Unbundling the Fintech Stack: Exploring Opportunities for Innovation

Randy Wootton (00:04):

Hello everybody. This is Randy Wootton, CEO of Maxio, and your host of SaaS Expert Voices, the podcast that brings the SaaS experts to you to help us understand where we are today and what's happening tomorrow. Today, I'm joined by a good friend of mine-

Brian Bell (00:18):

Hi.

Randy Wootton (00:19):

... Brian Bell. It's great to have you, Brian. Your background is so interesting in terms of starting off in finance, moving to product management, having exposure to big companies like Microsoft and Amazon, and then we had the good fortune of working together at Rocket Fuel. But then you took this really interesting turn to become an investor and focus in early stage startups, and so I think we're excited to chat with you about a lot of things, the world of finance, fintech, the office of the CFO, but I think it'd be really interesting if you could spend a little time talking about your journey, specifically that transition from operator, product manager to investor.

Brian Bell (00:57):

Thank you so much, Randy, for having me. It's good to see you again. Yeah, it's been a long journey. I think if I reflect, I grew up quite poor and worked full-time in college, worked really hard, got to Wall Street, got the CFA, the whole thing, and then I kind of washed out. I was like, "I don't like this." It was really disillusioning and had to take a long hard look in the mirror and be like, "Why am I here? What am I doing?" And washed out. I was teaching high school math actually in the Bronx of all places I was teaching.

Randy Wootton (01:24):

Oh, wow. When was this? Was this at the year-

Brian Bell (01:28):

2006, '07? Yeah.

Randy Wootton (01:29):

So after your financial analyst?

Brian Bell (01:31):

Yeah, after my little stint at Wall Street, and I just kind of started wandering around jobs. Some jobs I'd had for three days, three weeks, three months, and I would just keep trying things. And I remember I was really into music at the time, so I was interning at a music studio. I thought I'd be a sound engineer or something like that. I mean, I literally tried everything. I was doing BizOps at a design studio. I've literally wandered in and out of careers. I've done just about every kind of functional role you can do. It makes me kind of unemployable, but I think a good investor, and I kept asking myself this question, and anybody who knows me is tired of hearing this, but what would you do if you had $10 million in the bank? If you had $20 million in the bank, what would you do?

(02:18):

And that kind of guided me through the rest of my career, and it took me about 15 years to transition into being an early stage investor in startups, but I just kept pivoting into better and better things along the way. First, before I got into product, it was actually marketing demand gen. I thought after a little short stint in sales, I was like, you know what? I think marketing's the place to be. It's more scientific and fun. And after a few years of doing that at a couple startups, I realized that you have to change the product if you're going to change the outcome of the company. And so I pivoted into being a PM and I think Rocket Fuel is actually my second PM job. So I got warmed up before I came to Rocket Fuel. And then I remember way in over my head, I mean we had 30 PhDs on staff, very big data, 150 billion bid requests a day. Just lots of state-of-the-art AI, and big data systems. And I remember at night going home and spending two or three hours working through CS coursework, trying to just keep up.

(03:18):

And then, yeah, I always thought I'd climbed the ranks of products. So I got an MBA at Berkeley, and-

Randy Wootton (03:24):

I saw your case study on Rocket Fuel, proving that online advertising works. I mean, the fun thing about Rocket Fuel. So this, I joined in 2000 and, I guess it must have been 2012 to 2015, if that's right. No, that's when I was at Salesforce. I've been [inaudible 00:03:39]-

Brian Bell (03:38):

'15.

Randy Wootton (03:40):

... 2015.

Brian Bell (03:41):

[inaudible 00:03:41] somewhere there.

Randy Wootton (03:42):

And Rocket Fuel was real AI. I remember back then it was a lot of marketing companies that had marketing around AI, and that was the first Gen AI. Say a little bit more about that, your experience, I'm calling the first generation of AI predictive analytics, and we built all of those data centers and we had those 30 PhDs on staff. I mean, it was this enormous investment to be able to access the power of AI, which is absolutely transformed today in terms of generative AI. But maybe give a little background on your experience as a product manager at a real AI company.

Brian Bell (04:16):

Well, I think it was a lot of trying to figure out what our capabilities were, what our customers needed. And I remember at Rocket Fuel, I built quite a few things that nobody used. It was like, "This is a really good idea." And, "The customers are asking for this?"

(04:34):

"Yeah, we have so many people want this." And then so we'd go spend six months building out some new ad tech product, like Geo Audiences is one thing that I worked on where we take all the lat/long coordinates coming in on the bid requests, and then we'd create audiences based on where they were and space and time. And that was mildly successful. And they're like, "It'd be cool. What if we could go back and capture people at the Super Bowl last year?" I'm like, "Okay, we'll call that time machine." So we go build that. And of course, all these things struck out. We generated maybe a million of revenue, 500K of revenue. I learned a lot about, it's not just about the tech, but it's really about the customer needs and really understanding is this a problem that's pervasive with lots of friction that people will try to solve it twice a day every day and pay you for it to solve it and it's a really big pain point? Versus like, "Oh, this is really cool and we should build it."

Randy Wootton (05:32):

Yeah, it's the whole aspirin versus vitamin, the idea of product market fit. And as we transition to talk about your investment strategy, how have all these lessons learned, informed the type of companies you look to invest in? But okay, so at Rocket Fuel, I think one of the challenges with Rocket Fuel for me as well was we were so far out in front with the technology, so customers don't even really know what they want at that point. So I do think part of what you and the team are doing was we're doing these experiments, these fast twitch experiments to see what would stick. And so some of that, how do you think about the core horizon one products that are going to generate your revenue this year versus the horizon three, which are informing where the industry is going.

(06:13):

How do you think about that as a product manager and looking back on your success in terms of your allocation of headspace or allocation of effort in terms of the things you're building that customers want, that they're going to pay for you for today, versus those things that because you're so steeped in the specific industry and the problem set, you're on the horizon, you're helping define what's possible.

Brian Bell (06:38):

And I think that's right. I think that three horizon kind of approach makes a lot of sense. There's the stuff that you can do in the next six months, and then there's the stuff you can do in the next couple of years. And then there's kind of the long-term, multi-year kind of projects. And I think innovation's messy, right? You have ideas about what your customers want. What struck me when I joined Rocket Fuel as a PM, because I came from another startup that was much smaller. We had this roadmap and I'm like, "Okay, great. What kind of customer validation have we done?" I was like, "What are you talking about?"

"The product marketing people are telling us what to do."

"Okay, great. So who's telling them what to do?"

"Oh, the salespeople are telling them what to do."

(07:15):

"Okay, great." So the salespeople are talking to the customers and then they're telling the product marketing people who are telling us what to build. I think we should go probably just talk to the customers directly and watch them work in the product and figure out what their actual problems are. And so we have a lot of customer empathy and we can build the right things and get out of the building, as Steve Blank would say. I think a lot of it is that is figuring out what's the highest value, most pervasive pain that you can solve for your customer over those horizons. Because some things do take a sprint and sometimes they take-

Randy Wootton (07:51):

Years.

Brian Bell (07:51):

Yeah.

Randy Wootton (07:52):

That's great. Any other thoughts about Rocket Fuel? The thing that's mind-boggling to me is we had 23 data centers. We were processing bids in less than a 10th of a millisecond, meaning we were evaluating a bid opportunity and then we were determining not just which advertisers should bid, but how much they should bid at that point. And what I remember was we were able to demonstrate results that were three or four times better than just regular bid strategies run by agencies with media planners and buyers. And so it was a real example for me of the distinction between putting people out of jobs. So the terminator view of AI, versus if not the Jetsons, more of an augmented intelligence. We even changed our marketing to be about not artificial intelligence, but augmented intelligence and making media planning and buying smarter. And I think that revolution is what we're seeing today in generative AI where every function is having to use AI to make them better.

(08:53):

And if you're not practicing or playing with it, you're going to get disintermediated. Back when we were working in Rocket Fuel, it was such a big problem and you had to have these really smart people building the models for you to run it that we needed a whole team. I think it was another 30 people under Doug who were doing, they were acting as analysts on behalf of the clients. So you had this super powerful technology that had to be enabled with technology, excuse me, with people almost like a buffer between the technology and the client. But today in this new world of AI, you as a client or you as a media planner, you as a marketer are directly accessing the tools. So I don't know if you had any thoughts more about just the context of what it meant to use AI or the impact of AI back then versus then.

Brian Bell (09:41):

Yeah. Well, I think you see this play out throughout history, the Jevons paradox in economics, where there's automation that comes into an industry and they're like, "Oh my gosh, sky's falling. Everybody's going to lose their jobs. We're all going to just be sitting around doing drugs on the streets and everything's going to hell in a hand basket." And it turns out the sky's not falling. When you decrease the input costs in an industry, it actually paradoxically makes the demand for that good go up more than the decrease in the cost. And I think you saw this in ad tech over the last 20 years. It's bigger than ever, and it's gotten cheaper than ever to run and more efficient than ever. And I think we see this play out time and time again with technologies throughout the ages.

Randy Wootton (10:28):

Yeah, I think you're right. One of the stories I tell, so I joined online advertising. The funny story is I came out of business school and there were three business models that were making money in the internet at the time, porn, gambling and advertising, and-

Brian Bell (10:43):

Lot of funny stories.

Brian Bell (10:44):

... on the red rope. I've heard about this red rope area.

Randy Wootton (10:48):

Yeah.

Randy Wootton (10:49):

Totally. And so I got into advertising and at the time I think our TAM was about a billion bucks, and this was digital advertising and this was Avenue A at Quantum and I think TV TAM, I need to go look this up, but I think it was like $20 billion or something. It was huge compared to us.

Brian Bell (11:04):

Much bigger.

Randy Wootton (11:05):

And we never thought that we would ever compete with TV. And now digital advertising has surpassed TV in total TAM and the digital transformation has played out. But to your point, the TAM has continued to get bigger and just the innovation has continued at a faster and faster pace. It's just mind-boggling.

(11:24):

Well, great. Well that a little bit trip down memory lane and it was a lot of fun working with you there and then staying in touch and following your career since then and you've made this transition to Team Ignite. You want to maybe just bring us up to speed in terms of, okay, so you're trying to figure out what do you do if you have $10 million in the bank, you've tried all these different professions, but you end up coming back as an investor. What drove you to that and what is the thesis of Team Ignite versus some of the other folks that are in that early stage space?

Brian Bell (11:52):

Yeah, I mean easy to connect the dots looking backwards as Steve Jobs in his commencement address during the process, it's messy and you're like, "I don't know what I'm doing." And you're kind of pivoting around and flushing around. I went to another startup and headed up AI product at a company called Conversica and spent about a year there building a sales chatbot. It was one of those AI companies that didn't have much AI under the hood at the time, so we were skating to where the puck would be as they say. And we did build a bunch of AI that powered that product eventually. And then AWS called out of the blue, says, "Hey, you want to lead the AI category for us globally?" I'm like, "I don't know what that means, but yes, I'm in, let's talk." And first week on the job, I'm sitting in a room with Andy Jassy and he is like, "Whose project is this?" And I'm sitting over in the corner, it's like I'm five days in at Amazon. And like, "Me."

(12:45):

And so that project was called Optimist Prime internally, I don't even know if I'm supposed to say that. I guess it's like we've expired that project name, who cares? But it was a SageMaker Marketplace, the marketplace for machine learning models and algorithms. So the idea is let's monetize all these great models and algorithms sitting out there. Algorithmia was out there at the time, and I think they've since shut down, and Amazon always takes a very marketplace approach to things. So I launched that project for probably the hardest I've ever worked in my corporate career launching that. And then I was just completely dead in December, just hibernating after reinvent.

(13:27):

And then Microsoft called, Adam Lewis says, "Hey, can you come over and run some categories on marketplace for us?" And I was like, "Okay, that's another step up. Let's go." I was happy to stay at Amazon. And so I set up this team and we would basically recruit and scale startups for Microsoft, get them transactable in the agile marketplace, get them to co-sell, and basically invest money in them Azure credits dollars, programs, resources. And we set up a lot of the things that have made that a multi-billion dollar business now at Microsoft. And both the marketplaces are multi-billion dollar businesses now, at both of-

Randy Wootton (14:01):

Just coming back to the Amazon, you said something really interesting, and they're reputed to do this, and the people we know jointly work at Amazon talk about it as just complete customer obsession. And so if you think about the difference at Rocket Fuel where it was inside out and like, "Hey, we're just building stuff. We'll see how it works." How did Amazon as a very large company, maintain that laser focus on trying to do what's right for the customer? A lot of people talk about, well, they have super tight margins, so they got to constantly be innovating, but within really tight expense controls, which if you're at Rocket Fuel, we had more money than God at one point. We do it if we want. I think Microsoft also has that challenge. They have so much money, they're kind of bloated, but Amazon was able to retain that really scrappy, we got to be delivering value all the time. Can you maybe speak a little bit in terms of the difference between maybe Rocket Fuel, Amazon, and Microsoft's view of getting customer input?

Brian Bell (14:57):

Amazon's probably the best functioning large company on the planet in my opinion. They have lots of different cultural practices and ceremonies that Bezos has talked about, you can just search it on YouTube videos, and he was on the Lex Freeman podcast talking about the culture and some of the principles of Amazon. It felt like a really big high functioning startup. They start with the PR/FAQ of course. So you write the press release, how you're going to announce it, and you talk about the impact of the customer, what the customer pain point is? Problem you're solving, and that's the one pager. They call that the one pager. And then there's the six pager, which is the other five pages of FAQs. And you go work on these docs for weeks and you just iterate, iterate. You might have 30, 40 iterations of this document to try to crystallize what it is we're doing, for whom it is and how we're going to go about doing it.

(15:57):

And everybody starts a meeting by reading for 10 or 15 minutes the document, and then you have a discussion rather than, here, let me kill you with PowerPoint for an hour. And then everybody's just checking their email anyway. Silently, we're going to read and we're going to have a book report conversation on this. So it's just a very high functioning org. And then you juxtapose that with Microsoft, also a very high functioning org, but just in a different way. They just go about it in a different way. The analogy I like to use, and you'll appreciate this, it's like the Marines versus the Navy.

(16:31):

Amazon, they're like the Marines, they're on the beach, they're the first ones there. They're digging out the trenches. And Microsoft sees what's happening on the shore, but they're just kind of waiting for the right moment and gathering up all the aircraft carrier group and everything. But when they get there, they come with the full bundled force of their monopoly power and just overwhelm the competition. Look what's happening in the slack. Slack growth is flattened. Any market that Microsoft enters, basically, you're praying as a startup that you get acquired instead of competing with Microsoft.

Randy Wootton (17:04):

Yeah, I have a very good friend who just was recently acquired as a startup and he's like, wow, rung the bell, and now just rest and invest and figure out how to make it work. But it is interesting that Microsoft for, I think last week it was for a period of time more valuable than Apple. It popped higher. So whatever they're doing, they continue to do it well and incredible kudos to Satya for reinventing the company and along different dimensions. I think they're-

Brian Bell (17:32):

He's an amazing leader and seeing it from the inside, I was there for four years, just an incredible, empathetic, crystallizing leader that probably he'll go down as one of the best CEOs, I think.

Randy Wootton (17:48):

I agree. And very different than my experience of a lot of the other Microsoft executives when I was there. I described Microsoft as being a bit like Machiavelli's Prince when I was there. And I think when Satya came in or took over, he really changed things. And the people like you and I both know who've been there through that entire run of Gates, to Bomber, to Satya, talk about in three years, Satya was able to transform the culture.

Brian Bell (18:14):

I mean, managers are take 150 hours of training per year.

Randy Wootton (18:17):

Yeah.

Brian Bell (18:17):

I mean you're basically every week as a manager taking two or three hours of how to talk to people and how to empathize and how to coach, and it's just nonstop.

Randy Wootton (18:30):

The luxury. But at that, what's super interesting, I think this is where you were going is you were acting as an internal incubator at Microsoft helping to recruit and get startups up and going. And so maybe where we are with our interview is, maybe talk a little bit about what were the lessons learned from that experience in terms of looking for startups to help incubate that you've taken to Team Ignite? Because I know you have a very specific criteria that you've use as you're filtering opportunities, and I think the audience would love to hear more about what you developed at Microsoft, how you've evolved that into Team Ignite and what will shift into what are you seeing that's working or not working with the companies that you're evaluating these days.

Brian Bell (19:13):

Yeah, I think a lot of investing is pattern recognition. It's just heuristics, it's at bats, it's kind of like a golf swing or a basketball shot. I play basketball. I got a game tonight actually, still playing too old for it.

(19:28):

So I was lucky enough to have a job where our job, the team's mission was to figure out what startups to work with and invest in them and help them grow. So we did that with hundreds of companies, closed lots of seven and eight figure deals, and we had to prioritize the entire SaaS universe and then create a tier system. These are tier one, these are tier two, these are tier three, here's what you get if you're a tier two. And then seeing which companies succeed and fail was very enlightening as well where you're like, "Oh, I really like the startup." And then you're working with them and they're not growing. You're like, "What's going on?" And you start to identify patterns of failure or success. And around that same time, I have all the Microsoft Equity money coming in. They gave me a pretty good package, and that stock tripled while I was there, so I'm getting all this money coming in. So it was just coming right out of my Fidelity account going into venture funds and syndicated deals and some direct investments. And I did that for a couple of years and I realized I was having more fun investing and talking to founders than I was running a team at Microsoft.

(20:39):

And so it's just another like, "Oh, there's something better." Right? I've been pivoting my entire career. So it's just, oh, it's just another pivot.

(20:47):

And so I actually helped a friend of mine raise a fund, and I spent probably two or three months trying to figure out could I get a job in venture? Will somebody give me a job? And they're not forthcoming. It's very hard to get a job in venture. You basically have to come out of Harvard more or less, or Stanford. So I was like, "Okay, I guess I got to start my own thing." And that was Team Ignite. And initially it was a syndicate, which means it's a pool of investors, a group of investors that ignite startups. That's why we called it Team Ignite. Our vision was to have the LPs helping in any way, shape or form they can. And we grew that to a couple thousand people in the network, did about 50 investments and had about a 3x markup overall. And the rest is history. We just kind of snowballed that into more and more investment vehicles, and that's kind of how I made the transition.

Randy Wootton (21:39):

That's awesome. And so just going back to that pattern matching, so now, what would you say are the patterns of success and patterns of failure that you identified for startups?

Brian Bell (21:49):

It's funny. I've been talking to some VC friends of mine about this on my podcast and just privately, I said something funny to pretty well-known VC yesterday. I go, "I know it when I see it." He goes, "Yeah, that's the best answer I've ever heard." Because it is a pattern recognition kind of thing. I'm looking at 500 startups to potentially invest in every month.

Randy Wootton (22:13):

500 a month?

Brian Bell (22:15):

Yeah, 500 a month, at least, maybe more. At least 10 to 20 a day. Call it six, seven days a week and probably more. That's just a rough estimate.

Randy Wootton (22:23):

And what are you getting in terms, I mean, that takes an enormous amount of time. Are you using AI tools to-

Brian Bell (22:28):

No, that's probably 500 minutes a month. It's probably a minute per startup to decide whether-

Randy Wootton (22:34):

Holy smokes!

Brian Bell (22:35):

Yeah, it's about a minute, that's all it takes. I have about six questions I ask them and then I look at their deck and sometimes a demo and I can do that within a minute or two, and then it's just like you know within a minute or two, whether or not you want to meet them, and then you go spend 30 minutes with them. You get the pitch, you get the demo, you ask some questions, and you kind of know with 95% surety after the first call, whether or not you want to invest, and then you go do due diligence and you just make sure everything checks out and then you wire the check. Now, that's a certain strategy.

(23:07):

Some VCs will disparage it and call it a spray and pray strategy, but it's actually hard work to go invest in, call it 50 companies a year about a company per week. That's hard work. That's harder than investing one company a quarter. It's just more work. You just have to keep tabs on more startups and just work harder. It's easy to go invest in one company a quarter and sit on a board.

Randy Wootton (23:30):

Help me understand, are you willing to share the six questions that you ask?

Brian Bell (23:34):

Yeah, it's actually publicly facing. Let me pull it up here. It's basically-

Randy Wootton (23:40):

You have a substack where you're publishing. You also have your own podcast, and so if people find out more about your strategy or even early stage founders are looking for an investment, there's lots of ways to find you and how you think about the world.

Brian Bell (23:56):

Yeah, teamignite.ventures, there's a pitch us link there on my LinkedIn. There's a pitch us link on there, and it basically takes you to these questions. What problem are you solving? Describe the product. Why are you building this? Why are you the right team to build this? How's your traction? How are your revenues trending month over month for the last six months? How do you acquire customers? What's the LTV and CAC? What's your funding history? That's really important. Because sometimes you get a company that burned $5 million to generate $250K of revenue. That's not a really good burn, multiple. How much is committed in this round? How much is left? Who's in the round? That's important to know because we can't be first check in and extend your runway for a month. We're a small check, so we have to [inaudible 00:24:41] at a mid round. Demo link and a pitch deck, and that's all it takes to basically do the front-end screening of a startup, in my opinion. There are other questions you can ask. There's lots of variations that other investors use, but that's what I use.

Randy Wootton (24:55):

And then just being Maxio, we care a lot about operating metrics. So when you said LTV and CAC, I'm like, "Ding." Are there other metrics that you look at specifically? And it maybe you're so early that there isn't a lot in terms of gross retention or net retention, but where I focus in my sort of pattern matching is, that's series B, series C, you have a product market fit, you've got a replicable sales motion that should be taking off. You've got customer base that you're hoping that's going to continue to renew, and so that gross retention and net retention, are there other metrics for your investment asset class that you're looking at that you would encourage people to really represent?

Brian Bell (25:37):

Yeah, so I'm investing in the pre-seed and seed. These are early companies. They usually have a $100K of ARR up to about a million or two. And so at this early stage, you're not looking at rule of 40. You might be looking at in a series B situation. I'm not as concerned on CAC payback, although it should be a lot better than it is at series B. Your CAC only goes up over time. I don't think you get better at acquiring customers. So you're kind of looking for, wow, your average sales price is call it $1,000 a year, and you could acquire customers for $100 and you're growing 50% a month. I mean, take my money. This looks amazing. Versus like, "Oh, you're growing 5% a month. You have five months of runway. You spent $3 million to get to 300K of ARR." I don't think you have product market fit here. It sounds facetious, but being an early stage investor, it's like you're just looking for that one or two deals a month that are easy yeses. And so it's like an 80/20 rule. 80% are easy nos, and then you have this 20%, and then in the 20% there's lots of maybes and I don't know, I got to squint a little bit, and then maybe there's another 80/20 within that 20 of where there's just like an easy yes.

(26:57):

It's just like, oh yeah, this all checks out. The team looks amazing. It's a huge problem with lots of friction. It seems like the right time for this. You couldn't do this five or 10 years ago. It's a B2B SaaS, so it's 90% on the margin. There's no crazy interesting hidden cogs in there. The product demo looks amazing. This is better than I could ever build it in all my product years. I built a lot of crap in my day. Something's in market with traction growing. There's some sort of system of record, a moat, an unfair advantage and fair terms. It's not like a 50 cap pre-launch, pre-revenue. It's a lot of repetition. I run into angels. They're like, "I'm going to go make my own investments." And I'm like, "Okay, great. Are you working on this 60, 70 hours a week like I am?" Are you investing in 100 companies over the next three years? Because that what it takes. There's a highly risky asset class, and you have to have the right strategy and work at it.

Randy Wootton (28:00):

I think my challenge as an operator is always I fall in love with companies. The ones I look at like, "Oh, I could fix that." And I think as an investor, you're on the other side where you're just saying no, and-

Brian Bell (28:14):

I have to say no so much. I have to say no to marginal things where I'm like... I mean, people we know, mutual friends that are raising friends and family rounds. I'm like, I don't invest pre-launch/pre-revenue. And then six months later I'm like, "Hey, how's your startup?" I'm like, "Oh, yeah, we shut it down." I'm like, yeah, I would've burned that money.

Randy Wootton (28:29):

Can you say a little bit more, again, we were really focused on B2B SaaS. You said something interesting around you look and like B2B SaaS on the margin versus hidden costs. What do you mean by that?

Brian Bell (28:42):

Well, sometimes you have tech-enabled businesses versus actual tech businesses.

Randy Wootton (28:47):

Like tech-enabled services.

Brian Bell (28:50):

Fundamentally, you have something that... And you can have amazing tech enabled businesses. Uber is a tech enabled taxi cab company. Pretty amazing. A hundred-billion-dollar company. And so they can exist and generate high margins, but historically, B2B SaaS has been, and I include fintech in there, fintech SaaS has been the best. That's why venture capital exists, right?

Randy Wootton (29:14):

Right.

Brian Bell (29:15):

Is to scale these software companies. Now, historically, I guess you could argue there's silicon and stuff like that. But, yeah.

Randy Wootton (29:22):

Sorry. And so when you're talking about the margin, in this case, you're really talking about the gross margin, the fact that you can build a company ideally 80%, 85% gross margin, and you have the operating costs roll out after that, but then you're trending in a lot of profit because you have a high gross margin versus a tech-enabled service or an agency where your gross margins are down in the 15% to 20%. You can still eke out a business, but your profit, your EBITDA is going to be five to 10%, because you just don't have that much margin left to use across your OpEx. Is that basically what you're arguing?

Brian Bell (29:59):

That's it. Yeah. I mean, multi-tenant SaaS, right? Spitting up the end customer is practically free. That's what you're looking for. It's infinitely scalable. So once you have product market fit, our best companies don't need our help, and they're growing so fast that they need to raise money just to kind of keep the lights on, hire the people needed to service those customers and acquire more.

Randy Wootton (30:26):

I think that idea of going through those stages of getting product market fit, and then the stage that I'm most interested in is that expansion growth, and then you start to move into the scale. So how do you start to take advantage of the foundation? You have to get to some level of scale, and then you are starting to get real leverage out of your investments over time that then chop down to the EBITDA and you can grow profitably. And that is one of the big themes I think over the last two years we've seen is the growth at all costs versus efficient growth, rule of 40 in the world that I operate in is one of those indicators that you're tracking in the right direction. The other one is CAC ratio, which you were alluding to a little bit. How much are you spending to acquire every new dollar of ARR? Interesting, we're just on different ends of that bridge between the pre-revenue and the expansion growth.

(31:19):

Can you say a little bit as we, last couple of minutes, we're focused mostly on the office of the CFO fintech, the finance function. You've had a background in finance and you focus in this area. What are some of the trends that you're seeing in terms of the unlocking of the office of the CFO via technology or anything else that from your background and experience you would offer for people that might be in that role or that function?

Brian Bell (31:45):

Well, I think as an investor, what you look at is you want to figure out what part of the cycle you're in on bundling versus unbundling, right? And that's a James Barksdale paraphrasing. You only make money by bundling and unbundling. So you are looking at different parts of the market and trying to figure out where they're bundling and where they're unbundling. Right now in Africa, they're bundling. They're trying to figure out the platforms to solve the credit gap and build people's credit and underwrite loans. And so we're in some companies there that are bundling all that together. That's a bundling strategy. In the US, we're kind of more on the tail end of the unbundle, where you're seeing new verticalized SaaS fintechs that are founded to unbundle certain sectors of the fintech stack. So we have a company called B Generous, where they're basically building a neobank for nonprofits, which is an underserved verticalized fintech market, where they're underbanked by the banking institutions.

(32:51):

They have no loan programs that are especially suited to them. And he was on the podcast a couple of times already, and they're growing super fast doing this new loan program. And one of their offerings is a donate now pay later model, kind of like Klarna, where you can donate upfront to the nonprofit and pay over time. And nonprofits love that. They get their money upfront. Donators love it because they can donate more money and get perks and notoriety or swag or whatever. And so it's just like, that's another example. There's lots of long tail examples we’re in another neobank that's serving multifamily property owners, which historically you think like, oh, well, you just go down to your local bank, but they just don't have the size and scale at that regional level to properly serve a multifamily portfolio holder. So that's the kind of stuff you look at is how can you unbundle it or bundle the market.

Randy Wootton (33:49):

And so maybe then to that point, we were both in MarTech and sales tech. There are 10,000 vendors in MarTech. And I think part of the challenge is that, so that would be a theme of unbundling. What are the point solutions that you have to use? And I think the challenge is it's been overcapitalized, there are too many solutions and people, especially when times get tough, marketers start to do the, is it a must have, nice to have? And they start cutting stuff and the stuff that gets cut if it's valuable gets rolled into a bundled package. And so you start to see consolidation. I think one of the things that's been interesting in the office of the CFO is the unbundling that's happening right now. I was just grabbing this document, I was just looking at this today from Pipers Jeffrey that was talking about the evolution of the office of CFO went from spreadsheets to point solutions to, then you started to have native apps leveraging data integrations to connect to point solutions. So you have that unbundling and you have that connection.

(34:46):

And really what's interesting right now is we have this broad disruption that's requiring CFOs to rebundle financial apps and the AI and layering on top is an intelligent layer taking account all the data across these technologies. And so it is very interesting to think about what are the big guys out there going to do in fintech, the Oracles of the world that bought NetSuite, Sage who bought Intacct, Intuit, what they're doing in their marketplace, and is there room still to what you're describing as kind of thin slice, find an opportunity, either a segment or a specific capability that you can unbundle, create value for folks? Because ultimately 80% of all softwares companies get bought. So you're doing for some period of time until you get hoovered up by the big guys.

Brian Bell (35:37):

Exactly. Yeah. And I think it's a strategy where every platform shift that comes along enables new ways of doing things. And so AI is obviously definitely unlocking as it did 10 years ago. It unlocks a lot of different neobanking kind of verticals, like you have the SoFis of the world and things like that, where they had a different kind of slant on how to underwrite loans. I think generative AI, you're seeing lots of fintech use cases where they're redesigning the entire company around the AI, so it's as big as the internet I think. It just changes the way you can do things. And so now I'm seeing companies now where they're... I have a portfolio company, it's not quite fintech, it's more like data tech, but they're using AI to disrupt CoStar, which is a big conglomerate of real estate data. CoStar historically has had an army of 1500 people just calling around, getting data, just calling around, getting data, getting faxes, getting emails, and this company's like, "Well, I think we could just use AI to do that." And just redesign the entire operation of the company and just do it at a 10th of the cost.

Randy Wootton (36:54):

Yeah, I think that it's interesting. There are at least three ways to think about this revolution in AI. One is what we were talking about a little bit earlier, as a function, what are you doing differently leveraging the tools? So as a marketer, how are you doing marketing differently? You're just going to have to do that. I think there's this other area that you're pointing to, which is a company is if you are a system of record and have real data, how do you incorporate AI and to make sense of the data, the structured and unstructured data, so that you can move from just workflow automation to being an intelligence engine? If you don't have that, someone else is going to do it. And I think to that point, data is the new oil people describe it. You've got to get super clear in terms of what your data play is, your data strategy, and then what is your intelligence strategy that you layer on top of that.

(37:43):

And if you're not starting with data first, you're going to get screwed. If you don't have a core capability around that. And so we have $15 billion of billing and invoicing data that's flowing across our platform, and we've released our Maxio Institute growth report for the fourth time and are able to talk about what's happening broadly across our 2,300 customer base. It's all anonymous, but that data being aggregated, sliced, then can be an input to an AI system that then can make recommendations in terms of not just providing benchmark data, but literally recommendations for how you would optimize different metrics. So LTV, CAC, et cetera. It's going to take us a long time to get there. It's a capability we don't have as a company. We could go hire those data scientists that we had at Rocket Fuel. We got to go build the systems and processes. But I do think to your point, that platform AI is forcing everyone to rethink what their core capabilities are and should be and how they're going to play in a world that's AI. AI used to be on the periphery, now it's at the core.

Brian Bell (38:43):

Yeah. I had somebody on my podcast who's a VP of engineering, and we're having this discussion on, are there technological moats anymore?

(38:54):

Can you actually build a technological moat anymore with generative AI when you can literally go talk to a computer and start generating code and a 10x engineer becomes 100x engineer? I think what you're going to see is AI is eating software generating ever more software, and you're going to see the revenue per employee go up. I'd love to see that in the data if you guys have that as revenue per FTE. I'm seeing startups that have a million of revenue and no employees, maybe a handful of contractors, just two founders.

Randy Wootton (39:24):

Oh my gosh.

Brian Bell (39:24):

And they're using AI to automate everything and generate everything. And so I was placing a bet with a fellow VC of mine is when will we see the first Fortune 500 company with only e-staff? We will see that at some point. It'll just be like the 10 or so functional heads of the organization and everything else is AI underneath and maybe some contractors.

Randy Wootton (39:50):

That is a-

Brian Bell (39:50):

Maybe five years, maybe it's 10 years, maybe it's 15, but it will happen. We'll see a $5 billion company, I think that's roughly the entry point for Fortune 500, without any staff. And it's a really radical time and human evolution where we will now be able to spin up the resources. Because AI is getting 10x better every year. The model runs and the complexity of the models, the price performance of the computation, all that's feeding into each other to generate more software, software that solves our problems at an ever-increasing alarming rate. So pretty exciting.

Randy Wootton (40:31):

Exciting, but also terrifying. And I think if you're a young person starting in your journey, in your career and you don't have the time, the opportunity to do what you did, which is go mill about for a bit, explore this, explore that, because companies don't need you because they have AI doing those early stage career type roles like product manager of X product manager of Y or PMM. And look, I'm old, so I'm ready to go retire and ride my horses and-

Brian Bell (41:00):

How much older than I am.

Randy Wootton (41:04):

What do you offer as hope or other than... I mean, most of our audience is going to be those early stage people that may have the e-staff powered by AI because they are the founders and they're technologically oriented and they're going to unlock problems and deploy this technology. But for the rest of us, I was an English major. Right? What do you tell the English majors of the world in terms of how they're going to be able to build a career?

Brian Bell (41:27):

Yeah. I don't know. It's probably talking to somebody that was working on a farm and trying to explain to them what they're going to do when we don't work on farms anymore. 200 years ago, virtually all of us were involved, 90% of us plus were involved in food production. Maybe there's 80% something like that. And now it's like 1% of us. And so I think it's trying to talk to somebody on a farm and trying to explain the jobs that will exist in the year 2024, and be like, "Yeah, we'll have this thing called YouTube and you'll be able to create videos and content on it and get paid for it."

“Well, what do you mean? Like a play?" They wouldn't even get it. Right? Who's going to pay to make a play?

Randy Wootton (42:08):

Wow. Well-

Brian Bell (42:09):

There's somebody called Mr. Beast, and what he does is he creates videos, hear me out. They do crazy things like crash cars, million-dollar cars into fire trucks and stuff, and he makes $10 million a video. You couldn't even explain it to them. And so that's why they call that the singularity, I think. That phrase, and I'd recommend anybody read that book, Singularity Is Near, it changed my life. We just can't imagine what life looks like after AI is sufficiently advanced. It's a singularity. We just don't know. Right?

Randy Wootton (42:45):

Yeah. Yeah. Well, Brian, well, on that note, wow, what a great conversation. Really enjoyed catching up. Learn something from you every time we chat, and appreciate you making some time for us today.

Brian Bell (42:55):

Yeah, likewise. Great catching up. Thanks for having me.