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Transforming Marketing Analytics: A Conversation with Mark Stouse

CEO of ProofAnalytics.ai

In this episode of Wytpod, Harshit Gupta, Director of Business Alliance at Wytlabs, interviews Mark Stouse, Chairman and CEO of ProofAnalytics.ai. They dive into the journey of ProofAnalytics.ai, an AI-native GTM performance platform that enables real-time planning, predicting, proving, and pivoting of go-to-market investments. Mark shares his experiences in marketing and analytics, from his time at HP and Honeywell Aerospace to founding ProofAnalytics.ai. They discuss the challenges of proving marketing’s impact, managing remote teams, and the significance of AI in transforming business decisions.

ProofAnalytics.ai specializes in advanced analytics and automated marketing mix modeling to optimize business performance.

Mark Stouse
CEO of ProofAnalytics.ai

Hello everyone, and welcome to another episode of Wytpod. My name is Harshit Gupta, and I’m the Director of Business Alliance at Wytlabs. We are a digital agency specializing in SaaS and e-commerce SEO. I’ve got Mark Stouse with me today. He’s the Chairman and CEO at ProofAnalytics.ai. Now, Proof is an AI native GTM performance platform that enables you to plan, predict, prove, and pivot your go-to-market investments in real-time. A big welcome to your mic. So happy to have you with me today.

Hey, thank you so much.

Good to be Let’s start with your journey in marketing and analytics field, and what led you to found ProofAnalytics.ai.

I would say that in 2005, I started realizing that… The problem that marketers have faced in terms of proving their impact on the business is not a new problem. It existed in 2005 when I was at HP, and the big question was, were we just going to give up and steal away into the night, or were we going to try and find something that fixed the problem to the satisfaction of the business? We started working on it. I think at the time, we had a very limited view of what was possible and even what we wanted to really accomplish with it. But as we started to learn more and see, for example, what Procter & Gamble and others had done decades before and how they had matured the whole approach. By the time that 2010 rolled around, we were in a very mature state. I was, at that time, just starting as CMO of Honeywell Aerospace. I think a big reason why they hired me was actually all this work on the analytics side. It was very successful at Honeywell as an approach to leading the go-to-market part of the business. But we also realized that we were having to do a lot by brute force, by hiring lots and lots of analysts to do the work.

So software automation became a no-brainer idea. And so that’s why we ultimately left our respective employment and started proof. And built the platform. And it’s been quite an adventure, to say the least. I think you always go into it not realizing all the things you don’t know that you don’t know, and then you discover them. Yeah. No, but that’s why I think, initially, we wanted to be taken seriously. We wanted significance within the company. Then ultimately, we got to a place where it was really about helping people solve a deep problem that was taking one of the best professions around in corporate life and effectively ruining it. You just look at all the criticism that marketers get, the reduced budgets, all that stuff, it makes it less than rewarding for a lot of people, and it shouldn’t be that way. In fact, there’s one function in the average corporation that should actually have no doubts about its ROI, it’s marketing, because the same dollar spent on improving sales velocity or whatever is also helping recruiting and retention, and it’s helping investor relations. It’s getting multiple payouts from the same dollar, the same rupee.

Makes sense. The problem This statement that you defined, I’m sure, like majority of our listeners, do face this on a day-to-day thing.

Yeah.

How has your extensive experience in marketing, in communications, commercial strategy, strategy influence your leadership approach at growth?

I think in lots of ways. One of the things that I was taught that was really important culturally at HP was as soon as you became a people manager manager, they started teaching you about managing and leading remote teams. That became a pretty substantial skill over time. When we decided to create proof, we said, and this was pre-COVID, we said, We want to be remote first, and we want the talent to matter more than the location. We had the skills, and we also had the infrastructure had come a very long way from a software perspective, collaboration software, things like that. I would say that was a key way that we managed, created and managed proof. It was hugely successful for us, of course, during COVID. We didn’t really feel any effects of a shutdown or anything like that because we were already not in the office. I think that also the analytics, being very analytics-led in the way that we understand the world, meant that we didn’t have any expectations about what we needed to do to successfully go to market or anything like that. We started modeling a lot of these questions prospectively before we even got into the market because we wanted to follow the math, where the math was leading.

I think that’s essentially what being a scientist is. In general, it’s saying, Hey, I’m open to what the facts tell me as opposed to, I’ve got to jam reality into my preconceptions of what it should be.

Mark, since you mentioned that you are managing remote team altogether, which productivity suite or team collaboration softwares do you prefer using?

There’s a whole bunch of them that we use on the product management side, the product development side. That’s not my area of expertise, so I’m not even going to try and rattle them off. But Jura, there’s a bunch of them that are used. I think we really use tools like Slack a a lot.

One of the reasons why we like it a lot is that we not only use it internally, you have channels there for partners and all kinds of stuff. It’s all in one place. I would say that of all of the tools, the one that we use the least is email. It’s just if we have to, then if it makes sense to use email, then we will use But usually, anyone that we really want to talk to that’s not a prospect, we’re connected with in some other way. I think that Slack is a big one. I think proof itself is an intensely collaborative tool. Customers collaborate with us, with our data science teams, as well as their agencies or their partners or whatever in the tool to share data securely and model outcomes. I think one of the things that makes proof very attractive to teams is that it’s not just a data science tool. It’s a way for everyone to participate in crunching the numbers.

I think you launched back in 2019, right? What are some of the key challenges you faced when you started Proof, and how did you overcome them?

I think that even before we launched in 2019, we spent the previous three years building the platform. The thing about analytics is that you can’t really MVP it in the classic sense. Because for an analytics platform, it’s either complete or it’s not complete. If it’s incomplete, no one wants to talk to you until it is. You pretty much have to build it all. I think that creating the back-end is the computational end. It’s not the problem. It’s figuring out what the UX needs to be so that people who are not data scientists can look at the screens and know how to use the information to make a better decision. Because Because you can have everything else perfect. If you’re not enabling your customer to make a better decision on a regular basis, then it doesn’t mean anything. That was very tough. I think that One of the things that’s really challenging in general about a startup is that you wouldn’t do the startup if you didn’t feel that you had a unique perspective on a problem. Then at the same time, you You have to be willing to listen to what everyone is telling you, the feedback everyone’s giving you that sometimes doesn’t agree with your perspective.

That’s very challenging to walk through because it’s difficult to know when to stand your ground and when not to. I would say that’s a really super big part of the whole of everything that goes into a company like proof, is particularly when you taking something that has been historically the province of a few elite kinds of people, and you’re wanting to popularize it and democratize it, then what I learned was I’m so mature on this subject that I no longer represent our customer base at all. I can help them a lot, but I’m not them. Even though I can remember when I was just like them, that’s still not the same thing anymore. And features, for example, or in ways of interpreting the analytics on screens that really resonated with me that I personally really liked. A lot of times, the test customers would pass on that stuff. I used to find that very frustrating. Then I just decided, You know what? I’m just going to shut up and listen to what they have to say. Because the point is not, do I agree with it? Or even, are they right? The point is that if I want to have a business that is selling this software to people like them, then I have to be able to address these concerns.

What sample size was your test when you were making these iterations on your product?

We were very fortunate. We had 22 initial customers that included companies like Oracle and Intel and some agencies and some smaller businesses. We curated a group of customers that were all paying us money, not very much money. They were paying us money, but they were really paying us in product feedback. You also have to realize the value of that, that even when you don’t like what they’re saying to you, that’s compensation. They are paying you with insights. If you reject the insights, you’re effectively rejecting the payment. That’s stupid. But I think it’s almost a meme that the software founders have large egos. I think that part of that is they tend to be pretty smart in many ways. Part of that, though, is that they believe that they have a unique insight into a problem. It’s hard to temper that, but you have to.

How exactly is your feedback loop working now? What processes do you have in place to collect your existing customer feedback and make an improvement to your product?

We have a tool called Pindow that is embedded in our products, and It calibrates. It lets us know what customers are doing in the product, and it will reveal if there’s an area where all of a sudden it’s pretty apparent based on the patterns of use, that there’s friction in that part of the tool. It will identify that, and so we’ll know that we need to work on smoothing that out. It’s important to listen to what they have to say But what really matters is when what they have to say matches up with what they actually are doing, that’s when you have a real insight. I don’t know how it is in India, but here in the United States lately, around politics, they do a lot of polling. Then there’s the vote. It used to be that the polling would give you a clue as to how the vote was going to turn out. And now it’s the two are divorced because people are not really telling you what they really are going to do on election day. That also happens in the software business. So people will tell you, Oh, your product is great, but you can tell, based on the way they’re using it, that they don’t think it’s great.

Or they’ll flip it around. It’ll be the reverse of that. But it really does matter. That relationship between what people say and what they do is the source of all truth.

Can you please explain the significance of Approved being an AI native? And I may as be a certified platform?

Masb, M-A-S-B, is the Marketing Accountability Standards Board. It’s a partner with ISO in Europe, International Standards Organization in Europe. It When it certifies software, that’s a big deal. That’s a high credibility marker that tells any customer that they can trust the software to do what it says it will do. Even though we are more horizontal today than just marketing or go-to-market in terms of the cases for proof, that’s a big one. That’s where we started. I think that’s the significance of that because people Trust and confidence have never been more important with customers than they are today. It’s actually far more important than probably almost anything else. It’s the relationships, for example, between very low levels of trust and confidence and much longer deal velocity times. Deal velocity has almost doubled in the last two years for most B2B companies. An average deal size is less than half of what it used to be. There’s a lot of data, our data and other people’s data, that shows that those two things, among other things, are very much linked to this lack of trust, lack of confidence, fear of risk. The fact that 60% of SaaS deals today could to conclude in no decision, that’s a powerful stat, right?

I would say that it’s the trust and confidence piece. Then the other thing you were asking about was AI native I think that causal analytics is like multivariable regression on steroids. There’s a lot of very targeted AI in the tool that is mainly focused on helping people accomplish tasks faster and more smoothly. It’s not really about the computation of the analytics. It’s really more about ease of use and things like that. I think that it’s really because when we started building it, AI was certainly on the radar, but it was not what it has been for the last two years. So we just wanted to accurately reflect our tools. That’s why we included the. Ai in the name. It wasn’t… So I think we’re seeing right now a lot of. Ai’s pop up, and it’s AI washing, right? That’s not what this is at all. We use it where it’s appropriate to use AI. I think that today people appreciate AI, and they appreciate what it means. There is a bandwagon effect today that didn’t exist four years ago. No. Yeah, I think that’s actually pretty straightforward. I think that where we are headed is more than two years from now, proof will be heavily computational AI, and that will That’s going to be a game changer, not just for proof, but for any company that used a lot of computational AI, which is distinctly different than Gen AI.

Actually, a lot of marketers, especially in the SaaS niche, have used AI as one of the core USPs to such an extent. Now, that USP itself is now obsolete. People expect an AI integration on the platform. The majority of people, they do expect it on the platform that they use, at least to some capacity. I mean, it’s a bit redundant nowadays when it comes to the content marketing side, but it’s much more become a business need now.

Yeah, no, I think that’s true. I think that by the same token, I’ll say this, what most people think AI is based on the way that they experience it with ChatGPT or whatever is a very small part of AI, excruciatingly small. I think that when people talk about AI and what they really mean is Gen AI, they’re doing everyone a disservice by using the broader term, because what AI is going to mean to all of us in five years is substantially different than what we understand it to be today.

I remember on the podcast I had, was a team member from Jujji AI It’s a good organization. They are doing some heavy development on the cognitive AI side of things. It’s wonderful the bots that they have built and stuff. They’re achieving through it. It’s quite remarkable. You rightly put it. Gen AI is just scratching the surface of what can be through it in the next few years.

We’re also going to have to get really used to our assumptions being challenged because AI doesn’t care. It’s not human. It’s not concerned with offending anyone. It’s just there to provide the best possible answer. Sometimes it gets it wrong, and it will continue to it wrong sometimes. But for the most part, it does a really good job. It’s going to get in the same way that banks and financial institutions are using a lot of AI to find fraud, You’re going to see AI being used operationally within companies just to uncover mistakes or bad decisions, erroneous decisions. That’s going to be hard. That’s going to be People’s ego doesn’t really look at a lot of times. That’s going to be a very interesting thing because it’s going to be unavoidable. I agree.

I would love to understand, Mark, how exactly Prove differentiated itself from other marketing resource management tools available in the market? What are the core USPs?

We have two products. We have an MRM, a marketing resource management It’s the only one that’s native on Salesforce. That right there is a huge advantage for us. It’s very contemporary in architecture and the way it works and what it prioritizes It’s very inexpensive given how powerful it is. People can spin it up very quickly. It automatically downloads data out of any Salesforce clouds that you have subscriptions to. In addition, you can pull data very easily from sources outside of Salesforce. And then we have the analytics tool, which is native on AWS. It’s ported into the Salesforce products so that people can use it seamlessly inside Salesforce. We have far more competitors today on the analytics side than we ever did, say, three or four years ago. Our segment, our part of the market is booming right now in general. I think we still really differentiate based on how transparent we are, the product is about the math, and it will let you know if someone’s trying to game the system, so to speak. It’s very accurate and it’s very fast. You You can recalculate models daily, weekly, or monthly, and it happens automatically. Whenever the new data is presented to the model, it automatically recomputes.

It tracks on the screen exactly like a GPS on your phone. If you stop and think about it for a second, it actually works exactly the same way as a GPS. A GPS says, This is where you are. You say, This is where I want to go. It gives you a choice It’s a series of three routes, which are forecasts. You pick one. It’s then tracking your progress, so that’s everything you control. Then it’s tracking all these variables around you that you don’t control, but that could speed you up or slow you down or cause you to have to reroute. That’s exactly what proof does for a business, for any part of a business. It’s going to constantly recompute against everything you control, against everything you don’t control, so all the marketplace variables that are out there. Net of time lag against a outcome that you’re seeking to produce. It’s going to tell you when you need to make changes to the plan.

All right, Mark. Now, as a coach here of the modern GTM organizational structure at MASB, what are some of the main key initiatives you’re working on?

I think that the biggest one is the fact that everyone has started to really wrap their head around the fact that marketing and sales and customer success and product, and for that matter, anything else that touches a customer is part of go-to-market. It’s an ecosystem. And that each part of the ecosystem has a distinct role that has to be coordinated effectively with all the others to create a maximum positive impact. That means that organizationally, everything is going to be looking more and more different inside of companies than we’ve seen in the RISA past. The idea that there’s going to be a separate marketing, sales, product, customer success type delineation organizationally speaking, I think is going to gradually disappear. I think that the idea that alignment is based on organizational agreement, be far more specific. So what is the basis of agreement? It’s not a bunch of people saying, yes, we all have the same opinion. And so this is actually where analytics, in the broadest definition of the word, become the point of alignment across this ecosystem. One of the things that the analytics really shows about marketing that I guarantee most B2B marketers have never thought about, is that Marketing is a nonlinear multiplier of the performance of sales or any other linear function, right?

Yeah. So what does that mean? It means that marketing’s success definition is the extent to which it makes sales or something else more effective and more efficient than that thing would be without marketing. And when you look at it that way, All of a sudden, the focus on MQL and leads, top of the funnel, and all this stuff, the idea that marketing is essentially a supply chain function for sales, that gets upended completely. That is not the measurement of marketing’s value. It certainly is part of it. But then if it was really so effective, even right now, you wouldn’t have this major fact out there across many different companies that most sales transactions came from leads that were generated by sales, not by marketing. Is part of that just waste? In other words, sales just failing to follow up on marketing leads? Sure, absolutely. But what is the larger picture there? Say, it calls into question, how good are marketing leads? Is that the important thing that’s going on with marketing against sales? It’s really the importance of marketing is so much more than that. It’s just like The way that we currently understand marketing value or attempt to measure marketing value leaves about 90% of its actual value on the table, unrecognized.

I agree. Okay, man, I would love to hear any success story or case study where proof significantly improved our client’s marketing performance altogether. Give them much deeper insights and to take much more problem decisions?

I think we can start at Honeywell, even though that pre-proof, it’s the same system. We accelerated average deal velocity by 5% over a two-year period of time. In the case of Honeywell, that means that roughly $13 billion in revenue was moving into the company 5% faster, border after border. That was It’s such a huge thing just right there that it’s the main reason why the former CFO of Honeywell is on our board proof. Expanded average deal size, about 30%. We had the perfect control situation in this also in Honeywell, because in addition to the analytics showing it, the sales organization basically said, Look, it’s totally awesome that you’re doing what you’re doing, but we’re not changing anything about the way we operate. When all All of a sudden, things really started to explode and they started doing a lot better than they had ever done before, there was that plus the analytics meant there was only one explanation. That’s why we got the mentioned in three earnings calls and all that stuff. It was really cool. There’s that. Johnson Controls is a large B2B customer of proof that was tracking the performance of all of these different channels that they were in against revenue, margin, and cash flow impact.

They started to see that events, which would been a huge contributor to their success to that point, started to taper off gradually from, say, November, December of 2019 through January, February of 2020. Remember, this This was before everybody was really aware of COVID, and yet the data was already starting to factor in some of the earliest effects of COVID. In the analytics, we didn’t know the reason why yet, but it started to show that in-person events were tracking down non-seasonally. That was the other part. It was very different. They started saying, Hey, you know what? We’ve come to really believe believe in the readouts of proof. This is telling us something that we need to pay attention to. They started unwinding event contracts early and getting money back. They saved about $3 million by listening to the analytics. Then when COVID and the ramifications of COVID really hit, they weren’t out all this money. Later, finance came to market marketing at Johnson Controls and said, Hey, we’re going to cut you 40%. They were able to model the impact of that budget cut and show it to finance. Finance was like, Okay, not doing that.

That’s really bad. That would not be good for the company. In the end, marketing was only cut about 15%, and so much better, clearly. It’s clearly coming back in terms of the importance that people place on it. It’s always been seen as something very difficult to understand the impact of. In fact, I was just on LinkedIn this weekend having a huge conversation with people about this and We were talking about how you do it. We were being very prescriptive about how it’s done. That was something you would not have seen even two years ago, maybe certainly not three years ago. It’s those kinds of successes that people have, particularly when you look at, like with brand. The main reason why brand was killed as a major area of investment in B2B, probably 15 years ago, was because the business leaders looked at it and said, What does this do? What does it do? How do I know that this money isn’t just being poured down a rat hole somewhere? Now we can really show that it has a profound impact, particularly on the late stage performance of deals.

I think back then, definitely still now, to be honest, there are tons of companies which struggle with the right attribution, which, especially Well, yes, specifically when it comes to the branding efforts, the PR you did, what outcome it basically brought when it comes to the revenue that it generated. With the omnichannel, again, it’s so complicated. But yeah, it’s good to see that there’s a tool out there that can help uncover all of these things. All right, Mark, it was a pleasure speaking with you, learning from you, all the wisdom that you have shared on today’s session. I’m sure like this is going to appreciate this a lot. My best wishes for your company and the group. So thank you so much. Really appreciate. Thank you so much.

Thank you.

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