How Crossbeam Reached 17,000 Companies After Bob Moore Sold Stitch for $60M (Interview with CEO Bob Moore)

Event Context and Introduction

Nathan Latka

00:00Quick context. This was recorded March twenty eighth and twenty ninth. So a couple weeks ago at my live event, saasopen.com. We had a thousand software CEOs there. If you missed it, we hope to see at the next one, September fifth and sixth in New York City, sasopen.com. But for now, let's jump into the recording.

Bob Moore

00:18>> We started progressively missing the numbers worse and worse. So if you can't beat them, join them. And in twenty months, we got to as many paying customers as it took us eight years. Hey,

Nathan Latka

00:32folks. If we haven't met yet, my name is Nathan Latka. I launched and sold my first software company back in 2015 and went on to write a book about it, which you guys made a Wall Street Journal bestseller purchasing over 30,000 copies. Thank you so much for that. After the book, I launched this show and one went on to create founderpath.com. I raised a large fund to do non dilutive deals with b to b software founders.

00:59So far, we've invested in over 400 software founders totaling a $150,000,000. Here in 2024, we're doing three to four new deals per week. So if you're looking for capital and don't wanna give up equity, go sign up at founderpath.com for free to get your offer. Alright. Let's jump into the interview.

Nathan Latka Introduces Himself and Founderpath

Bob Moore

01:18>> Appreciate it. Okay. Thank you. Hey, everybody. I know we're in, like, the part of the afternoon where it's nap time. So hopefully, we'll be able to keep everybody pretty entertained and engaged for this one. I love talking about this topic. Currently, I'm the CEO of Crossbeam. We'll kinda get to a little bit of the Crossbeam story, but that's not what most of this talk is about. Most of this is about my first SaaS company, which is

Bob Moore Takes the Stage at SaaS Open

Bob Moore

01:44>> a business called RJMetrix, which I started back in 2008. And just the incredible ride that we had there and how ultimately, I think a series of decisions led to us missing out on what was probably a 2 to $3,000,000,000 market opportunity. So first of all, I just wanna acknowledge. Right? Like, there's there's some lights at the end of the tunnel as you look out at the market compared to, say, six months ago or twelve months ago.

02:09>> But by and large, I think something thematically that you're probably hearing over and over again today is that there is a bit of the tail end of a SaaSpocalypse going on where it has just been significantly more difficult to sell, to generate leads, to convert, to function in a ROI positive cash efficient way than it was eighteen months ago, twenty four months ago, etcetera. And part of the reason why I like talking about the RJ metric

02:36>> story is because I've kinda seen this movie before. And there are some moments in that story that remind me a lot of this moment that many founders are finding themselves in in this market right now. So let's hop in the time machine. We go back to 2008. I am wearing cargo khaki shorts among other things. That's me on the left and my cofounder Jake Stein. He and I worked at Insight Venture Partners, is now known as

03:00>> Insight Partners, which is an awesome investor up in New York. We were junior junior junior employees, basically cold callers on the investment team. And a side effect of being do that job for a few years is we just got to meet a whole lot of companies and see what kind of needs they had. And we identified what we thought was a really cool idea, which was let's bring this idea of business intelligence, which at the time

03:24>> was dominated by on premise physically installed software into the cloud, into this cloud movement that was happening. And they didn't even have SaaS as a popularized term yet. Things were called ASPs or application service providers, I think. I don't know if anybody remembers that era. But we decided to quit our jobs and launch this thing that basically followed the paradigm in the bottom right there. It's gonna do three things. It's gonna suck all the data out

03:50>> of your databases where it's really difficult to to query and it's sitting in your production systems. It's gonna store it in this centralized data warehouse that we host and we maintain so that you can run analytical queries on it. And then we're gonna give you this awesome reporting platform on the front end where you can build dashboards and charts, etcetera. So we stood up and we quit our jobs on a Friday in September 2008. And on

Bootstrapping Through the Financial Crisis

Bob Moore

04:14>> Saturday, Lehman Brothers collapsed. And we found ourselves out in this market where we had planned to raise venture dollars. We'd come out of a venture fund. We thought at least, hey, maybe the fund that we were working for would back us. We got nothing. And we looked at our bank accounts and we said, let's attempt to bootstrap this thing. And that's precisely what we did for the first several years of the business. We were kind of

04:36>> the tortoise in the tortoise of the hare story. Right? Like, we had some market pool, but we kind of were early to the market. And we iterated our way through just revenue driven growth, this glorious era of bootstrapping where we were able to kind of march along to get to our first several million dollars of ARR, mainly just through adding another customer, adding more dollars, using that to hire, and creating that cycle. And by 2011, the

05:03>> market started to wake up, and we found that we were actually in a much cleaner place of product market fit. Like, the market was actually looking for and actively seeking out analytics tools like these, and we found this really awesome sweet spot. Of course, when the market wakes up on a category, if we were the tortoise, there were a bunch of hares as well. So what we saw, we raised about $25,000,000 in that, you know, 2011

05:26>> to $20.14 range. In that same era, a whole universe of other players directly in our space were raising an order of magnitude larger capital. You've got at least three companies here that raised at least $100,000,000 to do precisely what we were doing. Domo in particular on the right was just raising as much money as they wanted at any given time. Josh James, the founder of Omniture, founded Domo and had a blank check from a lot of

05:50>> VC firms. So we found ourselves out in this market where there were a lot more dollars, a lot more competition. And while the market was blooming, it wasn't blooming as fast as the dollars going into it were.

06:02>> And then something else happened that ended up being even more important than all that, which is Amazon Web Services launched this product called Redshift. Amazon Redshift was the first player in the large cloud based scalable data warehouse market. It was great. Remember I mentioned that little middle circle in our product stack where all the data got stored and we would host it for you, and it's where you could run all the queries efficiently? This thing was

Amazon Redshift Disrupts the Middle of the Stack

Bob Moore

06:26>> like that only, no lie, a 100 times better. We had forked my SQL and built all kinds of bells and whistles on it. This was like a completely re envisioned, replatformed way for people to analyze their data. And it was better than that chunk of our product. So it created this really interesting paradigm shift where the middle part of the stack died for us. And a whole new market of products like Redshift, like Snowflake, like Google

06:54>> released a product called BigQuery, Microsoft has an offering in this area, came along and just changed where people physically wanted to store their data. And once people replatform their data into those data warehouses, well, a whole host of other companies came along that could sit right on top of those data warehouses, provide the charts, provide the dashboards, provide the data modeling, and not have to worry about all the hard stuff on the infrastructure side. So meanwhile,

07:18>> we're still doing all three. We really have to solve these three big technical problems, but we know our middle piece is not gonna win. And right under our noses, we were watching this new thing emerge known as the modern data stack. And this movement, I didn't realize it at the time. It was happening in analytics, but it was happening everywhere. It was happening in marketing and sales tech, happening in HR tech, happening in cybersecurity, happening across

The Modern Data Stack and TAM Collapse

Bob Moore

07:40>> all these different categories where the emergence of not just the cloud, but also the API economy, the extreme ease with which you can build interoperable products, was basically taking the world into this massive unbundling cycle where you used to buy this one kind of monolithic solution that was a sweet solution. Now the better move, the preferred move was that you buy your software in stacks, and those stacks are interoperable with one another. And what happened as

08:07>> a result of this movement is that we just saw our TAM get completely crushed at RJMetrix. Because on one side, all this money is pouring in to companies that are doing exactly what we are doing, which is making it really, really hard to scale in an economically efficient way. But on the other side, nobody even wants that stuff. They don't want it from us. They don't want it from GoodData. They don't want it from Burst. They

08:28>> don't want it from Domo. That market kind of stinks because there's been a shift in how people buy software that we don't actually line up with. So we're getting crushed in the middle here. And the way I always like to talk about this is founders are constantly on the hunt for product market fit. Product market fit is the thing, the buzzword that you will hear all the time. And very often, founders think about this like, Okay,

08:50>> the market is what the market is. And I don't control it. And it's kind of in one spot. And then where I have power and influence as a founder is my product. And I can modify my product. I can pivot. I can iterate. I can AB test. I can run the build measure learn cycle from the lean startup, and I can weave my way in until my product is overlapping with the market really solidly. And that

09:13>> may be true to a point. And many markets steer like the Titanic where products can be iterated on relatively rapidly. But I think what happens that a lot of people don't appreciate is particularly in the markets that many of us operate in, and AI is a great paradigm to look at around this, the speed with which markets actually are moving as well is really, really underappreciated. So while you are pivoting your way to product market fit,

09:37>> don't lose sight of the fact that the market itself is also drifting. And that's precisely what happened at RJ. You get this perfect, like, Goldilocks set of circumstances where we entered that market in 2008 early, And we had to bootstrap for a while. The market was not quite ready for the product. We had to have a really, really niche universe of buyers. And then we had this glorious window of product market fit. And as much as

09:59>> I'd love to take credit and say we figured it out, we iterated the product, we built great product, what we really did was not die when we were too early and be there when the market actually drifted into the window for what we had built. And just as quickly, while we were in a hiring frenzy and while we were focusing so much on sustaining the demand that existed in that product market fit window, we weren't seeing

Missing Numbers and SDR Model Breakdown

Bob Moore

10:21>> where the puck was going. And we eventually drifted out of product market fit after just three or four years inside that tight window. So this is like I've got a couple slides here that are just, like, brutal that I love sharing. This is our The red line is our targets in 2015, and the blue line is our actual MRR growth quarter by quarter. That is not what you want to see, and that is not what your

10:41>> board wants to see. We really, really basically just hit a point where the business stopped for the very first time. Right? This is seven years into its life. Not only did we start missing numbers, we started progressively missing the numbers worse and worse. We ended up needing to lay off a bunch of people in our go to market team because we had an SDR team where the economics were just incredible, and it made perfect sense in

11:05>> 2011 and 2012. And in 2015, everything just went upside down and underwater. And we realized we had the best SDRs in the world, but we didn't have the product market fit needed to actually make those phone calls resonate with people that were ready to raise their hands. And the SDR model stopped working for us.

11:22>> This is the other thing that happened, which is like for the founders in the room, I I I feel like it's important to show this slide. These are glass door reviews about RJMetrix from that era. And it is just the most heartbreaking thing to look back on, but it was a really, really challenging environment, especially for salespeople in that universe because as the business was deconstructing, I think we were basically not self aware enough to get

11:46>> out ahead of it. And kind of we were watching it feeling as though it was happening to us rather than taking control. I will point out that there's one or two of these that hate the company but approves of the CEO. So I have a little bit of a little bit of feather I can put in my cap there. Who do you think was building the terrible company? So these I always I I grab these screenshots

12:05>> at the time. They're like vanquished from the Internet at this point, but, like, I keep these around because I think they're important to to remember in in doing this message. So we get in this world where it goes from, like, too good be to be true to too hard to handle. And that reminded me of, you know, 2021 to 2023 for most of these companies. Right? Forget about raising cash. A lot of these strategies that used

Glassdoor Reviews and Cultural Fallout

Bob Moore

12:26>> to make a lot of sense kinda stopped working. Ads got too expensive for us. Buyers weren't buying in the way that they were buying before. And it was kinda like Groundhog Day, you know, going through the last couple of years seeing a lot of a lot of SaaS companies experience that. So what struck me though was that the modern data stack, all these companies that had adopted that new paradigm where the software is composable and the

12:48>> buyers are buying in stacks, they're buying software that kind of participates in an ecosystem, they weren't having these these problems. They had these incredible joint value propositions with the companies that they interoperated with and the products they were compatible with. The products were so sticky because if you rip these products out, all the other ones that are in that value chain are either less valuable or literally stop working. And the efficiency of their go to market

13:14>> strategies just worked a lot better because they were able to share pipeline. Like a win for one of them is a win for everybody in the stack because it's pulling people into this paradigm of buying inside of an ecosystem. So if you can't beat them, join them. We got very fortunate with RJMetrix in that we had a pretty decent sized business that was working really well in the ecommerce sector. And we were just kind of stopping

13:38>> seeing growth in all the other categories that we had previously played, SaaS, gaming, etcetera. But ecommerce was strong. And there was a company called Magento that had just spun out of eBay. They're the largest open source ecommerce provider. So shopping cart provider, like a direct competitor to Shopify. And they were private equity backed at the time. And they really needed a better analytics solution for their e commerce store customers. And we entered into a deal to

Stitch: Pivoting to the Modern Data Stack

Bob Moore

14:05>> be acquired by them. But in the process, we cut a deal. We said, going to conduct this deal, here's what we want to keep. We want to keep 20 employees, and we want to keep the IP that allows us to pull in data from all those different sources that RJMetrix knows how to pull. Basically, that of the red arrow there that's going from various servers and SaaS tools into that data warehouse. And Magento didn't care because

14:32>> they only cared about getting Magento data into the analysis tool. But we had built like 70 connectors. And we launched a product that was no longer supposed to be a suite solution. It actually fit into the modern data stack paradigm. So we went from being the enemy of this space to actually participating in it and living in this data integration ETL thing. So we had partners all of a sudden. Every single SaaS tool that you might

14:56>> extract data from, that was a partner. We also had partners in the data warehousing universe. Snowflake became a big partner. Amazon became a big partner. And everybody else downstream from there, all the dashboard providers, etcetera. And we were able to actually find really fast aggressive product market fit. And in twenty months, we got to as many paying customers as it took us eight years to get at RJMetrix with almost no salespeople. It was a PLG ecosystem

15:22>> led motion. Our biggest refers of customers were the very same companies that destroyed RJMetrix. It was Looker. It was Redshift. It was Snowflake. Sending us customers because we were the ones who could get the data into the warehouses so they could sell those value propositions to customers. So just 20 in, Talend came along. We hadn't raised any outside capital, and they kind of made us an offer we couldn't refuse. And we sold Stitch for $60,000,000 and

Stitch Sold to Talend for $60M

Bob Moore

15:48>> kind of had an interesting learning there. Oh, and by the way, my $2,600,000,000 mistake, which was the headline here, very shortly thereafter, Looker gets acquired by Google for $2,600,000,000. And Looker was the number one company that had basically won over all of the RJMetrix customers that kind of hopped away. So kind of missing out on that movement in the in the ecosystem led, in the modern composable data stack universe was kind of this this opportunity squandered

Crossbeam Launched to Solve Account Mapping

Bob Moore

16:15>> with with RJ. But seeing it work in Stitch and work so fast, I felt like the work was not done. And we had this learning, which was basically the most valuable collaborations that we had were ones where we did this thing called account mapping, which is pretty much, hey, let me compare the data in my CRM to the data in your CRM. Well, main problem was that you're basically trying to draw a Venn diagram between two

16:40>> things that were really not meant to be Venn diagrammed against each other. All kinds of technical challenges. If you wanna answer questions as simple as, hey, partner, how many customers do we have in common, who are they? Or are my sales reps currently selling to any of the same companies as your sales reps? Math is working against you Because you can't draw a Venn diagram unless you have all of the data from both of the sets.

17:00>> So if you want to know what's in the middle, you actually have to overshare with the partner. You have to give them your whole customer list or your whole sales pipeline. And that's a nonstarter for most people. So most companies either don't do this or they do it by emailing around spreadsheets of these very, very fragmented subsets of data, and it's kind of a losing strategy. But what we figured out with the partners we had at

17:20>> Stitch was if you can crack this and do it at scale, you can basically unlock this incredible fire hose of data. That's almost like you getting a little peephole into the CRM systems of every other product that is compatible with your product in some way. And it unleashes this this thing that we call the account mapping matrix, which is if you think about your prospects, your opportunities, and your customers, and you compare them to any given

17:42>> partner's prospects, opportunities, and customers, you get this really cool mind box where depending on what box you're looking at, there's a whole host of applications, playbooks, use cases where you can convert that data into go to market motions. So Crossbeam was launched as a product in early twenty nineteen to basically be that escrow service for data that sits in between companies who are collaborating with each other and provides them with this environment where they can compare

18:08>> those data sets but have really, really tight controls over who sees what, when, and under what circumstances, And ultimately, we're taking ownership over their own data and control over those access layers. And it's been really, really exciting to work with. So we've grown very, very virally over the course of the last five years. There's over 17,000 companies now on cross beam. That includes the overwhelming majority of the Forbes Cloud 100, a ton that are in the

17,000 Companies and Ecosystem Qualified Leads

Bob Moore

18:34>> large publicly traded space. I think we've got over 80% of the Bessemer Cloud Index that now uses it. And what's really kind of most important that has come out of all that is the plays and the playbooks. So this book, ecosystem led growth, just came out two weeks ago from Wiley, and it really is that treasure trove of here are the ways in which all those 17,000 companies, and in fact, the best ones among them, are

18:57>> using the data from the account mapping matrix, using this data from their partner ecosystems in order to build scalable growth strategies that convert into high ROI, high efficiency results. So I'll talk a bit more about that book in a second. But at the core is these playbooks, they kind of hit everywhere in the funnel. Right? Marketing, sales, customer success. And I don't have enough time to go through a huge number of examples here, but I do

19:21>> wanna talk about one of them just because it's so it clarifies a lot of this value really, really efficiently, which is this concept that's been widely adopted known as ecosystem qualified leads. So if you think about that three by three matrix, this strip along the bottom is the universe of your prospects, which can be a very, very broadly defined list. Everybody whose badge you've ever scanned at a trade show, every business card that you've ever logged

19:47>> into Salesforce in some way, everybody that you've accumulated on your email or content list, how does that intersect for each of your partners with their prospects, with their active open opportunities who are in the process of buying from them right now, and probably most importantly with their customers who are actually paying them? Now doing this with one partner is pretty interesting, but doing it with dozens of partners or many, many hundreds of partners as as many

Ecosystem Led Growth Book Launch

Bob Moore

20:12>> companies do ends up providing you with this incredible, incredible fire hose that's very, very dynamic that can inform where buying activity is actually happening among the universe of companies that you care about and specifically what products and areas they're actually making those purchases in. And what that translates to is this really powerful kind of second party data that is a a very, very useful example of intent. Right? It shows you where the hand raisers are who

20:38>> are bought into this idea that their buying decisions are actually governed by what tools are interoperable with the things they already have in their stack, which is probably the prominent buying determiner at this point for most software products, particularly in SaaS. Stripe is a big adapter to this. Pete Cummings, head of EMEA Stripe, has a section in the book where he talks about ecosystem qualified leads really being key. There's a bunch of really interesting playbooks there.

21:04>> But the book came out on March 12. It goes through all these things. Just wanted to also plug that I've got a bunch of them here, you can have them for free. So if you go all the way down the end of that hallway, at the very end, there's kind of a book signing station. I'm going be hanging out there this afternoon. We brought a bunch of copies with us. If you want to geek out on

21:23>> ELG, you've got anything you want to chat about in that universe, or you just want to share horror stories from the 2008 era, I am totally game. And appreciate the time. Twelve seconds left. We did it. Alright. Thanks, everybody.