“Slash the marketing budget – now!” Covid-19 is impacting businesses and many companies are immediately turning to marketing to save a buck. It might seem like a good short term strategy, but what impact will it have long term?
If you are wondering how crisis can be navigated effectively and cash managed through automation and innovation, you need to listen to this podcast.
In this episode, Mark and Kyle discuss:
- What companies should be doing to innovate and automate their data
- How to use sailing techniques to keep your business on track
- Leveraging marketing dollars for specific outcomes.
- The place of marketing mix modeling in businesses today
- and much, much more.
Hello. Welcome to the summit, the podcast where we’re bringing your knowledge and insights from industry leaders who are professionals. No fluff, no double digit overnight growth schemes. I’m your host Kyle. We’re on a mission to find secrets to success in business where we’re having real conversations with real people to get you really answers on how to elevate your business and your career. Today’s guests joining us on the summit is Mark stews. Mark, welcome to the show.
Hey man, great to be here. Thank you.
For those who don’t know, Mark, Mark is an award winning B2B COO and chief commercial officer. Mark is one of the first leaders to connect all types of marketing investments to revenue margin, cashflow impact in complex long cycle companies. In 2014 he was named innovator of the year for pioneering his work in the U S markets. His company proof analytics delivers marketing mixed modeling. It allows companies to understand their relative impact on ROI of their marketing initiatives and optimize accordingly. Mark, when I look back, did I miss anything about you? Is there anything else you’d like to call out?
No, that was, that was awesome. Man.
Well thanks for being here. I mean, we’re, we’re really excited to have you on the show and to get into our topic today, which is navigating innovation and automation to thrive in a coed 19 world.
That’s a big topic,
man. It, it really, it really is. But the thing is, is that there are some underlying principles and priorities that I don’t think any company has really ever faced. It’s not like you can say, Hey, you know what, the HPS or the, uh, the GMs of the world have been through something like this before. This is really something that’s new for all of us and we’re seeing a never before, um, impact on businesses. There’s this network effect that’s happening and it’s like all of a sudden yesterday oil is at a negative and negative commodity price. Like, when does that ever happen as you start to look at what’s going on, how businesses gonna prepare or begin to understand how to navigate through this?
Well, I think that that when you, when you look at, uh, at any point in history where you see a sudden major shock, um, to a society, um, followed usually by a lot more, right? They kind of go in waves, right? It tends to completely upset the status quo. There was actually a great article in the financial times. Um, that’s one example of this where the headline was why the wealthy fear pandemics someone, right? And if you look back, you know, say 700 years, there’s been a lot of pandemics, uh, during that time in particular three or four that really bad. If you had a deep stake in the status quo right before that pandemic hit, you’re almost guaranteed to be stripped of that after. And so that is one of those things where everyone’s kind of looking at this whole situation and saying, Whoa, I used to know who is on first, second and third base.
And now I’m not so sure, and I’m not even sure where I am on this field of play anymore. And so the idea of a GPS, it becomes extremely compelling, right? What does a GPS do? GPS is way up in the sky, right? So it has a point of view that, that you don’t have standing on the ground has perspective that you don’t have. It can tell you where you are. It can also respond to you saying, I want to go over here by saying, okay, this is where you are. This is where you want to go. This is the recommendation. The recommended route, right? Here are some maybe one or two other potential routes that you ought to consider. Here are some of the things that might get in your way. Um, if that gets to be too bad, we’ll reroute you all that kind of stuff, right? I mean, we all use this all day, every day in our personal lives, but that is exactly what society and companies and organizations and teams are looking for today because there’s suddenly so much thrown up in the air. There’s so much that’s uncertain or unknown that if you don’t have something like a GPS to help kind of put the puzzle back together again, you’re going to really struggle. And so that’s one way that we look at what we do is we are that GPS.
What’s the concept of a GPS is really interesting cause you think about, you know, it’s really to help you get from point a to point B and when we’re in this economic transformation or transition and there’s not really any one way point that we can rely on. You know, it’s kind of like when you get in your car and you turn on ways and all of a sudden you’re driving down the road and you’re like, well somebody forgot to Mark that there was construction here. I can’t go that path anymore. When you look at the evolution of, of navigation and you look at, you know, what’s going on with the network effects, how can businesses actually build that GPS or build that perspective so that Hey, we’re not constantly running into things where it’s like, Oh that’s under construction. And everything that I did was a waste. I have to actually go back, Hey, can you give us perspective?
Yeah. So this is, this is actually where automation and things like that, even AI comes into play, right? Because you’re essentially saying we had a map, right? So what does a map do? The map helps you visualize it in two dimensions and you may or may not have directions that go with that, but no matter what, it’s a static representation. So the map was drawn several years ago. Presumably it’s more or less still accurate. There may be some new streets though and certainly it doesn’t take into effect current conditions, rain traffic, whatever, right? So whatever you think is going on based on that man, it’s a very small thin picture of what you’re actually going to encounter. A GPS on the other hand is, is live. It’s dynamic. It’s saying, you know what, not only do I know exactly where you are down to probably a five foot radius, right?
But I also know where you need to go. And I have all these data feeds that are coming in, right. Telling me about traffic and things like this. And I am able to then say this is going to be the effect of that. On you. So now we’re talking about a fundamental difference between measuring something and analytics. So measurement being very static, it’s very important by the way, you got to have the data, but it’s very static. This is going on at this time and this place, but we’re making no guarantees that that’s still going to be the case 30 minutes from now. Right? Analytics is saying, I’m taking all this data and I’m associating it with other data and now I have a picture of the interlock of cause and effect that is going to help you or hurt you get from a to B.
Most most companies have data or reporting or what we’re calling the map. How do you go from, from data where I have a map and I know where I’ve been, the things that mattered before to this GPS. Like what does that, what does that even look like? Well, so, uh, it’s actually the fundamentals have been around for a really long time, right? It’s regression. Mathematics is really what we’re talking about. And regression essentially allows you to assemble a picture of the effect that all of these things are having against this thing over here. Um, so we think of it as cause and effect, right? And what’s the stack rank? What’s the power relatively speaking of these 10 things against this one thing over here. Um, however it’s been extremely expensive to do. It requires very, very, uh, highly educated data scientists and mathematicians pull off.
Um, those are even today not easy to find. And because it’s largely a human powered effort, it takes a long time to get the insights right. So if your world is changing quickly and your data analytics can’t keep up with that, right, then all of a sudden you’re going to get the news long after it’s become real in re, you know, and that, that’s not going to help you. So automation has been the big quantum leap in this area. So today, for example, with proof, we’ve solved all those problems just at one stroke, right? So it’s a lot less expensive. We’re talking about like 10% of what you would normally pay for the same service done the old way. Uh, it’s very, very scalable. You can, you can kind of use it however you need to use it. You can run it, run as many models, which are a model is essentially a mathematical structure designed to answer a specific question.
So you can run as many of those as you need to. And that’s been a big limiting factor in the past. And then it’s always on, right? So it’s proof is real time. So the value of being able to recompute all of your models more or less constantly as you’re moving through time, when the future becomes, the present becomes the past, it allows you to find out, okay, are our prediction, our projection into the future on this? Was that accurate or not? Right? Is, is the actual line right on top of our projection? Is it above it, below it? What does that mean for our operations? Right? So all of a sudden the impacts on that of that on the business are huge, right? Because it allows you to control your risk, right? So your, your risk isn’t all backend loaded, right? You can, you can manage it closer and tighter.
Um, you can really see what is not only changing in your performance, but what are the other things over which you have no control that are changing. And so what does that mean to your response? So that is really the GPS. I mean, if we think about, you know, the same things are true. Where am I? Where’s my business right now? Right? What, what, so what’s the lay of the land around me? What does that all look like? Where do I need to go? Well, I need this kind of growth and this kind of profitability and I need all this kind of stuff. Okay? So there’s the line from where you are to where you need to go. What are the things that can either make that happen for me or stand in my way? So those can be things, you know, the headwinds, right?
Can be everything from the macro economic picture, cov ID, all that kind of stuff. Competitive action. Your CEO could do something bad and have a reputational scandal and that hurts your business. These are all headwinds that could make it necessary for you to find a new, to get to that point that you need to achieve. Right? Likewise, you have certain things that come along that can really improve your business over which you have no control. Great example of this was back in the 1970s and eighties interest rates were extremely high, which was bad for most people, bad for society. But if you were a banker, that was good. That was a tailwind for you, for your business, right? So that’s a, that’s a, it’s all of those kinds of things and the unaided human brain is brilliant. It’s so awesome in so many ways, but it cannot handle more than three or four of those at a time. And so that’s where regression becomes really important. And then ultimately to make it operationally viable, you have to automate it.
You know, we were talking in our prep call about really this thought of a GPS isn’t new, but the internet of things that are happening in technology around automation and around innovation and in specifically what’s happening with, with Watson and you know, it’s, it’s, uh, untapped ability to machine learning and predict with AI what’s going on. How, how does the, you know, the futuristic tech that’s does not fully attainable like Watson have practical application. What we’re going to do in the next 18 months.
Well, I, so let’s start, let’s just use Watson, right? It’s a great example of this, right? And let’s be clear, Watson is a tool to force technologically speaking. It is an extraordinary technology. It is productized if you want to use that word through IBM global services to meet a specific use case, uh, for a specific client. Um, it makes it really super expensive and it is a big data solution. So big data as defined five ways. I won’t bore you with five ways, but for a big data problem, to be a big data problem, it has to check all five boxes. So most of what we’re talking about here is not a big data problem, cancer research for research and assimilate it and turn it into while an insight for this done right. So that is that, that’s an example of the power of that particular tool.
But in most cases, believe it or not because I say believe it or not because there’s been so much hyperbole used in the marketplace. But most business, not all business, but most business problems are not big data problems. They are small data problems. And so a combination of machine learning to find the patterns, the repeating patterns and automation is really the way forward is what proof and many others. Um, in the, in the business call augmented intelligence, uh, as opposed to artificial intelligence. The two, the difference being, uh, augmented says we’re going to make people smarter. Uh, artificial says we’re going to replace the human decision maker.
Yeah. The, the, the part that’s really interesting to me. There is a new term that I’d never heard of, which is pigmented intelligence, but augmented intelligence or even artificial intelligence still feels like, you know, we’re, we’re iterating off of people who call themselves innovators or technologists today. And it feels like most of them are just iterating off of all of this product is a variation of that particular product, but for this specific market and when we get into technology, all of a sudden it’s this melting pot of platitudes versus actually something that I can sink my teeth into and really make good
decisions from a, that’s help us as so true.
So, so help us understand what, what innovation really means and what it looks like. And you have a really good example. We have this on the call where you talk about the evolution of sailing and how you went from, you know, the map and track line to what is that today exactly. What does that look like as it relates to how businesses, what businesses might do moving forward?
Well, first and foremost, I think that one of the big learnings that I have had over my career is that, um, innovation that is not consumable by people is not innovation. Um, so if it, you know, we can talk about technology all we want to, um, and I guess if, if, if we’re kind of in a really tightly knit circle of technologists, it can be kind of fun to do that. But actually technology, um, as differentiated from a product technology is kind of boring. Um, because the real one makes the technology come alive is applying it to a particular use case to a particular human need. Um, that’s what makes it really exciting. And so, you know, what we were talking about before in terms of my, you know, my sailing experience. So you know, the way that that kind of goes together with this whole topic is it’s sorta like the family that, uh, the lot of blue water racing, sailing, um, things like that.
Um, I was taught, uh, among other things to be a navigator. Um, you know, he or she establishes where you are at your location, uh, at your plot at any time and then where you need to go. Right. And so, um, when I first started, I had these, uh, paper charts. They were laminated and I would put Xs on, uh, on where we versus where we were going. And I would use a rule and I would take a wax pencil and I would draw the plot line connecting the two and ever so often as we sailed in that direction, um, we would, I would get up on deck with a Sexton and shoot the sun, which, you know, you use the thing and you line up the optics and it, it tells you where you are on the earth based on the position, the sun.
Um, the problem of course with that was that clouds exist, bad weather exists. Um, and so sometimes you would go for days without being able to take a sextant reading. And so you literally had no idea where you were, uh, during that time. It could be 24 hours, it could be a week, right? Um, sometimes, you know, uh, figure 300 years ago, it could be even longer than that. Um, and so you could, you could find out the next time you took this, the site of the sun, you could find out you’re way off course and then you’d have to, you know, there are a lot of ways to time, uh, and all that. And you had to, to steer back towards, um, your plot, your plot line, right? And so it was sorta like this giant zigzag pattern that would run back and forth, back and forth across plot line.
And this actually became super important because on a boat you have finite resources, you have finite amount of water, finite amount of food and, and obviously you’re also trying to win a race, right? So the amount of time that you’re burning is, is really important. Um, later all of a sudden we had satellite navigation. So we had an antenna on the top of the mask that was constantly collecting, uh, position data. And we had a tied to an autopilot, which essentially is like automatically steering based on certain parameters that you put in. And so once we did that and all of a sudden we had constant access to position data, uh, we didn’t have these giant zigzags anymore. Uh, we were our little S, our little snake, we call it snake was riding pretty much right on top of the plot line. I mean, we would get still pushed by wind currents and ocean currents and all that kind of stuff.
So it wasn’t a perfect thing, but we shaved off 20, 25, 30% of the lost time due to these massive zigzag patterns that we had before just with that technology. And that technology actually not only solved the big problem in all the ways I’ve just said, but if you extrapolate that out in some situations on the ocean were running out of fuel and water and food can actually result in death, right? You’re now really solving a farm bigger problem than that. Um, there are a lot of voyages say two, 300 years ago it would have, uh, ended up much differently and much better for the people on those boats if they had had sat nav and autopilot.
So that’s, I think that’s a really, um, valuable visual illustration to think about. Okay. Sailing, you know, it’s tacking back and forth and the closer to tacking back and forth, you can get to a straight line cause there’s no straight line right in sailing. You’re never going to go from point of view. There’s always going to be something that’s, that’s, but I think it’s a really good visual for how we navigate what’s going on. And so the, the innovation was, is Hey, there’s a better way to, to navigate here, right? You went from your, uh, would you say shooting the stars or shooting the horizon or whatever it was to it. Then it, then it moves into, um, the, the GPS, which is now into satnav. And so every time there’s an duration that gets better when you can never control what’s going on with the, with the current or the headwind or the tailwind or, or you know, your own fuel, you have a finite set of resources that you have to manage to get from point a to point B.
When we look at what’s going on in, in our current economic state, in our current transition, we’re going through, I can’t think of a better example of what’s going on of how there is no one solution per se. It’s a matter of managing, Oh yeah. Managing the aspect, but managing the right network effects or managing the right elements to control your outcome. And that’s where the innovation will happen for, for businesses in the, in the next 18 months is, is we’re going to innovate on how to apply those that, that understanding so we don’t run out of resources in a more real time fashion than we have historically. Is that, is that a good understanding of what you’re saying? That’s exactly right.
And then it compounds, right? I’ll add one more big variable, right? Um, which takes everything that, until this point has been a linear relationship, right? And transforms it into a powerfully nonlinear one. And that is time, the passage of time, right? So something that looks highly correlated at 30 days, right. Can, can actually give you completely the wrong picture in comparison to looking at it a year in time. So if we think about it from a marketer’s perspective, right? So we do a lot of what’s called automated marketing, mixed modeling, which is essentially using regression analytics to run attribution on marketing. It’s been around a long time. We automated it. So we’re looking at three things, three investments that marketers have made to achieve a particular outcome. And at 30 days I’m doing this sort of, uh, as a, as an illustration, but this is actually happened at 30 days.
Um, they all look like they’re paying off equally well and none of them are particularly paying off like in some sort of amazing sort of way. But it’s respectable. It’s good, right? But then if you look at it, if you look at the regression analytics further out, like at 120 days or 150 days, all of a sudden one return on one of those investments has exploded in to like 7000%. Right? So it’s, it’s one of those things where if all you can do is optimize for the short term, which is what a lot of marketers have had to do, right until now, you actually are underreporting your value, your value is so much more. And if you knew that you would probably make different investment decisions. So again, this is sort of very much like running your 401k right? Marketing or you know it or any of these parts of a company, right?
Our investment books, they are, um, you, you have a certain amount of money and you’re being asked to invest it for optimal returns across multiple time horizons, right? Short, medium, and longer term horizons. It’s exactly the same. And so if you, if you can’t figure out what’s what’s working and what’s not working, what’s paying off and what’s not paying off and why and what are the outside influences that are going to change that or accelerate that, you’re going to always be doing it by gut and you’ll never be able to prove that your gut was right or wrong, which is really where a lot of marketers have been for the last time though. As long as I’ve been doing it 30 years. Well it’s a little bit like, you know, if you’re loose and clerking you, you found the
civic Northwest, but you really just kind of found it by accident, right? It wasn’t you. You were building the map as you were going versus actually taking a step back and, and having a true of what the topography and everything that was happening was going on to choose the best route. And, and you know, one of the things that I think about that we’re seeing happen a lot right now is, is there’s kind of this mass surgency to reduce people’s income and to put the business into survival mode for, for resources. Maybe we’re furloughing people or we’re, um, we’re jettisoning jettisoning things that we don’t think are working. But a lot of businesses are doing that focus just as much as if you were, it was like, Oh, I can only do PaperClick ads because I know they, they have an ROI of whatever in 45 days versus taking a longterm effect and saying, well, if I furlough 20% of my business or I get rid of 30% of my workforce, what are the negative impacts that we will see six months down the road? Like you [inaudible] a lot of businesses, I don’t think necessarily fully appreciate what that, that reduction in output or power means for the longterm stability and livelihood of their business. Is that a
Oh, absolutely. And so, um, one of the, one of the most powerful things that I, uh, was introduced to 20 years ago at HP was I was part of a group of employees that was designated high pot, high potential, right. And they put us through this series of courses and one of them, um, they had written a piece of software that was a simulation of the, of the business. It happened to be a simulation of the personal systems group in HP, which was the laptops. And, and at that moment that actually was where I was working. So it asks you to be Dwayne’s, that’s her who was then the EVP and general manager for the global business unit. And it would get, all of a sudden you would get messages and it would say, Carly says you have to cut your, your spend by 10% next quarter cause she needs a certain amount of EPS from you, EPS contribution from you, earnings per share.
Right. So you would say, fine, I’ll, I’ll do that. And then you would start playing around with the lever, right? The different parts of your business. And what you realized was, is it was super easy to give her that 10% right? And just do right. And, and in the next two quarters, it felt like, it seemed like you had gotten away scot-free with the consequences of that. And then all of a sudden the software started showing you, Oh, you remember that cut that you made three quarters ago? Well now it’s going to bite you in there. Right here. Right? And Oh, you know, when you cut marketing back by 20%, well now five quarters later, this is why business is struggling. And so what you learn is, is that there is no free lunch, right? There’s always, it’s a pay me now or pay me later proposition.
And that you CA you also really can’t make the optimal decisions with just your brain because your brain can’t look at the time lag, right? And so what, what the software at HP ultimately did for you was after it taught you that lesson, it would give you projections into time and you’d sit there and go, you know, I don’t really want to make that kind of longstanding, you know, more or less eternal negative impact, right. On my business. And so you figure out ways to kind of split it up. Right? And stagger it across time and space and you, you kind of say to Carly, I can’t give you 10 points. I can give you seven. Right? You’re going to have to get the three points from somebody else. Right. So it puts you in that put it really, that was actually the very first time that I had a vision.
Even though I wouldn’t say I had a vision of proof as a company, I had a vision of being able to do this at scale. Right. It was just, it was kind of like seeing the future, so to speak there for just a moment. So that is that I think one of the biggest messages that people need to hear on this is that all of us go through this, right? Many, many professions have been through this, um, pilots, right? So airplanes started really being a thing in 1908 with the Wright brothers and it flew at about 50 miles an hour and they got faster and faster. But even at the end of world war two, they were still sub 500 miles an hour aircraft. And so at that speed of activity, you could be a fly by the seat of your pants flyer, right? You only had about eight gauges on your dashboard, right?
It was pretty simple and it wasn’t happening super fast. Then all of a sudden you break the, you go into jet age, you’d break the sound barrier, right? All of a sudden things are moving along at Mach three, Mach four, um, you’re having to manage a lot bigger aircraft, a lot more complicated aircraft. All of a sudden, automation kicks in and also pilots start to be taught to don’t trust your senses. Don’t fly by the seat of your pants, fly by wire, fly by your instruments. Right. Powerful illustration of that was I, I, when I was at Honeywell aerospace, I had some kind of early, you know, low level kind of pilot training. Didn’t really go anywhere but um, but my instructor pilot, uh, took me into a fog bank into a, like a big cloud, huge cumulonimbus cloud. Right?
Speaker 4: (33:06)
we kind of flew along in this cloud for three or four minutes and then he said, so are you right side up or upside down? Well I kind of thought about it, I thought about kind of how I felt and everything else. And I said, I think I’m right side up cause I would kind of, if I were upside down, I’d kind of feel upside down and I don’t feel that way. Some right side up. And he said, great. He goes, that’s awesome. And he goes, so let’s get out of the, the uh, cloud bank. And I flew out and I was upside down. Okay. Now, if that sounds like a cute story, but let me tell you why it’s actually super crucial. So if I, let’s say that I thought I was right side up and I wanted to climb, so I pull back on the stick and I climb, but I’m actually upside down.
So instead of climbing, I’m diving, I’m, and if I keep going, I’m going to put myself straight into the ground, right? So this is where that cute little story all of a sudden isn’t so cute anymore. Right? And why they teach pilots don’t do that. Fly by your instruments and use the automation. Lots and lots of other stories about how other professions and other human experiences have involved evolved in similar ways. Right? That’s a, that’s a powerful one. Um, and that’s where marketing is right now. And in many ways that’s also where the whole business is right now.
I can, I mean, I can, I can completely see that. And I think that for, for me, sitting here listening, I think there’s a couple of really critical takeaways, which is you probably didn’t using, you’re using your story of the flying. You probably didn’t dive right out or, or try and climb right out of the clouds immediately. It took some sort of gradual process to make sure you could check your bearings before you did anything that was life threatening in the, in the economic turbulence that we’re in right now and the transition that we’re in, it’s probably wise for businesses to gradually make changes to see where they’re at versus cutting bait and, and trying to make,
except let me, let me give you the counter to this, right? I love this. Great. All right, so let’s say that you’re flying in combat. If you take a gradual approach, you’ll be dead, right? So, and, and so I’ll give you another example. Investing in the market, right? So the way that you make, if you, particularly if you don’t want to be like personally involved and you kind of want to do it more or less on an automated basis, right? The way for you to make money in a generally improving market, a strong market that keeps going up and up and up over time is to invest in mutual funds, right? Y, that’s the careful considered approach, right? You’re highly diversified. Yes. You’ll give up some earnings here and there, you know, where you could have made a big splash, but you also don’t have a lot of risks.
Okay. And as the market goes up, it just kinda takes you with it. However, in the current market, right? The, the people who are making a lot of money right now are making individual bets, right? They’re making individual bets and they’re doing that based on analytics. And so if we want to move this whole conversation back and forth into kind of various different analogies, you’re, so let’s take what I just said and let’s move it into the marketing space. So you’re a COO and you have been spending, you know, $50 million or a hundred million dollars and you’ve essentially not equally, but you have more or less peanut butter it across all aspects of your marketing operation, right? You’ve got something. If it’s a, if it’s a reasonably hot channel or a reasonably hot approach, you, you’re spending some money there, right? And it’s mainly geared to, I just don’t want to miss out right?
If there’s anything that might be creating value, I want to be able to say that I’m there. Right, right. And that is a fairly kind of cover all your bases relative from a certain perspective anyway, relatively low risk approach. However, with coven, all of a sudden a lot of this stuff doesn’t work anymore except it hasn’t been happening long enough for you to know for sure yet and you’re going to have to start saying so. So your CFO is coming to you and saying, gee really sorry, but you know we’re probably going to have to cut your budget for the rest of the year by 30% well, 30% is not a a cut that you can just kind of allocate equally across everything you’re doing, right? Peanut butter that right. You’re going to have to completely X out a whole bunch of stuff and you’re going to have to actually double down on some stuff. But if you don’t have the marketing mix modeling, if you don’t have the GPS, it’s actually telling you relationally what is what is working and what is not. You will find that almost impossible to make the right call. And that’s particularly in a highly volatile and fast moving situation. That’s where a playing it safe kind of thing or playing it traditional can actually really get you in trouble.
All right, fair. I mean understand the dog fight versus the, the uh, the slow, the slow decline in this situation, how do organizations get the instrumentation? So you’re now flying by wire instead of flying by the seat of your pants. What’s the, what’s the logical next step? Something I can do in the next six, eight, 12 weeks to put ourselves in success for the longterm over the next 18 months?
Absolutely. So the way this works is the very first step is what do you want to know? Right? What questions are you desperate to know answers for? Right? And what I’m really saying is what really powers your business and what and what are gaping holes in your knowledge, right? These are so you start with the questions. Some of the questions are going to be answerable with data, right? Like for example, where you are on a map, your GPS location, that’s not analytics. That’s data. Okay, where you want to go. That’s also data. That’s not analytics, but the relationship between those two things and what you have to do in order to get from a to B, that’s almost all analytics. That’s analytics consuming data, transforming data, so the data will only rarely be the end game. The end game is always going to be analytics.
By always, I mean like 99% of the time it’s going to be analytics is the, is the end game is going to deliver your answer that you’re looking for. So behind each question that you want to know the answer to is either a dataset one or more or an analytical model and a model is essentially a mathematical calculation of framework that says, okay, where are you going? Where we’re going to look at this situation in light of all of these things that we understand, right? It could be what we’re doing, what other people are doing, what the macro economic situation is, what’s the desired outcome? And we’re going to run regression right in this model. And that’s going to spit out an answer. The model then is also implicit in this is going to tell you what data you need. So a key. So if you follow this right, this is not a data first strategy, okay?
And you, and one of the most common things that we hear from people as well. I’m just, I’m not sure that I have the right data or enough data or whatever. I’m here to tell you no one shows up with the right data or all the data or whatever. That just doesn’t happen, right? What this, the way you have to look at this is that this is a way of beginning to shape your understanding and your knowledge. And it’s a journey. Everyone hates this statement. Everyone uses, it’s a journey, okay? Guess what? It’s because life is a journey. That’s just the way it is. Magic wand, right? So you’re going to continue to refine these models. You’re going to learn, you’re going to say, you know what, maybe this model actually needs this other dataset. I wonder what would happen if we added this data into this model and then started running it, right?
So you’re going to stats. That’s essentially the cascading effect and then the answers to that go straight into your planning and budgeting cycle, right? And that’s what proof does. Proof will take all the outputs. Um, we, part of the solution is a builtin NPM platform, which is essentially a, a, uh, a mini ERP for marketers, right? That allows you to track all your spend, your approvals, governance, compliance, all this kind of stuff. It tracks all your KPIs. If you’re a Salesforce customer, it’ll suck all that stuff out of the marketing cloud and sales cloud and block free populated for you. But it will, it will take all that. It’ll take the analytic readout and it’ll come around here. And when you go into planning and budgeting, it’ll say, okay, this is what’s working and this is what you probably should double down on or triple down on. And this is what you might want to cut by some amount. And so then the whole cycle kind of goes through again, right? And this is where you get to be. This is where you get to have, we call it proof of proof, right? So the proof is telling you what’s happening, it’s making recommendations. Did those recommendations turn out to be good or not?
Um, when you see that happening enough times, you’re like, okay, I’m totally sold on this. Right? And it, and it, that’s, that’s ultimately where people get the confidence to make bigger and bigger and bigger bets.
So it sounds like to me is, you know, for, for marketers specifically, that the, the power here doesn’t really lie in your data or what you think the answers are. The power in this situation is asking the right questions. If you didn’t ask the right question, you will be a power position through the transition to be able to bet where it makes the most sense for your company.
That’s right. I mean, another great example of this is digital transformation. And that is something that is top of mind in most companies right now with [inaudible]. Um, it’s a giant network effect though, just like marketing, right? It’s marketing is a network effect. Um, and if you don’t instrument digital transformation and you don’t understand the relationships that are driving it, you’ll never get there. It’s too complicated. And so a lot of people use proof for that as well. Right? It’s a, it’s a change management exercise and that’s really what we’re, that’s what the GPS is really a GPS for change. Right. I need to understand change. I need to understand what’s making it all happen.
Look, Mark you, you have done a wonderful job of kind of helping provide perspective, um, some sort of a compass, if you will, as it relates to, there’s something we can hang on to as we navigate these waters. I want to thank you very much for your generosity and being here today. It’s been, it’s been an absolute pleasure to have you on the show.
Thank you, man. It was, well, I’ve really enjoyed it.
Uh, what before we get off though, can you just give everybody your contact information if they have questions about proof for you or, or Hey, they need more insight on, you know, asking the right questions, how can they get all the Mark?
Sure. I’m of course reachable on LinkedIn. I’m, I’m in LinkedIn a lot. Um, and Twitter, it’s at Mark’s deuce, uh, is the, uh, is the Twitter handle. Um, the URL for proof is www proof analytics.ai. Um, and my personal email address if you want to go that route is Mark DOT’s deuce at proof analytics study.
Mark, thank you again. You guys have heard from Mark, the president and founder of proof analytics, uh, proof analytics. Dot. AI is, is we’re wrapping up our episode here on navigating your using, excuse me, wrapping up episode here on using innovation and automation to navigate these Covad kovad waters. Thank you for listening. Thank you for tuning in. And until next week, we appreciate you for being a subscriber to summit podcast. Mark, thanks again for being a participant.
Thank you so much.