3 Ways Marketers Can Become More Data-Driven with Maura Ginty of Mode

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Welcome to another episode of 3-Minute-Marketing, where we talk with some of the foremost experts in growth marketing and distill their best knowledge into 3-minute blocks for your listening pleasure.

Today I’m super excited to have a real marketing hero, Maura Ginty, on the podcast. Maura is the CMO of Mode, which is a leading collaborative data science platform. Among the highlights of her impressive resume, she’s reduced the cost-per-lead at Mode by 96%!

My question for Maura is, “What are 3 ways marketers can be more data-driven?”.

Show notes:

  1. Go beyond the simple math of the budget envelope all the way through to target (meaning things like ad spend, leads, MQLs, sales). Owning the revenue target should be a given.
  2. Truly data-driven marketers know how to segment, personalize, and evolve.
  3. Marketers assume that if they know what vertical someone’s in then they’ve defined segmentation but there’s a lot more to understand about product usage, satisfaction, customer journey, and more.
  4. Until you understand where your best audience is, you’re not going to be in a place to go out and find more of them.
  5. Personalization shouldn’t just be the job of your BDRs… all of your marketing should be personalized & speaking your customers’ language.
  6. Evolution will be driven by both machines & humans: machine-learning & AI will be able to handle the “simple math” of your funnel. Marketers must evolve to focus on thinking through the elements that are less predictable to find unopened opportunities.
  7. Marketers need to get out of the habit of just “ticketing” their data team about the numbers or accuracy of the data. Instead, it’s critical to query around insights that will help you solve your core marketing problems (e.g. instead of, “Do we have all the boxes ticked for lead scoring”, ask “What are the behaviors of our highest-value customer cohort & how can we replicate those behaviors early in the funnel?)


– [Chris Mechanic] Hello again, everybody. Welcome to another episode of “3-Minute Marketing”. I’m your host, Chris Mechanic, longtime performance marketing geek 3-Minute Marketing is basically like three minute TED Talks. We look at some of the, or we talk with some of the foremost experts in growth marketing and basically distill some of their best knowledge into snackable three minute little blocks for your listening pleasure. Today, I’m super excited to have Maura Ginty Maura is the CMO of “Mode”, which is a leading collaborative data science platform, that looks quite interesting. And before Mode, Maura has had a very, very impressive career, even at Mode, I think your accomplishments, I mean, per your LinkedIn to the tune of 96% reduction in cost per lead, and like improving the mix of enterprise to just standard leads to up to 25% from less than 5%. That’s amazing Maura. You seem like a real marketing hero in a lot of cases, especially in some of these B2B so we’re excited to have you. Welcome to the show.

– [Maura Ginty] Thank you very much. It’s great to be here.

– [Chris Mechanic] Awesome. Awesome. So let’s jump right into it. We have a burning question for you, which we wanted to keep a little bit broad so that you could just flow with it kind of, but the question is, what are three ways marketers can be more data-driven? Your time starts now?

– [Maura Ginty] Great. Well, I love this question because as a long time marketer, it was really, it was a wonderful place to land and to work at Mode with so many great data teams. And it’s part of an ongoing evolution for me personally, as a marketer to go beyond what starts is very simple math I think it takes, it’s not just the heroism of being a marketer these days, it takes a lot of tenacity. There are so many changes in the role. There are there such a dramatically change in environment from the technology, to the expectations, to the techniques that we use for customer acquisition. So I would start with that. I would start with encouraging all marketers to go beyond the simple math of the budget envelope, all the way through to target. Those are things that are manageable. Those are things that in the future will be able to be handled systematically. So this simple math of how much am I spending on page search? How many leads am I getting? How many in QL? How many sales qualified leads? How many opportunities? All of that is necessary. And I would say that for marketers these days, the revenue targets should be given. We should be responsible for what source of marketing to turn into revenue for the company. If you work with those assumptions, I think there are three things are really important, and that is to be able to 1. Segment, 2. Personalize and 3. Evolve. Segmentation is a really challenging one ’cause I believe that marketers assume that if they know what vertical someone’s in, that they’ve defined segmentation. And there’s a lot more to understand around product usage, satisfaction, customer journey, expansion, and contraction of these types of contracts over time. Until you really understand where your best audiences is, you’re not going to be in a place to go out and find more of them. The second part is really on personalization. And we’ve talked about that one for a while. It started with the BDR team starting to really have to personalize it and do more crafting of every message that they send. But ultimately, every part of marketing, every channel that we use, should start to have that level of personalization so that we’re using the customer’s vocabulary and not ours. That’s critical to successful marketing. And I think we’ll see more of that over time. And to evolve, I think that there are two parts to that. One is going to be driven by machines and the other one is going to be driven by humans. A lot of the basic math that I mentioned before, that forward facing and predictive work that the machine learning and AI will be able to handle in the future. That’s part of how the marketing function is going to evolve. And a lot of these tasks and a lot of these deltas can be brought to us to solve problems. What’s going to be tricky is thinking through the things that aren’t as predictable. Which is an interesting thing to say, coming out of a pandemic, but we can get so used to predictable numbers and then how to have confidence in that predictability that we can lose track of the unopened opportunities. And that’s where the conversations with data experts is really important and learning how to have that conversation driven by curiosity and exploration. Where we look at the data that’s different than what we look at every day. And we use it to make the kinds of discoveries that can alter the course of a business.

– [Chris Mechanic] Wow, Maura, you nailed it. And actually taught me a good bit and gave me a good bit of ideas. But just to summarize some of the key things that I heard on the segment, I think you’re absolutely right. Most people do just choose an industry or choose a persona, but things like product mix, product usage, expansion of contracts over time, like that’s just mind blowing. So absolutely, segmentation runs deep. And then on the personalization piece, yeah, like the standout there was speak to customers in their language. It makes a lot of sense. And I see B2B is guilty of this all the time. And then of course the evolution piece, I’m interested in your take on the robots on evolution. But no, that was fantastic, Maura, thank you very much for that. I want to continue talking. I think you have a few more minutes, So if you could stick around.

– [Maura Ginty] Yeah, I’d be happy to.

– [Chris Mechanic] Yeah, absolutely, thank you. And folks, if you enjoyed that, and if you want to continue hearing Maura in my conversation, there should be some additional footage or a link in the show notes to that footage. If you liked this as always, please drop us a like, a comment, share with your friends. We love hearing from you. Let us know if there’s somebody you’d like us to interview or a topic you’d like to hear about. Maura, any closing thoughts or otherwise just let the audience know where they can find out more about you or Mode.

– [Maura Ginty] Yeah, I would love to just mention, I talked about the conversation between the domain experts in marketing and the data experts that they work with every day. We actually just published a guide, a Data Team’s Guide to Working With Marketing Metrics. So that should help the conversation go forward. It was a whole lot of great marketers working with the data team and Mode and seen different examples from our customer base, where we know this work has happening.

-[Chris Mechanic] So we’ve got a guide, how do we find the guide? or you can share. We’ll definitely include the link to the guide in the show notes. But is it findable elsewhere? Just mode.com go to the re,

– [Maura Ginty] Yep, it’s on mode.com.

– [Chris Mechanic] All right, cool. We’ll include the specific link in the show notes, as well as some additional footage. That’s a wrap for this. If you want to hear the rest of mine and Maura’s conversation, please find the link above, below, or to the left or right of this video, and we’ll see you on the other side. All right. Well, let’s talk a little bit about, ’cause I’m intrigued by that. I like that you added that point of clarification ’cause you kind of got cut off at the end, right when you started to talk about those conversations between the marketers and the data teams. Which I think is a really awesome, ’cause it’s kind of like left brain, right brain in a way, in some ways. So I can imagine that.

– [Maura Ginty] It is a little bit of that. Yeah. But I think that’s one thing that marketers now have to work with all the time. The emphasis of digital marketing means that we’re left brain, right brain all the time. We’ve got one of the more significant tech stacks of any business unit. So there’s typically a set of technical power within the marketing function, but we look at it differently. It took me years, even though I started as a digital marketer, it took me years to figure out how to have enough of an open-ended conversation with the data team or the data expert, to really start looking at unexpected sets of information. Whether that is looking for product market fit from an unexpected audience, there was one example I can think of where we found actually a much easier audience to pursue, because it was, you had to be accredited for it. Can you imagine like being able to go out and look at an easy list like that from a discovery and the data that you already had, that they were effective users of your product? That’s a huge win for a marketer right there. And just letting them know the more general level of what you’re trying to pursue about your audience or your segment or your market, or the competition that that can leave a whole open-ended level of creativity. Other than just saying, can you tell me how many, how much referral traffic we’re getting from this review site? Things like that. So, yeah.

– [Chris Mechanic] So yeah walk me through one of those conversations. How would it typically go? Do the marketers generally and of the open-ended then an effective variety. Not the how much referral traffic am I getting. But do the marketers generally come with questions or they describe sort of some of their objectives and then the data team comments, or does the data team come to the table and say, “Hey, we have access to all this data as well marketers, like what do you want?” How do those conversations usually go?

– [Maura Ginty] We have to fight our traditional habit here. ‘Cause I think marketers are responsible for so many numbers that nine out of 10 times, we only go saying, “Tell me where this number is. Or, “Is this number right? I’ve seen the Delta, can you double check whether this number is actually accurate? Is the data source wrong?” And even if you just change that initial question to, “Can you help me figure out what’s going on here?” Or, “Are you seeing this? Is this the most meaningful Delta that you see in my set of data?” Or, “We’re seeing this behavior from part of our audience, how can we find out more?” It’s the framing of the conversation that is the really critical first thing. Because it’s the difference between ticketing, a ticketing system, ’cause you’re not able to explore the data on your own, or you don’t trust it, and going into, how can we figure this out? It’s the difference between, do I have all the right boxes ticked for lead scoring? And, what can you tell me are the most important behaviors from our successful customers, and which ones can we replicate early in the funnel. If you ask a question like that, that can revolutionize your lead scoring. But we come from such a standard set of recipes that we can easily forget to approach it that way. It’s approaching it with a fresh perspective, every business that you go into.

– [Chris Mechanic] Yep. 100%, 100%. I think even beyond data, just when it comes to like marketers and developers or engineers interacting and we’re guilt, I think everybody is guilty of this at some point. Where you ask for, like, instead of describing sort of the why and the what you’re trying to accomplish or what you’re hoping for, you just get prescriptive and you say, “Hey, I need a banner ad 300 by 250 with this copy on it. Make it look like the homepage.” kind of thing. And I don’t know if that is because of busy-ness or if it’s, or if it’s something else, but one way or the other, I wonder if there’s some kind of mechanism that we could put in place, or even if it’s just kind of some kind of mental thing to realize when we’re doing that so that we can snap back. Like, for instance, I learned early in my career when speaking with developers or engineers to never use the word, “just”. Like, “Hey, just change the, just change the thing on the top. just do this.” And so, somebody really laid into me one day probably for saying that. And so it made a wrinkle in my brain and I never do that anymore. How do we make that into a habit to approach it in a more open-ended kind of way, and essentially allowing others to shine and do their work?

– [Maura Ginty] Exactly. I think we have to remember similar what you’re saying. When we work with developers and we say, “can we just”, we’re assuming that everything is a low level of effort. We assume that we know everything about the different ways that they could construct something and that the task is simple. If you make it more open-ended, then in the same way that as a developer, allows a developer to think more creatively about how they solve the problem, and that can lead to different levels of effort and different paths forward. When we talk to the data team, we have to remember that this is outside of the pressure cooker of the go-to market, for lack of a better phrase, like the sausage factory. Like we know we have to put things into the top of the funnel and we know we have to help facilitate that, and remove all the friction for them to go to buy. It’s a funnel mentality that we go into. There’s a lot of pressure on making the numbers that I hope is actually being shared more with the marketing team and not only the sales team. But that can cause pressure on that relationship. We also know from various studies, that marketing is one of the least trusted functions. So there’s a lot of defensiveness and the numbers that we choose to pursue. It also tends to be part of the creative efforts that marketing leads. There’s a lot of second guessing on the colors and the designs, that’s really hard for anyone to get away from. So there’s a lot of numerical defensiveness in the function itself, but there’s also a lot of creativity. And that is already there. We can bring that impulsive over. And when we talk to data teams, I think it’s not just the open-ended part, it’s thinking of them less as a partner in the gigantic Google sheet of the world. But thinking of them more as a value pursuer. Like we’re all looking for how we can provide value to the customer, we’re trying to figure out how they think, how they make choices, what makes them confident, what makes them happy about the work that they’re doing, we want to think about the company’s larger goals, and we want to think about our buyer’s careers. So if you put all of that together, you’re starting to get this multifaceted view of the person that you’re trying to develop a relationship with, which is the prospect and the customer. And as we rely more and more in digital, there’s more proof of that. There are privacy rules that are changing, but there’s still a lot, there’s so much more information that we can use to benefit the type of information that we provide them and when. And when we work with data teams, we’re going to be more of an expert on interpreting all of those different elements and figuring out how to take our day-to-day problems and turn them into an alerting system, a more passive alerting system than someone receiving a report once a week, and trying to figure out what’s wrong. As we evolve, that is where things are going to get really interesting. And that’s going to challenge our creativity and theirs. And both sides of this house have a common problem. We’re on the receiving end of a lot of tiny requests. Change this copy, I need this one pager. They get a lot of like, set up this report for me, so I can watch this number. There’s a comradery there, and there’s a need to collaborate that both sides understand it’s just getting to that conversation and both sides seeing that as a chance to really leverage that creativity and rational mind to pursue something impactful, to get out of the reactive space and to drive meaningful business strategy for the market.

– [Chris Mechanic] Yeah. No, I like that quite a bit. I want to change the subject here real quick. I know we only have a few minutes left, but it seems, so you’ve been at Mode now for a couple years, and it looks like one of the first things you did was revamped the go-to market. And you posted some of the biggest wins I’ve ever seen. Like 96% reduction in CPAs and 60% more leads, so I want to know, like, thinking back on that, like, what were a couple of secrets to your success? Like, did you do really well?

– [Maura Ginty] A lot of it is, it’s attention to details. I would say that the reduction in accounts is that when you’re a startup and you’re doing well, it’s really easy to have a lot of, it’s easy to have a lot of tools. It’s easy to stop watching a lot of the different ad spend, because if you have just one person looking at it, part-time in an early startup, it’s easy for that to get out of control. And the team at Mode had done really great work in a lot of areas, but it was really strapped. So I think a lot of that was just the ease of setting up larger systems, so that we could monitor that. So that we could improve efficiency. And so that we were really much more careful. And then we’re lucky that we did a lot of that work before some economic changes that helped us continue the right motions going forward.

– [Chris Mechanic] Yeah, so what gets measured get managed.

– [Maura Ginty] True. And it’s not just on the revenue side. It’s the other part of that is being a good partner with your finance peer. So doing a lot of that work can be underlooked, but that is part of the larger system. You’ve got spend to get to leads on one side, you’ve got operational management across all of it, and then you’ve got pricing and packaging as the direct revenue levers that you can influence, if not own.

– [Chris Mechanic] Yup. Well, you heard it here first ladies and gentlemen. What gets measured, gets managed. It’s easy to not just in startups, even in any, even larger organizations, especially larger organizations. It’s easy to overlook things, lose sight of things. There’s so many platforms, so many spreadsheets, so many different things, centralized data hub would be really nice to have if you don’t have one already and it’s time to shop for 2022. So, I was actually looking at the Mode product. I think it looks pretty bad ass. I think we might have to take it for a test drive. I’m serious.

– [Maura Ginty] That’s a great idea. We also just relaunched our free trial. So if you know SQL, you can get in there on your own.

– [Chris Mechanic] Cool. I do not know it personally, but I’m sure my data team does.

– [Maura Ginty] Perfect. Okay.

– [Chris Mechanic] All right. Well, thank you so much Maura for your time today. We really enjoyed it. We really appreciated it. And will you come back on the show one time, another time, rather?

–  [Maura Ginty] Definitely, that’d be great. Happy too.

– [Chris Mechanic] Cool. All right. Well, we will see you soon.

Maura Ginty

Maura GintyMode

Chris Mechanic

Chris MechanicCEO & Co-Founder

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