Salesforce Inc

NYSE:CRM

Welcome to Salesforce's Fiscal 2024 Fourth Quarter and Full Year Results Conference Call. Please note, today's call is being recorded. [Operator Instructions] I would now like to hand the conference over to your speaker, Mike Spencer, Executive Vice President of Finance and Strategy and Investor Relations. Sir, you may begin.

Thank you, and good afternoon. Thanks for joining us today on our Fiscal 2024 Fourth Quarter Results Conference Call. Our press release, SEC filings and a replay of today's call can be found on our website. Joining me on the call today is Marc Benioff, Chair and CEO; Amy Weaver, President and Chief Financial Officer; and Brian Millham, President and Chief Operating Officer.

As a reminder, our commentary today will include non-GAAP measures. Reconciliations between our GAAP and non-GAAP results and guidance can be found in our earnings materials and press release. Some of our comments today may contain forward-looking statements that are subject to risks, uncertainties and assumptions, which could change. Should any of these risks materialize or should our assumptions prove to be incorrect, actual company results could differ materially from these forward-looking statements. A description of these risks, uncertainties and assumptions and other factors that could affect our financial results is included in our SEC filings, including our most recent report on Forms 10-K, 10-Q and any other SEC filings. Except as required by law, we do not undertake any responsibility to update these forward-looking statements. And with that, let me hand the call over to Marc.

All right. Hey, thanks so much, Mike, and hey, thanks, everyone, for being on the call.

Look, as you can see from these numbers, we've had just an incredible and incredible quarter. Well, actually, we've just had an incredible year here at Salesforce, with strong performance across all of our key metrics, revenue, margin, EPS, cash flow and, of course, our CRPO. Look, it's been an extraordinary year of transformation for Salesforce. You all know that. You've all been there with us. You've been the support that we have needed during this year. Thank you to all of our shareholders, and thank you to all of our stakeholders.

It's been a year of incredible transformation for our industry, with the emergence of this next generation of artificial intelligence as well. It's been really 2 unbelievable things happening at once, the total transformation of the Salesforce and the total transformation of our industry.

All right. Let's start with the transformation of Salesforce. Okay. Look, it was over a year ago, we said Salesforce had to transform. And you, many of you came to me, came to our whole team and you said, "Look, we're going to transform the whole company." We did it together. We could not have done it without you. We said we would restructure our business for the short and long term, we did that.

We said we would place a laser focus on increasing productivity and operational excellence from across the board, we've done that. We said we're going to double down on innovation to make our core products even better, we've done that. And when you see what's coming in TrailheaDX next week, you're not going to believe it. Not just our next-generation artificial intelligence, not just prompt builder, not just our copilot, but this data cloud, which I'm going to get to in a second, our fastest, most exciting new product ever, fastest-growing, most customer traction that I have ever seen, that has been incredible.

So let's talk about all of this. And -- let's talk also about how we have also strengthened our relationships with our investors. Thank you, Mike, for everything you've done. And Amy Together with the management team, with our Board, we've really focused on you, the investor community. We've accomplished all of that together. We've completely transformed this company together, and we're very grateful to each and every one of you.

And that transformation, while it has driven incredible results and you're seeing productivity is up, profitability is up, margin is up, revenue is up, and you're going to see it again in our results for our quarter, you're going to be looking at these full year numbers with phenomenal cash flow with incredible margin growth -- well, margin growth that I've never seen in any software company over the last 12 months, 18 months, it's completely unprecedented. And you can see the incredible speed and success of the transformation that we've undertaken.

Now we believe that Salesforce not only needs to be a great software company for our customers, our employees, our communities, but also a great company for our shareholders as well. We've certainly seen that with the exceptional performance of our equity over the last few months.

Now I'm thrilled that we're opening the door to another incredible part of our ongoing transformation today, with the introduction of our first-ever dividend, and that's amazing. To say that word for the first time in 25 years in Salesforce history, our first-ever dividend. What you're going to hear more about from Amy in a moment, and if this year has shown anything -- if it's shown anything at all, it really shows that we've committed to serving all of our stakeholders.

We closed out fiscal '24 with $9.29 billion in revenue for the fourth quarter. That's up 11% year-over-year, 10% in constant currency. Pretty awesome at our size and scale, incredible. 8 of our top 10 deals in the quarter included 6 or more of our clouds, really showing the depth and breadth of our product line and our portfolio. And all of our top 10 wins included sales, service and platform, and we're really focused on delivering that full cocktail of all of our clouds to all of our customers.

And our deals greater than $10 million, well, they grew nearly 80% year-over-year in fiscal year '24. That was also amazing. Our customers just get so much more value, and they can do so much more when they take the full advantage of our Einstein 1 Platform. And I want to explain that to you because we have such a rich set of applications that when we're working with all of these employees through the whole company and also the customers as well, we're filling our platform with the data and the metadata that our customers need to be successful.

And there is no other time in the history of our industry, that, that rich data and metadata together in one place is so important because that is what you're going to need to drive this artificial intelligence. And you're going to see that next week at TrailheadDX, as we show you our copilot for our first time and prompt builder for the first time and data cloud for the first time and how it works together so that you can get the insights that you need.

Now this is all possible because we're delivering this Einstein 1 Platform. But before I get to that, I just want to make this one last point. For the full year, we delivered $34.9 billion in revenue, up 11% year-over-year. One of the best performances of any enterprise software companies ever.

With our continued disciplined approach to margin expansion, non-GAAP operating margin for fiscal '24 was also 30.5%, up 800 basis points year-over-year. We closed fiscal year '24 with operating cash flow reaching 10.2 billion. Operating cash flow, up 44% year-over-year, a major goal for the company this year. Well done, highest cash flow in our company's history.

CRO, our current remaining performance obligation, was $27.6 billion, up 12% and 13% in constant currency year-over-year, fantastic display on CRPO. And total remaining performance obligation ended the fourth quarter at $56.9 billion, an increase of 17% year-over-year.

Now let me just say this again, $57 billion in RPO, amazing. For fiscal year '25, we expect free cash flow to grow between 23% to 26% for fiscal year '25. That is for fiscal year '25, we expect free cash flow to grow between 23% to 26%. And we're guiding revenue to $38 billion at the high end of our range, 9% year-over-year, expecting to deliver fiscal year '25 in subscription and support revenue growth of above 10% year-over-year in constant currency. We're going to get to that detail in a second. We're committed to delivering non-GAAP operating margin of 32%. All told and a year of transformation from the financial metrics to help us get it done, our boomerangs, our Ohana, thank you to everyone who's made this possible.

Just look at where we are now. Salesforce is the world's #1 AI CRM, #1 in sales, #1 in service, #1 in marketing, #1 data cloud, incredible. And since the start of the pandemic in 2020, we've doubled the size of the company. That's amazing. We doubled the size of the company and scale since the pandemic started, which was about 4 years ago. That's incredible at our scale.

We're the largest enterprise applications company in the world. We passed this AP. That was amazing. That was a huge accomplishment this year. But now, we're the third largest enterprise software company in the world and the second largest in Japan. And to all of my Japan, [Foreign Language] for what you have done with the Japanese market is incredible. We're not stopping. Our management team and our extraordinary employees are focused every day to make our business as strong as it can

be. Personally, I've never been more excited about the future of Salesforce. You're about to hear why. It's not just the incredible financial results, not just the unrivaled success of our customers, but it is the incredible door that has opened through artificial intelligence once again and the evolution of our entire technology platform, it's what our engineering and product teams have done in the last 12 months is nothing short of amazing. I'm so grateful to their leadership. And to David and Srini and to all of your employees, thank you for what you have done for Salesforce. Your leadership, your vision, your insights, your creativity in rebuilding the platform so quickly. And Data Cloud for artificial intelligence, for Steve, what you have done for Jujhar, my whole team, it's incredible.

As I said, it's not only a remarkable year of transformation for Salesforce, it's been an amazing year of transformation for our entire industry. As I talk to CEOs around the world, they tell me, they want 3 things. You may have heard me say this already, but I'll say it again. One, they want more productivity, and they're going to get that productivity through the fundamental augmentation of their employees through artificial intelligence. It's happening. It's empirical.

Number two is they want higher value customer relationships, which is also going to happen through this AI. And they want higher margins, which we are seeing empirically as well through the -- when they use this artificial intelligence in these next-generation products.

As we look at productivity, as we look at higher value customer relationships, as we look at higher margins, how do our customers get these things? How are they achieving these goals? It is AI. It is why every CEO and company knows they need to make major investments in AI right now. And I believe this is the single most important moment in the history of the technology industry. It's giving companies an unprecedented level of intelligence that will allow them to connect with their customers in a whole new way. And with our Einstein 1 Platform, we're helping out our customers transform for the AI future.

Now many of our customers have inspired by OpenAI's GPT 4. I have a Cohere, I have an thoracic, I have an inflection, I had and also all the amazing models on hugging face and other AI models, all these things, amazing. And everyone has been wowed by what these AIs can do, incredible things and a lot of party tricks, a lot of magical things.

And then we also realized there are some other things, too. Let's talk about the truth. The truth is that these AI models are all trained on amalgamated public data. You all understand that. You've all seen the New York Times lawsuit of OpenAI or others who are really going to take, hey, this is all -- this amalgamated stolen public data, much of it used without permission, unlicensed, but amalgamated into these single consolidated data stores.

Now some of my people even say this is just stolen data, but all this public data has been amalgamated into what they call training sets. And these training sets then get turned into what we call inference, which is how the AI then is able to start to deliver its insights. But there's other things that it's providing besides insights. These AI models, well, they could be considered very confident liars, producing misinformation, hallucinations. Hallucinations are not a feature, okay? And I'm going to get to that point in a second. And I think you all understand it that already because at this point, we all have a high level of experience with AI, don't we? Everyone has had that experience.

And there's a danger though for companies, for enterprises, for our customers that these are not trusted solutions. And let me point out why that is, especially for companies who are in regulated markets. Why this is a big, big deal. These models don't know anything about the company's customer relationships and, in some cases, are just making it up. Enterprises need to have the same capabilities that are captivating consumers, those amazing things, but they need to have it with trust and they need to have it with security, and it's not easy.

Look, we all read the story. Now it just happened last week. An airline chatbot prompts by a passenger to book a flight with a 90-day refund window. It turns out the chatbot, running on one of these big models, we won't have to use any brand names here. We all know who it was, hallucinate the option. It did not exist.

We all know what that's like. We've all had the experience. So here's the chatbot. It hallucinates the option. It's working with the customers. It didn't exist. It did not exist. The airline said, "Oh, listen, that was just the chatbot. It gets that way some time. We're so sorry -- you know what, that's just a separate technical entity, a separate legal entity and the airline, "We can't -- we're not going to hold liability for that."

Well, guess what? That defense did not work in a court of law. The court of law said that, that AI chatbot that made up that incredible new policy for that company, well, that company was going to be held responsible, liable for that policy, that they were going to be held liable for the work of that chatbot.

Just as they would for a human employee, they were being held liable for a digital employee. The reality for every enterprise is that to deliver trusted AI experiences, you need these 3 essential components now. You need that compelling user interface. There's no question, a natural and effortless experience.

And at Salesforce, we have some of the most intuitive user interfaces that deliver insights and intelligence across sales and service and marketing and commerce and industries. Many of you are on Slack right now. Many of you are on Tableau. Many of you are on MuleSoft are, one of our other products.

Okay. Now what else do you need? Number two, you need a world-class AI model. And now we know there's many, many models available. Just go to hugging face, which is a company that we're investor in or look at all the other models. And by the way, not only the thousands of models right now, but there are tens of thousands, hundreds of thousands of models coming. And all the models that are available today will be obsolete 12 months from now. So we have to have an open, extensible and trusted framework inside Salesforce to be receptacles for these models. That's why Einstein 1 is so important.

Then you have to be able to use these AI models. The ones that Salesforce is developing or these public models on Hugging Face or other things, or even bring your own model. Customers are even making their own models, fantastic. Of course, we have great partnerships with OpenAI, with Mythropic, with Cohere with many other AI models.

This is the second key component. One is the UI, the second is the model, all right? Now for those who have put like, for example, copilot on our phone or any one of the copilots, on the App store, we have a compelling UI, and we know underneath there, there is a compelling model. But third, we also know there's a huge data set there. But here we go.

Now we're in the enterprise. In the enterprise, you need deep integration of data and metadata for the AI to understand and deliver the critical insights and intelligence that customers need across their business, across sales, service, marketing, commerce, whatever it is. That deep integration of the data and metadata that's not so easy. That's not just some amalgamate stolen public data set. In the enterprise, that deep integration of data and metadata. Oh, that's what Salesforce does. We are a deep integration of data and metadata. That is why it's very, very exciting.

I'd like to say, and I love NVIDIA, by the way, and what Jensen has done is amazing, and they are delivering very much. In the era of the gold rush, the Levi's jeans to the gold miners. But we all know where the goal is the data. The gold is the data. And that's why we're so excited about Salesforce because we are one of the very largest repositories of enterprise data and metadata in the world for our customers. And customers are going to start to realize this right now.

And they try to stitch together a variety of AI tools and copilots and this and that and whatever I've had so many funny conversations with so many customers that come to me that they're experts in AI and their. And then I just say to them, but how are you going to deliver this experience? And then finally, they realize, "Oh, I need the deep integration with the data and the metadata. The reason why the metadata is so important is because it describes the data. That's why so many companies are turning to Salesforce for their AI transformation.

Only Salesforce offers these critical layers of AI for our customers, the UI, the model and the deep integration of the data and the metadata make the AI smart and intelligent and insightful. And without the hallucinations and without all of these other -- all the other problems.

For more than 2 decades, we've been trusted with our customers' data and metadata. And we have a lot of it. And a lot of you are customers, you understand what I'm saying. But many of our customers also have islands and thousands of systems of trapped data.

Now what I'm going to say is very simple. Trap data is all over the enterprise. Now what trap data could be is you might be using a great company like Snowflake and I less Snowflake or Databricks or Microsoft or you might be using Amazon system or even something like Google, what do you say, BigQuery, all these various databases, but put your hand up if you're using Snowflake every day.

Put your hand up if you're using one of these other systems. Put your hand up if you're using Salesforce, Sales Cloud, Service Cloud, Tableau, Slack, we need to be able to, through our zero copy, automatically integrate into our data cloud, all of those systems and then seamlessly provide that data back into these amazing tools. And that is what we are doing because so many of our customers have islands of trapped data in all of these systems, but the AI is not going to work because it needs to have the seamless amalgamated data experience of data and metadata, and that's why our data cloud is like a rocket ship.

The entire AI revolution is built on this foundation of data, and it's why we're so excited about this incredible data cloud. It's now deeply integrated into all of our apps into our entire platform. Its self-service for all of our customers to turn on. It is our fastest-growing product ever. It's our total focus for fiscal year '25. With Salesforce Data Cloud, Salesforce can unlock this trap data and bring together all of their business and customer data into one place for AI, all while keeping their data safe and secure, and it's all running inside our Einstein Trust layer, and we've deployed it to all of our customers, we unleash now the copilot as well to all of our customers deeply built on our pilot on our data and metadata.

And while other copilots just sit and spin because they can't figure out what the data means and if you haven't seen the demonstrations, you can see these co-pilots spin, but when they use Salesforce and all of a sudden becomes intelligent, and that is the core of the NSN platform. And all of our apps, all of our AI capabilities, all of the customer data and 1 deeply integrated trusted metadata platform, and that's why we're seeing incredible demand for data cloud. Data Cloud brings it all together.

And we are so blessed to have data cloud in our company. And it's also why in Q4, 25% of our deals already over $1 million have included Data Cloud. And we've recently added over 1,000 new customers to Data Cloud. We've never seen traction like this of a new product because you can just easily turn on the data cloud and it adds huge value to Sales Cloud. It adds huge value to Service Cloud, the Marketing Cloud and the CDP. You've all seen the Gartner Magic Quadrant that got published last week about the data cloud or if you haven't go to my Twitter feed and you'll see how amazing that MQ is and it's the fastest-growing organic product in the history of Salesforce.

This last quarter, more than 7 trillion records, 7 trillion records were ingested into Data Cloud. Unbelievable, 7 trillion records in just in a data cloud with over a trillion activations driving customer engagement, lighting up all of those sales service marketing cloud users, all the platform, Tableau, it's all integrated into Data Cloud.

And because Data Cloud and all of Einstein 1 is built on our metadata framework, as I just described, every customer app can securely access and understand the data and use any bottle, use an EUI workflow, integrate with the platform. That means less complexity, more flexibility, faster innovation, but also we want to take to buy to these hallucinations. We want to say goodbye to all of these crazy experiences or having with these bots that don't know what they're doing because they have no data or metadata, okay? Or the data that they have metadata is like productivity data like the highest level data that's not deeply integrated data.

So only Salesforce can do this. Only Salesforce has this vision of this kind of platform and only has -- we've been working on this for 25 years, and we are not done. We are just starting because let me tell you now of a story of how we're delivering a high-quality, trusted AI for our customers. We all know the HR and payroll leader, ADP and their incredible new CEO, [indiscernible], amazing. ADP has been a great sales cloud customer for 2 decades. They've used Einstein for years. They are one of the first customers we ever have. We're so grateful to ADP, amazing and work with so many of their great CEOs over the decades. And the company wanted to transform now customer service with AI to give their agents real-time insights, next best actions, auto generating case summaries. But what I have to say to you, it was a little bit embarrassing Salesforce is not #1 on their list.

And I said to them, "How can that be? We're the #1 service cloud. We're #1 in the Q. We're #1 in this. Number went work. No, we're going to go evaluate this. We're going to look at all the different solutions -- we're going to look at all the new AI models. We think we're just going to hook this model up to this, and we're going to do that. And it sounds like a big root Goldberg invention what was going to happen there. And so we had to go in and we just wanted to partner with them and say, "All right, show us what you want to do. We're going to work with you, we're going to be trusted partners. Let's go.

But like a lot of our customers move into AI, ADP realized it didn't have a comprehensive deeply integrated platform of data and metadata that could bring together all of this into a single source of truth -- and then you get the incredible customer service. Then you get the results that you're looking for.

And it's deeply integrated with their sales systems with marketing and custom applications. And ADP discovered the only sales force can do this. We were able to show ADP how we could unlock trap data with data cloud, 0 copy, drive intelligence, productivity, efficiency for their sales team with Einstein to levels unimagined just a year ago. We're now incredibly excited to work with all of our customers to take their AI to the next level with Einstein copilot, which is going live tomorrow.

Einstein CoPilot, which if you haven't seen it, and if you haven't, please come to TrailheadDx next week. This is the first conversational AI assistant for the enterprise that's truly trusted. It's amazing. It can answer questions. It can summarize. It can create new content, dynamically automate task on behalf of the user. From the single consistent user experience embedded directly within our platform. But let me tell you the 1 thing that can do that's more important than all of that. It is able to read across all the data and metadata in our platform to get that insight instantly. And you're going to see that -- so the sales rep might ask the Einstein CoPilot, what lead I should focus on or what is the most important thing I need to do with this opportunity. And it may say, you need to resolve this customer's customer case because this escalation has been around for a week or you better go and answer that lead that came in on the Marketing Cloud before if you want to move this opportunity for it because it's reading across the entire data set.

That is something that individual users cannot do that the copilot can do. With access to customer data and the metadata and sales force, including all this real-time data and website engagement and the ability to read through the data set, that's why Einstein copilot has all the context to understand the question and surface belied that has the highest value and likelihood to convert.

And it can also instantly generate the action plan with the best steps to close the deal, such as suggesting optimal meeting times on the lead contacts, known preferences even draping e-mail. If you haven't seen the video that I put on my Twitter feed last night, there's a 5-minute video that goes through -- all of these incredible things that it's able to do, there's never been an enterprise AI capability quite like it. It's amazing.

All of us can understand the task that copilot is performing, and I bet a lot of people even on this call that a lot of other companies might say they can do this, but I assure you, without the deep integration of the day of the metadata across the entire platform within copilots deep integration of that data, they cannot do it. I assure you they cannot because they cannot. -- because they don't have the data on the meta data, which is so critical to making an AI assistant so successful.

And I encourage you to try the demos yourself to put our copilot up against any other copilot. Because I'll tell you that I've seen enterprise copilots from these other companies and actions and they just spend and spin and spin -- and some have a different copilot for every app, some with different capabilities, restrictions, grounding this, Wizzywig builders or whatever. It's very cute. -- very nice, exciting it's really cool for the first minute, and then you realize, wait a minute. And you leaized what data is available to this copilot. Only a conversation with you, okay, can start to understand all these things if it has this access. Only after a conversational UI for canned queries or don't understand the customers to customize the copilot, none of these things are going to work.

I've used those copilots from the competitors, have not seen them work yet. Okay. The thinking icon, spinning, it goes on and on and on and on. In stand copilot, you're going to see -- you're going to have your hands on it now. It's been released into the wild to our customers, to all of you this is fundamentally different kind of AI.

Just like Einstein was a different AI, which became the democratization of AI, which is why Einstein does a trillion transactions a week. Einstein is the only copilot with the ability to truly understand what's going on with your customer relationships. It's one conversational AI assistant, deeply connected to trusted customer data and metadata.

It's one integrated system for all of our customers across any role or industry, and it's why we call it Einstein One. It's 1 platform. 1 integrated system, that is what you need to get AI to work. Next week at our Trailhead DX conference in San Francisco, I hope you're all coming. It's going to be amazing on March 6 and 7. You're going to see how we're bringing even more AI innovation to our customers.

So be prepared to be amazed by Einstein CoPilot builder, prompt builder or model builder and so much more that we're doing to help our customers make every employee more productive and to transform every customer experience, and I hope you're going to join us in person or you can join us online at Salesforce plus.

And with closing, I just want to thank all of you, once again, for everything that you've done for us for the last year. We're so grateful to each and every one of you and to our entire management team, all our Ohana and all of our customers as well. We're so grateful as we look forward now to our 25th anniversary in March 8, I've never been more excited.

You can hear, why? Not just the fundamental transformation of the company, but also the fundamental transformation of the product line and the product vision as we move into this incredible new intelligent world that we're all seen with AI. So thank you. And now I'm turning it over to Brian, who was employee #13, our Chief Operating Officer. He's done a phenomenal job this year. Without him and without Amy without our whole management team, it would not be possible. I just want to thank again everyone who has been a huge part of everything, and I'll turn it over to you, Brian. Here we go.

Well, thank you, Mark. I really appreciate it. I couldn't be more proud to be part of Salesforce the past 25 years, especially this past year as we took on a pivotal business transformation, while delivering incredible innovation for our customers and returns for our shareholders.

Our continued focus on operational excellence, high performance and new growth initiatives helped deliver strong results in the fiscal year and remains our focus going forward. In FY '24, we laid the foundation for success through strategic restructuring, streamlining our go-to-market approach, deeper inspection and continued operational excellence. As part of our transformation, we also refined and scaled our big deal motion and introduced new product bundles to give our customers comprehensive solutions on a unified, trusted platform.

And we're unlocking customer spend with new channels like AWS Marketplace and driving C-level relevance through strategic collaboration with McKinsey. The adjustments we made are paying off. As Mark mentioned, our deals greater than $10 million in FY '24 grew substantially 78% year-over-year, and we closed 86,000 multi-cloud deals. Our pricing and packaging strategy is driving higher sales and delivering more value for companies of all sizes and industries.

Since launching in April, we've added 3,000 new logos through self-service with Salesforce Starter, a solution for small businesses that include sales, service and marketing with AI and data cloud built in. We're excited by the momentum we're seeing in UEs bundle, which is now called Einstein Edition. It's providing substantial returns for our customers and for Salesforce.

In fact, we continue to see significant average sales price uplift from existing customers who upgrade to Einstein 1 edition. It's also attracting new customers to Salesforce, 15% of the companies that purchased our Einstein 1 addition in FY '24 were net new logos. As you heard from Mark, with our Einstein 1 platform, including Data Cloud and Einstein copilot, we are rapidly infusing conversational AI across our entire product portfolio.

Einstein 1 is a huge differentiator for us in the industry, transforming -- excuse me, as the industry transforms in this AI revolution. It's the fastest and safest way to unlock an organization's data to create better customer experiences, augment employees with AI and drive productivity and improve margins and profitability. Every AI strategy starts with data.

As Marc said, Data Cloud has strong momentum. Data Cloud is approaching $400 million in ARR growing at nearly 90% year-over-year. And in Q4, 25% of our deals greater than $1 million included Data Cloud. Customers like Xerox and London Stock Exchange and Daikin turned to Data Cloud in Q4 to build their trusted data foundations and unlock their trap data within Salesforce.

And we're excited about our future. We just were named, as Mark mentioned, the leader in the inaugural February 2024 Gartner Magic Quadrant for customer data platforms. I met with a dozen CEOs and business leaders over the past few months. and they're all focused on fueling growth and strengthening customer relationships within their current budgets and workforce, and they see AI as the tool to augment their people and drive more productivity.

Companies like ADP, Intel, McLaren and Sonos are investing in Ensign to become AI-first organizations. In FY '24, we closed 1,300 Einstein deals, as more customers are leveraging our generative and predictive AI capabilities. Take Scheiner Electric. They want to standardize and simplify customer care across their 3,000 support agents, speaking 15 different languages around the world. Instead of talking to customers, service agents were spending way too much time searching for answers across different systems and summarizing cases.

Dealing with 7 million cases per year leads to time-consuming interactions for their support agents. Now Einstein will automatically create e-mail replies that agents can use to respond and summarize their cases. With the Power Mines 1, Standard Electric support teams are already seeing a 15% increase in case efficiencies. And it's not just their service agents, their sales teams are also seeing incredible benefits from our AI capabilities.

We're just at the beginning of a new innovation cycle that will spark a massive software buying cycle over the coming years, and Salesforce is leading the way. We continue to see strong demand for our data products as customers lay the foundation for AI, specifically, MuleSoft is helping companies such as Rasingall and Teekay Elevator in North America bring together their data from any source a critical step to prepare for AI.

MuleSoft was in 8 of our top 10 deals in the quarter and executed a record $319 billion workflows -- automated workflows every month, up 100% year-over-year. Tableau was in 20 of our top 25 deals in the quarter and is fully integrated to Data Cloud. Wins in the quarter included customers like IHG, Heathrow Airport and Brazilian fintech stone.

Tableau Pulse, a phenomenal new product that's just been released generally available last week actually, already has 2,000 customers, powered by Data Cloud and Einstein, Tableau Pulse automatically delivers personalized AI-powered insights in both a natural language and visual format.

We're also excited about the innovation coming from Slack, which was included in nearly half of our top 50 deals in the quarter. We just launched SlackAI with features like AI search channel recaps and thread summaries to meet the enormous demand for embedded AI in the flow of work from customers like Australian Post and OpenAI. It's amazing to see what Slack has accomplished in a decade.

And frankly, it's just the beginning, we have a great vision for the future of Slack as a conversational interface for any application. Our specialized industry products continue to fuel our growth chosen in the quarter by customers like Japan Post Insurance and TPG Telecom and USDA. Collectively, our industry businesses finished the year at $4.8 billion ARR, up more than 20% year-over-year. We saw strong growth internationally with wins at Volvo and Genpact, Hitachi and Boticario. India continues to be a bright spot for us, growing new business at 35% year-over-year, and we continue to invest in the region to meet the needs of customers, including Bajaj Finance.

I had the great opportunity to meet with our CEO, Rajeev Jain in January, and a top priority for him was using Einstein to deliver predictive and generative AI across their entire lending business, which they run on Salesforce.

In Q4, Bajaj became the second largest data cloud customer globally, building their AI foundation on the Einstein One platform

I want to close by acknowledging that our success is only possible because our phenomenal employees incredible partners, trailblazers, shareholders and amazing customers who have trusted us for 25 years. As we proved in FY '24, when we focus on something as a company, we deliver results and FY '25, that focus is on profitable growth. And with that, I'll turn it over to you, Amy.

Thanks, Brian. Let me join Marc and Brian on saying what a year it has been for sales force. At this time last year, we laid out our accelerated transformation plan, and I am incredibly proud of the significant progress we made this year against that pla. Throughout fiscal 2024, we delivered on increasing profitability, revenue, productivity and operational excellence. Q4 represents another quarter of strong execution and continued discipline across the business.

Now let's turn to the results. For the fourth quarter, revenue was $9.3 billion, up 11% year-over-year and 10% in constant currency. The growth was primarily driven by resilient sales and service performance as well as strength in MuleSoft and Tableau. And for the full year, revenue was $34.9 billion, up 11% year-over-year in both nominal and constant currency.

From a geographic perspective, in Q4, the Americas revenue grew 9%, EMEA grew 14% or 11% in constant currency, and APAC grew 14% or 19% in constant currency. We saw strong new business growth in LatAm, India and Canada, while parts of EMEA remain constrained. From an industry perspective, in Q4, public sector and travel transportation and hospitality, both performed well, while retail and consumer goods and high tech were generally more measured.

Our multi-cloud momentum also continues. In Q4, 8 of our top 10 deals included 6 or more clouds, and more than half of our top 100 wins included 6 or more clouds. As you've already heard, AI starts with data, and we are seeing strong momentum in Data Cloud. In Q4, more than half of our top 25 wins included Data Cloud.

Q4 revenue attrition ended the quarter at slightly above 8%, generally in line with recent quarters. In Q4, our non-GAAP operating margin was 31.4%, up 220 basis points year-over-year. And for the full year, in line with our guidance, we delivered non-GAAP operating margin of 30.5%, up 800 basis points year-over-year. And GAAP operating margin ended the year at 14.4%, up 1,110 basis points year-over-year.

Q4 operating cash flow was $3.4 billion, up 22% year-over-year. Q4 free cash flow was $3.3 billion, up 27% year-over-year. And for the full year, operating cash flow was a record $10.2 billion, up 44% year-over-year. Full year free cash flow was $9.5 billion, up 50% year-over-year.

Now turning to remaining performance obligation, RPO, which represents all future revenue under contract, ended Q4 at an incredible $56 billion, up 17% year-over-year. Current remaining performance obligation, or CRPO, ended at $27.6 billion, up 12% year-over-year and 13% in constant currency, particularly driven by strong execution on early renewals. We also benefited from new business performance and timing of license revenue from MuleSoft and Tableau. As expected, this was partially offset by a 1 point headwind from professional services, which we had noted last quarter.

Now let's turn to guidance. Starting with full fiscal year '25. On revenue, we expect $37.7 billion to $38 billion, a growth of 8% to 9% year-over-year. A few items to note on the revenue guide. Our expectations incorporate a $100 million FX headwind year-over-year or a 30-basis-point impact. We also expect our professional services business to remain under pressure in FY '25 and expect it will be a headwind to revenue.

Within our revenue guidance, subscription and support revenue growth is expected to be slightly above 10% year-over-year in constant currency. As a reminder, our top line expectations include the impact from the measured buying environment that began back in fiscal year '23. This takes time to flow through our subscription revenue stream due to the lag effect of bookings to revenue recognition.

That said, we continue to execute well in the measured buying environment. Over the past 2 quarters, I'm happy to say that we've seen improved bookings growth. And as you heard from Marc, we're incredibly well positioned to build on our success and bring our customers into this new AI era. Now turning to attrition. Starting in fiscal '25, we are including Slack invoice in the metric. Despite expecting a modest headwind, we expect attrition to remain consistent at slightly above 8%. On margins, we continue to drive operational excellence, productivity and efficiency. And for fiscal year '25, we expect non-GAAP operating margin of 32.5%, representing a 200-basis-point improvement year-over-year, while still making key investments in growth opportunities, notably AI, data and our core businesses.

Stock-based compensation is expected to be below 8% as a percent of revenue as we continue to take a disciplined approach to our equity-based program. As a result, for the fiscal year '25, I am pleased that our GAAP operating margin guidance for the first time is expected to surpass 20% at 20.4%, representing a 600 basis point improvement year-over-year. We expect fiscal year '25 GAAP diluted EPS of $6.07 to $6.15. Non-GAAP diluted EPS is expected to be $9.68 to $9.76.

As a result of our focus on profitable growth and continued transformation, we are seeing a market improvement in our cash flow outcome. We expect fiscal year '25 operating cash flow growth of approximately 21% to 24%, which includes a 10-point year-over-year headwind from cash taxes.CapEx for the fiscal year is expected to be slightly below 2% of revenue. This results in free cash flow growth of approximately 23% to 26% for the fiscal year.

Now to guidance for Q1. On revenue, we expect $9.12 billion to $9.17 billion, up 11% year-over-year in nominal and 12% in constant currency. This includes a headwind from the timing of license revenue in MuleSoft and Tableau, Additionally, Q1 has a 1 point benefit from an extra day of revenue recognition given the leap year, which has no impact on our full year revenue or CRPO.

CRPO growth for Q1 is expected to be 11% year-over-year in nominal and 12% in constant currency. For Q1, we expect GAAP EPS of $1.42 to $1.44 and non-GAAP EPS of $2.37 to $2.39.

Now to capital return. We are deeply committed to driving free cash flow and return to our shareholders, while investing in new organic growth initiatives. In Q4, we returned $1.7 billion in the form of share repurchases, bringing the total return in FY '24 to $7.7 billion or more than 80% of fiscal year free cash flow, which more than fully offset dilution from our stock-based compensation. Since the inception of our repurchase program, we have now returned $11.7 billion to shareholders, with an average purchase price of $182 per share.

And I'm incredibly excited to announce our first ever dividend. We are enhancing our capital return strategy reflective of the confidence we have in the future of our business and our ability to drive long-term cash flow. Our Board has approved the initiation of a quarterly dividend starting at $0.40. More details of this dividend are available in our press release.

Additionally, the Board has approved a $10 billion increase to our share repurchase plan, bringing the total authorization to $30 billion. Based on our progress to date, the remaining balance in the program is approximately $18 billion.

In closing, I want to echo Marc and Brian. This has been an extraordinary year. I'm very proud of the progress we have made throughout the company. We are executing with discipline, while also investing for our future. I want to personally thank our employees who have worked so hard this past year and thank our shareholders for their continued support over this past transformational year.

Now Mike, I think we better open up the call for questions.

[Operator Instructions] Your first question comes from the line of Brent Thill with Jefferies.

Marc, last quarter, you had said that you're starting to see some green shoots, and we're not ready to say you completely turned the corner, but I'm just curious if you could give everyone an update in terms of just what you're seeing from customer behavior? And ultimately, how you think that plays out through the year?

It's a great question. And I think Amy will go back and say, it was really this kind of moment in the middle of fiscal year or whatever it was '23 where we started to see this kind of weird behavior. And then I would say, starting -- last quarter, like you said, we saw these green shoots, and now I would really say it was kind of a 180. It's really that AI, every customer realizes, number one, they've got to start a major investment cycle if they're going to remain competitive. Every customer is trying to achieve more productivity.

I think we all know what that means. We certainly do. We've had to achieve more productivity ourselves over the last year. And they -- that is really about, in many cases, augmenting your employees. A lot of you've heard my Gucci story. There are so many stories. There's going to be so many more stories where these tools, all of a sudden, really start to deliver much more productivity, better customer relationships and higher margins CEOs get that. I think that is driving the 180.

Obviously, we're also in the third phase of the pandemic. The first phase we all went through together. It was horrible. It was my first pandemic. I had never been through anything like it. Then all of a sudden, we're in the post-pandemic, where we were in this crazy interest rate and inflation environment.

Now we're in the third phase, post-post-pandemic. And in post-post-pandemic, things are just better. Not just because we're going through this technology search, but because all this other stuff is behind us and we're in a new normal and people know, "Hey, we need to invest to grow. We need to invest in technology to grow."

And that, I think, is really driving the $180 million for our customers, for ourselves, I think for a lot of you, we can all see it in the equity markets. That is not the equity markets that we had in 2021. So we are in a new place and we are ready to deliver. You're going to have -- you can be the judge yourself. When we get to TrailerDx, I hope that you're all going to -- most of you have my text and e-mail, Then email me and tell me what you think. Because if you see anyone else being able to deliver on the promise of enterprise AI at the level of quality and scale and capability of Salesforce, I'll be very surprised. And this is driving through different geographies or different product portfolios, green shoots. Brian, I want in here and talk about these green shoots, but really the 180 that we're seeing...

Yes, I really appreciate it. And we are seeing tremendous demand for data cloud and for AI. I do think, Brent, that we are still operating in a measured environment. And we are still having to ensure that we're doing the deep inspection and managing the business very tightly in the way that we have over the past 6, 7 quarters in this environment.

The green shoots around data cloud, around MuleSoft, regional performance that we've seen, have been really outstanding in Canada and LatAm and Spain. I mentioned the India performance on the call. Our focus on industries is really paying big dividends. So we are seeing parts of our business really accelerate, but there certainly are some -- still some measured environments out there that we have to continue to take into account the way that we manage this business.

Amy, I think you should come in here and also talk about how you've seen the transformation of the business and the green shoots that you see happening or kind of the 180 that I'm talking about.

Sure. It's been an incredible couple of years. Mark, as you mentioned, going back to really the beginning of July in fiscal year '23, where we suddenly saw this measured buying environment, the elongated sales cycle, the additional approvals, the compressed deals.

And over the last few years, what I've really seen is not so much a shift in the buying behavior, but a shift in our ability to execute. And I think we've seen that over the last couple of quarters, in particular, that we are just executing much better in that. I do think that there is a lot of excitement to come on AI and data, and we'll see how that plays out this year.

Your next question comes from Keith Weiss with Morgan Stanley.

Excellent. Congratulations on another really nice quarter. A question just on sort of buying cycles and sort of the timing for this AI goodness to kind of come into the numbers. And maybe a question for Brian.

How should we think about how customers are ingesting this, right? Like how are they purchasing the Einstein platform? Does it start with Data Cloud and then they move into more of the application functionality. And then importantly, how should investors think about when this could potentially impact numbers? When this will become material enough to see the inflection in kind of revenue growth?

And then maybe one for Amy. Another 200 basis points of operating margin expansion in the guide, super impressive. Can you give us some indications of where that's coming from? Were there be additional areas of leverage that you're seeing in the business?

First of all, Keith, thank you. I really appreciate the question. You kind of nailed it. In your question, we're seeing our customers with tremendous desire to take advantage of AI capabilities to drive the efficiencies in their business, to drive higher margins and productivity, but it all starts with data.

And so you saw some of the numbers that we put out in my comments, Data Cloud approaching $400 billion and growing 90% year-over-year. This should be an indicator of the demand that we're seeing for people to get ready for the AI transformation they want to put their company through.

And so we're really excited about the opportunity ahead. But every customer I talk to says, I've got trap data. I don't have a great data strategy. My architecture is off, and that's why we're seeing such great performance on our data cloud products.

On the AI front, I think we're going to start to see that show up further out in this fiscal year. We don't have a lot of it factored into our guide right now to be candid. -- just because there's so much work that needs to happen.

Now the demand is heavy. And as we just launched this CoPilot product is yesterday's announcement and launch it tomorrow, as you'll see next week at enormous demand for it, and we think we have a massive opportunity to go faster here. And so a big upside, but not a lot factored in here. And I'm going to flip it over to Amy to talk a little bit about some of that.

Sure. So just following up, Ryan, on the comments in terms of the new product. In Data Cloud, we're already seeing this great traction, which is certainly factored in. On some of the gen AI, it's still early. And given the adoption curve, as really our size and scale as a $38 billion company, we're not factoring in a material contribution from these new products into our FY '25 revenue guidance at this time.

Turning on op margin. Yes, really happy to see another 200 basis points this year as a commitment. This year, we are just seeing amazing leverage from many of the hard decisions we made last year. They're continuing to flow through and really benefiting the business. A few things I would call out, a lot of discipline around headcount over the past year. We are starting to grow in some areas at this point, but it's really investing into our most productive areas, AI, data. And we're doing that in a cost-effective way, really trying to leverage areas that have high, high talent pools and low cost.

We're also looking at things like top line. How are we doing with our product and pricing? What are we doing in terms of go-to-market efficiencies? Brian has been great this past year in making changes and drive on productivity. I think you'll see additional changes coming -- digital benefits coming from all of those areas.

Your next question comes from Kash Rangan with Goldman Sachs.

Mark, as you talked -- you talked to a lot of CEOs, right, across all the breadth of industries. What are they saying about their business and their propensity to spend real dollars in Data Cloud with Salesforce? And if that comes through, could the company reaccelerate top line? One for you, Amy.

You seem to sound confident that leading indicators are rebounding. What are those leading indicators. We can't quantify at least. Qualitatively, can you talk about the leading indicators? And how much of a lag is there between those indicators and how they show up in revenue?

Well, Kash, this is -- basically what every software company wants. You want a new killer app. Sometimes you can get it through organic innovation. Sometimes you get it through inorganic innovation. We got lucky. We've done it with organic innovation, with Data Cloud.

I think Data Cloud is everything that we want at this moment for a few different reasons. First of all, yes, it's an incredible new cloud, and we've seen what that kind of can do for Salesforce when we add Salescloud to Service Cloud, to Marketing Cloud to platform. And of course, we also had these other clouds that we picked up inorganically, commerce, Tableau, Slack, et cetera, but this incredible new organic cloud.

The difference with this cloud -- and the difference between what's ever happened with Salesforce before, this cloud makes every other cloud better. So the hot, new exciting version of Sales Cloud, the hottest new feature in Sales Cloud, what's going to transform the tens of thousands of Sales Cloud customers that we have out there that we've been working on building for the last 2.5 decades is Data Cloud and Service Cloud, the new version of Service Cloud is the Service Cloud plus Data Cloud.

And Marketing Cloud read the Gartner MQ. We vanquished all of the other competitors completely with this product because it's so deeply integrated with what we're doing already in everything else in marketing and the platform is extended with data cloud. And if you have this other data infrastructure in your company, any of the BigQueries and the Red Shifts and the Snowflakes and -- I went through all this -- it's made better with data cloud because it unleashes that trap data to your users.

This is a compelling reason to use data cloud all by itself. But that would be if we were not in the greatest transformation of our industry with artificial intelligence, where we so badly need this data. Yes, we always love to have another -- a data lake that we would have loved to have a data lake, integrated with Sales Cloud many years ago.

Okay, we have that. But why is it more important right now? Yes, we have the data lake. We have the repository, we have the warehouse, but now it has deeply also integrated into the AI. That is why every customer must buy this product if they are going to achieve the Nirvana that we can see for businesses, the trinity that we talked about, productivity, customer relationships, margins, when you get data and AI working together.

We can do it. This is our message to our salespeople, to our partners, to all of you. This is an incredible moment. That is why we have to execute like hell this year. Fiscal year '25 needs to be one thing, the year of Data Cloud.

Okay. Great. And Kash, thanks for the question about leading indicators. I think first, you obviously heard the excitement about data cloud. If you didn't...

I can go through it again. You have it. I'll do it one more time.

Let's just start with that, but I'm looking at a leading indicator. So specifically, there are a number of things that we look at that tend to be leading indicators that things may not be as good. Now that would be something like create and closed, SMB, self-serve. I've talked a lot about those over the past few years. But I do feel very good about some things I'm seeing right now.

It is the execution from our team, and we've really seen this over the past 2 quarters, and that's really led to improved bookings growth. we think AE productivity, that is up. Brian talked a lot about that last quarter. It was fantastic. We look at our pipeline for indications going forward.

That said, as we talked about our top line expectations do include the lagging impact from the measured buying environment that began a couple of years ago. It's just going to take time for that to work through our system, but I am seeing some nice indicators that give me a lot of hope.

Your next question comes from Karl Keirstead with UBS.

Okay. Great. Maybe a 2-parter for Brian. Two elements of the business that I think you have a responsibility for. One is around pricing and bundling and you mentioned Einstein 1. Just curious, when will that be a needle mover for revenues? How much of that uplift are you baking into the guide this year? And then also on the pro services side, typically not a focus area for anybody on this call, but down 9% in the quarter was obviously an inflection down. What's happening with that? Is that tight discretionary spend? Or is that Salesforce consciously pushing more work to our SI partners?

Okay. So before you hit that, I want you to hit the service, but before you -- when you think AI and you think -- obviously, we all know what ACV is. I think it's basically a term that we created. Now it's industry-wide, AOV CSM, Brian, you created that.

ACV, this year, we obviously have huge goals internally, okay? A material part of this ACV needs to be data cloud. This is important. This is the AI number. This is everything that AI, Einstein 1, the artificial intelligence, data cloud, we have to bring this all together. That's why we call it Einstein 1. Look at the Einstein 1 SKU. Look at what we call UE+. That is where you're going to see the material ACV traction. That is our focus intention.

Of course, we don't know what's going to really happen. But when we got all of our -- we did a huge kickoff last week in Vegas. We brought 5,000 of our top executives, most -- 80% for sales. We had 70,000 online. We have one message to them.

Data Cloud, #1 data cloud, #1 AI, become a great storyteller about these stories, number two. Number three, sell UEs cell Einstein 1; number four, deliver the customer success, number five, our incredible new OHANA 2.0 culture. These are the 5 things we're doing this year. So it's deeply integrated with that, and that this absolutely must be part of everything we're doing. But when you think AI, I think Data Cloud. Brian?

Thanks, Marc. Karl, back to your question. On pricing and bundling, we're excited about the progress we've made here. UE Plus is a good example of what we're seeing. Good acceleration. It's not the only thing we're doing in pricing packaging. Obviously, we did a price increase last year and seeing some benefits to that, certainly.

We're simplifying the way that we are putting quotes in the market, fewer SKUs, making it easier for our sellers to get out there. In terms of materiality in the short term, you're not going to really see it show up. We did in the second half of last year. And so while we've seen great progress and there's a lot of promise for it, in terms of this year's revenue guide, not a huge factor in our growth numbers this year.

You will see it start to show up in year 2 and 3 as we roll through the renewals, the uplift, et cetera, and some of the incremental pricing changes that we're going to do. On ProServe, A good question. I think the big issue, and it's really been felt across the entire professional services industry, a bit of headwinds on customers' willingness to do massive transformation. We really felt that during the pandemic that customers were coming to us and saying, "I want to make a multiyear commitment to your services and spend significant amount of money. These very large transactions and services.

Now our customers are saying, hey, let me take a bite -- smaller bite at the apple. Let me start smaller to time to value faster. Let me get the benefits of the technology sooner. And so while the demand remains high, it's just smaller transactions that are getting done vis-a-vis last year and the year before that. So the tough compares on large deals, smaller transactions. For us, in a lot of ways, very good. Let's get our customers proving out the technology. Let's go faster, but having an impact on our professional services business right now.

Your next question comes from Mark Murphy with JPMorgan.

For Amy and Brian, the gross margin and sales efficiency metrics are quite strong this quarter. And so I'm curious just from a standpoint of eating your own dog food or drinking your own champagne, have you been able to realize any benefit from deploying either service GPT or sales GPT internally to save time for your own customer support agents or your own sales teams? I'm just wondering if you're -- are they suddenly becoming more productive or able to do more with less already?

Yes, Marc, thank you. We are a big believer on sales on Salesforce. We are deploying our own AI technology internally. Our sales teams are using it. Absolutely, we are seeing benefits right now. But the biggest benefit we've seen actually has been in our support operation, with case summaries our ability to get -- to tap in a knowledge base is faster to get knowledge surfaced within the flow of work.

And so it absolutely is part of our margin expansion strategy going forward, which is how do we leverage our own AI to drive more efficiencies in our business to augment the work that's being done in sales and in service and in marketing and even into our commerce efforts as well. So we're excited about the future there as well as leveraging our own technology to drive those efficiencies.

Amy, I don't know if you have anything else to add to that?

No. I think that was great, Brian. We have to be customer #1 and use it, and I'm excited that we are. Lots of opportunities for us.

Your next question comes from Kirk Materne with Evercore ISI.

Congrats on a great fiscal year. I don't know if Brian or Marc wants to take this one, but we realized AI is applicable to every industry. But I was just kind of curious, are there any industries that you believe are farther along in terms of taking advantage of AI, where there, frankly, could be a domino effect due to the competitive advantage? One customer could get over another, if they don't start down this path?

A very good question and unknown. I mean this is the future -- look, does anybody really know what is going to happen? I mean we saw a Minority Report War Games. It was written by our futurist, Peter Schwartz at Salesforce many decades ago. We've seen the movies.

Her terminator, is this our future? Do we really know what's going to happen? Look, at the end of the day, we all know that everything is underway with AI. The future is unfolding between our eyes. And we all remember the Minority Report scene when Tom Cruise walks into the Gap store, and the whole store turns into a highly personalized experience. And the digital sales agents and the human sales agents all start talking, "Oh, we've got this jeans last time. You need to buy the new jeans this time." Listen, if I go into the Gap store right now and I love the Gap, amazing new CEO, San Francisco company, fantastic, incredible, worked with him at Mattel, but the store has not yet transformed into the Tom Cruise scene. We know that, okay? But great products, great brand, great company, great lineage, just great founders.

Okay. We are on the verge of something huge happening for all of our customers. We have to be driving that. We think we have the solution. This is going to happen. We also need to be guiding it with the right values. We all know that. We have to have the right core values.

I went to this AI Safety Summit, not enough focus on values. The value is not just the woke values that we're seeing in these filters, which are horrible, but the values of trust. And that story I told you on the script. When I saw that last week, I'm like, I'm putting this in the script, that this company, which is a great company and a customer of ours, but did not use our technology, went out there and used some kind of rogue AI that they picked off the Internet.

Some engineer just hobbled it, hooked it up, and then it started just skewing these hallucinations and false around their loyalty program, and the courts are holding them liable. Good. Let every CEO wake up and realize, we are on the verge of one of the greatest transformations in the history of technology, but trust must be our highest value.

And that is why at Salesforce, we are going to lead this not just with great technology like you see. But also, and I just put on my Twitter feed, I hope you see at the top of my Twitter feed, the results for the quarter, but please watch the 5-minute video that's on the Twitter feeds. You can understand coming into TrailerDx, what we are delivering with AI, a trust-based AI for enterprises built on our data and metadata. This is what's truly important.

Great. Thanks. Bernda, we'll take our last question now.

Your final question comes from Brad Zelnick with Deutsche Bank.

Listen, great to see the data cloud traction, the recognition of Gartner's Magic Quadrant. And Marc, I appreciate you taking us into why the architecture is different from general purpose data platforms and that it brings together the data and the metadata.

But my question is a 2-parter. A, it's clear data cloud is optimized for customer data and customer-related apps, can you take it beyond that? And then, b, how much of the customer base today is really viable to take Einstein 1 on and UE Plus a 50% higher list price point? And how far penetrated are we into that?

Well, I'm going to do the first part, and then I'm going to turn it over to Mike Spencer to do the second because he not only has run a IR, but he also runs FP&A, and he's been doing that analysis. So I know he was going to come in on this.

Look, number one, this is a huge upsell opportunity for us. You probably know, I think not even 50% of our Sales Cloud user, use Service Cloud. Not even 50% of our Service Cloud users use Sales Cloud. Maya Copa, that is on us, okay? I wish I could say that all of our sales users are service users or service users or sales users, but even ADP that I talked about in the script, who we've worked with for more than 2 decades.

And I remember the first time I made a sales call there, to extract Siebel from their infrastructure. Was not yet using us for service. So we have a lot of work to do to sell our existing clouds into our customers and also to upsell our existing customers and cross-sell them with Data Cloud, with Einstein 1, with the full platform, we're rewriting our whole platform to be deeply integrated. We will no longer have all these separate acquired platforms.

When we're done, we have one integrated platform, Einstein 1. One unified data and metadata platform. This is something I have deeply focused on in the last year to make sure it's clear to all of our engineers and are also financed that this must be funded, which it is.

And then we will deliver this capability and then we will light up and give you these great success stories. Look, some companies operate at the highest level of the user in the productivity level. That's not where we are. Okay.

Some companies, okay, they operate maybe at the model level. That's also not where we are. We are a data company. We operate at the data level. Yes, we're about customer success, made possible by data. This is an AI revolution. It's a data revolution. There's no question. You cannot have the AI without the data. That's why those AI companies stole all that consumer data, so they could have some semblance of these party tricks.

For the enterprise, it's not going to fly. You've got to have these comprehensive data sets that are informed by the metadata. And Mike is now going to answer the second part, and we'll wrap it up. Mike, go ahead.

Brad, thanks for the question. I think the way to think about the price uplift moving to Einstein 1 addition used to be a limited edition plus, is really about the value that we're providing to our customers because at the end of the day, our ability to get increased price is about the value that we're going to provide.

And so as customers start to ramp up their abilities on AI, ramp up their learnings and understand what it means for them economically, our ability to get price will be dictated by that. Early signs of that are pretty strong. We feel good about the progress we've seen. It's only been in market for 4-plus months now in FY '24, but we're encouraged by what we're seeing. But at the end of the day, we're trying to make it as simple as we can for our customers to buy it, but it's going to be predicated on the value.

I agree. And just one last comment for us it's Brian. We want to be able to deliver data cloud and AI at all levels in all segments. And you see that in our offering around Salesforce Starter, where we're building in AI and data cloud capabilities as part of that. So every segment of our customer base should be able to enjoy the power of AI and Data Cloud.

So thanks for the question, Brent. And we thank everyone for joining the call today. We look forward to seeing everyone over the coming weeks.

Thanks, all.

This will conclude today's conference call. Thank you for joining us. You may now disconnect.