Back in July Yogesh Gupta, CEO of Progress Software, could scarcely conceal his glee at what he clearly viewed as snapping up a bargain as his firm finally sealed Domo’s doom when it picked up the analytics maven for a cool $400 million: 

Being able to acquire Domo for a little more than 1x revenue makes it financially very attractive.

On a more positive note, he said at the time: 

We have a track record of acquiring companies that were barely breakeven. We've done this before… historically, we've done this stuff before.

Flash forward three months and Gupta is now ready to drill down into more detail about Progress’s intentions for its latest purchases, as well as revealing more about what he’s found under the covers now that he’s had a chance to get ‘down and dirty’ inside Domo as a company. One of these is positive, the other perhaps less so…

Before outlining the Progress plans, Gupta takes a step backwards to consider the wider context - and the c-word is very important here: 

Context grounds AI in trusted data, institutional knowledge, and business policies to produce reliable and dependable outcomes, while control ensures security, governance, and the management of the infrastructure and the cost of the AI projects. Organizations that successfully bring these two elements together are the ones that can scale AI with confidence and realize lasting business value. 

That is one of the reasons for adding Domo's AI and data platform business to Progress, he says:

What makes the Domo business particularly exciting is its ability to connect data across the enterprise, apply AI to that data, and deliver trusted insights and actions directly into business workflows. Customers across all industries are using Domo to build AI-powered applications and agents to automate decision-making and to empower employees with self-service access to real-time intelligence. They are using Domo offerings to turn data into measurable business outcomes from accelerating growth to improving operational efficiencies. 

For example, a leading sports broadcaster connects all fan social interactions, customer service conversations, and operational data using Domo, creating a real-time intelligence capability that provides the context to understand what fans are experiencing across live events and how to improve that experience. This allows the broadcaster to have the confidence to make real-time, data-driven decisions, improve fan engagement while resolving issues quickly, and continuously enhancing the viewing experience of its audience. 

From a technology and product perspective, he argues, the strategic opportunity for integrating Domo's cloud-native AI and data platform with Progress' data platform is compelling:

As data and data platforms become increasingly important layers in the AI-enabled enterprise architecture, combining and integrating Domo's data transformation, analytics, and agent workflow capabilities provides significant acceleration of our overall data platform. Progress already provides critical elements of the AI-enabled data architecture, including ontology management, unstructured data management, semantic analysis, agentic RAG, intelligent decisioning and AI-powered automated workflows. Domo adds real-time data integration and transformation, analytics and visualization, automation, and agentic orchestration. Together, we can deliver a far more complete AI-ready data layer that takes complex data in and delivers deeper insights, automation, and trusted AI-driven outcomes.

So, that’s the theory. As to how that’s going down with customers, Gupta says he’s been out and about to meet with Domo users to brief them, including this week meeting with the firm’s Customer Advisory Board. It’s also launched a global customer meeting tour covering a dozen cities around the world, where at each event, senior executives expect to meet with 50 to 100 Domo customers. The first of these customer events also took place earlier this week. 

One topic likely to be recurring agenda item in such conversations is the shift to a consumption-based pricing model. This was an objective of Domo, but one which the firm failed to deliver on quickly enough with the result that a significant portion of the user base sits on legacy seat-based arrangements. That’s not going to last, suggests Gupta: 

The most exciting aspect of Domo's AI and data platform business is the part that is on the consumption-based model. Throughout our due diligence process, we have believed that the seat-based business of Domo will continue to see significant churn, and that we would also continue to de-emphasize Domo's services business, something Domo itself had already started.

The volume of data that businesses are trying to now consume, and they realize the value of, has suddenly become dramatically larger, and it's growing larger. It’s showing up in two places. In places like, obviously, Domo products, it's showing up as greater consumption because it's on the use of the data. In products that are more traditionally capacity-based, it's showing up in greater capacity needs, bigger server needs, a larger number of servers, a larger compute capacity, therefore larger number of licenses on the server side. 

For its part, Progress is in a different place: 

The vast, vast, vast majority of Progress products are either on the volume of infrastructure or volume of data in terms of capacity more than anything else. That also impacts our infrastructure management products positively -  as the infrastructure gets more complex, as they bring in more compute infrastructure to deal with AI workloads, all of this leads to additional capacity needs when it comes to observability products or our security products and so on. 

We see this whole rising tide on the use of data, the rising tide of complexity because of new types of hardware coming in. People are buying these AI compute boxes to put on people's desktops, and they're putting them in their own private clouds because they don't want to pay and run models on those rather than trying to pay some other AI company for their foundational models, etc. All of these things add to complexity and scale on the infrastructure side as well. 

As to his assessment of Domo’s own consumption model push, Gupta says: 

One of the things that we are doing, that we have been, actually over the last 90 days, is analyzing Domo's consumption-based model and trying to understand how it can apply across a variety of our products across our portfolio.  I think there's a tremendous opportunity to do that because the vast majority of our products are something where the value is derived based on the amount of information, whether it is structured data or unstructured data, content, you name it. The amount of workflows that go through those and therefore the consumption of  that content or that data, I think those are the right metrics because that's where the business value lies. 

Things are changing and there’s only one direction of travel, he argues: 

The human seats are going to get replaced by automated AI agents. We all know that, which is why I think the seat-based models are under pressure out there, and which is why we've been talking about the fact that the vast majority of our business is not on seat-based models. 

So we continue to look at how we can apply the consumption model to any of our businesses that are still on seat-based models as well. And also maybe some of our capacity models. We could basically use consumption as a metric for capacity as an alternate measure if a customer wants those rather than actually just volumes of data managed. They can say, ‘No, we want to use the volumes of data used rather than managed’, because the volumes of data managed is actually right now growing extremely fast. As time goes on, the volumes of data being used is going to go up even faster because the more the data becomes valuable because of AI, the more it's going to get consumed.

Users who are leveraging Domo for just the AI portion are actually expanding as they go forward, he adds: 

Folks that have converted over [to consumption] are much more stable in their net retention rate. The seat-based business reflects more the simple BI (Business Intelligence) aspect of things, where really the value is thought to be in the user experience rather than in the back-end aspect of data aggregation, data transformation and applying AI on top of that. That's not reflected in the seat-based model, which is why the seat-based model has continued to see more meaningful churn, even at Domo. 

Outside of this, expect changes to the go-to-market strategy around Domo tech, he suggests: 

The reality is that Domo had a strategy around trying to grow the top line very aggressively. We expect the top line of Domo to be mostly stable, maybe grow somewhat, but it is not the same level of focus on top line growth that Domo had…Our initial plan is to focus really on getting the business integrated, getting the synergies done, and so on and so forth, and, by the way, improving retention of customers, paying attention to existing customers that Domo has, making sure that they recognize that it is a better home for Domo than maybe they previously felt that they had. 

As such, Gupta isn’t majoring on Progress-Domo cross-sell opportunities for now, although that’s clearly something that will lie in the future: 

I am extremely excited about the cross-sell opportunity because the Progress data platform combined with the data platform and AI capabilities of Domo are truly compelling. I really, really do see cross-sell opportunities over time. I think it's just premature right now for us to talk about sizing it.

The future lies this way - time to consume it, it seems.