Alex & Michael: Episode 527

Transcript

[0:00:23] MR: In 2019, $130 billion was spent on digital advertising alone. That’s billion with a B. There’s no denying that the age of the internet has changed the way companies market to their consumers. But despite these massive digital marketing budgets driving global ad campaigns, many companies and marketers still lack the knowledge of whether their digital marketing campaigns are effective. In the new book, Crawl, Walk, Run. Michael Loban and Alex Yastrebenetsky discuss six focus areas in digital transformation, including how to choose the right platform and staff, strategies to upscale your team, and how to build effective processes for everything from Google Analytics, 360 to how data governance and privacy guidelines work. In today’s episode, Alex and Michael share why this is so important in today’s world, the six P’s for digital transformation and the kinds of data you should be keeping track of, so you’re not left behind in today’s data driven world. Enjoy. Hey everyone, my name is Miles Rote and I’m excited to be here today with Michael Loban and Alex Yastrebenetsky. Coauthors of Crawl, Walk, Run: Advancing Analytics Maturity with Google Marketing Platform. Michael and Alex, I’m excited you’re here, welcome to the author h our podcast.

[0:02:01] ML: Thank you for having us.

[0:02:03] Alex Yastrebenetsky: We’re excited to be here Miles.

[0:02:05] MR: Yeah, I’m excited to be here with you all too so before we jump in to – there’s so much about your book that I want to talk about but before we talk about that, why don’t you each give us a little bit of background on who you are and then we’ll talk about what inspired you to write this book?

[0:02:21] ML: Sure, my name is Michael Loban as you’ve mentioned. Alex and I, we started the InfoTrust a little over 10 years ago and currently, I work as a chief of gross officer within InfoTrust, and predominantly my role is to meet with our partners, which happens to be a lot of their large advertisers, large enterprises, and help them determine how digital analytics can help them grow, can impact positively their digital customer experience, and create more revenue for their businesses.

[0:02:56] MR: Alex? What about you?

[0:02:57] Alex Yastrebenetsky: I’m Alex Yastrebenetsky. I’m actually the geek in this relationship, if you will, with Michael. I’m an engineer by training and while Michael is coming up with all these brilliant ideas, I focus on innovation and building things. In my day-to-day role, I focus on both the RND for our company and innovation and building new solutions.

[0:03:25] MR: Sounds like quite the dynamic duo. I feel like that’s what you got to have is the ideas and then the executor, that’s awesome. As far as coming up with these ideas and then executing on them, what does that look like? Who should be reading this book? What are you working to solve, what problems are you working to solve?

[0:03:44] ML: Sure, when we began working on the project, we started with quite a bit of market research to see what books were available on the market, and also having numerous conversations with our partners, with our clients, asking them what information they read. Immediately, we noticed that there was a gap. On one hand, there was a lot of research, a lot of content created in Harvard Business Review and number of other publications about what the future of analytics is. Those articles were quite high level, very business focused. Somebody who may be in a position of executive vice president, CIO, C-level might be reading and then task of their organization with, “Here’s where we want to go, help us and get us there.” And then there were a lot of very technical topics such as how do you deploy Google tech manager on your website or how do you track analytics? But certainly, there is quite a bit of gap between those two topics. The question that we set out for ourselves is how do we, in this book, share best practices and help organizations across different industries determine what the future of analytics holds? What they need to be doing across their businesses? But also, how do you actually roll up the sleeve and do it from standpoint of what does your team look like, who are the people that you need to hire, what are the platforms and tools that you need to be using? And we focused on Google marketing platform. How do someone with the processes look that you need to build within your organization? We see this book as really a field guide to where, yes, we will share with you where analytics is going to help you determine where you want to be over the next two, three, four years. But then, we will also provide you, there is quite a bit of actionable recommendations and how to for how to get there.

[0:05:50] MR: Wow, this sounds like a book not only helping companies understand what they need but then, actually, how to do it. Who should read this book? Is it CEO’s, is it those engineers actually implementing these changes, or is it for all of the above?

[0:06:07] ML: Let me start there with something that you’ve mentioned. We kind of said it seems like this is something that people need to understand and then determine where to have. Understanding and knowing is maybe 20-30% of the job, right? We seem to be very focused about, “Well, I just want to make sure that we have the right strategy. I want to understand what analytics can do for our business. I want to better understand my ROI from analytics,” right? We tend to obsess quite a bit on that vision when, in reality, the results and what differentiates organizations that are killing it with analytics versus the ones that are dreaming about analytics, are the ones that have a plan in place and they execute better than anyone else. With that in mind, the book is actually written for those that are executers within their organization. We look at VP of digital, VP of marketing, head of analytics. Those are the people that this book was written for, and then the idea is you take this book and you give a copy of this book to everyone within the organization who is tasked with digital experience, is delivering the digital experience to your audience, and you use this book together to determine, do we have again the right team? What are the processes that we have, what are the processes that might be missing within the organization, and what does that look like day-to-day when we begin to execute? Because otherwise, it will be just yet another book on a shelf, not used by anyone.

[0:07:46] MR: Right. I can imagine that, for so many companies, as they try to transform into the digital world that this is really where they can get most caught up, and most frustrated, or lose out on the most potential for opportunity. Maybe let’s discuss a little bit about that. Why is this topic so important and why are analytics in gathering this information, why is it so important to businesses in the first place?

[0:08:17] ML: Well, analytics, the way we see it, can help us diagnose the situation, right? Analytics can help us determine what is it that we have right now that is either working, or maybe not working within the business, within all the markets and that, and then, if used properly, it can help us most forecast or predict where we are going to end up and what we need to do to get there. Now, one of the chapters in the beginning of the book, they use the framework that Google and Boston Consulting Group have put together, where they define the four stages of digital analytics maturity. The framework is quite important to help organizations really determine where they are in terms of their digital analytics maturity right now. Because if you ask somebody, do you use digital analytics, or are you getting the value of digital analytics? People have distinctly different responses. Some feel like, “Yes, we do,” some feel, “Well, we could be doing better.” It’s very difficult to actually accurately pinpoint where the organization is in their maturity. We started with let’s first help us determine where your business is right now, in terms of how you are capitalizing on data that is available to you. Are you in stage one, maybe where you’re just getting yourself to collect right data about customers? Or are you at a more mature stage, where you are actually able to use analytics on regular basis to help you deliver the best experience to your customers?

[0:10:02] MR: When companies are implementing these analytics and they do start to bring this into their company, is this something that you recommend they try and do in house? Or is this something that you recommend companies should outsource and hire outside for?

[0:10:17] ML: There is quite the bit that can be said about this topic and over the past year or two years or so, there’s been a lot on topic of in house, right? As more and more organizations take this work in house and start building out their teams. It really depends on the organization and the leadership. We’ve seen quite a bit of success with companies taking, for example, media buying in house, they can create it in house, taking and building their own data like data warehouse in house. Organization can choose to do everything themselves but we need to be mindful aboutm what is our organizational business model? Can we really do all of this ourselves? Or, are there certain things that we want to control, that we want to own and manage, and then we will bring in different partners to help us execute along the way? I think a lot of companies have maybe bad memories when maybe they’ve worked with an agency, as our partner, who would provide them with insights but would not tell them how they got to those, or would not share all the information. They did not have access to clean, transparent data and so companies said, “Well, we want to do this ourselves so we own data,” which is such a crucial competitive advantage. The organization makes that statement and says, “Look, it’s now an opportunity for us to do and own more in house,” they can absolutely do this, and still build a flexible framework where they bring in different partners to help them along the way. I would say that companies that want to do everything in house either should have a history of being able to do that and deliver, or they might find themselves in the challenging position where they will over promise to their own leadership, and then, they will not be able to deliver, which is infinitely worse.

[0:12:22] MR: Right. Let’s talk about now, I guess, the process of what that looks like. Let’s say, a company is ready to take it on and they want to transform and become digital, and really using analytics to capture everything in the process. You actually have a formula for this with your six P’s of digital analytics transformation. Purpose, people, platforms, process, pace, and payoff. Can you tell us a little bit about those and why those are the most important in your eyes?

[0:12:56] ML: Absolutely. As I mentioned, we used the framework or the four stages of digital analytics maturity that Google and Boston consulting group have put together. As we would meet with our partners and clients, helping them determine where they were, the next question was, “Well, that’s great that we are at a [inaudible 0:13:19] stage, that’s fine, we will own that, but how do we know that we progress to the next stage? How do we become let’s say, multi-moment?” That was a question that that we did not immediately have the answer to. Yes, we could say, we needed to have more access to data, we need to have more tools, we need to train your team but we did not want to be all over the place. We spent quite a bit of time determining what are the things that the organization really needs to do to capitalize on, and be able to move from one stage to another? The first one was purpose. Well, we need to understand why they actually want to do better this data. Funny enough, a lot of organizations don’t have a great answer to that. That’s really a place to start. Why are we about to make so many changes within their organization, why do we want to invest in analytics if there are plenty of other things that we need to be investing in? That’s why the purpose is so important. Why are they doing this? Then, once why becomes clear, then we look at three levels of execution. To do anything, we need to have the right people, that’s people, right? Then we need to have the right tools which is our platforms, right? In this book, we talk about Google markets and platform as one of the key solutions that organizations that can and should be leveraging, and then processes, how do the right people use the right processes to accomplish the right results? The last two, pace and payoff, well, like any type of project that the organization might be working on the question is, how do we know that we are successful? That’s what we want you to measure. We want to measure payoff, so are we actually able to generate more revenue or generate more profitability for our business as a result of our work? Then pace, are we able to move faster than other organizations? Because speed to market, speed to implement it is absolutely crucial. So having access to data is a good start but we need to be able to leverage it sometimes faster than anyone else can put their data to good use. How do we outperform and outrun our competition?

[0:15:46] MR: Right and when it comes to data and collecting data, I think it is such an obscured term for some people as far as what does that look like, what does that mean? So when it comes to data and what companies should be tracking, what are some of those metrics? For example, customer lifetime value, I know is one, but what is some other metrics that are really important with the work that you all do when it comes to setting up companies, to help track their data?

[0:16:16] ML: So in terms of what should be tracked, I think that is one common answer that a lot of people in the industry give out, let’s track everything. Yes, you can make the decision, how you store data is cheaper, so let’s track everything that we can, but if you don’t know why you’re tracking it, you’ll have a hard time figuring out what to do with that information, right? So what we suggest is focusing on, what are the metrics, and we might go from super technical metrics to more business metrics. For example, a metric as such as customer lifetime value, right? That is very much business metric that can impact how we target the people, who we target, and how much we are going to spend on advertisement, knowing how much revenue we can generate. Profit per channel, percent of sales, influence per each channel, incremental revenue via testing, there are different business metrics that the organization can focus on, and then the question is really how do we build almost a funnel of metrics? From the standpoint of when the user comes to a website, how do we collect what they’re doing on our website so we can impact our website conversion rate, our website click through rate, to the set of metrics, in terms of who are really our ideal customer types are, and here, how do we use things like the customer lifetime value to determine who we should actually be going after and who we shouldn’t? So in terms of what do we want to collect, it really comes down to what are the decisions that we are working on, and that we need to make.? And then based on that we will take one or two or three steps back to determine what information that will help us make that decision. Alex, do you want to talk a little bit more about data collection itself from the technical standpoint?

[0:18:17] Alex Yastrebenetsky: Yeah sure. There is a couple interesting things to keep in mind. First of all, something that the readers of the book definitely need to be very familiar with these days in terms of data collection is all the privacy and compliance. Something that’s fairly uncommon from analytics world, we spend a significant – it was inside of the book, talking about data privacy. I feel that in this day and age, to talk about analytics, talk about data collection, without first stepping back and making sure that the data that you are collecting about the visitor is compliant with the privacy policies, for example, in the state or in the country where the visitor is coming from, would be an oversight. Because certainly, marketing people would love to collect all sorts of data but it doesn’t mean that, in this day and age, you should be allowed to collect this data. Something that we would definitely encourage the readers to look into is a new legislature that is coming from the State of California called California CCPA, consumer privacy act. I don’t want to take us down the rabbit hole of talking about all of the details, but two years ago, there is major piece of legislature in Europe called GDPR, and a lot of marketing people are familiar with it. I feel that if this was not the year of COVID and the pandemic, and everything being sold disrupted, at least the advertising in the market saying industry this year will be totally preoccupied with the California Privacy Act, simply because it is not just impacting California but it is impacting businesses that sell to citizens of California, snd also now more than half of the States. I honestly do not remember the last count but more than half of the States have their own flavors of copycat legislatures that are at some stage of being opted, which means that if you are a larger size company for example, the CCPA is 25 million and above, you really need to understand how to stay compliant, and what to do with the consumer data before you even start collecting the data. So that is one of the points that Michael asked me to cover. The other thing is what do you with this data, basically once it’s collected? And this is where geeks like me come into play with all of the really – so if you think about what happens with the data, the first step is obviously the governance. That has to oversee, I guess, the process of data collection, and then once you collect the data then the next step is, once the data is compliant, what are you going to do with this data and how are you’re going to make this data actionable? Obviously, we are getting more and more into the times when we’re not going to have analysts looking at the data and reading the charts, kind of like 30 or 40 years ago, you had stock analysts reading the charts. We are having more and more of the decisions that are made by the machines. In many cases, data that’s coming from analytics is getting combined with other data sources. For example, data sources about the purchase, and data sources about – from customer relationship management systems and so on. Data scientists can run the data through algorithms and come up with things, like Michael had mentioned briefly, customer long term value, which is one of the most common things to do but you can do all sorts of other things. For example, calculate propensity to buy and so on. It is a very interesting – the industry overall is going through a very interesting phase right now as more and more of the KPIs and the metric that are collected from analytics can now be better analyzed and should be analyzed by the machines, not by humans, to figure out what to do with this data and let me just give you one example. Let’s take visits from a website. That is a very technical metric if you will. So do you want this metric – for the analyst to start thinking about what to do with this metric, or do you want to plug it into a fairly simple algorithm to figure out what has to change across your channels to drive more traffic to your site?

[0:22:50] MR: Right.

[0:22:52] Alex Yastrebenetsky: There is a ton of tools for example also that automate testing of website performance. Those are the kind of things also that can be left to, in many cases left to machines to figure out, instead of having the user figure out – the user, the analyst or the web ops person try to figure out what to do with this data.

[0:23:14] MR: Right and Alex, I am so happy you brought up the privacy component, because I think it is such an important topic and obviously very important to businesses ensuring that they are compliant that there is so much they can go into that it can be overwhelming. You do cover a lot in the book about this. Another thing that I really loved about the book is the different tools that you have. Michael, you mentioned just having so many different things dependent upon the company as to what is needed. And you have so many different tools that people can use in the book and fill out, and forms people can fill out to really identify those needs. So, thank you for putting all of that in there, but Alex, to your point about the artificial intelligence or machines being able to actually take all of the data and then analyze it for us, how much and how important is the Google marketing platform for all of this, and how can it be leveraged to help businesses?

[0:24:14] Alex Yastrebenetsky: That is a very good question. How much time do we have for this podcast? Because I can probably talk about it for the next three hours. But the fundamental, like one of the key features that is available in the Google marketing platform, that makes it extremely exciting, is that as long as you have what’s called GA360, which is the premium version for Google Analytics tool, you can get access to the raw data. So you are no longer looking at the averages, you are not looking at the average. You are looking at the world data collected from the consumers. There is one of the most exciting, for geeks like me, features of Google Marketing Platform, and it’s called BigQuery. BigQuery is a big data that allows you to take this world data collected from Analytics, and because it is a part of Google Marketing Platform, it can access data from Google Analytics directly. As a matter of fact, it doesn’t actually matter, Analytics can just put all of the data in BigQuery. You know you can run your analysis on this data without doing any additional work. You do not need to move the data from point A to point B, the data is right there for you, but in addition to be able to run your models, BigQuery makes it extremely easy to take data from other sources at hub, and add it to your models, to your calculations, to see how, for example, combining this data set together with your analytics makes a difference. So that is one of the key, I guess, capabilities in the Google Marketing Platform that makes it so exciting for marketers and for advertisers.

[0:26:02] MR: It’s amazing. Michael, I would love for you to chime in on that and on the idea, just maybe to close this podcast out a little bit, is the idea of just marketing changing so much, and how these tools really can benefit companies in a way like never before in the past.

[0:26:20] ML: Sure. In the beginning of the book, they published a graphic that most marketers have seen at some point, is the amount of different tools and solutions that are available to marketers. Every week, I get an email or a LinkedIn message from somebody sharing that there yet another tool that will either collect the data or will analyze the data better. There are certainly [inaudible 0:26:47] solutions. There are a couple of things that are important to remember. When you get pumped by the data there is so many new tools. One is we only have a very good understanding of your own strategy to help you determine what you need and what you do not need, because a lot of the times we see these companies, they get so excited about the promise of yet another solution, that they end up using about 50 to 60 different tools, and the result is that they are accomplishing are there are those solutions are miniscule, right? So we spend a lot of time and money getting those new shiny objects, but then they are not able to capitalize on them. That is one of the reasons, in this book, we spend so much time talking about how the organization needs to build their teams and establish processes and then determine what solutions are needed, what solutions are not needed, what the company can build themselves versus what company can buy. We spent a big chunk in the book on Google Marketing Platform just to showcase how much one company can accomplish this one full integrated solution without the need for buying 20, 30, 40 different products. So there is certainly an opportunity to be creative, curious, and add new solutions to your marketing stack, but you want to be very careful about what you say yes to, otherwise you’re going to go about this as if you were like technical Frankenstein that has very slow to move, very expensive, and does not really provide a lot of ROI.

[0:28:35] MR: Such good advice and for clarity on exactly how to do that, and that’s what your book is for. So Michael and Alex, this has been such a pleasure and I am so excited for people to check the book out. Everyone, the book is called, Crawl Walk Run: Advancing Analytics Maturity with Google Marketing Platform, and you can find it on Amazon. Michael and Alex, besides checking out the book, where can people find you?

[0:28:59] ML: Probably the best is our company website. We also set up a special resource page for the book, there’s a lot of additional information. So everyone can check that out which is infotrust.com/crawl-walk-run, and that will connect with us personally. For me, LinkedIn tends to work the best or filling out a form on the landing page on our website about the book.

[0:29:26] MR: Perfect, thank you so much and everyone, the website is infotrust.com. Thanks again guys.

[0:29:36] ML: Thank you.

[0:29:38] MR: Thanks again for joining us for this episode of the Author Hour Podcast. You can get Michael and Alex’s book, Crawl Walk Run: Advancing Analytics Maturity with Google Marketing Platform, on Amazon. You can also find a transcript of this episode as well as our previous episodes on our website at authorhour.co. For more Author Hour, subscribe to this podcast and thanks again for joining us. We’ll see you next time, same place, different author.