In this episode of Riva Revolution, Mike Fazio, Head of Marketing & Rev-Ops at LSQ, joins Betsy Peters, VP of Marketing & Product Strategy at Riva to talk about how CRM’s have evolved into systems of action, how to get started in Rev-Ops, and how machine learning will push CRM’s to the next level.
Guest: Mike Fazio, Head of Marketing & Revenue Operations at LSQ
Mike Fazio is a marketing technology executive with more than a decade of experience helping companies get the most from their CRM and marketing technology stack.
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Speaker 1 (00:04): Welcome to the Rev-Tech Revolution podcast. Today’s episode is hosted by Betsy Peters. She is joined by Mike Fazio, head of marketing and RevOps at LSQ. They talk about how CRMs have evolved into systems of action, how to get started in RevOps, and how machine learning will push CRMs to the next level. All of this and more on the Rev-Tech Revolution podcast.
Mike Fazio (00:32): Yeah. So I’m Mike Fazio. I’m currently the head of revenue operations and currently the interim head of marketing. Hopefully we’ll make that permanent soon. And I work for LSQ revolution. We’re working on revolutionizing access to working capital for businesses. I’ve been there for a little over a year and based in Atlantis. Spent a lot of time on the software we’re about to talk about, just in software companies and purchase and consulting companies as well along the way.
Betsy Peters (01:05): That’s great. So when you say revolutionizing access to working capital, is it for any certain type of company? Is it small businesses, large businesses, everything in between, or who do you usually work with?
Mike Fazio (01:16): Yeah. Thanks for asking. So we have solutions across the board, right. Everything from AR financing type solutions for smaller and mid-size businesses up to supply chain financing solutions for large enterprises. And that allows large enterprises to take control of their working capital. Same way that does a smaller supplier. I need cash today to pay payroll tomorrow, we can help with that. As opposed to a giant company might say, hey, I need my quarter to do better, I need to make sure that I have more cash flow to reinvest in the business. We can help with all those types of solutions.
Betsy Peters (01:54): Cool. So you’re serving a range of different masters, it sounds like. And that can be a challenge when it comes to setting up a CRM. Although I will say for the listeners, Mike’s been at this for many years, so I’m eager to hear kind of your perspective as a veteran. I heard you built a web-based CRM as an intern, so let’s start there. Tell me about, how did you get into this crazy game of CRM and what attracts you to it?
Mike Fazio (02:21): Yeah. We’ll get in the Wayback Machine and see some crazy stuff. Yeah. I mean, this was nothing spectacular. It wasn’t an early Marc Benioff by any means. Yeah. Actually my dad was working for a software company in Delray Beach, Florida, and they needed a simple CRM type solution. They were just using spreadsheets and what people had in their, Outlook. So I think I ended up teaching myself like MySQL and probably Pearl because I had buddy who used Pearl. I was like, okay. And so I built this. It worked right. You could get data in, you could get data out. They loved it at least in theory. They ended up merging with a company, I think a few months later who already had homegrown CRM data, so they ended up using that one. Probably infinitely better than what I made, but it was a good experience to see it in action.
Betsy Peters (03:18): Well, so it makes sense how you got your start helping out your dad, but what hooked you? Why did you stay in it for this long?
Mike Fazio (03:24): Yeah. I mean, think maybe the theme of my career was, always being willing to jump into something new and see what happens. I ended up working there as an intern for a little while, just kind of odds and ends around doing various things. I was a little on the sort of geeky but creative world, and that’s again sort of a theme that will kind of tease out. So I ended up getting a different internship with a buddy’s dad this time with a much larger company called Deco Software, and I came in as sort of marketing. So doing website, other graphics, PowerPoint presentations, kind of that standard creative stuff, but they also knew that I was kind of geeky as well.
So I ended up getting pulled into their Salesforce instance by the head of America sales. It just kind of clicked right like, wow, I can do these cool tech things while still also doing some marketing stuff while learning more about the business. And that evolved into marketing technology, kind of doing some early vendors on… We picked some ridiculous vendor that was terrible instead of Marketo. I got a demo of Marketo and it was when Marketo still looked like you were kind of scrolling the data at the back end of your OS. It was just a terrible UX, but it was cool. But I’m like, listen, we’re trying to support an international marketing team.
Most of our marketing team was in Europe and I’m like, I’m not going to teach all these people how to basically be an IT backend admin to send some emails. Sorry, this is silly. So this other technology, I don’t remember it now, but it was okay. We sent some emails, they had made some landing pages, but again it was like, whatever. A few years later Marketo reached back out and we were like, okay, let’s try it again. And they actually had re-skined it and it was like, okay, we get it now.
I also had a little bit of a bigger team. I think there was probably three or four of us. And so we onboarded Marketo. And that was just a cool jump into the world of marketing automation. What does it mean to do lead scoring? How do we actually get sales to be okay with the fact that we’re not just going to give them a bunch of terrible leads all the time? Because we still have leads. I can call somebody, so it’s better than nothing. It’s not better than… Just a little…
Betsy Peters (05:48): Sneak preview, it’s not.
Mike Fazio (05:53): Yeah. Sneak preview, it’s terrible. Yeah. I mean, I got you a little further than your question I think, but this one jumped in.
Betsy Peters (06:04): Yeah. It’s really interesting to think about how things have changed from the beginning of CRM and kind of the advent of the digital age and where we are today. So in your broad brush across that time, how would you characterize the development of this technology and how it’s helped businesses like yours or the ones you’ve been involved in?
Mike Fazio (06:28): Yeah. Absolutely. Yeah. I mean, I’m probably not going to be fair to any of the other CRM solutions because I’ve been a Salesforce person unintentionally for many years and then intentionally for a number of other years. And really it’s gone from this sort of Rolodex. Like, okay, it’s a CRM, it’s a customer relationship management solution, you kind of put some data about your customers, maybe some of your prospects, maybe do a little forecasting here or there, to really this system of record. A real simple kind of system record to this system of action.
So for me, where I’ve seen Salesforce specifically come in and be the most valuable part is that it’s sort forcing all these other tools to give me structured data that I can then do something with. I can make sure that the data all goes into the right records, the right objects, and then other tools whether that’s part of it or marketing cloud or whatever we want to call it today can send emails and do automations.
I can do automations and do different data inside of Salesforce and then I can push that data back out to Outreach or Salesloft or one of those tools. I can also feed that data in a nice, clean, structured way back to my data lake and let the data scientists do stuff with it. So really for me, that’s kind of where I feel like the idea of CRM has come from. I think maybe the name more implies to this sort of system that is in the center of go to market action activity.
Betsy Peters (08:06): It’s a really nice framing which you just gave, that concept of system of record to system of action. And where would you say that they fall today, they meaning Salesforce, on delivering on that promise in terms of system of action versus system of record? Because of course we’re all software and we’re all trying to make these things work, right?
Mike Fazio (08:28): Yeah.
Betsy Peters (08:28): But what’s the reality of system of action? And why are other applications like Outreach and Salesloft needed to deliver on the promise?
Mike Fazio (08:37): Yeah. I mean, it depends who you ask. If you ask a Salesforce sales rep, they’re going to say, you don’t need those other tools. Salesforce has their high velocity sales. I mean, I demoed years ago, so it’s probably a lot better than when I saw it, but I think what still made Salesforce successful and sort of needed in the central part for me is that I do have some very powerful, easy to use automation tools inside of Salesforce that I can do things with that’s very generic. That I can have access to and not necessarily need a data scientist or a programmer to do.
Flow is a very powerful automation tool that I can use to change data, clean up data, automate tasks in a way that then serves up the right data at the right time to these other tools where teams can live in Outreach, Salesloft, or your marketing automation platform, or any number of other tools. But I think Salesforce does try to play in like we’re the everything, but I… I don’t know. I think the strongest is that core platform play. I think we’ll see what happens with some of these other tools if they can…
Because you get Outreach, you get Salesloft, you get all the other ancillary tools that are out there that are useful, that are powerful, but how do you deal with it? How do you manage this cloud of other stuff? So part of me hopes for a really good consolidation. I want Salesforce in the next few years to buy a few of them to really make them stick and like, okay, this is going to be perfect, but I don’t know. I’m not sure that this is going to happen.
Betsy Peters (10:25): So you like the monopolists, is that what you’re saying?
Mike Fazio (10:27): Yeah. And probably come asking for an invoice. Send me a cheque.
Betsy Peters (10:33): Right. Of course. Make it easy for me, but don’t make me pay for it.
Mike Fazio (10:37): Yeah.
Betsy Peters (10:38): So you’ve got another theme that kind of I am hearing from you is that you’ve got this interesting kind of one foot in tech and one foot in marketing has been your background, and that you’re appreciating the tools that allow you to not have to be super tech heavy. You get it, you understand automations, you understand structure and all of those things, but you want tools that allow you not to have to rely on an IT team for example, and that kind of makes that data move around and do what you need it to do. Is that fair to summarize what you just said?
Mike Fazio (11:10): Yeah. Absolutely.
Betsy Peters (11:12): Given what you’re seeing today, is there a trend where the data’s starting to get abstracted from the applications, where you think about the data layer separately from a platform layer, an application layer, that kind of thing?
Mike Fazio (11:28): Sure.
Betsy Peters (11:28): How does your team look at that?
Mike Fazio (11:30): Yeah. I think it does and I think that’s a good thing. You don’t necessarily want me digging too much into data because I will find a way to make it tell the story that I wanted it to tell whether that’s the real story or not. That’s why I appreciate that our team has some data scientists and we’re investing in that world. And I think we’ll see the fruits of that. And from the go to market standpoint, I think having the data have sort of its own layer managed by its own team, sort of owned by its own team, lets us get the most out of what that data is, and again, not lie to ourselves about what it’s saying.
From a system of action standpoint, the way that I’m thinking about building a couple things internally is, customers are going to do certain things and the data team is capturing all these activities, whether it’s visiting to opening the application to transactions to whatever customers are doing. And it sort of can happen across the board for anybody. I’m not going to be able to track all those 80 big transactions and data points inside of Salesforce. I don’t want to pay for the data, I don’t want to set it up, but the data lake, that’s what it’s there for. That’s what it does. We get inputs from all the different spots, we can normalize it, get some insights.
And then I want the data team to say, okay Mike, here’s the Delta, here are the changes, this is the change in the behaviors. From a first layer it’s just like, give me a date of the last time or every time that someone, whatever does it, has some sort of transaction. Give me that one date and maybe a couple small pieces of data. So I have the latest of what’s happening. So I may be able to have an automation that says, if this transaction hasn’t happened in 30 days, start sending this customer email. Nurture them and say, here’s the benefits of doing it. If you need any help, reach out, et cetera.
The second layer down is asking the data team to go and build some models and say, okay, I have some assumptions on what I think this lack of data, this change of data means, but one, I might be missing trends that machine learning might be able to find. Right. I had a guy, a buddy of mine who I hired in a previous company, Adam. He came in and built this really interesting tool on a tech stack looking at part on activities. So you could go with Salesforce Marketing Cloud Account Engagement. It’s what it’s called now instead of Pardot.
We could use the API to essentially get the activities from Pardot to see how many emails you’re sending and form fills and things like that. And so we could do what that data is. You look at form fills, especially if you have a bigger company where you’re actually getting multiple form fills a day or a number a week, you feed it in this little program and it starts to do some modeling to say, okay, your standard form fills are 20 a week or whatever up. Here’s kind of the normal range, 10 to 50 or whatever. Well, for the past two weeks you’ve had zero, so I’m going to send you alert and say, something might be wrong with your site. Something is not right. There’s an anomaly here.
So I think something even as simple as that can be powerful, but then you add that into thousands of transactions and all sorts of other customer data and you can really get much more actionable information from these heavier tools. And then just tell us, alert us, hey, this thing is happening. Now we can take action. I can alert someone, I can send an email, I can send an urgent Slack to the whole company. Whatever needs to happen, I can take that action. I just need the data layer to sort of be the intelligence and watch for that stuff.
Betsy Peters (15:16): That makes sense. That of course means that for people to use that and trust the data, you’ve had to shop a little bit about the models and do some convincing to your end users. What’s it like at LSQ right now in terms of your sales team feeling like they trust the data in your CRM and some of the cutting edge things that you are doing to try and enable them with insights? How is that going? And what have your challenges been along the way with data trust?
Mike Fazio (15:47): Yeah. And I think this even comes into trusting the tools themselves, right. And I’m trying to think of… Internally, I feel like we have a pretty strong trust of the system and of the data because we haven’t… Some of what I’m talking about, what I want to do hasn’t gotten there yet. There’s some back and pieces that are still building. So we have a pretty straightforward data model in Salesforce right now, but one of the big things for me kind of getting back to sort of, I guess, building the foundation of making sure things are right so people trust it is to make sure that all of my systems are speaking the same language and I’m not getting these weird silos, because what I can’t have happen is I can’t start sending out automated emails to prospects or customers that are going to make our team look silly.
I don’t want an email to go out to a late stage opportunity, introducing a new partnership that might completely blow this big deal out of the water. So I need to make sure that in Salesforce I know where an opportunity is, in Marketo that… that Marketo used to have. Pardot knows where that opportunity is, and so does Outreach and all the rest of the tools. So that when we’re building automation, you say, if something is in one of these stage opportunities, do not send this email because that is going to sink us. So ensuring that our data is not going to make us look silly, it’s sort of number one for me in trusting, and any sort of automation that we’re building.
And I think that just goes a long way. The other part is making sure that we’re dealing with duplicates well. So we deal with a bunch of referral sources. And when you get that kind of thing, it’s just territory management. You can’t be messing with a salesperson’s commission trick because you let this source kind of recommend and it was already assigned to this person, but this person know so they started working with them. And now what happens? That kind of thing. I think making sure we understand as sort of RevOps leaders that our decisions and what we build inside of our platforms has real world impacts on people’s jobs and how they work and the paychecks they get at the end of the day. That’s a little bit a roundabout way to get back to your point there, but it’s a big thing that I think about. Making sure people trust the data and tools.
Betsy Peters (18:28): It sounds like you’ve touched on this, but just to dig one layer deeper, is there any way to have trust in the data without a really rigorous data quality program that you put in place?
Mike Fazio (18:40): I mean, to find rigorous, I think it’s… I think you can’t drive yourself completely crazy by getting into many of the things at the same time. I think it’s a hierarchy, it’s a prioritization like anything else?
Betsy Peters (18:57): It sounded like you prioritized duplicates, which makes a lot of sense. What is in your hierarchy for data quality in general?
Mike Fazio (19:07): Yeah. I think duplicates are huge. For me I’ve seen duplicates be potentially large problems when… For instance, if I go back to the opportunity situation, if I have a duplicate as a lead and as a contact, it’s part of an opportunity, that person and the opportunity might be excluded from the email, but the person who’s the lead with the same email address is not, right. And they still get the email. That was a big problem with one of the changes that Pardot made a few years ago. So it was like, wait, so if the person who shared the same email address, one of them could be opted out the other person won’t be, that doesn’t work for me. You’re killing me here. And so that’s a big thing is, if this person is in the system, they need to have one record or you’re going to do silly things.
Duplicates are big. I think understanding your needs for account ownership, contact ownership, it’s also going to get into… I mean, I’m thinking about scaling. So my big thing is scaling, and part of scaling is making sure that territories make sense, that we have a few different teams that do a few different things. I don’t necessarily want team A to be able to dabble in team B’s records. Not because I think people are inherently going to do something intentionally bad, but I think people make mistakes and I don’t want them to make a mistake in this other opportunity. Yeah. I think those are sort of the top… I mean, kind of at the top of my head.
Betsy Peters (20:51): Is there anything Mike… So you guys have customers over probably a long lifetime in terms of multiple years of a relationship.
Mike Fazio (21:00): Yeah.
Betsy Peters (21:02): Is there anything that you think about in terms of data quality when it gets to year five or year six or year seven that’s important to you in terms of multiple opportunities and multiple people from the buying committee and the implementation group and all of that? So anything there that you use as a rule of thumb about data quality when it gets real complex?
Mike Fazio (21:24): We do a fair amount of cross sell work and different opportunities for the same people. Even some of the data that we start with is suspect. And I don’t know that I have necessarily a rule of thumb. I think one of the things that we’re talking about with our data team is, do we want to engage with, maybe use their help, or maybe just get a tool directly in Salesforce to look at more mass scale enrichment of data? Just make sure, hey, go through and clean it up if we haven’t touched it in X amount of time.
Betsy Peters (22:10): Well, let’s shift gears just a little bit from data back to applications and your thoughts about this explosion. You talked about a little bit with new tech applications. How do you think about the trade offs there? What are important things to consider when you’re adding new tech to an existing stack?
Mike Fazio (22:30): I think it works both ways for a new stack or an old stack. Yeah. I mean, we’ve all seen the explosion of applications and solutions out there, right. There’s the chief MarTech blogger who kept making the bigger and bigger eye charts of just what he calls marketing technology. Then you slap on all these other sales tools and all other things.
Betsy Peters (22:55): Sales technologies. Yeah.
Mike Fazio (22:56): Yeah. It’s a little bit ridiculous. I mean, for me, I think what’s important is… Again, I have to go back to, if it’s not going to communicate well with Salesforce, they’re not a strong API connection. I can’t deal with it. When and if I’m ever at a billion dollar company and I have a huge team of people, maybe we’ll talk. I could build my own integrations. And I’ve helped some large companies do that kind of thing before. But for me the appeal of some of these is like, can you work with campaign membership in Salesforce? Can you work with opportunities in Salesforce? Can I trust that your sync isn’t going to blow things up or I can’t go and deal with sync errors every day. I just don’t have time.
So I want to make sure we get it set up once, set it up well. And occasionally stuff is going to go wrong, you have to play with it, but for me that’s a huge part is I need to make sure it’s all going into my system of action. So that can be true for whatever your system of action is. Everything has to communicate there. And then it’s just digging in and trying to find what are the nuances of the platform? They all have their own kind of claim to fame, they’re all trying to make their own market category. I’ve demoed 6sense and Terminus and Demandbase and Zoom info, all four sort of marketing targeting for advertising and ABM plays and intent data and they all have their own thing. And it really comes down to, what is your business vision? What is the business trying to do? And does it fit for what that platform is focused on providing
Betsy Peters (24:49): For sure. As you’re going through those demos, et cetera, in the back of your head, are you thinking about, okay, how could I leverage existing technology to do this by moving data around better? What are your thoughts around that?
Mike Fazio (25:08): As we started off, I’m a tinker. I will build my own stuff just because it seems kind of fun. That’s obviously changed a little bit as I’ve gotten higher up and I can’t spend as much time getting in there, although I still want to go build some flows and do some stuff. That’s where I start personally. It’s like, okay, what is available to me? Especially knowing that I have these powerful tools already, can we do what we needed to do? But then I need to ask, is that scalable?
And am I going to be mad at myself in a year when I realized that I built this thing and now we’re stuck with it and it’s not great? So I’m always trying to think of scaling and building towards the future. And that’s going to be a big part in, am I hacking something together just to get it done and because I want to not spend the money? Or do I actually think this is good enough and scalable enough and replaceable or upgradeable in the future?
Betsy Peters (26:05): That makes sense. Tell me a little bit about, you’ve made your decision, you want to bring something new into the stack, you think it’s the right thing. What do you go through in terms of heuristics to make sure it’s right, make sure it’s essentially going to generate some ROI as well as give you scalability and all the other pieces you need?
Mike Fazio (26:28): Yeah. Again, I mean, I go back to making sure that I understand where I see the business going and how we’re going to get there from a high level business standpoint before I even think about the tools. And then obviously I try to get as many demos as I can stand. I try to ask as many hard questions as I can to the sales team, knowing that they have their script and they’re going to paint things in a certain light and try to drive you to certain answers, but I really just try to get past. Okay, you’re my friend right now and I appreciate that, but I need you to tell me the truth about what this specific technology thing is. And if you don’t understand it, we’re going to have to talk to a solution engineer or someone on your support team.
So from that aspect I do appreciate when a vendor brings in their customer support reps or something like that, because they can typically speak a little bit deeper into what some of these things are, because it all looks real shiny on the demo until you dig into the details. And then if I can find anybody in the community and a big part of this is community and trying to figure out, what have you seen? Where has this fallen short for you? Where is it excelling for you? And again, trying to fit those things into my business priorities.
Betsy Peters (27:54): How often do your requirements when you begin a journey like this evolve? And by how much as you’re learning?
Mike Fazio (28:05): Yeah. Absolutely. It’s a lot usually. I mean, I’ll give you an example. Just recently we switched to a different ABM intent platform. I thought I wanted something a year ago and it didn’t turn out to be… The platform was a little lacking, sure, but it was also just different than what I think we really wanted. As I went through a couple of other big platforms, I started seeing that what I was looking for was actually more of a sales platform than just sort of marketing by itself, because I think without getting into another topic that marketing sales alignment is just huge. I mean, I think that’s why we have RevOps is because it’s silly to have marketing ops and sales ops and our own silos and we’re all doing the same thing especially with data we’re using. It all needs to be together, right.
Betsy Peters (28:59): Right.
Mike Fazio (29:02): Yeah. I think I went into expecting kind of one thing and came out with a tool that goes closer to again where I think the business vision is taking off.
Betsy Peters (29:17): Just to backtrack a little, tell me about how RevOps became a thing at LSQ? How did you get that alignment?
Mike Fazio (29:27): Yeah. It’s a funny story. I sort of did from the outside of LSQ. So before I joined, my buddy has been working at LSQ for five or six years. He was head of marketing. And we were kind of chatting. I was thinking about maybe something new in my horizon, and I said, “Hey, if you’re looking for a RevOps person, I might be interested in talking.” And kind of talked a little bit about what that would be and whatever. He’s like, “Yeah. Okay, I’ll let you know or whatever.” So we kind of stop chatting. A few months later he calls me back and says, “My boss is looking for… We want to do RevOps role.” And I’m thinking, well, I know somebody who might be willing to talk about that.
And so really, they kind of brought in the… I would like to believe that I put the RevOps bug in his head, but my current boss, Vikas Shah, is a really smart revenue leader so he gets the need for it. So I’m sure he brought it up on his own. So I joined and started it off. They hired me straight out as the head of revenue operations to say, go and build this thing for us. And then I’ve gotten that sort of lee way to do it. A big part for me was… I mean, I think what we’ve all seen is just getting the tools together, getting a handle on Salesforce and what’s happening there, making sure you’re getting back to your question of trust before.
The system when I inherited it had been kind of going through a few admins, wasn’t really much. My buddy who was the head of marketing was also trying to be the admin and just was like, it was too much. A lot of hands in the pod, a lot of older automations that were built out that just would break for random reasons. And so I wanted to make my life easier, so I fixed all those things. Ripped out, this ripped out that, cleaned up a bunch of permissions and all that kind of stuff. I actually found… I got lucky. There was a lady on my team, Tabitha, who’s just great. She didn’t have any RevOps training or whatever. She just sort of had figured out Salesforce and could do reporting and data imports and stuff like that. And I realized she was in sort of a role that was undefined. I was like, I want her to be on my team. And that’s sort of been.
So she’s really helped. She’s really jumped in and has become a great admin over the past year and just helped with a ton of stuff. So really it was just sort of cleaning up a lot of technical debt as the first part, getting our tech stack in order, and then trying to build that trust again around Salesforce and these platforms where now the team uses day in and day out. We run all of our dashboards. We have our weekly pipeline calls, all lot of Salesforce dashboards. We clear reports, the whole deal, and it’s sort not questioned on. This is the data, this is right. If you want your deal to be on the board, it has to be in Salesforce in the right way. And we constantly try to just make that easier for people as much as possible. It’s been an interesting year growing and building the brand new team.
Betsy Peters (32:48): That’s great. It’s interesting kind of a theme again that’s been running through. We’ve had a couple folks on the podcast who have talked about this new concept that was new to me called technology quotient. So EQ for emotional and IQ for intellect, now it’s about technology. And the RevOps team seems to have this balance of all three or needs to have a balance of all three. So how do you think about that? And what are you looking for in talent for your RevOps team? And then as a corollary, where do you think the new salesperson has to go with that balance?
Mike Fazio (33:26): Yeah. That’s a great question. And when I heard that on the podcast, it got me thinking because… So a previous company I worked for, Sercante, my friend Andrea Tarrell started it back in 2017. I was employee number one and we started building this company and we’re starting to hire some people. We started like, okay, we need to be intentional about who we’re hiring and why. So we sat down and kind of started writing some things out and we’re like, there’s still something else about these people that were hiring that is working.
And we sort of looked at our backgrounds and we both came from this place where we learned. We had a certain amount of business acumen is what we called it, where we understood how businesses worked. We were both really fortunate to work at companies that were mid-size and growing, but have direct access to top leadership, the CEO and the rest of the team. And so we got to really dig in deep early on to understand how business works. On top of that we’re both geeks.
So we like to get the nitty gritty and build flows and build automations and talk about data. And there’s this whole piece, but we also kind of marketing and being creative. So for us, we realize that there’s this traditional marketing role. And they’re the people who make the campaigns, do the creative writing, and understand how businesses works and how it flows and do all that kind of traditional marketing stuff. And then specifically what they’re thinking…
Betsy Peters (35:02): Which has always had an analytical component, right? It’s not just creative.
Mike Fazio (35:08): Right.
Betsy Peters (35:08): Yeah. The best direct marketers were the biggest data geeks, right?
Mike Fazio (35:12): Yeah. Exactly. Right. And so you have this traditional marketers and then you have these tools. So IT is going to own tools because that’s what IT does. They own tools, they provision them, they deal with users, they deal with permissions is what IT does. Well, now you have this sort of marketing technology that comes about, and it’s this merge of these two things. And IT sure can get them involved but they’re going to be too slow. They’re doing what IT does. They’re making sure we’re compliant and doing all that good stuff, but these aren’t scary enough systems to necessarily require all of that.
And then you have marketers who… Some of them are like, well, what the heck is this tool? I’m trying to go do my own data analysis somewhere else. Now, you want me to use this tool to send emails and create landing pages? What the heck is going on? Well, we found that there’s certain people who have both that business acumen and this technical geekery and it works really well in this sort of now the RevOps space, because it’s sort of been marketing sales and smashing us all together. What I really think is interesting is that we grew the first… So it was Andrea and myself and then we grew and hired a succession of, I don’t know, it was probably five or six women unintentionally. It’s just sort of what happened.
And then we finally got another guy whose name was also Mike. So it got really weird there for a while. There was just two guys were named Mike and then the rest were women. It was a very strange dynamic, but moral the story, my theory is that marketing and marketing operations and now revenue operations is a gateway to help women who are sort of traditionally pushed out of IT and engineering type roles to get into this more geeky role where now… While you’ve got marketing operations, we also have Salesforce. And Salesforce is very inclusive and very much bringing people into the forefront. So I think that was really interesting for me as a hiring manager to see these really smart geeky women who, again, maybe, maybe not. I’m just assuming that based on the history of education and kind of how we got here…
Betsy Peters (37:22): That’s STEM. Yeah.
Mike Fazio (37:24): Yeah. Exactly. I feel like that’s really been interesting.
Betsy Peters (37:29): That’s a cool observation. I also see at least in my history that people who do product development also do well in RevOps, because really what you’re talking about is a bunch of feedback loops. And RevOps is feedback loops on steroids. Hopefully it’s an iterative system that allows you to learn quickly and it’s ultimately a big learning platform if you do it right, about the customers that you want to have and the customers you do have. So I think that’s really interesting. So tell me about folks who might be young and just getting into this game. What’s your best recommendation about how to get started?
Mike Fazio (38:13): Yeah. I mean, I think I’m going to go back to what I just said, do what you can to understand how business works, get into that. Understand that the fundamentals of business, maybe even get some of these entrepreneurial books that come out. There’s Traction and there’s a number of them. Read through some of those and just get that cash flow is important and all these other things. And then more generically, just always be curious and ask questions. Never lose that.
Always question what the status quo kind of thinks, but starting out though, I think Salesforce has a great community for RevOps people because, one, it’s very inclusive, very open. There’s a lot of free training resources around it, and it can really get you into the community and it’s sort of a gateway to these other tools and things. Yeah. I would say understand how business works, get into Salesforce to find some other of those kind of free trainings. I feel like Salesforce is a really solid platform to start. I don’t know. That’s what I got.
Betsy Peters (39:27): I think that’s excellent advice. And I totally agree with you in terms of their approach to the market and developing community and making sure it’s an inclusive community. So that’s a huge plus for Salesforce as far as I’m concerned.
Mike Fazio (39:38): Yeah.
Betsy Peters (39:39): All right. Now I’m going to ask you to be a futurist. So let’s fast forward five years. Is data its own layer of the tech stack? What else are we thinking about when it comes to applications or platforms or sales and marketing and all of those things? What’s your predictions about the future?
Mike Fazio (39:58): Yeah. So as far as the future goes, I think data’s its own layer right now. I think it’s only going to continue as far as what that looks like in five years. I mean, I think there’s just an interesting thing. This idea of machine learning and building models is going to be more commonplace to where it’s going to be like, okay, well, what does the model tell us what we need to do right now? If you look at 6sense, they’re all about their machine learning model that looks at, we think that your prospects are in this stage of the buying cycle right now. But that to me, I think is really interesting.
And if you can take that even on your own data, I think that’ll really help you win just to pull out customer attention. What are your customers doing before they want to leave? What are your customers doing when they stay? How do you encourage that behavior? Because I think that RevOps can’t just stop at close one opportunity.
Betsy Peters (40:43): 100%.
Mike Fazio (41:03): So we got to make sure to keeps your attention and cross sell. And again, how do we bubble up and see what the right cross sell opportunities are and get that in front of us? And continue to dig into seeing maybe ripping the data out of CRM, dropping the data lake and giving us a better idea of, what are our best chances at success? I think there’s the external data models like Salesforce, Einstein. And obviously I mentioned 6sense has their deal, but I think if you can have your own model, I feel like that’s going to be even more powerful. And I think that’s an even more accessible.
Betsy Peters (41:44): Yeah. Everybody’s customer journey is different. So having something train on big data versus your data is important.
Mike Fazio (41:52): Yeah. And I think both of those tools promise to use your data as well, but just… I don’t know. I think the real keys in five years will be… You’ll still want some sort of a data scientist or someone to give you an idea of, are you on the right track? But you’ll be able to do a lot more of yourself. You won’t need a whole engineering team to build these things out. It would be more like a flight of Salesforce flow kind of idea. It’s technical. You need to know what you’re doing, but a lot more people can get to it. Sort of democratizing big data access at least is what I’m hoping.
Betsy Peters (42:24): Yeah. It’s interesting. I went to an O’Reilly conference on AI three years ago and went to the Microsoft booth and they said by 2024, which was his prediction, you will be able to open up Excel and all the data models you’ll need will be in Excel. I was like, all right.
Mike Fazio (42:46): Clocks ticking.
Betsy Peters (42:47): It’s a good promise, right? Let’s get going. Yes. Anyway. Yeah.
Mike Fazio (42:52): Yeah. When you have a prediction, you got to do 20 years, because then you can say anything. It’s like, well maybe…
Betsy Peters (42:56): Right. Absolutely. Then you get into the realm of science fiction, which is more fun anyway.
Mike Fazio (43:01): Exactly.
Betsy Peters (43:04): All right. Anything else that you’d like to leave the listeners with in terms of encouragement? Because sometimes it can be a slog getting your sales people to trust you and getting the data quality issues slain and all that. Any words of encouragement for somebody who’s been there, done that?
Mike Fazio (43:23): Recently my boss, Vikas, mentioned making some big bets because the day to day stuff is always going to kind of happen, but what are the things that kind of make you stand out? And I think that also layers well with just this idea that sometimes you got to make a decision and go with it. Really that’s the best thing I can give is, go through, make the best decision that you can and give it a shot. Let everybody know that maybe this is just a test. Like, hey, we’re going to give this a shot for the next six months or a year. If it’s terrible, please let me know. You’re going to have to just learn to be okay with it.
Sometimes it’s going to be terrible and you’re going to make the wrong decision and you’re going to go back and they’ll fix it. There’s a quote that I keep on my Slack that’s something like, success is about routinely absorbing manageable damage while avoiding catastrophic failure or something. You’re not completely getting destroyed. And it’s true. I do silly things or whatever. I’ve made some changes to the system that within a week or two I was like, no. Didn’t go over well with the users. It’s not going to happen.
Betsy Peters (44:40): Revert.
Mike Fazio (44:40): Yeah. Exactly. Make those big bets, make the best decision you can and run with it. Don’t get stuck in that analysis by paralysis or paralysis by analysis. So those are the important ones. That’s what I got.
Betsy Peters (44:54): That’s awesome. And you’ve lived to tell many tales, so all of those things have served you well, obviously.
Mike Fazio (44:59): Yeah. Absolutely. Yeah.
Betsy Peters (45:01): Awesome, Mike. Thank you so much for spending some time with us. I really appreciate it.
Mike Fazio (45:08): Thank you for having me.
Speaker 1 (45:08): Thank you for tuning in to the Rev-Tech Revolution podcast. If you enjoyed this episode, please don’t forget to rate, review and share this with colleagues who would benefit from it. If you would like to learn more about how Riva can help you improve your customer data operations, check out rivaengine.com.