Speaker 1: 0:23

Hello everyone, welcome to another episode of OpsCast brought to you by MarketingOpscom, powered by the MoPros out there. I am your host, michael Hartman, flying solo with Rizzo out at Inbound 2024 and Naomi dealing with chaos, I believe. So that's all right. We have done this before we're going to power through it. Joining me today is Eric Holobone Eric, I should have asked you how to pronounce your name, so hopefully I got it right. President and CEO of DemandLab, a global digital marketing and ops agency based in Ottawa, canada. Before joining DemandLab, eric led brand management and revenue funnel growth as the director of marketing and recruitment for Algonquin College. Eric is a three-time Marketo champion, a two-time REVI Revenue Performance Excellence Award winner, founder of the Ottawa and Higher Education Marketo Regional User Group and an active participant in the Ottawa Salesforce Users Group. Eric, thanks for joining me today.

Speaker 2: 1:20

Oh, glad to be here, Michael.

Speaker 1: 1:22

How do I do on pronouncing your name?

Speaker 2: 1:23

You got it right, e-s-o-y Wow.

Speaker 1: 1:27

Got it, got it, all right. You Canadians are always so polite.

Speaker 2: 1:32

We try to be. We have to live with some good neighbors in the South.

Speaker 1: 1:39

Oh yeah, I'm sure. Well, I'll take it on face value. How about that? It's the only way to, that's right, well, eric? So, as we get this thing kicked off, when we talked earlier about this episode, we realized we both have engineering backgrounds, which is not something I think is all that common for ending up in marketing and marketing ops. So one of the things that you said that I thought was interesting and I think I thought mostly that this is a truth as well is that you thought marketing is both art and science and that you think it should be more science. So why don't we start there? What did you mean by that statement and why do you think that's the case?

Speaker 2: 2:22

So I actually had some thoughts as we went through this discussion as well, and we've had a had some thoughts as we went through this discussion as well, and we've had a. Let's say, modern marketing is about 120 years old let's put it that way or around that time, and we've had a lot of people doing the creative side, the brand side, the customer engagement side of marketing. But really only in the last 10, 15 years, since about 2010, have we had the digital tools to make marketing more measurable. And that has opened up the world to the analytics side, Like you could do analytics before, but it was a very expensive proposition and by bringing in the digital platforms, it's opened that up to every business as opposed to just the enterprises that could afford it before. And that allows a new type of person to be part of the marketing team, somebody who's more process-oriented and data-aware and can help focus marketing efforts towards goals.

Speaker 2: 3:25

So it's brought a level of two of my favorite words precision and accuracy to our marketing efforts and, as an engineer, if you know what those words mean, one tells you how close you are to the target. The other one tells you how well you hit the target that you're going for, and thus you're not wasting any effort and energy. So bringing the science to marketing has allowed us to refine our tools, our skill sets, our reach. To be more specific, it's just been a great way of giving marketing that performance boost to be effective at what we do. But there's another part of the story, which I think we'll get into later on, which science has also helped us talk to the rest of the business. We'll get into that in a little bit.

Speaker 1: 4:12

Yeah, yeah, but it's interesting what I was just thinking. There's, oh gosh, who who posted this on LinkedIn? I'll have to have to think of it. I'll think of the name here a little bit, but someone was making a point that, in terms of like traditional, if there is traditional marketing, education, right, it was usually centered around with the four p's, right so product pricing, placement, promotion. But it feels like today those first three p's have been sort of ignored in a large extent, like everyone's focused on the promotion part. And um, it's interesting because I hadn't really thought about that, because I think I do. There's a, so there's a part of me that believes, yes, marketing should be, both art and science there should be. I don't know what the right mix is and it probably depends on some of the particulars.

Speaker 2: 4:57

I think that'll depend on every industry, because they're going to have a different, and also depends on the company stage a lot of ways, because if you're an early to market or a startup, you're going to need more promotion. You're going to need more promotion, you're going to need more awareness than you are going to be building your lead funnels and so forth. So the one will follow the other. So at different times, through marketing, organizations, maturity they're going to need more of one than the other at any given moment and it's OK to swing the pendulum back and forth. It's just recognize that there is a pendulum and you need both sides, and the best part about it is you get the best results when everything's in balance or in harmony.

Speaker 2: 5:35

Yeah, and too long. I think we've focused too much on one side over the other without the understanding of what that really brought to the table. So, um, I just wanted to touch on. One point you made, which was one of my lifelong passions is we've got to get the digital side, or the science side, into marketing in higher ed, and we'll get into that as well. Potentially, I think it needs to be taught at the university. Grads coming out of schools and I worked in higher ed and I couldn't convince my own higher ed group to start adapting the curriculum because they said there was no demand for it. So I think there's a. There's a employer piece that has to demand for it, there's a student piece that needs to recognize it and there's a faculty piece to bring it up. But there's a long story there that probably needs to be knitted together at some point in the future as well.

Speaker 1: 6:19

Yeah, I don't think. I think if you're talking about the same kinds of things that I think I would bring up in that context about education, it's things like I think marketers in particular, it's really important with all the data we have these days, whether it's general marketing or marketing ops right to be able to understand data and statistics and data analysis, and I think that's probably missing for a lot of folks.

Speaker 2: 6:41

Could I even say one thing further? I would just like to be able to hire marketers who come out of a university program that can build an email. I would just like to be able to hire marketers who come out of a university program that can build an email, like literally understand the basics of online digital communications, pathways and so forth. And it starts with the basics and I feel sometimes I don't even get the basics. But that might be getting us a little off track.

Speaker 1: 7:02

Yeah, I think that could be a whole. That could definitely be a whole episode, because I tend to get on a soapbox about these things and I'll have to control myself. You keep us honest, eric. Okay, that's your job here, well, okay, so we talked about that art and science and marketing, so I think this is both on the same page. Is that marketers, somewhat ironically, are not great at articulating the story about the financial value that they bring to their organization? So A, do you think that's true as well? And I think it's true especially for B2B marketers? But what's your take on that? Do you think that's something that is a problem, and what do you think is?

Speaker 2: 7:48

behind it. I think it's been one of the things that's holding back marketing for years and to go into it in several different ways. The one way to look at is marketing's spend within the company, or resources within the company, especially when times get tight, are sometimes seen as disposable or marginal or can be cut back, or as one of the more discretionary aspects, and I think that directly relates to especially in the B2B world marketing not telling its own internal story. And they don't. The reason I think that comes about is they're good storytellers to their audience but they don't perceive the internal people as an additional audience that they need to be working with. And to convince that internal audience is not the same as convincing the external audience. The internal audience has to work in business paradigms and for that to happen you have to be speaking the language of the business.

Speaker 2: 8:43

I look at it in the way that if everybody's at the executive table and there's a dollar of investment to be had, everybody's going to be articulating why they should get that investment and I want marketing to have its fair share and fair say at that table. But if you say a dollar should be spent in sales or a dollar should be spent in operations or manufacturing or customer delivery. Marketing has to come to the table and say why that $1 should be spent in marketing. Marketing has to come to the table and say why that $1 should be spent in marketing. If you can't articulate in those terms to a CFO or a CEO why that dollar should be spent in marketing, you're behind the eight ball before you even start. If you come to the table with engagement or clicks or awareness or reach, you haven't told the story that helps the rest of the company understand why you need that resources over anybody else Because, let's be honest, it's a competition to get that resource when that resource is limited Absolutely.

Speaker 2: 9:35

Absolutely. If you're not telling that story, there's no way that you're making your audience do extra work, which we know in any kind of sales process is not the best place to be in. So it's internal selling process as much as anything else. Not the best place to be in, so it's internal selling process as much as anything else. So that leads me to my second point is I think marketers don't know how to translate what they do into something the company can understand, and to do that you have to express it in the sole currency of a business, and I use currency as the word I'm going after here.

Speaker 2: 10:05

You have to express your value, or your gained value by your opportunity, in dollars and cents that somebody can believe, which leads into a whole gamut of stuff is where's the science in marketing? Where's the measurement in marketing? How do we measure so that we can prove what we say at that executive table can come to pass? There's a lot in there, and this is where the connection of why mops is so important, because, if you look back, the art side of marketing struggles to tell that story. The science side of marketing is the ones who need to put that story together in a way that it can be consumed by the rest of the company. And you are actually the translator between the effort that marketing is doing as a whole and to the rest of the business, because historically we've shown the other people can't do it and they've done a. I'll call it out. They haven't done a particularly good job of telling their story internally.

Speaker 1: 11:00

And.

Speaker 2: 11:00

I think the mops people are sitting at that interface between the rest of the company and marketing, marketing, and they have that connective glue and be able to talk in both sides of the conversation one to the marketers who want to be creative, one to the business who wants to be analytical. And I think they have a prime opportunity to assume that role and get the win for the marketing department yeah, I think you, you hit on a key couple of things that I think are interesting.

Speaker 1: 11:29

One you said they need to be able to tell the value and it be believed, right, I think that second part is really important. The other part is you talked about some metrics that I think we yeah, you hear the term vanity metrics thrown around and I think those are things. So I did a white paper for the marketing ops community not too long ago and part of it was around measurement and there's sort of two main components to it. One is you need to think about metrics not just as a one set, but there's sort of five different ways to look at performance, and one of them actually is even metrics, and I would call it more of a narrative kind of approach. But I also said the other part is like knowing, like of those five, like who's the audience for that.

Speaker 1: 12:10

So if you're using, you know, what I would call sort of operational type metrics about your marketing and you're trying to use that to communicate to the C-suite, right, you've got a mismatch on what you're trying to communicate to the audience, right? They? Because they're not. It's not really about the value part of it or the currency component of it I like. I like the narrative component because, you know, attribution type modeling has been probably the closest to getting to some way of articulating a financial component of what's the return on a dollar spent on marketing yields X, you know, multiple. The challenge is the math is complicated, right, and what I tell people is I don't say don't do that, but don't use that as the sole thing you're doing with your executive team.

Speaker 1: 13:02

I think narrative stuff has been really helpful in my own career, where you talk about you find deals that were won or closed in the last month, quarter, whatever the time frame is, and you then go and really you take a deep dive analysis. You're like what were all the activities that happened across sales marketing that helped us win, and you want to find ones that are hopefully represented, specific examples that are also generally applicable. Yeah Right, and that reinforces, I think, the numerical things in a huge way.

Speaker 2: 14:27

Well, I think at the end of the day, no matter how you approach it, marketing is all about storytelling to the right audience. If you have numbers, that help you articulate that story, even better. But to get any human being motivated you have to hit them at an emotional level. So if you're not telling a story that will move somebody from decision point A or position A to position B, you have to do that through a story. Metrics just help you tell part of that story about the whole process. So the two, for me, are intertwined. You tell a narrative based upon what the story tells you, but then you can also use the numerical or scientific or analytical side to help you build the story and construct the story to have a strong foundation. You go back to telling the story. Well, part of telling the story at the executive table is, it happens, weeks or months in advance, by walking over to the CFO and having a conversation and building a rapport with that person. The best thing I've ever managed to do was go make friends with the CFO.

Speaker 1: 15:30

As the leader of marketing.

Speaker 2: 15:32

my second handshake in the door is go talk to the CFO, because if I can get the CFO on my side and vet my ideas and analysis through him or her at their department level when I get to the executive table, they don't have to believe just me. I'm going to have some ally in that conversation that says, yes, I vetted that plan. It makes sense to me. I understand the risk-reward-benefit-investment, whatever axis you want to put it on, and it's credible. You get credibility by working with the people who bring the credibility to the table. And yeah, so my other argument would be marketing leadership. I know this is definitely off topic, but marketing leadership, aided by the marketing ops department or the marketing ops group, helps you engage the CFO, because there's so many CFOs out there that go back to that traditional statement. We've heard in the media that I spend a dollar on marketing and I don't know which 50% is spent well or not. I'm very much paraphrasing that whole argument, but your job as a marketing leader, with your support of their mops group, is to go make that conversation relevant and make it true in the CFO's eyes that they understand where the investment is going. You can't do that without numbers. You can't do that without understanding the effort and the ROI and everything else involved.

Speaker 2: 16:50

I did want to touch on one very quick one, which was the way I proved that to a CFO is I ran the first control group comparison. I did this on prospective students but I showed we introduced a calling program and we showed that the people we called actually ended up converting to students at a higher rate. Now in higher ed, just take out the word dollar and put in student, they're virtually equivalent. We just count into a different currency called people who enroll but at the end of the day it's dollars to the, to the university to do it. We were able to prove that the cost of the calling program was well exceeded. We had a four and a half times ROI as we engaged a certain group that were late bloomers or late deciders in the door before the enrollment closed and we showed that to the CFO.

Speaker 2: 17:40

When I did that, that was the sort of watershed moment for that individual to say I've got a partner in marketing, they understand what I'm trying to do, they've worked through all the details. Yes, there might be some numbers in there that we could go after you always can but the general premise was we did something in marketing, we showed the effort, we had a control group versus an active group and we could, and it didn't affect the overall enrollment, so that we could therefore prove that the roi was implemented. So the pilot went, moved from uh to full-blown activity, uh, the following semester. Um, by doing that, you've won the race. And you, you've've almost asked for anything you want at that point.

Speaker 1: 18:21

Yeah, I, I have a similar story in a business context where I, we, I inherited some stuff already in motion, including doing a pilot of a of a new program and, uh, small, small, uh data set. Right, it was like 14 programs that we had to go on, but the idea was okay, well, I did it. I did a deep dive analysis with finance where I got historical data. I said, did it? Can we? Can we narrow down impact on?

Speaker 1: 18:49

In this case was an event business, so right, event this year compared to the previous couple of years, and and try to control for other variables as much as we could. And I built a case that said like if we scaled this to all of our events, even if we assume that the impact will be half of what it was for these other ones, it's still a huge impact, right? So I wasn't trying to claim that it's going to be, you know whatever percentage it was. I was just saying like I'm doing it being conservative, but I think it's like this proves out, like we'll spend this extra money to get this to a point where we can scale it. And same thing, right, I was able. That helped me build the credibility I needed for not only that, but other future things.

Speaker 1: 19:30

So totally agree with you Like getting making friends with your finance partners is a huge thing for anyone in marketing ops. So let's talk about marketing ops right. We've kind of danced around this. I agree with you that I think marketing ops folks should be uniquely positioned to have access and understanding about the data that's being generated and accumulated for what they're doing. Yeah, what do you think that they should be doing to help with this kind of measurement and supporting the case building for their marketing leaders and being able to do more?

Speaker 2: 20:05

So I go after this in two ways one tactical and one strategic. In a tactical way, marketingops may be a little unpopular for this, but won't exist without another marketing group. I mean MarketingOps is a service bureau within the marketing framework. Without another marketing group, I mean MarketingOps is a service bureau within the marketing framework. You're the pipeline under which the content gets pushed out to the right audience at the right time. But without having the other branches of marketing you won't be there. So from an internal support function, marketingops has multiple activities, but the primary one is to make the campaigns execute better. And how do you make that next campaign that that person's trying to do a better campaign than what they didn't do before? So what analysis are you bringing to that person as a marketing ops person to help improve the campaign operations person or the campaign person's net result? Because if you win, they win and you both get credit for it. And that's the tactical level is you should be looking at yourself as somewhat of a service bureau within the marketing group. You're also a facilitator, you're also an IT problem solver, but in the impact of marketing, the thing that matters is getting campaigns in market, doing them better than you did last time proving the result and then tying it back to some impact that can be walked over to finance or revenue at some point. So that's the trajectory there.

Speaker 2: 21:30

The second part of this story is proving out at a strategic level that marketing is doing the right thing, and one example of this is as marketers. We go in and we make a ton of assumptions at the beginning part of any go-to-market process or anything else. But rarely do you see people go back and retest whether the assumptions were correct or not. And I'll give you one classic example the persona ICP problem. And I believe that marketing ops is the group that needs to be testing the assumptions and helping the rest of the marketing team refine and progress on the assumptions and move from assumption to fact. And what I mean by this is let's take the ICP. We've all done this, especially as you're going through a go-to-market explosion. Like everybody makes their best estimate, we throw out a number called TAM. We decide how much we can get in that TAM. We start to figure out what traits we think are a part of that TAM. Then we start to build our segmented audiences and everything else. Okay, okay, great, that's a good starting point and everybody has to start from zero. But once you've got a little bit of data, it's okay.

Speaker 2: 22:43

Now go back and validate that that's actually the right ICP you should be targeting and you can do that depending on what your level of engagement with the data is across the lifecycle of to sales in a B2B situation. Then you use that point as MQL or the handoff point. You can give early indications of whether that ICP is actually the ICP you're passing off or not. Or, better yet, if you can get to dollars through a contract and a sale and an opportunity close process, then you can really validate is this the ICP is actually buying? So then you can go back and refine that ICP and the persona traits to match who's actually buying your product and you're going to get 60% of it right, 50% of it right just on guessing.

Speaker 2: 23:33

But when you really tie it down and validate, should the market segment be 5 million plus for a company or should it be 10? Well, with an ICP you can actually with a validated against the success of the ICP. In other words, you take all your successes, you take all your close one opportunities, you map out the traits and then you start to group them together in ways that cluster, and there's ways to do this. You can put it into Pareto charts, you can put it into whatever mechanism you need to visualize that data. But then you can make educated cutoff points that, hey, 80% of my market has at least 4 million or more Great. There's the start of my ICP threshold. And if you get up into another cluster that's a 50 million or 250 million depending on the size of the company you're going after you can then threshold that out. And now you've got market segmentation. Now you've got small, medium, big, verified data. So that becomes a key brick in your building, your segmentations and credibility that you know exactly the audience you're targeting.

Speaker 1: 24:31

So I have a follow-up question on that, because you said in the middle of that something about like you can get I think it was guess and be 65% accurate on what you think it should be. So do you? Here's a. I hear a lot of people talking about wanting to be data driven right. So what I would a reaction I might expect to hear from people when they say, well, 65% is all you can get with guessing, they're going to want more data before they make a decision to get closer to accuracy and precision right, using the terms you used earlier. My assertion is you shouldn't go for that right. I think you pick a number like 60,. 65% is probably good enough, knowing that it's not going to be static, that you're intentionally doing it that way to learn and then get better and more accurate and more precise over time, but you have to build that into the process. Is that what you're suggesting too?

Speaker 2: 25:30

I would say guessing is great. When you have very low maturity and very low resources in terms of the ability to buy, you can always change it by going to an analyst or going to a data broker and buying that market segment data and advancing your cause. Most of us, as marketers, don't have that luxury. It's very hard to get approved. It's a constraint of how much time do I have versus how much money do I have versus how much knowledge do I have. So if you take any product launch or go-to-market effort, you start with low maturity and you gain experience as you go through the process of understanding and collecting.

Speaker 2: 26:07

So guessing at the initial stage is probably as good as anything. But, as you say, you don't want to sit there all the time. You want to start refining that benchmark as you go forward, to say what it really should be over time. But the other end of it is, once you have enough experience, stop looking and do periodic checks to make sure it's still good. Don't go off and polish the bowling ball more than it needs to be because it's not going to be any more effective. So there is a happy window in between that says put you know, do your best with the data you have, and the one thing I've learned in my career progressing through the ranks of corporate structures is as you move up, you have less information to work from.

Speaker 1: 26:50

The same thing happens with it's ironic that way, isn't it?

Speaker 2: 26:52

Yeah, you have to get comfortable with the lack of data. So when you do a go-to-market in a brand-new market, if you're truly going into a blue ocean concept, you don't know enough, so you start throwing darts at the wall. But you should quickly start taking those darts off a wall and start shooting at a precision target as you can and as resources allow. I don't want to ever say that guessing is your good enough and be all and end all. No, it should be. Guessing gets you through the first segment of your growth journey and then you have to switch into more refined collection and analysis techniques to actually really prove out what you're trying to do.

Speaker 1: 27:29

Yeah, and I don't think, just in case anybody listening heard that and said would think that guess is a random thing, right, you still should be using your experience and intuition, right? So it's not a completely random guess. Experience and intuition, right? So it's not a completely random guess. This is my point.

Speaker 2: 27:45

No, it's not. It's an intuitive guess. But I'll go back to our point earlier. Intuition is not how you convince a CFO of anything.

Speaker 1: 27:55

Agreed.

Speaker 2: 27:56

And eventually you do need to come up with an appropriate description that will convince them that you've got the credibility you need. Once you have that credibility, the next effort to take a flyer on the next go-to-market program will be much more eagerly received and you get more rope to do it. It doesn't mean it's going to be right, but it means you've built up enough credibility that they're going to start trusting your intuition and you've gained that credibility to get there.

Speaker 1: 28:23

Yeah, I agree. Yeah, I think the idea there is. You should be seeking to continue to get more data.

Speaker 2: 28:32

Totally in the continuous improvement mode. But continuous improvement. To a point and I'll go back to the Voltaire statement perfect is the enemy of good. A point. And I'll go back to the voltaire statement perfect is the enemy of good if it's not differential in your marketplace, is it good enough versus being perfect?

Speaker 1: 28:49

yeah, and that's a.

Speaker 2: 28:50

There's a lot wound up in that statement, like where your differential be the best you can be, where your commodity just do do enough to make it work. I'll give give you a very quick example that'll be relevant. Nobody comes and joins our organization in an employment hire situation because we have the best email program around. It just has to be there, it has to work. When I'm trying to go to market, I want to join a team that's innovative, that's working, that's targeting, that's being out there, being a little bit guerrilla tactics, innovative in its ways. That's what makes people want to join my team. That's an employment scenario. But okay, change that into an audience scenario or a technology scenario or something else, it doesn't really matter. So be differential where you have to be and be good enough where it counts.

Speaker 1: 29:36

Yeah, and I think of the Pareto principle, the 80-20 rule, right? Yeah, there's a point where the marginal effort doesn't generate the kind of return, right, so there's not a point to it. And that probably goes for seeking additional data, right? It's not really going to make a difference, and that's something I've seen people kind of get stuck in analysis, paralysis or whatever well, actually, I think that's the classic mops pitfall we build systems for theoretical outcomes that never get used.

Speaker 2: 30:11

We collect data that's never going to make a difference. Um, I've seen systems with 1500 parameters in their crm, on the lead and contact pages, and I'm just sitting there going like who in the world's ever looking at this?

Speaker 1: 30:24

No one.

Speaker 2: 30:25

Why there's an expense to collecting data. There's an expense to holding data. There's an expense to cleaning data. There is just expense Every time a data field gets proposed that people really don't understand the whole. Again, that goes back to a little bit of the finance side. There's a total cost of ownership. That factors into this whole thing that if you just randomly want every single parameter under the sun because you think you might need it, that's not a good exercise. So here's where I'm going to go back and plug engineering. Engineering is a decision-making system that always lives within constraints. There's no perfect world to do anything. You're always making a compromise. Same thing has to apply in mops. We cannot collect everything, we cannot store everything, we cannot clean everything and make a perfect data system. There is no such thing. There's only we can spend this amount of money up to this point to make it effective for the rest of the organization.

Speaker 1: 31:18

Yeah, I use the term trade-offs all the time, but compromise right, opportunity costs right. All those things are like different ways of saying when you invest in one thing, that means you're not able to invest in something else, generally speaking, whether it's time, money, resources. So you brought about data points and reporting a little bit. I think I'm with you in that.

Speaker 1: 31:42

I think a lot of MOPs teams are falling into sort of two traps related to reporting and analytics. One is they just, you know, they get asked to generate a report, they generate the report. They don't. Really they don't. They don't do two things they don't ask what's the purpose. And the second, they don't look for and proactively say, oh, I generated this report, I noticed this thing that doesn't fit a pattern, right, and bring it up and it because they're not anticipating that someone else is going to notice that and ask why, right, what's behind it? So I think there's that that one and then the other is, I think, a tendency to just think the numbers are enough, right, kind of goes back to the storytelling. How do you think Mops folks can help provide some more consultative type of approach and rigor to reporting and analytics with their teams?

Speaker 2: 32:43

so, as part of the overlay of the storytelling, what I've always taught people who bring reports to me which I'm now high enough up to actually have an influence on is I always go back to. You got to answer the, the six basic journalistic questions who, where, what, when, why, how. If you can't answer those, then you haven't done your job, because I'm going to be quizzed on any one of those things. Is this the right audience? Well, that's the who. Have you done it? What's the what? And you know.

Speaker 2: 33:05

But fundamentally I truly am a believer of the Simon Sinek world. It starts with the why. There's a statement out there that I really like, that I'll assign to a smart person but won't name them. But the worst thing you can have is having a really smart person optimize a process that has no value or no meaning at the end of the day. In other words, the best process is no process, the best part is no part. That's because they didn't answer the why or they didn't test the assumption of it going into it.

Speaker 2: 33:40

So those things need to be built in as just checkpoints along the way of how you're creating that next report or how you're doing that investigation or are you doing the right thing. It also helps you stay on track so you don't add in the rest of the world like we'd like. There's some people who like to boil the ocean, and this is a way of stopping the boiling the ocean is. Stick to the principles under which you created this activity, and it can be a small report or it can be a whole analysis for a QBR. At the end of the day, you're trying to answer those things, but guess what? Those same questions help you form the narrative that the report is going to support Absolutely.

Speaker 2: 34:16

There is one exception to that, and that is another principle I'd like to bring in. That engineering taught me is understand when the model you're working with doesn't work anymore, and that goes back to your outlier that thing doesn't fit what I'm doing anymore. You've got two choices. You could either figure out why it doesn't fit and discount it properly that was because this data wasn't aligned properly, or they don't fit it or have I got a discontinuity or another opportunity that I could segment down the future and actually open up a new marketplace, because I've discovered that three or four or five or six or more things are suddenly lining up in a cluster that I didn't expect. Well, that may be an opportunity for a future endeavor to go after those people. But the other thing I would really caution marketing ops people is you need to understand your tool set and understand when your tool is telling you the right answer and the wrong answer, and that comes by understanding the limitation of the tool.

Speaker 2: 35:12

Computers are dumb. They do exactly what we tell them to do Doesn't mean they're giving you the right answer. The classic case of that right now is the AI thing. It's you know what is AI? It's the average answer of the normal distribution across the human population, so it's going to give you its best average answer. It's never going to give you a good answer, it's never going to give you an excellent answer, but it's going to give you the average answer. So if you're starting at zero, getting to average AI is a great tool. Getting from average to excellent AI is a horrible tool. So you've got to understand where the tool fits in your tool set and when to use it and when not to use it. I mean, there's a classic example of I think some lawyers used chat GPT once and it started to make up cited articles and the judge called them out of it and they got in trouble with their legal licenses. So I mean it comes down to those people didn't understand the limits of the tool before they used it.

Speaker 2: 36:08

Right Tools are there to effectively get us from point A to point B faster than we could do ourselves. That's why we buy a tool, that's why I invest in them. But you've got to know the limits of your tool and you can't apply it blindly, and I think too many people do, because they don't ask the question of what is this tool doing for me? Why is it doing this? I mean we get examples of this is how do you deal with bots at the end of the email chain when you're sending it into a large company and they've got data loss prevention algorithms running on their firewall and all of a sudden they see a thousand email messages from you showing up as a campaign activity and they flag you as nope, that's spam.

Speaker 2: 36:46

Well, that's because you have to understand all of the pieces of the interaction right and therefore plan it out. Do I batch them up? Do I send them in small batches? Do I get them to whitelist me as a customer, to do all? There's mitigations you can take against that, but but if you don't understand what's going on, it makes it very hard to get your message across. Now, I did wander the universe there.

Speaker 1: 37:07

Well, so it's interesting because I don't know that I would have gotten to the email, potential blocking, blacklisting, whitelisting stuff. But when you were talking about these data, I'll call them anomalies. Right, you've got to do some data. The other sort of alternative to hey, maybe this is identifying an opportunity that I hadn't otherwise done is to also identify you. This is where understanding the systems and the processes that go behind them can also help help you discover uh, let's call it, operational problems, right or or unexpected things. So I have multiple examples of doing reporting that went across sales and marketing. That helped me identify behaviors and things that were happening, primarily on the sales side, that I would not have otherwise, like no one, because they were sort of embedded in the way the business was done. I didn't know that was to be expected. So one was you know, we turned on Marketo at this place and had never made marketing, I hadn't really been involved with anything and tracking that kind of stuff. Well, also, we started getting attribution reports that started saying we, we had influence on opportunities that were like two years old and I was like this is weird, what's going on here? Well, it had to do with how that company initiated opportunities for multi-year deals, you know, as opposed to doing one opportunity. It was like a difference between revenue recognition and execution on projects and, um well, I had no idea, but like no idea, but it stood out to me. It was like this doesn't make any sense on the face of it.

Speaker 1: 38:42

I had to go dig into the data to figure out what's going on and ask questions. I had another one where I started seeing I was doing regular updating on again attribution reporting and kept seeing the number of opportunities from previous months were changing. They had closed and I was like what? Like what's going on? And the amounts have changed. I was like what's going on? Well, this particular company sold uh products to government agencies, or you know, near government agencies. They had these long-term contracts. So instead of opening up like just new orders like they were opening, and up like just new orders, like they were opening and closing opportunities as new orders were coming in. And so it was like so I struggle with calling the data right or wrong in that case, because it's just, it is what it is, but there's a reason, like understanding what it means is important.

Speaker 2: 39:38

It is what it is, but there's a reason, like understanding what it means is important. We could do a whole episode just on. Why do we use people opinion based data to do our sales predictions become a data-driven sales process by adding in factual steps that are verifiable, that turn an opinion-based funnel into a fact-based funnel. Anyway, that's a conversation for a future day, absolutely yeah.

Speaker 2: 40:09

But I wanted to touch back on. You reminded me of one thing that data and process also do and I think it's almost an obligation on marketing ops people to help the rest of the marketing group do this. Marketing ops can help you say what not to do. Where can you save your energy and effort when something's not effective is as much in good information as what's being?

Speaker 2: 40:33

100 so if marketing ops can go back and prove that you know you're in an email communication drip or nurture train and the likelihood of getting that next engagement click or engagement point is less than the unsubscribe rate, you've probably reached the law of diminishing returns. So instead of trying to build a 14th, 15th or 27th email in that chain, maybe you stop and go build another campaign entirely instead of continuing this one. So I think the other thing that marketing ops needs to do is really watch the long tail of diminishing returns and tell the rest of the organization where they need to stop doing things so they can refocus their energies on something else. It's also the secret of how you get time back in a marketing unit is figuring out what you should not be doing.

Speaker 1: 41:25

I cannot agree more.

Speaker 2: 41:26

Because nobody's going to give you more resources until you prove that you can use those resources effectively. So how do you create that time in the first place? You figure out what you can stop doing first, and it's very small at the beginning. It's one or two percent, it's even 5% at the most. But if you can then turn that 5% into something more effective, you've got a feed forward system instead of a feedback system which is just going to produce more positive results.

Speaker 1: 41:51

First thing I do is try to figure out what meetings I don't have to go to.

Speaker 2: 41:54

We could debate meetings all day.

Speaker 1: 41:58

Well, so you're bringing up an interesting thing. So you had mentioned that idea of like kind of knowing how to when to stop emailing someone. You know, automatic suppression list based on frequency of emails to specific people.

Speaker 2: 42:13

And it can be dynamic, it can be across products, it can be across audiences. Again, there's no demand.

Speaker 1: 42:18

You've all been doing some of this stuff at Demand Lab, right. So can you walk us through some of those things, because I know that, in particular the one about trying to say have we saturated a particular contact across a bunch of different emails, say, they fit into, like, we've got a newsletter and some nurture and we've got promotional stuff and it's all sort of happening at the same time to know, is this one person? Should we not send them this one piece? How do you pray? So that's always been a challenge, because I don't think I have yet to find a marketing automation platform that can do that kind of by itself. Very well, I would agree with you.

Speaker 2: 42:59

And I think it's due to the nature of how the products have been created and sold that the marketing automation vendors have their area of control and they're interested in giving you reports that help them sell that particular platform. And I would argue the same about the CRM vendors as well. They're very focused on giving you reports that help you justify the purchase of the CRM or renewals in continuous years. What I would suggest most marketing ops folks understand is we need data from across all the environments to tell all the story as best we can. And that's where I think a lot of marketing automation vendors specifically have fallen down is the strategic side of reporting, and they look across an individual email or campaign, but they don't look holistically across the whole database. They do in some cases, but it's crude, it's not dynamic, it's not week to week variation, it's a hard limit. Like you can, if this person gets 11 emails, don't send them the 12th, and then they don't tell you what to do with that 12th. They just don't tell you anything and then you think your message has gone out. And then somebody goes back and checks the stats that hey, I've got 15% less emails going out than last time on the same batch. So there's a lot of gotchas in the implementation of our automation systems. You know they're good, sometimes they're excellent at certain aspects of doing things, but you can. You got to know what it can do and what it can't do. And without the holistic information about figuring out active suppression lists like if you were to have a person do that, they'd spend all their time just trying to figure out which audience. So this is definitely a job for a computer system of some sort, and we have helped clients who have, and especially it's true of Fortune 500s and multi-product, multi-segment companies.

Speaker 2: 44:49

Each product team is usually independent of the other product team, so they don't care if they oversaturate the audience compared to the next group. They've just got a business target in front of them. So they're going to do everything come hell or high water. And that's where you get into channel conflict, not like with direct indirect sales, but I'm talking about product group to product group or product offering to product offering and everybody's in a free-for-all situation and marketing has to be the same voice of control at the end of the day and saying no, that's not a good thing. We've already emailed Joe and Mary twice this week. We're not doing it a 14th and 15th time, and we've seen that way too often.

Speaker 2: 45:24

So it's about governance, it's about control, it's about education, but it's also about bringing that proof to the table, showing how these people have already interacted and you're getting an ever diminishing rate of engagement on those particular things after an nth degree. So you know, if you plot out and bucket your engagement rates over the number of emails over the time period, perhaps even segmented by product or location or interest or anything else, you're going to end up with a multi fragmented table and depending on which one you need, you need to then go tell that story to that particular group or bring them all together in a room saying you know, individually you're going for it, but overall, corporately, we're sucking wind on this and we've got to stop and therefore we're going to make a system that works. There's a lot of governance that goes into that, especially for the more complex clients.

Speaker 1: 46:12

Yeah, but you all have done some of that stuff with your clients.

Speaker 2: 46:16

We have. In fact, what we're doing right now is taking all of what we've learned over the last 15 years and putting it into our own version of a product that we're working on and we're bringing that to market very shortly. It's basically we're trying to think about putting a marketing consultant in a box or a marketing analytics consultant in a box. Yeah, so we're going to be releasing that over the next few weeks to months. In fact, perhaps at Mopsapalooza we might be doing that.

Speaker 1: 46:40

Oh, okay, there we go. Well, good, good. So we're going to probably wrap it up here in a few minutes, but is there anything that we haven't touched on that you wanted to share with the audience?

Speaker 2: 46:55

I would say we touched on a lot of it, but I think there's one area that I think marketers could improve personally to get that next job especially marketing ops people I think there's two key skills that you don't have to be an expert at it, but you have to have some knowledge of it. One is basic stats. You have to be able to understand when a stat is telling you the right direction and the wrong direction. I'm not talking like you have to go into student T tables and look at P values and something. You need stats for marketers and there's plenty of online places to do that Know the difference between median and mode and

Speaker 1: 47:35

average those yeah average medium mode.

Speaker 2: 47:39

Um, let's see I'm gonna forget the other I'm going blank too, right now yeah, and the other one is like that accuracy and precision number.

Speaker 2: 47:45

Those are two different concepts about the same part of data. It speaks basically, is your stats telling you the data um is working for you or not? I mean, one of the key concepts you have to understand is a normal distribution curve and what standard deviation means to you. Three standard deviations means you've got 95% of the population. One standard deviation you've got 89% of the population. Those are numbers grilled into my head that this is the way you have to do it. And then you have to know if a standard deviation is even accurate, so that you're getting a representative sample that will actually tell you I can apply this generally. So that's one. The other one is we've touched on the beginning part of this process is you got to have some financial language to do that, and if you don't have enough financial language, go get it. There's so many ways to get that externally to your company Go make friends with the CFO, but you've got to be able to speak in their terms.

Speaker 2: 48:36

One I just wrote a whole blog article about what is material. Material is this concept of it's board level reportable stuff, usually set between three and 5% of the profit earnings of the company per year. If something is significant enough to material, it has to be declared by law to the shareholders. So if marketing isn't material in its efforts to the overall organization, do you think marketing gets listened to? No, no. So you have to think in terms of what does materiality thing mean to marketing? Well, it means you have to have impact that other people believe and understand. And that's just one small concept in a whole soup of financial terms that you have to get to. You have to be able to think about how to set up an ROI study.

Speaker 1: 49:21

Yeah, cashflow analysis.

Speaker 2: 49:23

You have to be able to read it, and even on your competitors or audience profile or whatever another one would be. How do you read a financial statement? How do you break down a GNL to tell you how much marketing? So here's one I did very quickly. How do I know if a target company is spending enough money on marketing?

Speaker 2: 49:44

I did a proxy through the number of people they hire in the marketing group compared to the overall numbers of the employees In a small company. 10% should be marketers and that's under, say, 50 people. From 50 to 250 people should be around 3% of marketers and above that it drops to around 2, 2.5% and you can track this. So if they're not spending enough on marketing, how am I going to sell my product? Yeah, right, so I can, and I can use places like LinkedIn to very easily get all the titles that I have and associated with marketing.

Speaker 2: 50:13

I do a data pull, bring it in and say, yeah, these guys spend an above average amount of data on marketers. Now, if I combine that with looking at their online profile and combining all the tools that they have outwardly facing on their website, I can also get a proxy for are they spending enough money on marketing. Therefore I can go sell them something. That's my view of the world. So between those data factors I can figure out is this a good prospect or not. Yeah, the only way I can do that is by understanding math and metrics and stats and all those kinds of things that come together.

Speaker 1: 50:46

Yeah, it also like it sounds like work right, like you actually have to put in effort. I mean, I'm not trying to be flippant about it, because I think there is a little bit of we think technology will solve all of our problems and what you just described. I'm guessing you use technology to some degree, right, but some of it was just you had to manually go I'm going to assume maybe it's not totally manually go pull data from LinkedIn, for example, right, that's where we started.

Speaker 2: 51:14

Yeah, prove the premise of the point, because it cost me nothing except time.

Speaker 1: 51:19

Right. So I let you go through that, because I feel like I'm always the one saying you need to learn basic statistics and basics of finance, and it's going to put you ahead of almost everybody else, if you're not already in finance, for example. So thanks, I'm not the only one on that soapbox.

Speaker 2: 51:41

We are a rare breed but I think we are very helpful in. Really, at the end of the day, I think both of us our objectives would be we want to make marketing a better partner to the business and have a bigger impact on the careers of the people we talk to and the outcomes for our current employers, whoever they may be. That's my goal at the end of the day is talk to and the outcomes for our current employers, whoever they may be. That's my goal at the end of the day is, I know marketing can be so much better. If we can implement and start to implement and move up the chain on these small things that eventually will snowball into big things. I think marketing has.

Speaker 2: 52:11

The is one of the few groups in an organization that has a corporate wide view. Very few of them do sales. Sales generally doesn't. They get partitioned into tiers of sales and other things. We don't tier marketing into enterprise marketing and non-enterprise marketing. We may have that internally, but marketing is marketing. It's supposed to represent the audiences and everything else and ultimately, the compelling story that we're trying to tell, and so I think marketing has this fantastic potential to be super impactful and I think it's underused currently in our current environments with the companies we work for.

Speaker 1: 52:51

I think that's a perfect way to end this. So, eric, I think you summed it up super well. Couldn't agree more. So if folks want to keep up with you or learn more about what you're talking about, what Demand Lab is up to, what's the best way for them to do that?

Speaker 2: 53:04

Well, there's two ways, of course. I occasionally write on the Demand Lab blog, so you'll find I'm currently writing a series about finance right now. I do it about every six weeks, but I'm trying to gear up on the how do I elevate marketing leadership? That's one of my passions. I know we can get better. And the other one is LinkedIn. Of course, you know that's a common meeting ground for all of us. So there or at Mopsapalooza, I'd love to sit. I'm going this year, so I'd love to sit down and talk to people about these kind of topics and do some thought leadership around that.

Speaker 1: 53:39

Yeah, mopsaloo is a 24 just around the corner. We're recording this in mid September, so just comes up fast, eric. Thank you so much. Thanks for our listeners out there. Continue to support us. If you have other suggestions for guests or topics, don't hesitate to reach out to Mike, naomi or me. Until next time, everyone.