Brian Robins: Yeah, so there — there’ll be an RQ, we’ll follow up later today. It was roughly about the same flat quarter-to-quarter. And we don’t break out the difference. Well, I guess from a price increase perspective, we don’t break that out in particular, but one of the things I talked about is in the net dollar retention rate, what the percentage was between seat change, price change and tier change. Historically, seat change has been roughly about 50%. Price change and tier change have been 25%. Because of the price increase, the price change now makes up roughly about a third of the total of the net dollar retention rate. The seat change is a little less than 50%. And then the tier change is a little less than 25%.
Ryan MacWilliams: Excellent, thank you guys.
Sid Sijbrandij: Thank you.
Operator: We will now hear from Kash with Goldman Sachs.
Kash Rangan: Hey, thank you very much. Happy holidays. Great to see the results. Sid, question for you. It looks like the tone — your tone and confidence level and conviction level in going after the comparative opportunity with Atlassian and Microsoft is actually stronger than before. I’m curious what gives you the conviction to pursue that comparativeness and what are things that GitLab has to do from a product perspective and a go-to-market perspective to be able to take advantage of what you consider to be these nascent opportunities? And second and final, the — we were waiting for Google to more closely align or for you to closely align your Generative AI efforts with Google. How close or how far are we from a full blown integration and announcement of sorts? Thank you so much.
Sid Sijbrandij: Thanks, Cash. Yeah, the customer feedback on our AI functionality has been positive. And as you might have heard in the prepared remarks, customers like NatWest and Nasdaq are using it in their engineering teams and seeing the value and the productivity and efficiency that it brings. Our customers have reported efficiency improvements upwards of 50% with code suggestions. We recently spoke with a leading international travel agency and they said that the features they tested, they believe that GitLab offers a better quality there. We also spoke with a multinational financial technology company, and their team is excited about using GitLab DO for generating configurations, test generation, bug finding, and automating operational work. So we’re very excited that we have a broad platform so that we can do AI across the life cycle with 14 features for customers available today. You’re muted.
Kash Rangan: Sorry, the other question, the competitiveness against Atlassian and Microsoft, what are the things you have to do from a product and go-to-market perspective to really take advantage of the opportunity that you see, the replacement opportunity?
Sid Sijbrandij: Yeah, I think apart from AI, I think it’s really unique to GitLab to have better security and compliance. Our features like SaaS and DaaS, container scanning API security compliance management are unique to GitLab. We also talked about the planning and management features. We talked about enterprise agile planning, but also think of value stream management and Dora metrics that are all unique to GitLab as a DevOps platform. And for example, we had a Q3 deal at a European telecom. We partnered there with AWS and we won against GitHub.
Kash Rangan: Thank you so much. Happy holidays.
Sid Sijbrandij: You too.
Operator: Nick with Scotiabank is next.
Nick Altmann: Awesome. Thanks guys. I wanted to build on Ryan’s question just around the Generative AI functionality with GitLab Duo. It sounds like there’s not going to be really any difference in feature functionality and sort of folding in some of the new enhancements into SaaS and self-manage, but I wanted to ask how you guys think about layering additional feature functionality into premium versus ultimate and whether there’s going to be kind of any difference there? And then just as a follow-up to that as you sort of layer in more functionality into that ultimate SKU more broadly, how do you think about pricing? Thanks.
Sid Sijbrandij: Yeah, I think our code suggestions I think is very comparable to a market. But I think what’s unique about GitLab is having 14 AI features in the platform available to customers today. I think that’s a big differentiation. As for how do we sell it, some features will be a different SKU, for example code suggestions and that’s then available not just to ultimate and premium but also free customers that might be not paying for GitLab today. I think that’s an exciting opportunity especially over the long term. And then some of the features we’re going to put into ultimate or premium and there might even be extra SKUs we introduce in the future.
Nick Altmann: Thanks, guys.
Operator: Michael with KeyBanc is next.
Michael Turits: Hey everybody, good evening. Hey Brian, hey everybody. So given some of that weakness you did call out in SMB from sales cycle and the size perspective, can you just be a little bit more specific about what really drove the upside in the quarter, you still call it an enterprise and or public and how that might be related to some of the things we’ve seen more broadly this quarter with cloud optimizations seeming to stabilize and some of the cloud consumption model companies seem to do better?
Sid Sijbrandij: Yeah, if you look at cloud consumption, it’s an increasing part of our business, but it’s currently a relatively small part of our business. So we aren’t materially affected by the cloud consumption stabilizing.
Michael Turits: Right. I guess I meant more from the general demand perspective. In other words, people are using more cloud. Is that driving more need, demand for GitLab subscriptions, seats, et cetera? And again, what’s really offsetting that SMB weakness that drove the upside in the quarter?
Sid Sijbrandij: I think that with GitLab, it has the biggest benefit the more complex your organization is. So the more complex your security and governance, the more heterogeneity in your projects where you go from kind of having projects on mainframe to the latest agile, that is where we can really shine. By bringing that all together in one platform, we typically see a 7x acceleration of cycle time. So give us the hardest problems, that’s where we shine. And the enterprises are having the hardest time of kind of having to move really fast, having all these things they have to move at the same time, but having the most compliance and security questions to do. We do believe if you look at the overall market, software is just going to keep getting more complex. You get AI now, you’ll have more regulatory friction coming for everyone. So that gives us a lot of optimism about the future.
