[00:28:33] Peter Mahoney: Well, that’s. That is awesome. Thank you so much for the generous offer. And I encourage everyone to check it out and it sounds like a really important book, by the way, I did text it and it magically came back.
So I’m going to check out this really awesome SMS bot, too, that Dan just exposed me to, because this is amazing and a great tool for all the podcasters out there to convert audio into, into leads. So now I am now forever a lead in.
[00:29:02] Dan McGaw: And conferences, if you ever do conferences, the text magic is a lot of fun.
And I will say this, you know, one thing that we didn’t talk about, we’ve talked a lot of stuff about with CMOs. SMS is an amazing channel, right? It is really, really powerful, but you have to make it so that SMS is a two way communication channel people tell. The spam other people here it’s 10% off. That is a horrible way to do SMS and get you a ton of unsubscribes.
If you can make it magical and make it. So it’s a two way conversation using these tech spots. It doesn’t have to be perfect. You’re going to have just a better outcome. So for all CMOs, who were thinking about SMS marketing you’ve leveraged platforms like Twilio, where you can actually create a bot and do a two-way communication, it’s really going to change the way that you can have your messaging.
[00:29:43] Peter Mahoney: Yeah. I’m glad you brought this up because I think that. They with the increasing restrictions around third-party data access that are coming up, it’s going to become more and more important for people to, to, to build, collect, and, and really maintain and protect. Their first-party data. And so you just brought up this really important thing.
Don’t spam people. I mean, that’s an obvious thing, right? Although a lot of people seem to be doing it. So there seems to be some issue out there. But tell us a little bit about how we should think about in this, how important is first party data. I just led the witness and said that it is. So if you disagree, I’m going to feel dumb, but how important is that in?
What should we be doing differently? If anything, given the impending restrictions on third-party data for cookie.
[00:30:34] Dan McGaw: Yeah. And you know, I was introduced a few weeks back to zero party data. I don’t know if you’ve heard of the new one, but soon we’ll have second-party data to the seventh-party data, but, you know, zero-party data is the information that our customer gives us.
And then first-party data is now being classified as the information we track about our customers without them having to do anything. So like our normal tracking, you know, I think this zero party data, if you email. Slack that, or excuse me, you text that text bot. It’s going to give you zero. You’re going to give us zero-party data.
You’re giving us your data, uh, very, very willingly. Then don’t get me wrong. First-party data, what we track on the websites, and stuff like that. Once again, there’s the new term for everything, but whatever, you know, I think this is super important. Our company’s mission. So literally our company’s mission is to help businesses of all sizes realize that their customer data is their most valuable business asset.
And then to help them really. Through marketing technology and all the tracking, really as a company, getting customer data and storing that is extremely, extremely important because you need to know what’s going to make your customer happy. What’s going to make them sad. What’s going to make them mad.
Right? And you can’t do that unless you know who they are and you collect that data. So personally, and also with our business, we think your customer data is the most valuable asset you had. And we also see companies who are worth a hundred billion dollars. Let’s just joke about it facing. W w or Google or, oh yeah.
I forgot iPhone. You know, the, the, the data is what’s most important at the end of the day, don’t get me wrong. Apple makes all their money off of selling devices, but you know, apple knows the most about you out of any single tech company in the world. They’re on my wrist, they’re on my phone. They track my health.
They track my sleep, they track every single thing I do. So you really do have to realize that the most valuable companies in the world. I have the most customer data about their customers. So it is extremely imperative for your business to get more data and then to leverage and harness that data to drive your business forward.
I personally, I think it’s the most valuable asset. Any business.
[00:32:28] Peter Mahoney: Excellent. Completely agree. And I’m glad because it would have been embarrassing if we didn’t. So that’s, that’s great. Well, Dan, believe it or not, we’re coming toward the end of our time here. This has gone very quickly, but before I lead into my last question, I just wanted to make sure that you share with the audience one more time, how they might learn more about mygov.io and in your other initiatives, we heard about how to text to get your book, but tell us how to learn more about the company.
[00:32:56] Dan McGaw: Yeah, for sure. I mean, is really easy go to the website. So you’ll be able to find out a lot of stuff there. That being said, if you’re really looking to engage and follow along, I would love to talk with you on LinkedIn. I’m most active on LinkedIn. So go to LinkedIn type in Dan and Legon or GoDaddy Yelp would love to answer any questions you have, or be able to point you in the right direction with something that can help you.
I always love being able to chat with other marketers and other people in general. So looking forward to chatting.
[00:33:20] Peter Mahoney: Awesome. Thanks for sharing that, Dan. And then the last question we like to ask everyone who comes on the show, what advice would you give to current or aspiring CEOs?
[00:33:31] Dan McGaw: I would definitely say you need to become more data-centric and more technology centric.
Those are the main things that I think most CMOs or new CMOs need to really focus on in the next five or 10 years. You know, marketing is going to be run by machine learning and artificial intelligence. It’s going to be less people it’s could be more machines. You need to understand how the underlying data works and how the technology works, or many people that you’re going to get left behind a little bit.
So I think that’s really impaired.
[00:33:55] Peter Mahoney: Well, absolutely. We certainly agree with that too here. And Dan, I wanted to thank you for joining me on the next CMO podcast and thank you all for listening. And if you have suggestions, ideas, comments, complaints, please let me know at the next CMO at Plannuh dot com.
Make sure you follow us on LinkedIn and Twitter. And thanks again for listening and we’ll see you out there soon.
nextcmo
16 Nov 2021
