Domo, Inc. (DOMO) Earnings Call Transcript & Summary

Take as long as you think. We've got some time.

Okay. Yes, I'll give you some perspective on that. So there -- when we started, we didn't really think that -- I'll be honest with you, we were maybe somewhat naive. I think at the start, we didn't think that the big sort of enterprise customers were really going to be as interested as maybe more mid-market customers, right? To your point, because they've already made these huge investments in all of these technologies and whether it's monetary capital or political capital that different people have invested into it, it's hard to kill your darlings, right? It's hard to sort of admit that we need something else because isn't that admitting failure. It isn't the admission of failure, the worst thing you can do in an organization or for your career. But right from the start, and I agree with you, I think we did, because of that, maybe position ourselves as sort of the full stack answer to everything. And maybe it was -- it came across as more of a rip and replace mindset, and that's not a very popular one. But that's not really what we meant to create. I mean what we've created here is a platform that connects your data no matter where it comes from, your people no matter where they are, your systems, no matter where they are or how they talk to each other to come together. And so really, our approach is to create a very open agnostic platform that our philosophy is really more embrace and extend what you have. For some, it might make sense to replace what they have because Domo can do it better and we see that a lot. But to your point, you brought up say, Snowflake. Snowflake is a new and really exciting partner to have. And you would think, well, why would Snowflake need that? They've got very powerful software. They've got a cloud architecture, I think the last time I looked, they were like a $90 billion market cap. Why would they need to even talk to someone like Domo. And I think it goes back to the same problem, which is there is a tremendous amount of complexity. Yes, it's very easy to sort of build one-offs, but to build applications to pull all of those pieces together to have the governance, the compliance, the security at scale, the ability to -- whatever you create there to show up in into the palms of each one of your customers or colleagues is very, very difficult. I'm just thinking of our connector framework. We have over 1,000 connectors. Those are ridiculously difficult to build. And as I mentioned, some of our naivete at the start, we thought that was going to be easy, right? That was not easy. And it's still not easy, right? It requires a full sort of team and systems that monitor and check because APIs change all the time, right? There's no wonderful clearing out that says, hey, guess what, Facebook is going to change their marketing information or Google analytics is going to change. It requires a lot of work. And that's value that is very hard to find other places. So to answer your question, like where -- how do we sort of view the market and where we're going. We are in the business of data and in the business of helping organizations, big or small, modernize and transform digitally. So we've built this thing to go anywhere. And that might sound maybe a bit self-serving, but there isn't really a line there, right? We thought at the start big enterprises wouldn't be interested. It turns out big enterprises are really very interested, the ones who get it. And those are the ones who are pushing us to say, we want more. And you asked how do you sort of distinguish between the wants of maybe big customers who can be very persuasive, as you know, and what the market really needs. And that's kind of the -- that's kind of the art and science of it. That just takes really experienced team members. It takes maybe not a big mouth, but a big ear and trying to understand where are we seeing similar kinds of requests because I think where other companies would struggle is in trying to see that what looked like very different problems are actually the same kind of problem. You just have to look at it in a slightly different way. So sometimes reframing the question and sort of pulling out the general sort of pain point is the kind of thing that we question all the time. Are we building this as a one-off? If so, it's not going to scale. Are we building -- or have we discovered a general problem that we have a great solution that can then be customized individually? So for example, our focus on user experience and self-serve analytics. That's an example. We could have gone down and said, we're just going to tell you for this particular industry, here's how you should look at all of your data, and we're going to build those tools specifically for that. Instead, we built a platform of capability. And I think that's one of the things that, frankly, becomes a little bit of a challenge in terms of selling, right, because people want something to solve that specific problem. And instead, we've had to learn -- well, look, here's the capability that allows you to be nimble, turn your data into much more valuable assets very quickly and push decision-making to the edges, along with start rolling in AI and automation because that is obviously where a lot of companies are moving, and it's very, very difficult. So I don't know if that answers your question specifically, but that's how we kind of look at it. It's a big problem. It's a big world. And we try to draw from it through our sort of front row seat working with these very huge companies. We look at it as an opportunity to buy information and then build what our customer -- what our competition doesn't even realize is a problem yet. And just to sort of finish that up, I remember reading -- I won't say who it was, but it was maybe 2 or 3 years ago, someone who's done very well regardless, was looking to move into our space and I could tell by what they were saying that they were 4 years behind where we were thinking because that's what we had thought exactly 4 years before. So you don't want to discount the fact that, yes, we are making huge investments in R&D, but that R&D is not just in the technology, it's in getting the opportunity to learn more from your customers and from the environment before your competitors do. I think that something gets overlooked quite a bit.

Got it. Maybe along those lines, you're probably familiar with the expression that people overestimate what can be done in a year, but underestimate what can happen in 10 years?

Yes. Yes.

As you think, not even necessarily about Domo, but the market for data analytics and the possibility of what we could see out on the horizon in being able to harness, which is the Fibonacci Rabbits that are growing in the way that we call data. Any thoughts or observations, prognostications you leave us with?

Yes. So yes, like where are we going to be in 5 years? What does the BI space look like in 5 years? Well, I think although you can do world-class business intelligence on Domo. Again, we've never thought of it as just a BI tool. And I think what you're starting to see more clearly now, especially as these other companies like Google and Microsoft and Salesforce are building these fuller stacks is that one, you need a platform, right? The platform approach makes sense. And I think one of the things that you're going to see as a big shift is that the platform, not just as an application, but the platform as a new kind of business model is going to emerge, right, because the platforms are starting to take over the world anyway, right? The Amazons. I think Amazon I think they hired like over 400,000 people this year, right? They've got the digital infrastructure to hire that many people and make them effective wherever they are, because they have a platform business model, a platform mentality. And what does that mean? What that means is you're using your data and your applications to create a new kind of economic ecosystem, right? So if you're looking 5 years down the road, I think platforms like Domo are going to offer companies to transform into hybrid-type platform organizations far more quickly. I think that's ultimately what digital transformation is about. I think from the standpoint of data and analytics, well, that's definitely shifting, right? I think we're -- we've clearly, you started to move past the dashboard, right? The dashboard is really a design metaphor, right? It's a way of representing an idea of how do I explore and relate to information. As opposed to, and this is what we've seen definitely through the pandemic, companies really leveraging the speed of the platform to create smart applications for their organizations, both internally and externally. Right now, we're seeing a lot of organizations using, say, Domo publish everywhere. So the ability to like take their data and turn that into a different kind of asset. That's a platform move right? That's taking stuff that you would typically think of as an internal resource solely and putting it out into the marketplace to figure out how we can create greater interactions. Unilever and Target is a great example. So both Domo customers. They use Domo to sort of share shelf level data. So Target is sharing their inventory with Unilever, which is using AI and assemble models to predict how demand is changing at a shelf by shelf level. Well, that's a different level of cooperation that is only possible with a platform. And that's where I see things moving. I see the sharing of data, along with AI. AI is going to become the new data, clearly. And I don't want to say it's going to be a future where people are kind of drowning in apps, but definitely using data as to drive action. Through applications that are specifically designed for the right person in the right role in the right situation to get things done. Because ultimately, you need to, especially in the sort of remote -- suddenly remote workforce world that we live in, you have to push data to the edges, right? That's -- you need to sort of tap every ounce of creativity from your network as opposed to, as we said, people just sort of sit in and you just do what you do well or what we thought you did well or what we demand that you do well, right? We need people out there understanding how customer behaviors are changing. How the environment is changing. What happens when the next unexpected event happens? Are we able to respond faster than our competition? So that's where I see things moving. It's not dashboards. It's not just pie charts and bar charts, right? It's a very different way of taking data, making it decision ready and then pushing it to the edges so that you can have a bigger effect on your -- on the outcomes of your organization.

Chris, it's so interesting to hear your thoughts and your perspective on things. Unfortunately, we're actually -- we only got a minute or 2 left here but maybe my final question for you is from an investor standpoint, where I sit and others that are listening in, what do you think might be the most underappreciated aspect of Domo that people just may misconstrue or -- and that can go not only for investors, but even from customers, partners, all the other constituents that you serve.

Yes. Well, I mean, I think we touched on a lot of them. And I think the biggie is that we have created a platform that allows you to scale very, very quickly, leverage all of your BI extremely fast and to everyone within your organization. And that because we sort of were built to integrate from the very beginning with this sort of open platform, the opportunity to extend your business, create new kinds of business is kind of endless. So we run into challenges from companies every day from L'Oréal to Coca-Cola Swire to others, where they're able to do things that they just didn't even think was possible. I mean they've told us, like, you can't do this and like, okay, you have to go to where the customer is, right? You have to answer what the ask is of the customer. But then all of a sudden, they get hungry, right? A little bit of success becomes very, very contagious. And so I think although it's been a long, very challenging few years to put this together, I feel like we are super well positioned because we didn't overengineer for one sort of problem, right? We didn't build software when the whole world was building software at that time, we built a platform that gives your company instant capability to embrace and extend the work, the people and the technology you may already have and then begin to experiment because I think -- and this is the key point, I believe, we -- as you've seen -- I mean, I read your reports to see what you think of us. And I've seen that with the pandemic, we thought -- Bruce, I'm sure has talked about this, we thought we're going to lose 20% of our business, right? And instead, what has happened, we're growing it at 20%, right? I think that is the evidence that gets me very excited because like people are recognizing it. We're learning more, we're leveraging. And as we bring on bigger and more complex sort of customers, I think people will get the confidence to say, "Oh, they can solve this problem that we have to get solved". But now all of a sudden, like we've seen with our customers, you guys can solve these other problems, which we didn't even think we're solvable. That is a very magical place to be. It's not easy. It's taken a lot of investment and a lot of work, but that's what I'm very optimistic about.

Awesome. Well, with that, Chris, we are out of time. Truly delightful to have you and hear your thoughts.

Thank you.

And it's really great to see you at this annual -- 24th Annual Credit Suisse Conference, even though it's virtual at this time.

Yes. Thank you.

But we look forward to having you guys again in the future. And with that, we're going to wrap up. Thank you.

Thank you so much, Brad. I appreciate it.