Why Proprietary Data Beats AI Software for 2x Pipeline Growth with Ann Davis

0:00You are the driver of this, not the customer. So make sure you're in the driver's seat and you're not just being driven by them because they'll take you through all the windy roads and end up at a dead end. And what are you going to get for your time? The most valuable asset salespeople have is their time. If they're not diligent and smart about how they're using it, busy doesn't mean successful. Sorry. Welcome to the Revenue Builders Podcast, a weekly show featuring B2B sales leaders and executives. Hosted by five-time CRO John McMahon and force management co-founder John Kaplan, the show takes guests in the barrel, behind the scenes with the people who've been there, done that, and seen the results.

0:46Revenue Builders covers best practices for scaling and growing your business while sharing the pitfalls to avoid. I'm John Kaplan, and I'm joined today, as always, with my co-host and great friend, John McMahon. Our guest today is Ann Davis, Chief Revenue Officer at Crunchbase. Ann spent five years at Google Cloud running their data and analytics practice, and before that, led sales at a company called Looker, who was acquired by Google. One of my favorite parts of Ann's background is that when she started her career, she was configuring camera systems on sidewinder missiles for the F-14 fighter program.

1:31She's been in tech now for 32 plus years. Ann joined Crunchbase about a year and a half ago to help lead their shift from a product-led motion to an enterprise motion. And she's got a strong point of view that we're going to dig into that in the AI era, it's proprietary data, not the software, that's the real longtime value driver. We're going to get into that. We're going to get into what good data actually means for a company trying to get AI ready, where she thinks AI genuinely changes the seller's job versus just speeding up existing tasks. and what it really takes to pull off a PLG to enterprise pivot.

2:14Anne is direct, she's sharp, and she does not hold back. We hope you enjoy this one. Let's listen in. So, Anne, I thought I'd just kick off the conversation. When I first met you, I thought your background was so cool. So interesting. thing uh tell me tell us tell the audience a little bit about kind of the how we get you here today as like you know the CRO of Crunchbase to go from a you know product-led motion or PLG to an enterprise but before that you're like designing like rockets for you know to go on with Northrop Grumman so tell us a little bit about how you get here today. Yeah I think for me I was a math science undergrad and nobody would hire me but technical positions back then.

3:07And so I started off at Grumman and found myself working on the mission computer aircraft for the F-14 and then moved on to some secret missions back then, which were legit just putting, you know, recon cameras in a Sidewinder missile. But then when I realized that really wasn't for me, nobody else would look at me on the business side because of the technical undergrad. So I was sort of forced to go back and get my MBA and I got it in corporate finance and strategy. And I did that as a full-time basis because everything had been technical up till then. And so I made my move into sales coming out of there and was at Showtime Networks, grew my territory by$3 million and they tried to give me a$25 ,000 bonus.

3:50And I'm like, wait a minute, this doesn't really add up. And so I decided to jump over to tech sales and I've spent the last 32 years plus there. And your background, you know, you've got an incredible background in data and data analytics and you spent some time at Google doing just that. Yeah. I was struck with our last conversation you and I had in the prep where you talked about proprietary data is the primary long term value driver versus the software. So you're kind of a data first person. Talk to us a little bit about what that means to you. Yeah. And I think that, you know, having spent, you know, several years at Google and prior up and leading into the acquisition, I mean, at Looker and then the acquisition by Google, it's really became very apparent that AI is only going to be as good as the data that it's built upon.

4:52And everyone, you know, the big seven or eight that are out there, they're gobbling up as much proprietary data as they possibly can so that they have a competitive differentiation in the market. But if you look at most public available LLMs, they're really going to go into what's in the public domain, right? They're going to be a better, you know, Google search engine for you. And it's going to be aligned to the prompt that you put in, right? But what I'm seeing in terms of our AI partners, as well as customers, is they're trying to find a way to co-mingle that with the appropriate proprietary data sets that are important for their particular industry.

5:35Financial services is a big one. There's a bunch of AI players in that space. We partner with all of them because obviously our private market data intelligence is extremely valuable to that segment. So from that aspect of it's like, OK, I'm, you know, JP Morgan. How do I put together what I want my corporate AI engine to look like? And what are the data estates that I want to be able to access within that? So when you look at companies, a lot of companies, their main piece of proprietary data is all the information they have internally. It's emails and it's slacks and it's documents and it's things that they've done that support the research or the product or whatever it is that they're building.

6:23But you need to take all of that and mix it with the appropriate third party data sets to really bring forth the most robust and successful AI experience. Because when you look at AI, it's really there as a tool to save time predominantly. Whatever it is you're trying to do. I'm trying to write this program. I'm trying to build this. I'm trying to ascertain or analyze this. And if you don't have the proper data sources plugged in, you're not going to be able to make business decisions off of what comes out. I like that. I'm wondering in the world that we live in today, that there's this security and there's this need to hang on to your data.

7:16So if you have valuable data to hang on to that data, but yet in order to coexist in a world today, effectively, you've got to be able and to get productivity gains, you've got to be able to apply certain models and certain, you know, other data sets into your, into your rhythm. What are your I mean, think about like Crunchbase. Like if you would tell us just for our listeners, I'm sure they got it in the intro, but just tell us a little bit about like what Crunchbase is and and how you see that as like yours is very, very specific, the data. And a lot of people are probably thinking that they can go out and get that data in other ways.

8:01So talk to us. Correct. Correct. So the main reason I left Google after five years and joined Crunchbase in the first place was because of their data set. Like I knew data is the new gold and I knew that this is what is going to feed successful AI ventures for many, many years to come. So Crunchbase has done a very good job over the last 10, 15 years at building and focusing on private markets. We have more private market data from, you know, inception through, you know, Series K than anybody on the planet. And that being said, it's not just what the company is and who they do, who their competitors are, who their investors are, what is the rounds of funding that they have received, et cetera, et cetera.

8:49So you can really piece together and understand what is the trajectory of this company? Are they gaining momentum and are they on the upswing or are they not? And they're on the downswing. So I think that from an intelligence perspective, having all this data and our 80 million plus users of the software and being able to watch their digital body language that nobody else has access to has really enabled us to come out with a very unique position in the market, along with the fact that private markets are becoming increasingly more and more important because I think they're up to like 75 or 80 % of the NASDAQ market cap now.

9:30I mean, didn't Databricks just close a series K billion dollars? Like when in our history has a company ever done a private market round in a billion dollar level? Like it's, I've never seen it in my history. Yeah. You know? So I think from that aspect is, again, it's being consultative about what your data can do and what are the business outcomes it can drive. So when I'm talking to a head of sales or CRO and I'm saying, look, I can tell your sales team definitively which companies you guys should be going after for what you're selling versus the ones you should be staying away with. And that fact alone is what drives pipeline growth 2x in six months and drives top line revenue growth 25 % in that same six months.

10:23Because if you just know who to focus on and it's not all left to the rep or the SDR to figure out and read the tea leaves or whatever the AI is spitting out without any proprietary edge to it, it makes it very difficult. And I think that this is just the right sort of combination of AI technology as well as productivity play for sales organizations all along. Like I've been a student of sales for many, many years, as I've already mentioned. And I just don't think I've ever seen these things sort of come together in such a way before. Let's talk about the, Johnny and I talk a lot about expectation of the customer.

11:08that they expect us to be educated, regardless of whether they're public or private, they expect us to be educated. And the need to do that and the information that's out there is probably unlike ever that it's been in your 30 years in sales. It's the same for Johnny and I. So there's a high, high expectation. Just in general, talking about and to sellers, what are some of the tips that you would give that says minimally you would show up with this type of information about a customer? What are some of the minimum things that you would say are just table stakes? Oh, well, absolutely. Having done, you know, a quick little couple prompts or two to figure out, you know, where they're at in terms of priorities and what's listed in their K-1.

12:05That's still like the greatest resource for salespeople on publicly traded companies that's out there. But they're not going to read it all anymore. Come on, we're talking about salespeople. So the fact that at the tip of my finger, I can get, you know, sort of the printout of what it is, right? You know, research on the person and what they've done and what's important to them. So I think that from the just a basic couple prompts can give you a much better confidence level, you know, walking in. I, you know, we have the, you know, the SDR motion in our firm. So it's like mandatory that they listen to that.

12:45And of course, a lot of them are trying to shortcut it, which is give me an AI excerpt of that. But either way, showing up with this is what I understand, you know, what is missing? Is this accurate and what is missing? Right. Because I think the one thing that customers really demand more of is don't waste my time. I'm not going to repeat myself, you know. So you have to show that you have the consultative sales approach from the get-go to understand the problem, how your solution fits into and solves that problem, and what are the specific business outcomes and ROI that we're going to deliver on this for you.

13:25And I think when when sellers can be as succinct as that, that is what makes sales cycles go faster than anything. I talk a lot about to my team and all the teams I've managed is you are the driver of this, not the customer. So make sure you're in the driver's seat and you're not just being driven by them because they'll take you through all the windy roads and end up at a dead end. And what are you going to get for your time? The most valuable asset salespeople have is their time. If they're not diligent and smart about how they're using it, busy doesn't mean successful. Sorry. I like this. I'm just wondering, as I'm listening to you talk, I'm thinking about the value proposition that Crunchbase has.

14:15I have access to data. and you have a PLG motion that's going to an enterprise, like, do you, here's the feedback that I get from sellers. I don't want to have to go into 17 different sources to get access to information. I'd love a thought partner that can take some of the things that you're just saying to me about, you know, attaching the biggest business issue. What are my competitors, what are their competitors doing? What are some of their top initiatives? What are their top people talking about? Like, how do you think from a seller point of view, it's clear that we need the information and we have to be, you know, we have to demonstrate that we have that information to a customer.

15:04But man, there's so many different ways to get it. So what I hear you? I mean, I believe wholeheartedly that the foundation is going to be one of the big LLMs, whether you're using OpenAI and ChatGPT, you're using, you know, Grok and or you're using Claude or Gemini. right? And if you're outside the country, Manus AI or whatever, those are sort of the table stakes. So those companies are doing a great job at selling enterprise versions of it, right? So that is going to enable you, whatever size company you are, to mix your internal data with this without feeding their LLM or training their LLM.

15:47But you connect other sources like what we did here. We just launched a month ago our MCP server. It is absolutely insane what you can do. My people spent five minutes and built a daily rundown sheet that's going to connect to Gong. It's going to connect to Salesforce. It connects to our MCP. And it lets every sales rep know exactly what they have to do in that particular day because of what happened since they were last working. I love that. So a classic example of the data is the gold being the interface of giving it to the end user at the workflow level. That was not the big, you just wanted to make, you wanted to make it open or open is probably not the right word.

16:35It's called headless. Headless. So you want to make it headless so we can get into the workflow of the seller. Correct. because your sales motion has changed. Oh, absolutely. Absolutely. And it's only with the release of our MCP and we use ChatGPT as our, you know, corporate provider that we were able to say, okay, let's connect Salesforce. Let's connect this because it just brings the entire picture to your point of all the tools that an AE has to use in their stack. It doesn't matter if it's Gemini, Grok, ChatGPT, or some homegrown one on the front end. It doesn't matter. It's about how you seamlessly bring together the data sources through the AI interface to deliver real value.

17:25Ann Davis: And in these headless cases, and you talked originally about how data is gold. If I'm a data supplier or an older, let's say, SaaS product that has a bunch of data in it? How do I, in that environment, how do I prevent myself from being relegated to just a system of record? Yeah, that's a good question. I mean, I think you have to flip the mindset, and this is what we had to do here over the last 15 months, is we recognized early on, or I'd say Jagger and the executive team recognized early on before I joined that AI is probably going to come in and take a big piece of Crunchbase's business. So we have to anticipate that.

18:10And the best way to do that is to develop proprietary data sets that they can't replicate. But secondarily is around being able to support all the new solutions that come out. And that's really where you're growing your data distribution partnership strategy, right?

18:31Ann Davis: But you could still be relegated as a system of record in a headless environment. Yeah, you still save that role. All you're doing is opening up the data so that your internal AI systems can access it for the people within the organization that need to slice and dice that data. So, you know, Looker was probably a revolutionary BI tool, hence why Thomas Curian came a knock in and paid$2.6 billion on a$100 million run rate company. Not going to, you know, argue with those numbers. They bought my second house in Florida. But that being said is that that was light years ahead because it was about the data model and the semantic layer of how the data is managed and maintained.

19:23And so when you look at sort of AI, it's just, it's the analytical cherry on top where we were constantly struggling. You're constantly building dashboards, your team's building dashboards upon dashboards, but it was never fast enough to say, okay, show me X, Y, and Z over this period, blah, blah, blah, blah, where you could just natural language a question in and get like a board level ready image. out of it. Like that is like what is saving people millions upon millions of trillions of hours. Right.

20:02Ann Davis: To quickly play what if. Yeah, exactly. You can play what if. Right. And you can understand all that versus, I mean, I'm a big spreadsheet person. I love my Excel, as do most people in financial services. But at the end of the day, you know, when I've got people working for me that I'm starting on my old process and they're already giving me the answer. You're like, I got to acquiesce here. Yes. So it's fascinating to me to just tell us a little bit about like when you show up and you're going to go from a PLG to an enterprise motion, like what are some of the things that you have to contemplate on running a sales organization?

20:45Just tell us kind of like what you faced and what you did about it. Yeah, I mean, I am a very decisive person. I have done this. I've seen this movie. I know how it ends. I've done it seven prior times. Not to the level of having a company that had been established down another path and was making the turn. It was more of a startup sort of situation. But a couple times I had to shift where they were going. And I think, look, at the end of the day, you're only as good as the people that you have. And just being honest about the resources that are in the organization and who can make this change and who can't.

21:23And it's OK if you can't, because we're going to help you find a place that's right for you. Right. And I think that I don't want to lose track of that, that, you know, you're coming in and, you know, decimating a department. But at the reality of the day, we have numbers that we have to hit and I have to get there as fast as I can. So really giving everyone a period of time to either demonstrate they have the skill sets to make this type of move or they don't. And to be honest with you, 90 percent of the people tagged themselves out and said, I don't have enterprise selling in my DNA. I don't want to do that.

21:59I think I just want to go over here and find something else. And that's OK, too. So so I think it was a lot of restructuring very early on and very quickly. And, you know, putting people in place I have worked with in the past. I know exactly what they're going to deliver and how they're going to do it was important. I brought over five people from Google with me. So so I think that was an important thing. But now I'm at the stage where, OK, sales and we've got the flywheel starting to move in the new motion for the sales team. I got to get the rest of the executives aligned and in the same boat with us.

22:37Because a lot of people down to, you know, everyone in engineering or everyone in product or product marketing, they may not really understand fully the strategic direction in our North Star. So now I need to spend the time of bringing everybody up and making sure everybody knows where we're headed and what's important and what doesn't have as much value anymore. Yeah.

23:04Ann Davis: And who's the persona you're trying to get to, Anne? Is that the CRO? We have many personas. We have three ICPs and it's pretty much the financial services that runs the gamut of probably 20 different types of subcategories in financial services and the associated personas. We've got product builders. So we have a big amount of partnerships with AI companies and others that need our product embedded into their solution, not our proprietary data that's only offered on a BYOL basis to keep that sacred for us. and then the go-to-market teams. So yeah, that is a big segment. I would say probably the financial services angle and the go-to-market are our two biggest.

23:52But we talk a lot to RevOps leaders, people in sales enablement, because their job is to make it super easy for an AE. Like we laugh about, when I was at Google, I was managing a team of 10 sellers in the data and analytics space. And they literally would take five weeks, January into February before SCO to put together their territory plan. Five weeks, five weeks. I could feed in my book of business of 350 ,000 accounts and get a territory plan back in five minutes with Crunchbase. I go, I as a seller would pay out of pocket five grand for that because that just meant I got five weeks back of selling to the companies that it was directing me to.

24:42Ann Davis: Right. And I stayed away from the ones who wasn't because my company wasn't with it enough to provide this data for me. Yeah. It's a simple math equation. Yeah. Right. Yeah. It's so it's so crazy how and I'm just so fortunate that I get to like watch this. Like I laugh that this is my swan song and I'm done after this. But it's just to see this culminate at this stage is really exciting. And we talked a little bit about some of the things that you're seeing like with Crunchbase data. Like, for instance, I saw Crunchbase said that global venture funding was in the first half of 2026 was 510 billion, but OpenAI and Anthropic alone took close to 50 % of that.

25:29Ann Davis: So the question I have for you is, do you think that that makes the software market healthier? Or do you think it disguises a weakness like underneath the surface? Yeah, I think that whoever is in the software space needs to be figuring out what their data strategy is for their data. Because your point, John, you pointed out earlier on that like you're this system of record, you have all this important data, right? Doesn't mean it only has to be accessed through your software. You can have a way to license the data within that software application and have another revenue stream. So as your software may be declining on numbers of users, your data revenue associated could be on the rise because you're just going to be licensing it to enterprises for their AI front end.

26:28Ann Davis: Right. But do you think all that money moving towards open AI and Anthropic, do you think the software market overall is healthier or is there something brewing underneath the surface? Anyone in the SaaS software business that's not seeing a hit to their revenue from AI, I would be surprised. It's just a matter of how quickly they come up with what is their go-forward strategy. We hear two stories, really. We say SaaS is dead, and then AI is creating the biggest software opportunity in history. So which one is closest to the truth? Because now you're hearing sales apocalypse, and now you're saying, well, maybe SaaS is coming back.

27:13Ann Davis: So what do you I don't, yeah. I think the interface, when I'm talking about a SaaS provider, their interface, because we took a hit on ours and we continue to, which was anticipated, right? is I think that if they think that they are so important to the enterprise that they're never going to lose revenue on their user model or what have you, I think that is not accurate of them because I think AI will find a way to get into their business and steal from it irregardless. I'm just saying I would go in and recognize if that was me and say, okay, this data is really valuable to the enterprise. Let's find a way to license it to and get it provided to a lot more people.

28:01Companies will never buy enterprise licenses to anything normally because I've got 500 ,000 employees or I've got 200 ,000 employees. But if we bundle it up for X amount and it made sense and there's some usage component on top and it's like an MCP, you pay 40 cents a query or what have you, then there's another revenue stream that could save these companies. I think the ones that are burying their head in the sand and saying that, no, no, we're fine, we're fine, they're going to have issues. Because if you're not attached to an AI companies in some way, especially as a data provider, like we don't expect our AI to, I mean, excuse me, our SaaS software to live on.

28:41We've already got our MCP on the front end, and that's the new SaaS. Right. That's the new interface, which is, again, it's headless. You can use ours or you can use any one and just point it at it. I don't know if you guys have looked into at all what MCP is and what it does, but it is. When it's done right, it's a game changer. And when I say done right, it's got to be incorporated with natural language and it's got to be expert queries because those are just game changing things. We take a financial analyst that his job is to research new markets and new companies for them to invest in. They can do their whole job of a full week as research in probably 30 minutes.

29:27Ann Davis: Yeah. And so then you start to see, OK, what is all that going to lead to on the productivity side? If we can really get through this analysis this fast. But again, goes back to what's your data? What are all the data sources that are going into that? And that's where I think those internal company files and memos and emails and research and stuff, mixing it in with whatever other data sources is what makes this stuff is going to be the mission critical that's going to be very differentiating for customers and companies, quite frankly. Like we have our, you know, we call it, you know, predictions and insights, which I want to move away from that word because every financial services company or person you talk to says, well, that's our job.

30:13You know, we're in the job of prediction. So don't take that away from us. And so it's like we don't measure it based on accuracy. It's on precision and recall, like how much of everything did we find and how much did did we not? Right. So if we're calling 85 percent or 90 percent of the funding rounds two to six months in

30:34Ann Davis: advance and we're right 92%, that's a value add to someone whose job is to figure out what new markets and segments should we be investing in. Yeah, good point. And when you look at the crunch base data, what separates enterprise software companies that are getting funding versus companies that investors are saying no to? Can you see, derive any insights from that? Sadly, there's not very many hours left in my day to dive in and do all the research I want. So I don't really have a good perspective on that. But I think, you know, from the funding aspect, it's just it's lion's share to AIs. But, you know, like I said, 9 ,700, maybe over 10K now, AI companies have like popped up.

31:20We'll go into companies that say we know about 2000 of them. Who are the other eight and what are they in and what segments are they in and what subsegments of industries are they in and how much how much are they getting? Right. But it's also a lot to like following investors. You know, I want to see everything that they invested in and when. So it's pretty there. It's so broad. And we're finding use case risk management around like providing credit. Like, think about it. Remember back in the day, we always used to go. You have to have your DNS number. And, you know, Dun & Bradstreet was like the one that would say if you were creditworthy.

32:00They don't know these startups from Adam. How are they going to be able to give you any any accurate information about whether this company is creditworthy? Or we've had customers of ours that say, we're going to give different percentages or different packages of lending numbers to different people. Same thing as they would do with people with our credit score, but, you know, doing it on the company level. Like, it's just there's so many ways. Super exciting. Yeah. What about the PLG to enterprise journey? and we have CROs that, or even companies just like listening to us here. And some of the big things that when you looked at this opportunity, what are some things that you would look at to see whether or not a company is actually going to make, I mean, obviously we talked about data.

32:58If there's a good data source there and the data is gold, you got a great shot of it. what are some other things that you look at when you were analyzing whether or not this was going to be something that it was a fit for you or not? Yeah. I think first and foremost, it's always starts with the product or services that they have. And is this something like we talk in sales a lot about going and catching the next wave, right? Your career is made up of a series of waves. And when do you start to paddle out? And are you going to be there to catch the set and ride it, you know, all the way in? So I knew from my time at Google that this was the right time for me to make this type of move.

33:43Secondarily is what has the company done already to sort of anticipate how AI is going to, you know, enhance, hinder, steal from, add to, et cetera, in their business over the next five years? Like if they've done some sort of, you know, analysis or something to stand off. And then, you know, I think it's really important, like don't underestimate good old fashioned, you know, target addressable market, like understanding who you're selling to, why, what's the value proposition and what are the business outcomes? Like I came into a PLG is a lot of like feature function, like, oh, it can do this.

34:27It can do this. And I kept saying, OK, where's the value? What's the business outcome this is going to deliver for me? And they kept looking at me like I had three heads, but I must have said it a thousand times since I've been here. Because if everything in your messaging is not orientated around that, you're just wasting time. Like I'm not a time waster, very efficient, efficiency expert. So let's just get to it, right? So I think that those are all things to think of. And then you've got to look at the people, like the management team, you know, how leaning in are these people to do something new?

35:03How energized are they? Because it all falls downhill. So if you don't have an executive team that is gung-ho about driving what you're going to bring to the table, then it just makes it harder. You just run into extra roadblocks that you don't really need, right? We talked about the ICP. Definitely having a look at the ICP, you've mentioned now the messaging, which is critically important. The engagement model, I would think that this engagement model for Crunchbase has probably changed quite a bit. Like how does the buyer buy what we're selling? And how do we meet that buyer wherever they are in that process?

35:48Did you make major changes to that? What did it look like? Well, I think that we're definitely moving upstream into enterprise. And as most enterprise companies are putting together what their internal AI solutions for their employees are going to be, that's where we wanted to be, right, is more in the enterprise mix. I think Crunchbase was a lot heavier in definitely, there's not a financial services firm on the planet that doesn't know who Crunchbase is, but maybe the value prop is different now than it was. And they still know the old Crunchbase from 10 or 12 or 15 years ago, right? So the brand, let's not underestimate the value of the brand because having the brand is what I said is gonna be our secret sauce because we can easily go in and say, this is the new crunch base.

36:39But when you're trying to reach out to people you don't know and they don't even know your brand, that is so much harder. Like I always used to talk about how selling behind a Google name to get a meeting is so much easier than selling behind ABC that nobody knows, right? So that adds another level of complexity. And all this stuff factors into the exact sort of type of person, type of salesperson that you need in the organization. And I think that's something a lot of people don't understand. Like salespeople are not a dime a dozen and there are certain types of people. You need people that are used to working in ambiguity and changing things on the fly and creating things and having the creativity to put together new deal structures and different things that make sense because they're smart enough to do that.

37:30Right. Those are the people I want. I don't want the people that want like the playbook and the price list and they're just going to do the transaction because we're not in the transaction business anymore. But we can be and we can allow people to buy and access to the MCP right off the website, immediate connection, et cetera, et cetera. Click here and away you go. So it's about trying to figure out where your specific market is and what are those buying experience lanes that we have to create in how we structure the organization. What kind of impact does that have on a success profile for the seller?

38:08So you talked about ICP, talked about a value proposition, you talked about an engagement model changing the way the buyer buys changes, who's doing what, when in the organization has changed probably. Oh, yeah. And then like, is there anything that you could share with this that changed markedly on the success profile of the seller, like specific characteristics that have changed? Yeah, again, I think for me, it was finding people that are used to driving complex, potentially complicated sales cycle. AI is new to a lot of people. So understanding that. But it's also like good salespeople. We love a startup because we got an uncapped comp plan.

38:59And we want to come in and be rewarded for what we bring in the door. So, yeah, is there a little bit more risk because everything's not proven out? Yes, but it's also more opportunity and that you could just be at your local Publix and bump into somebody you hadn't seen for a while and, you know, get a sale. like it's it's you know it's about the amnesia of a leadership team sometimes which says well we paid our sdr type person this amount and you want to go pay x amount for enterprise like how how did how did you kind of three s what is it oh yeah at least three x means more or more oh yeah and and i think about the planning process with the cfo yeah i was just gonna say that was probably the hardest pill to swallow for the CFO, but I think he would have did a little AI research on his own and figured out what percentage range he needed to be in to make sure that I was coming in under that.

39:59But, you know, we are very fortunate in that we have multiple sort of revenue streams and our partnerships, you know, drive a lot. Like, not every deal is touched by everybody. So I think I was able to get him more comfortable with it in that, okay, direct sales is probably our most expensive channel, but they're going to be focused here. And this is what they're going to look like at 100 % or at 150%. But I'm going to get, you know, X percent of revenue from this stream over here. And this only costs us Y. So I think that that that was definitely dissecting that. That's falling back on my math skills.

40:45Yeah. What about the planning process that says, and I know you probably don't want to get too specific here, but how much are we going to be in the same motion that we had? And how much are we going to be in the enterprise motion? And by when I'm trying to think of CROs that are trying to figure out whether or not to join a company, you've given some really good indicators on what should be present there. Like they should have some thought of enterprise before you show up. But is there, you know, how do you negotiate that? Because companies get that wrong. They're like, you know, we're going to make a bet.

41:22We're going to make a bet. We're going to say all this is going to come. I mean, Johnny, I don't know what we saw in the last 10 years, but all SDRs were out, went all enterprise, hired a bunch of customer success people, fired the customer success people. Yeah, yeah. What advice do you have for people on the planning process of this? Yeah. Knock it over your keys. Yeah, exactly. I would say don't underestimate the time to close. So I can say without a reasonable doubt, because I just lived through this, that, you know, Crunchbase had lived a lot in, you know, what I'd call, you know, SMB corporate world.

42:03It's not that they didn't have enterprise customers. They did, but they didn't have hundreds of thousands of them, right? So it didn't define the motion, whereas the smaller group did. So making everyone on the executive team and the board crystal clear in that an SMB deal is going to take about three months. An enterprise deal is going to take 12 to 18. and our pipeline is a barren desert. So I need the runway to get to that. So even if I got, you know,$5 million in the pipeline in the next six months, it's not going to close for another, you know, 12 months. So just really making that crystal clear and then also defining and understanding the difference between demand fulfillment and demand generation.

42:58So this is critical because demand fulfillment is people are coming into us or we're talking to people and they're like, yes, we've got a budgeted project. We're going to get this done in three months. We're moving forward. And this is, you know, blah, blah, blah, blah, blah. Versus demand generation is we're going out and selling people on a story that we have crafted that's delivering real value for people saying, you want to get in on this, but they don't have a project. They don't have budget, that adds another six months plus onto an enterprise deal. So I think those two facts alone were what I insisted upon.

43:38I even talked to the board members that I interviewed with it about it. Like you got to be prepared that it's not going to happen overnight and it's going to take some time.

43:49Ann Davis: A lot of them say yes to that, but then they have a really hard time buying into it along the journey. So now it makes it nine months in, 12 months in and they're like, when is this going to happen? And you have to remind them. Oh, and it happens all the time. Why it takes so long. They have no idea why it takes so long. Exactly. But also to like, at least from the board members, like really how much time do they spend knowing your business? They're there for a quarterly meeting. They probably spend a couple hours a quarter. Right. So I just coffee. What? Yeah. Donuts and your coffee. Yeah. Yeah.

44:22So I try very hard to just reinforce a lot of my same, you know, messaging along the way. But again, obviously, I left a very comfortable, lucrative position to come here. And it was because I saw the opportunity. And I'm just a person that's going to make shit happen. What is the channel play? What are the discussions around? How much of this would we kind of drive through a channel and how much would we drive through direct selling at an enterprise customer level? Have you, is there some thinking behind that? How do you test it? Oh, there's a lot. Well, again, I think one of the first things I did when I came in was figuring out what all my revenue streams were.

45:11So I have about four that I've developed over the last year. Some are better than others. Some are less friction. Some are less people dependent. And I think for me that as being sort of the architect behind it without a lot of other resources understanding per se, what I'm doing has been nice for me because I can just drive and I don't have a lot of people in the car asking questions like, are we going to get there yet? Are we going to get there? No, no, we're not. But that must be your strong personality as well. Most companies would still ask. Yeah. Oh, yeah. They're still trying to ask, but I'm, you know, trying to figure out how to like, you know, and so it's like then you got to post something big.

46:02So we have some big announcements coming up that I think that the board will be very happy about. But that being said, you understand what the revenue streams are and what sort of energy and resources and effort needs to get them going. And for me, I started all four. And I'm starting to see there's definitely a clear winner in it. And there's one I got to adjust and change. And for me, it's about being decisive and taking action fast because there are so many people in this world that are willing to just say, oh, let's just give it till the end of the year. Like I'm making changes right now, announcing next week that are for the rest of the year because I'm not waiting for more months because I know it needs to get done.

46:49So what is it going to benefit me to wait? I need to do it now. So I definitely believe in, you know, just the decisive action, you know, of the CRO. And look, people follow you. They follow you or they don't. And I'm very fortunate enough that people buy my vision and they purchase my products. So I'm very fortunate that, you know, I have the skill sets that I have to drive this. But there's lots of people that do. And it's just, you can't let other people influence it. And I think that's really it is, again, fortunate enough to come into a company that was a PLG Motion and being one of the only enterprise people, you know, within it, at least when I started and just being like, this is what we have to do.

47:39Like, I've done this seven other times. Like, I know. Do you also wear your own RevOps hat or do you have a RevOps person? I do not have a RevOps person currently. I have worked through two. Neither have worked out. So I'm putting a pin in that position right now and am driving a lot directly with the controller and the CFO. But all joking aside, could you tell us some of the things that you would expect out of a position like that in order to help you? Because there's a lot of CROs or a lot of potential CROs that are listening, and there's a lot of discussion around RevOps, whether you are more analytical than most.

48:26And so you have that advantage. What are your thoughts on that? some advice to CROs as it comes to RevOps. Yeah, I think that, again, if you have like an AI type of front end on top of your Salesforce and your gong, you can do most of the analysis that you need to do. Because again, obviously, there's the devils in the details in terms of like cycle times and how long this these particular deals take and this, that and the other that that you want to provide the proof points to your CFO and your board and CEO as to why your strategy is working, right? So I think that that's one of the biggest areas I was looking for in the two RevOps people that I have hired and had to let go because they weren't doing it is that whole analysis, like help me understand the business and dissecting it and doing it or not.

49:25But fortunate enough, we've got MCP and I'm just plugging away and chat GPT and figuring out everything I need to support or prove wrong and make adjustments to it. Right. So I think we just depended on a person or a team of people to do that for us in the past. And we don't have to any longer. And, and you still can, if you have, if you can find, you know, good people that are, that are going to deliver that for you. But for me personally, especially as I just mentioned, being very decisive and making changes when needed and not waiting around, having the data behind it, again, very data-minded, it's got to support some of that if I've got other people I have to convince.

50:15Does that make sense? The thing about RevOps people is RevOps means different things to

50:20Ann Davis: different people and different companies. It's not well-defined between companies. Correct. So you have some people that have a background in sales or a background in tech or a background in finance. So they're limited in what they actually know. And then some companies, the person's in charge of the CRM system and maybe building some reports and forecasting reports. And other people are in charge of recruiting and onboarding and training and analysis of what's going on in the sales force. So it really differs. You got to be really careful when you talk to somebody that has a RevOps title, what is it that you actually do?

50:56Exactly. And that's why I always say, show me someone's resume and I'll show you what to expect from them because I wouldn't expect them to do anything vastly different than, than the things that they've done in their past. Right. Right. No, I think you're exactly right. I mean, we used to call RevOps sales ops. It was always sales ops. And then all of a sudden it's now RevOps. I go, why is it RevOps? What's different? Why is it? Yeah. No. And that's a great question for your CRO listeners to understand is what does RevOps in your actual organization do? It's just great now that there's so much more available at our fingertips to get deep into the data, which we never had before, ever.

51:39Put your prediction hat on or your crystal ball and tell us five years into the future, what does the role of an enterprise seller look like? I think the role of the enterprise seller is to still be the person to drive the value proposition, the business outcomes, and the ROI for their particular service or offering into the people that they're selling it to. I don't think we're going to get away from that because it's always about proving it along the way. When you're talking enterprise, I'm talking, $500 ,000 plus type deals. I'm not talking about a$5 ,000 deal. That can be completely automated, right?

52:32You don't need a seller for that. But true enterprise selling, because there's so much of the interconnected tissue at the company you're selling to that a seller is responsible for. I've got to bring all these people to the table in such a way and get everybody on the same page and moving in the same direction, get them in my boat and rowing in my direction. That I don't think is ever going to change at the enterprise level. Right.

53:00Ann Davis: Well said. Thank you, Ann Davis. Appreciate it. Thank you, John and Sean. Amazing. Great energy, Ann. Yeah. Yeah, you're really lacking a lot of energy, but I don't know if you're going to need a cup of coffee or something. I did not have coffee. And I won the over-under on whether or not you had a rev ops person. Yeah. I just had to let my second one go. It's not, not, we're not working out. That's a big brain. Somebody's got to tap into for you. Shit. Yeah. All good. Super, super fun. Really enjoyed the conversation guys. Whatever else you need from me, just let me know. Thank you, Ann Davis.

53:46Ann Davis: Thank you, John. Kathleen. And thanks to everyone for listening to another episode of the Revenue Builders Podcast. Thanks for listening to today's episode. If you enjoy the content, please subscribe, rate, and review the show to help us reach more people. This show is brought to you by Force Management, where we help companies improve sales performance, executing the growth strategy at the point of sale. Check out forcemanagement.com for more information.

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