Business Breakdowns
· Ben Hensman
[00:00:00] S1: Yeah, I think this is a really important part of the Monday story. When we look across those revenue drivers that I talked about and going through them again, that's seats or team-based expansion or consumption with their AI pricing which we can come back to later, tiers, products, geographies and price, those five levers together are producing a net dollar retention ratio of 115% today. Our view is that that can actually be a little bit higher in a more favorable economic environment and be sustainable at that higher level. If you look at businesses that have been through this journey, and I grant you these are enterprise examples, but if you look at cohort histories of ServiceNow and Salesforce, where the breadth of those software portfolios and their ability to solve problems, as well as having similar levers of growth enabled incredible cohort growth over a long, long period of time. If you look at Salesforce in 2010, it had around $1.2 billion of revenue, similar margin structure to Monday.com today, and a growing portfolio starting with CRM and starting to move outside CRM. ServiceNow came a little bit later. Those businesses were able to advance net dollar retention at close to 130% blended across a 10-year period for some of those cohorts. So not saying that Monday can exactly replicate that profile, but it's an example of where you get these factors right and you're able to solve many problems for the customer and you have the ability to capture some of that surplus value created for the customer through an ROI-based mechanism or having these different levers of growth, you can sustain net dollar retention at very high levels for a long period of time. Monday's not quite at those incredible levels of Salesforce and ServiceNow yet, but we think it has the potential to get there and it's one of the reasons why we think that it can really grow into this very large addressable market, selling into effectively any business in the world. There aren't very many categories of software or businesses that you can access on the public markets that have that ability to look at any vertical, any size business in the world. And it's an incredible set of growth levers that they can draw on and they do so in a very efficient way.
· Matt Reustle
[00:00:00] S0: Yeah, it's helpful to at least have a precedent for a business that's done it before to prove that it can be done, if nothing else. You mentioned the term of the year or the term of the past two years, which is AI, and rather than wait to get to that, it makes sense to address it now. What type of impact has that had on the business either from a top-line perspective, from a cost perspective, but just an overall perspective? Talk a little bit about how AI is impacting the business.
· Ben Hensman
[00:00:00] S1: Yeah, absolutely. I think software, there's a theme running through here which is that Monday has really changed the way that customers use software from a fixed rigid model to an open and flexible model. And AI takes that to a different level again, where customers can automate and work with software in a new way. They can use natural language, they can have much greater capabilities themselves. And so that puts a really high bar on what you do with software and how powerful it is. And so there are definitely risks ahead for Monday for other software providers, but we also think it's a really significant opportunity. We have to think through things like the evolution of the user interface. We have to think through things like how the business model changes, which today is predominantly tied to seats. But as I said, we think inside this starting point that they have are really exciting opportunities as that flexible platform of primitives that they have. The trust that they have with large and growing customers, particularly non-technical customers, puts them in a really good position to be a carrier for these rapidly evolving technologies. And they can do that while keeping the experience and context really unique to each customer. It's a different experience to how scaled incumbents like Salesforce and Microsoft are making similar capabilities alongside their rigid software products in a copilot-type format. What we're seeing in the early days of Monday releasing product and AI is a clear starting point of customer context that gives them the ability to help drive value in a way that's really accessible. And I'll give you a clear example. They have three core areas of AI product that they're focusing on today. And this is definitely going to evolve, but it's given us clues as to how powerful this can be and it can start to accelerate some of the discoverability within customers and drive expansion over time. And they're pairing this with a consumption-based model, so an ROI-based or per workflow, per action-based business model that will scale with customers generating value. And the three products that they have called AI Blocks, AI power-ups and then the AI digital workforce. And I'll talk to these briefly.
· Ben Hensman
AI Blocks is the first product that they've launched and it is embedding AI in the columns of the Monday boards that all customers use in really, really simple ways. And in a simple example is if you're ingesting tickets on Monday service or candidate responses in a hiring pipeline, you can use out-of-the-box functions like categorizing that text, extracting, summarizing, translating to quickly triage and move items to the next step of the process. With an automated trigger. You can also dive into the prompting layer, but without too many bells and whistles. It's just a really simple interface where you can create custom columns with natural language, test those, adjust those to eliminate further manual steps, and add a layer of leverage before human intervention. And we've got a taste of how well that's going. So by Q3 last year, they'd seen about 3 million total actions using these AI blocks. That jumped to 10 million in Q4 and then up to 14 million by January. We haven't had any disclosure since, but an incredible growth pace, albeit from a low base, but just shows how straightforward it has been for customers and for partners to adopt this functionality. The second product that they have is AI power-ups. These are sitting on top of each of the core products. A good example within work management is a predictive risk management tool. So I mentioned before McDonald's, they have an overarching dashboard that looks at every area of project and campaign work that they're doing. This predictive risk management tool will sit on top of that and allow managers and operating teams to really quickly understand the health and the risk of all the projects in the organization with deep context, not just into the timelines and whether something's actually running on schedule, but much, much more than that. All of the detail within the boards and surfacing the key issues and the key takeaways. And this has been really helpful for companies like Bloomberg that I mentioned before that have been able to really quickly triage projects across the business. It's been useful on the go-to-market front as well that we were talking about before around top-down selling to executives and really understanding the value that comes from multiple teams driving processes and workflows.
· Ben Hensman
On Monday the 3rd, and I think this is where the greatest potential is and where they will need to run really hard and be competitive, is the AI digital workforce. And that's really just agents, but based on specific functions inside Monday, depending on the use case of the customer. The first of these to launch is Monday Expert that identifies areas of overlap and use cases and different boards. It allows you to use natural language to customize the board, build workflows, automations, and then adjust them purely through a chat interface. And then it can go away and create entirely new use cases for customers and helping with that discoverability and smoothing expansion. What we're going to see in the coming months are sales and service agents that are actually members of your team executing on your behalf to close out a ticket or progress deals through a pipeline in a really trusted way and in a way that you can control. And it's really accessible to customers. So there's clear opportunity there to accelerate all of the factors we've talked about and the flexibility of the platform in solving more problems for customers which can flow through to the financials and success. There's a piece in here about change management and trust which we've written about recently and that's incredibly important, particularly for non-technical customers to really feel that they can trust their use cases for AI. And that's going to be a process to go through. We think Monday is very well placed. Their approach to account management allows them to be very well placed in navigating that. On the risk side, I mentioned the fact that they're a seat-based model today. This means that the value of the product is tied to how many individuals are actually using it as opposed to the specific value. Even though a lot of their pricing and a lot of their pitches to customers are ROI-based. And so there'll be a process to go through over the next five to 10 years depending on how much AI is flowing through the product and how it interfaces with customers. They'll need to move to more of a hybrid model of seats or organization-level pricing and consumption and ROI-based pricing, and that's something that they will have to navigate, as will all existing software players.
· Ben Hensman
One thing that we're excited about is that they're not sitting on a fixed and rigid software model where they are building software to serve an existing and very, very successful business model and product. They're building products on top of a platform of primitives. And Monday Service is a great example of this. It's effectively an AI-native product built with a proactive-first approach to handling internal and external service, rather than an existing service product built in a certain way where they're having to layer in AI in an artificial way. So we're really excited about what that can achieve in terms of cost internally. Monday's always been a very efficient business and a very lean business. I mentioned their approach to development earlier and ensuring that they aren't over-resourcing and getting to feedback really quickly. You see that flow through in other teams. So their starting point is already very efficient and very commercial. But it has been incredible to see the pace that they've executed internally. And their democratization of data over their entire history means that all teams have access to the beating heart of Monday, whatever part of it is relevant to them, whether it's the marketing team, how they interface with external parties, how they interface with other external teams, how customers are using the product. And so their ability to see ROI and test is really enhanced by having that level of data transparency within the organization. So very early days on both the demand side and on how they use it internally. And that's the same for the entire industry. But we think they're making really good progress and we're excited about what's possible.