Find who to contact next, even before they’ve shown intent

About Rev

Jeffrey: Rev is an AI-backed technology that focuses on helping companies in the B2B space identify what we call lookalikes. There’s always a need for companies to find their next best customer. What we’ve built here at Rev is the ability to create a very sophisticated model, which means looking at lots of different patterns to identify and say – hey, your best customers look like X, Y, and Z, let’s find a lot more companies out there that look and have X, Y, and Z. That’s a simple way to think about what we do here at Rev.

What happens when you run out of high-quality prospects?

Jeffrey: This gap between high-quality prospects where companies usually find that through a lot of these days, it’s through intent, right? You can imagine you’re a company, and the best prospects that you can possibly have are the ones that are always visiting your services, right? They’re attending your webinars, signing up for a free trial, and interacting with you. Those are your best prospects, right? Because they already know about you, they already have an interest in you. They want to learn more about you and are typically ready to buy from you.

What happens when you run out of those types of companies? Then what you do is you settle, and you just go and say – okay, I don’t have any more of the good stuff, so now I’m just going to hunt through the bad stuff, right? They use data tools and say – hey, I’m looking for a company that’s a hundred people in healthcare or makes $10 million. But guess what? There are millions of those types of companies.

You go from one place where you know really well that these prospects want to buy from you to a place where I have no idea if any of these 10 million companies are interested in what I do. We’re trying to solve that gap, which is don’t go from really good to really bad, go from really good to identifying ones that maybe are not really good but should be because they look very much like the excellent prospects.

Rev best features

Jeffrey: First of all, it’s the lookalike engine. What the lookalike engine does is it analyzes your list, and it looks at all these factors and says – okay, for the 50 companies you just shared with me, I’m able to find the common characteristics suitable and build a model. And then, using that same model, I go out and find lookalike companies, right? Based on what I can see. That’s one significant technological innovation. The other thing is what’s fueling this lookalike engine. What we had to do was build an entirely new data set that we call exographics, right? Exographics is understanding the behavior of a company. How do you do that?

In the consumer world, you can do that. And there’s a whole data set called psychographics, right? Before psychographics, you had demographics, right? You had age, gender, you knew where someone lived, and you knew maybe some of their hobbies, but that’s all you had. And then companies like Facebook and Google came along and basically tracked everything you did digitally, which website did you visit, what do you buy, how often you were on the internet, what news you read, etc. These companies, like Facebook and Google, developed a whole data set called psychographics that then understood your behavior. That made the consumer world a lot better when it came to audience segmentation. The B2B world doesn’t have that yet, and we think exographics solves that problem.

You have companies right now that leave what we call breadcrumbs on the internet. They have their website, they have their press releases, and they have news about them. That’s very interesting. Then you have all the people that work for them, they all have LinkedIn profiles, and then you have job posting data. Companies are hiring, they’re firing, right? They’re adding to their teams or making reductions to their team. Our whole job here is to take all those breadcrumbs about the company, about the people that work there, about different things that they’re doing, and use that information to develop this new set of data that we call exographics so that we can understand how a company behaves similar to what they did in B2C commerce. We’re trying to do the same thing for B2B.

Rev costs of starting out

Jeffrey: The pricing varies depending on how many profiles you want to build. We call it a startup package where the company has one core market they’re going after, right? Typically the range is about #20,000 to get started with us. And then some companies have lots more profiles. They have many more market segments, so the pricing increases depending on how many profiles you want to create and store. If you sell healthcare, that’s one profile. If you sell to healthcare and finance, those are two separate profiles you want to create because, typically, companies look different depending on their profile.

Do you have any integrations with other platforms?

Jeffrey: Yes, we do connect with multiple CRM systems. We connect with Salesforce. One can take our information and push it into Salesforce. We connect with HubSpot, but we also have connections with Outreach, as well as ZoomInfo. Suppose you want to conduct research within our platform as well. As we get more customers, they want us to do more integrations, so we’ll continue to.

What teams can use your product?

Jeffrey: Use cases often revolve around the need to find your next best target, right? I’ll go through two different examples of use cases. One use case is on the sales side. What sales teams are always looking for are high-quality fit accounts, right? Because you have sales reps and want to ensure they’re spending time on the right accounts. One of the use cases is around helping sales teams identify what we call net new targeting accounts. They provide us with a set of who they think are their best customers, maybe who signed with you in the last year.

And then, we can use that information to build a target account list that now their sales reps will start reaching out to and engaging, which is a lot better than having your sales rep individually go out and find their own targets. What typically happens is when you tell your sales rep to go and find targets, they typically go after companies that they’re familiar with, companies that they’ve worked with in the past, or they’ll just write down companies that are names that they recognize, right? Often what happens is those are probably not necessarily the best companies to target, right? That’s one use-case example. Marketing uses us to help them find the next best intent lookalike.

Marketing departments really love intent data, as they should, right? Because intent data, as I mentioned earlier, tells you who’s visiting your site, right? Who’s spending time with you? But frequently, they run out and need to create more awareness. Who should they target with their awareness campaigns with their advertising? It’s the same idea, put in who shows the highest intent, and we can tell you other companies that look like them so that you’re spending your advertising dollars on companies that at least resemble your high-intent people versus just any other company out there. In both use case use cases, it’s really about helping them fine-tune how they build their audience so that they’re spending time with the right people.

Do you have any competitors for Rev?

Jeffrey: A lot of competition comes with people trying to use existing data sources to find companies. There are lots of data sources that have company data, and I think what you realize is the ability for you to apply certain kinds of filters is very limited, right? Again, you can do a headcount, you can do revenue, you can do vertical industry, you can do the funding, and all that stuff. All of those are important, but how do you get deeper? How do you understand the behaviors of a company? That data set doesn’t exist out there in what was available. It’s a substitute for what we do, but I think what we’re trying to do here is much more depth than what has been available in the market regarding these kinds of company data sources.

What is the story of the company?

Jeffrey: Rev started it started helping companies on demand. You can imagine every B2B company wants to generate demand, and there are lots of different ways to generate demand. One of the popular ways is to buy what we call MQLs, marketing qualified leads essentially. Companies would come to us and say – hey, for this quarter, I need 500 MQLs, and we’d say – sure, we have services and preferred partners that are able to run those campaigns and provide you with those 500 MQLs. But the first question we would always ask is where do you want those MQLs to come from, which companies?

There are different answers, and some companies would already have an ABM list. They’ve already identified the list of companies they want to market to, which is great. Some companies don’t have a list at all, right? You can go out and buy MQL from many different providers, right? Some are much cheaper, and some are very expensive, it just depends. For us, where we really shine and why our customers keep coming back to us is we just didn’t accept the list and said – okay, we’ll just use this list. We wanted to go further and ask why these companies are on this list. What makes them a good match for your business?

It’s surprising that a lot of the time, there really wasn’t a good answer. The answers would be – well, these companies are already in our CRM. Well, how did they get there in the first place, and why? And they would say – I don’t really know, or the answer was – we paid another company to build this list for us. And then we would say – what criteria did they use? Why did this company belong on this list versus another one? Oftentimes the answer was they just looked at similar companies that had the same number of employees or they were in the same vertical or industry.

You’re getting marketing qualified leads, but they come from companies that really have no business doing business with you, and they were just a company on a list. Where we were successful was we took that list, and we said – no, the first thing we should do before running a campaign is to actually prioritize this list and to make sure that if we’re going to generate MQLs for you, it should be from companies that are important to you, companies that are a fit for you, companies that ultimately have a redo business with you. Our MQLS ultimately ended up being much higher quality because of that extra step we put in, and we built a whole business that way.

And then we realized, two years ago, this whole process and technology that we built to help companies prioritize their targeting can be used outside of just generating marketing qualified leads. Sales teams could use it, marketing teams could use it, and lots of different departments could use it. Then we built a whole software now where companies can interact with our technology directly instead of going through our services, and that’s where the company expanded from.

How big is your team?

Jeffrey: The team is around 50 people, if I’m not mistaken. Much of the team is built around engineering and data science, and those are the two biggest departments within our company. We’re a technology company, and it takes smart people to build a technology and software company.

What do you actually do as the Chief Go-To-Market Officer?

Jeffrey: Go to market is a function that more companies are paying attention to, right? Before, it was a shared responsibility between the CEO, CMO, and COO. I think for me why this particular position was put in place is that we’re seeing this discipline starting to grow across lots of different companies, which is really understanding your go-to-market motions, understanding how marketing fits in with sales, how sales fit in with customer success and, and the entire customer journey, right? Part of my responsibility as the chief go-to-market officer is similar to what revenue operations do now, right? Let’s look at the entire customer journey and then at all the ways that we interact at the very beginning when they first hear about our company, all the way to when they become a happy customer.

All those interactions, all the different friction points. How do we measure our success, our effectiveness, and our efficiency? Every day what I do is look at data, and I look at how we perform at different parts of the customer journey. Some days, I focus on the mid-funnel, and some days, I focus on the top of the funnel. Some days I focus on the customer success side of things, it just depends. But I think my job is to make sure we’re, we’re constantly in rhythm right with each other, that like we’re not getting too far ahead on pre-sales, where our customer success is, struggling or vice-versa, right? Maybe we have too many customers, and we’ve gotta figure out how to fix onboarding or something like that. It’s just ensuring that the entire journey is successful that I pay attention to daily.

The role that I have is similar to revenue operations, having a holistic view now and say for us to be successful as a company. Every part of our customer journey needs to be measured and aligned, right? A lot of what I think about daily is reducing the friction across the different departments, whereas before, departments would work independently. Sales would do its thing, marketing would do its thing, customer success would do its thing, and then maybe once a month, everybody would tell you about all the problems that they’re having. A lot of time is wasted, and a lot of effort are wasted. In my role, we want to identify the friction points much sooner so we don’t have to wait a month or a quarter to figure it out. We can figure it out much faster and ensure that the experience continues to be done well.

When did you join Rev?

Jeffrey: Officially, I joined Rev a little bit over a year ago. Before that, I was just helping as an advisor in an advisory role. And then I saw what the company was doing, and it got me really excited about this problem that we’re solving. I used to be in b2c, in e-commerce, and I saw the same problem on the consumer side. And I see Rev here solving that same problem now on the B2B side. It got me really excited to think that this is something that companies are going to need. That’s exciting.

Why companies aren’t looking to buy more software

Jeffrey: Every company right now is navigating the current economy and the economic headwinds. As for every software company right now, budgets are tight and frozen, and lots of companies aren’t looking to buy more software. I think we went through a whole decade where companies bought a lot of software, and their tech stack grew really big and probably overbought, to be honest. I think nowadays, the mentality is – okay, how do we not necessarily downsize, but how do we get more efficient with everything we currently have and not look to buy more?

That’s challenging, right? We’re a software company, and we’re looking for customers like every other software company. How do we help our potential customers understand that this is important, this is valuable, and that this is actually the right software you want in this current economy? You want to be more efficient, and you want to do more with less. People are still very nervous about making sure that they have enough cash in the bank to pay their employees three months from now because of the economy.

What is your vision for the future of Rev?

Jeffrey: I think Rev it’s going to help companies be smarter with their time and with their budget. It’s the same thing I saw when I was in e-commerce right before this whole idea of psychographics came right before Facebook and Google, and it was hard to target customers very precisely, right? I knew in the back of my mind that I was probably spending money on advertising to people that really didn’t care about my product, but I couldn’t differentiate. I think the same thing has been happening in B2B, where I believe many companies are using tools like Outreach, but unfortunately, it turned them into ways to do more spam. They’re using these tools to cast a wide net because they just didn’t have a way to be more precise with their audience segmentation.

The vision for Rev is we continue to get better at understanding how companies behave and continue to improve this data set. I always joke with my team, and I want to set the world record for the least number of emails to hit our quota, right? One of my visions is that if we need 10 meetings, I only want to send 12 emails to get to those 10 meetings. Right now, to get 10 meetings, you probably have to send 10,000. It’s a crazy ratio. Can we do that? I don’t know. But that’s hopefully the dream that companies don’t have to do as much but still get to the right quality numbers at the end of the day.

What is your story, Jeff?

Jeffrey: I was an engineer, a chemical engineer, actually from college. Then I started off my car career completely away from software. I actually worked in the oil field, helping with exploration, and then I did that for a few years. After that, I went to the Peace Corps, I was a volunteer math teacher for a few years, and when I first came back, I moved back to the Bay Area, where I grew up, and that was my first startup, right? I started my tech career in customer success, I started on that side and then moved into sales at another startup company. I learned how to focus on numbers and inefficiencies and all that stuff.

And then, I happened to move into e-commerce which is an interesting departure from B2B software, but that was a good experience, and I learned a lot about customer acquisition, right? That was one of the biggest lessons, and I’m seeing the same thing on B2B now. In B2B SaaS, a lot of it now is really understanding your acquisition cost. How much does it truly cost to acquire a customer where that hasn’t been the focus for a long time? We do a bunch of things and generate a customer, but now I think B2B companies need to pay attention to the actual cost of acquiring a customer and lifetime value. All the lessons learned from B2C are now happening in B2B for me, which is like watching history repeat itself, and it’s fun.

I see myself more as an operator. What I love is looking at data and understanding the story, right? What story is this data telling me? And how do I use this information to help educate the people around me to either fix problems to get better, whatever the case may be? I love to teach. I always joke that if I weren’t in my current career, I’d be a middle school math teacher because I love to teach and I love to share information. That’s the role I see myself as an operator.

What’s one piece of advice you tell somebody wanting to become that or a chief go-to-market officer?

Jeffrey: For me, it’s really important to have that curiosity, it starts there. Try and understand as much as you can, and don’t accept a situation where you’re unsure of the answer, right? Keep going, keep digging, keep trying, and keep asking questions. And I think as you progress in your career, you’re going to realize that those questions are really important. And most of the time, people are afraid to ask that question because they’re afraid of the answer. But I think if, if you want to be successful in my role or in revenue operations or anything like that, people are looking for someone who’s not afraid to point out, – hey, we’re making a mistake here. But here’s also how we can fix the problem. Being a problem solver and having that curiosity is really valuable.