Salesforce, Inc. (CRM) Earnings Call Transcript & Summary

All right. Thank you, everybody. Marc Benioff, in case you're listening, we actually have more people this time than we had for you last year. I hope you're not listening actually. I didn't say that. This is a fact. It's a fact. Real delight to be able to host Brian Millham. Brian's title is President and COO. But when I ask people, Brian, I've known you forever. We've not really sat down on stage together. First of all, welcome to your very first Goldman Sachs Communacopia & Technology Conference.

Thank you. It's great to be here.

And it feels like I've known you forever, since the beginning of time, since the...

Not that old.

But time's very transient, right? So I think I saw you at the very first Dreamforce, 2002 -- I think 2002 or 2003. And finally, this is the day that we get to host you, so thank you for coming. And if you happen to do your due diligence on Brian, I think you'll hear a term, presidential. So you've been termed presidential. And also people say that you're the kind of guy that will run through a brick wall for. So I don't know how you developed that reputation so whatever, this is fantastic.

Well, thank you for that. Appreciate it.

So good to have you here. A quick introduction. How long you've been at the company? I think it's 25 years?

Sure, yes. No, 24 years at Salesforce, 24 years tomorrow, actually.

Congratulations.

Yes, thank you. Currently operating as the COO of the company, running sales, our service organization, support our success teams, alliance and channels and recently took over our HR function we call employee success. IT CMO now works for me. Just hired a new CRO, so a lot of functions around the business now rolling up through the COO.

That's great. The only thing that doesn't report to you is financials, right?

Well, product, too. David Schmaier runs product, and Amy, obviously, is the CFO.

Yes, excellent, yes. So Brian, let's talk a little bit about what has happened in the last 12, 18 months. So with that in mind, as you march forward, we can talk about the past a little bit, but I'm more curious to see how -- since you've been at the company for a very long 24 years as of tomorrow, how do you see the next 4 to 5 years playing out for Salesforce?

Great question. Hard to see beyond the next couple of quarters here. We've seen a lot of change in the last 12 months, obviously, at the company. Our focus is going to continue to be on customers. We're going to put the customer at the center of everything that we do. Obviously, we're very excited about where we're headed from an AI perspective. Big investments that we're making on the AI front, but also making big investments in data as well. Very important that we start with the very complex world of data so that all of your AI that layers on top of it can be as effective as possible. So hard to see 5 years out, but I know if we are sitting here 5 years from now, I would hope that our customers would be depending on us more for delivering technology to help drive their efficiency and growth and that we'd have even deeper trusted relationships even more than we have today. And so that would be my hope for 5 years from now.

You're welcome back in 5 years and in the intervening periods as well. Many have asked me, so why are you doing your conference like right after Labor Day? I tell them, you got to ask Brian Millham why. Because Dreamforce conference is next week.

Yes. It's unbelievable it's next week.

Can you tell us a little bit about Dreamforce? Not that it was something I had in my mind but just since we're in the topic of Dreamforce, what can we look forward to next week?

Yes. Marc called it the biggest AI event of the year. We're going to have some of the greatest minds around AI in the world joining us for Dreamforce. And so we're excited to tell a story. Many of our customers are looking for us to help guide them. We want to be a pioneer in the AI space and we're doing that next week. Very focused on the trust element of AI, and you'll see that threaded through the entire conference, ensuring that we are delivering on the expectations our customers have for us around being the most trusted enterprise in the world.

Excellent, excellent. So let's talk about the macro picture a little bit. Our chief economist, Jan Hatzius, presented yesterday. He lowered his recession odds from 20% to 15%. He's been largely constructive on a soft landing. In fact, we're going to call it a software landing. That's patented, in case some of the sell-side firms are listening to this. Software landing is Goldman Sachs terminology. So he's been calling for a soft landing. And given your perspective, you practically talk to the whole world. I mean you have a customer base that's one of the largest in the industry. What is -- what do you observe to be customer behavior with respect to spending on technology? It looks like the recession that everybody has been waiting for, waiting for, waiting for, it seems to be dodging us. So what are -- when are customers going to wake up and say, I need to do the right thing? So where are we in that cycle?

Well, I'm not an economist. I'm thrilled to hear that, that is a possibility, that we're seeing less likelihood of a recession coming our way. Based on my experience and what we've seen over the last couple of quarters, we're seeing the same tough environment that we face, a very measured environment in the markets out there. Deals that we used to get done would sort of sail through the process, constrained, more deal approvals, more layers to get through, smaller bites at the apple on the transactions. And so we're factoring that into all of our guidance going forward. I hope you're right. We have to be a little bit thoughtful about how we're guiding for the rest of the year. And so we're predicting that sort of same thing for the second half of the year. If we're -- if I'm wrong and we're wrong, then great. It's upside. But for now, we have to be thoughtful about what we're doing. We've changed a lot of the way that we operate as an organization, knowing the environment that we're operating in obviously. And so our sellers being much more thoughtful about justifying spend, very value-oriented in the way that we're selling. We're making all the enablement changes that we need to and having good impacts. You saw the results. We're happy with where we ended up in the quarter, but it's certainly harder out there than it was, say, 18 months ago or 2 years ago. And so our -- my view of it is sort of stabilized but still very difficult to be out there, not any better, not any worse. We've got to continue to operate in that market.

Stability is good. That's what we've heard from a lot of other management teams as well. So what are customers saying about their budgets for calendar '24??

I mean, I think everybody is trying to figure out how they take advantage of AI. My guess would be many of them are looking to sort of, in their same envelope that they have, find ways to spend in this AI world. We're very hopeful that, that will happen. Budgets on software, again, probably stable to what they're doing. We see many CIOs are saying, we want to invest in AI, we want to invest in data strategies, but many of them have also told me that their budgets haven't gone up. So it's a trade in an envelope on an existing spend that they're going to have to find dollars to spend to go make it happen.

Got it. [indiscernible] works with me on Salesforce.

Yes. Thank you so much for spending the time with us. We really appreciate it. And so to jump in here around AI. I think it's a great segue to talking a little bit about the AI Day that Marc and you and the team hosted a few months back and maybe talk to us a little bit about the customer conversations that you've been having since then. How are they thinking or framing that productivity unlock that they can reach? And maybe what are the hesitations or even technological challenges that they're facing?

Yes, it's a great question. Every conversation we're having with customers these days seems to be anchored in AI. Everyone wants to take advantage of it. Two things that I think are top of mind for every CIO and CEO that we're talking to, number one, is my data in a place where I can take advantage of it? And have I managed it appropriately from an architecture perspective over the many decades that we've gathered data? And typically, the answer is no. So we're very excited about the fact that we have a product that can go help our customers bring that data together, harmonize it and then leverage the AI on top of it and get the great insights and the efficiencies and the growth that's required. The other piece is trust. So many of our customers are concerned about trust. The big part of their hesitation is, hey, how do I know that when I leverage your AI, it can be trusted and we've delivered a trust layer as part of our offerings out there? Many of you know trust is our #1 value as a company. It's how we started the company 24 years ago, now 25 years ago, I should say. It is core to who we are and how we have to operate. But trust is top of mind for all of them. And so we'll continue to educate them. Next week will be a great opportunity for us to talk about what we're doing around the trust of their data, ensuring that they can remain in compliance and that their data does not float outside their enterprise. And so we're excited to showcase that next week.

Yes. No, that's super interesting and also thinking about the prior cycle of AI and thinking about Einstein versus the new GPT [ set of ] features that you're releasing. How -- where do you think we are in that process and in that cycle of even fully embracing Einstein and then how GPT is different than that?

Yes. So 10 years ago, we started making investments in AI, all predictive. We do 1 trillion transactions or predictions a week for our customers today. Marc made fun of me on the earnings call, I think, talking about how we use it internally to guide us on forecast in a given quarter. All the inputs around our pipelines, close rates, geographies, products that we're selling, size of deals, all inputs to our predictive Einstein product that gives insights to where we're going to land in a particular quarter, that's been part of our offering, embedded in our technology on the sales and service side, marketing for over a decade. We're very proud of what we do there. It's very exciting to see who's more accurate, me or the Einstein guidance in any given quarter.

And who has won so far?

It depends. As Marc would tell you that I'm -- he called me a sandbagger on the call, which is an indication of what he thinks about the Einstein capabilities. But that's always been part of who we are. And I think the next generation will be very interesting as we start to deliver generative AI. We see so many use cases out there in the customer base where they're going to get tremendous efficiencies from what they do. I'll give you an example of things that we're talking about internally where when we use generative AI as an example and customer adoption of our technology, unbelievable that we can see all the insights, all the signals around how our products are being used and also leverage things like, hey, are these -- is your clients showing up to events and know that information about -- give predictions around the health of a customer in the future? Could we also be generating a success plan, a proactive outbound to a customer that says, you should take these 15 actions based on our information that we see and the way that you're using our technology automated for our SMB customers where we can't dedicate resources today. Could we do that through a generative effort that drives better outcomes for our customers, higher success in the use of their technology, better efficiencies and growth and also better results for us from a retention perspective? And so we're very excited about the use of generative. We think internally, we can use it, and many of our customers will be leveraging the technology to drive results for their customers.

So on that, the internal use cases, how have you deployed your own technology? What are the kind of -- because you are the ultimate test case, right?

We're deployed. As you know, we released our product on July 19 for Sales GPT and Service GPT. And so everyone wants to know the results. We're still early innings. It's not -- we don't have a ton of deep knowledge yet, but we're seeing some efficiencies in the sales organization right now around e-mail generation. On the service side, case resolution happening very quickly. Even on our engineering side, seeing some efficiencies in the way that code is written. And so we're already seeing the benefits of our own technology there that's being leveraged inside Salesforce.

And how about the marketing domain? Is there any efficiency, productivity gain?

Of course, there will be many there. Just released -- in fact, I don't know if it's released or coming out at Dreamforce. I have to go back and check, but it's either been just released or will come out next week. Content generation, as an example, more personalized e-mail that's being launched. There's a lot of great use cases on the marketing side.

So Brian, which brings us to more of a macro question, the effect on the labor market. I mean, have you thought about whether this efficiency gain might actually go forward the other way and constrain the number of salespeople and marketing people, service people?

Yes. There are a lot of people who are in this camp of, hey, how many heads do you take out of a business? I run our call center. A gentleman in my organization runs a call center for Salesforce. And I've never seen a call center that was overcapacity. In fact, almost every single one of them is undercapacity. I actually think we can automate a lot of work, a lot of the generative can happen within the call center. And the people that you have end up adding more value, doing more complex work. They're -- the work they're doing is more fulfilling for them, in my opinion. I'm not a big believer in, hey, in the next year, you're going to see completely autonomous call centers and no one's in these call centers. I think humans will always be in the loop, particularly as it relates to our world of customer success, empathy that we show to our customers, judgment that has to be used in engagement with your customers. I think we have a long way to go before we see a completely autonomous call center in the world that we operate in today.

And touching on that really quickly, just pulling on that thread around productivity and seat base, then thinking through the go-to-market for these generative AI solutions, right? So they're not necessarily just out of the box. Maybe some will be, right? But I think that it would be helpful if you walk us through the data cloud and the other components that will really unlock that productivity and the usability of that within Salesforce. And I also think you're using maybe some consumption element to the seat base. How is that different from the other core products that you've been going to market with?

Yes. The pricing models are going to have to change and shift a little bit as we get into this generative world. One, we don't exactly know how the products are going to be used. What are the use cases? What is the demand going to be for the generative products? Again, we're early innings here. We've designed a pricing model that is fixed base. You pay for a certain amount of licenses to get the technology, and then there'll be a consumption component of it as well. As I think all of you know, the cost of delivery of some of these technologies is very high, and you have to make sure that you're managing the cost side of the equation as well. And so we want to make sure, as our customers drive tremendous value from it and they're using a lot of your CPU power, that you're ensuring CPU power, you're ensuring that you're able to monetize that through the consumption models. We have many consumption products today. As an example, our commerce product is consumption-based. MuleSoft is a great component of our C360 offering is consumption-based. So we have models today that we can leverage and great learnings from those. So we're early and we're learning. We're taking a lot of input from our customers right now around these use cases, how they want to be leveraging the technology, and we want to make sure we have the agility and flexibility to meet their demands with the pricing structures going forward.

All right. Back to me. How does that change the go-to-market, the shift towards consumption? As it introduces -- is it introducing new complexity or is it going to be less friction?

I mean it's really interesting. I've gotten the question a couple of times around, hey, in a world where you're consumption-based, do you need to move and design different go-to-markets? Our orientation around customer success has always been there. Adoption has always been a core part of how we orient to our customer engagement. Consumption is obviously a component of customer success. If you see the consumption going up and to the right, then you're driving value for your customers. And so we believe that these products are great add-ons to the existing footprint our customers have. I am excited about the fact that we can go sell these Einstein products, these AI-based products, GPT-based products to our customers use for sales and service and marketing because it's in the flow of work. We believe that the engagement model, the insights, the actions that will be taken will happen in the sales environment, in the service environment, in the marketing environment. And so -- and kind of where the customers want to see the insights happening. And so we're very bullish on our strategy around multi-cloud. We've got many strategies around growth. Industry is obviously a big play for us. International is a big strategy for growth. But this multi-cloud opportunity with new innovation that's coming around Data Cloud, which is the fastest-growing organic product that we put in the market...

Tell us more about the Data Cloud. Everybody -- even Marc is like so buzzing about Data Cloud.

I think it really is an indicator of how important data has become for a company. The insights that you get around your data, all the customer information that you have, it's sticky work, it's hard work. But if you get it right, then you get the insights around it. Data Cloud is the product that we put in front of all of our AI technology today, allowing you to ingest all the data around your customers in a single data lake and then use that to power all of your AI technologies. And so interesting that we're talking a lot about AI, but the product that we're seeing a lot of traction with and great growth in the organic -- the fastest organic product that we've ever put in the market today is Data Cloud and so a lot of momentum around that.

And just what you said, there seems to be a little OpenAI, some Snowflake, some Databricks and some Salesforce, that's fascinating. I listened to Frank Slootman and Jensen Huang do a fireside chat a month ago or so at their conference, and they were talking about the value of structured data in an AI world. And when everybody is excited about generating poetry and images and videos, whatnot, I think the takeaway from that discussion was structured data is where really it's at and there's so much value in the structured data. How do you guys think about the -- I've always been fascinated by my view, and perhaps you'll agree, that you have probably the most valuable data on the planet when it comes to purchasing intentions, commerce. It's real transactional data, not intent necessarily alone. So how do you think, in an AI world, the company can leverage this -- the treasure trove in conjunction with all these new technologies that we're working with?

Well, we're about to find out. We agree with you. We think data is the currency of the enterprise today. We believe that data is hugely valuable. It sits in Salesforce today. We have the privilege of managing all that data for our customers, and they really look for us to help guide them in this AI world. Those things all combine to be a great value offer for our customers around Data Cloud and our AI offerings. And so Slack is another example of a ton of information that's floating around companies today that we get to capture, that they want to capture, our customers want to capture and make sure they're getting the best insights about best next product to sell or how do we go drive a better engagement from a success perspective in our call centers. How do we build better content from a generative perspective in your marketing campaigns? How are we more personalized in the way that we're showing up in front of a customer or a consumer with an e-mail that drives better conversion rates? Those are all things that we're excited to drive for our customers.

That's great, that's great. The Customer 360 framework, how does that work with the Data Cloud? Is there a bearing for how -- because this is the idea that the entire industry has been working towards a common view of the customers. You guys have been on it for multiple years. Where do we stand with the Customer 360 strategy?

Well, it's -- the beautiful thing about -- one, I think you heard us talk on the earnings call about more on core. We're bringing more of our technology on a single platform, our core platform, Marketing Cloud, Commerce on core, along with Sales Cloud, Service Cloud, our platform to get that single source of truth around the customer. We want to put the customer at the center of everything, all the data in the center of the C360, and Data Cloud becomes the repository of all that data. It doesn't mean it's just the customer data that we store either. We're seeing more and more customers bring in data from outside Salesforce into Data Cloud to have better insights around their customers, ingesting data from their financial systems, purchasing systems, whatever it is. We're seeing extreme amounts of volumes of data coming into Data Cloud. And it's all on the single platform, so that data is readily available for any AI strategy that you have.

That's fascinating. Can you tell us any example of a customer that's using the Data Cloud at scale? And you don't need to mention the name, but again, anonymize -- [indiscernible] scale of how this thing is working.

Well, I'll give you one. Salesforce is using Data Cloud extensively internally. And I'll give you the context of it in the lens of our motion around customer success has always been super strong, as I mentioned earlier. And we think we should be capturing more and more data around the use of our -- customers' use of our technology, how often they're showing up at our events, how many resources they have trained, what features and functions are they using. Are they not using [ to dub ] what we call Health Score. There are thousands of pieces of data that we can know about our customers that give us better insights into driving adoption and retention from those customers. It's a model that we've been building actually for the last 6 months and now getting the insights. We're going to launch it at Dreamforce next week. Health Score is for every customer that then they can action and get insights from Salesforce automatically around ways that they should be driving better consumption of our technology, more adoption and what strategies they should be employing to get better outcomes from the product usage, a product that we did not have a year ago now adding value to our customers in everyday interaction and a very exciting opportunity for us.

That's great. Now I want to get to the Street's favorite topic, maybe not necessarily for someone who has been in go-to-market all their life, but margins. Let's talk about margins, a little margins. You guys have done an amazing job. I mean it's unthinkable how quickly you've gone from 20 points of margin to 32 points of margin. So that must have resulted in a lot of change as you went down a path that you've not been. Tell us a little bit about what the transformation has been like, both positives and negatives. And we can talk after that the path forward as well.

Yes. Obviously, you go through a process of structural change. The restructuring that we did in the first part of the year was difficult to go through. Not a fun process to live through. Necessary -- we had to get it done. And the structural changes that we will have going forward, we sort of put those -- that in a bucket of short term, the work that was done in the last couple of quarters. And then we have some long-term structural changes that we're making inside the organization. Impact to the organization, no doubt, impact to our culture, but I feel like we're in a very good place right now. The organization is very inspired by the fact that we have a vision around AI really driving sort of the excitement in the company in new ways. And so Dreamforce, a culmination of that next week. But as we think about the structuring, we really look at it through, for now, 5 lenses, which is, one, how do we make decisions around profitable growth and productivity in the organization? Very important that this sort of guides us is everything that we do is around profitable growth. Kash, you've been around us for a long time. We used to talk about growth. We're not talking about profitable growth, an important strategy for us. Our prioritization around our product offerings. How do we make sure that we're prioritizing the products in the lens of profitable growth as well? How do we continue to look at the long-term structural changes that we need to make in restructuring this organization, short and long term? Important that we're doing, making decisions, really core decisions each and every day with margins in mind. And this is decision-making around the organization around trade-offs in an envelope. Do we invest in this, do we invest in that is an important part of how we want to operate. Obviously, we want better relationships with all of our shareholders and importantly, stakeholders as well. How do we make sure that we're driving great relationships with all of you out there, that you understand our strategies, where we're going, our focus on top and bottom line growth as an organization. And then finally, we want to -- Marc added in this last earnings call, we want to be seen as an AI pioneer. How do we continue to drive this business forward? We've got a lot of work to continue to do and leveraging automation around this business. I talked about some of the work we're doing in Data Cloud. But there's a lot of manual processes that we continue to automate in this business. I think there's pricing and packaging changes that we can make that can drive better efficiencies in the organization and better [indiscernible].

Can you tell me a little bit more about the pricing and packaging changes?

Yes. We have always been a company that puts great product in the market and lots of SKUs out there, and we dedicate sales resources to them, and we go sell to our customers, a great strategy that worked for us for many, many years. Fast forward to the last couple of years, and we've got a lot of people showing up in front of our customers, and it can be a -- not the best experience for our customers but also not the best experience for all of us internally when we think about the efficiency of the organization. Why not bundle products together that address a particular buyer's need? If I'm selling to VP of Sales, can I have just one seller show up instead of 3 or 4 sellers show up? We can go bundle products together that are much more focused on buyers versus the SKUs that we've put in the market. We can also go to market by the same strategy around verticals. How do we put products together that support our vertical strategy as well? And so my view, big upside as we think about going forward as we package products together that are highly adjacent, that are needed by a particular buyer, and we just go sell them in a single bundle and one single motion, not 5 different selling structures. So that's -- or selling motion. So that's really where we want to get to, in a structure that [indiscernible].

How [ does ] the Salesforce that's not used to that [indiscernible] SKU make the transition? Do you think everybody makes it or some people make it and then you have...

Yes. I mean, I think we're all aligned to what we need to go accomplish. I think we're -- product teams, the finance teams, the selling teams, everyone understands what we're trying to accomplish. Great outcomes for our customers, great outcomes for investors, great outcomes for us. These things seem pretty easy to get aligned behind, not too hard to go out and make those changes if you're solving for customers, investors and ultimately, Salesforce. So it won't be too difficult for us to get through it.

Got it. And before we open up to a couple of questions from our investors, I also wanted to ask you about the boomerang. You have a CRO who is not a new CRO. You have a Chief of Staff who is not a new Chief of Staff. You have a CMO who is not a new CMO. It's funny that when -- I didn't realize that Ariel had left Salesforce. He would come back in his capacity as AWS executive. I never felt that he left. He left but he's back. So talk to us about how you have 2 important functions that report in to you. You've seen coming back of the old guard. How does it feel to the company and how are customers reacting or partners reacting? What's the vibe like?

I think the vibe is great. I'm excited to bring back people who understand who we are, understand our culture, want to be back at the company because they see the future is so bright. Ariel is a good example of someone who went to AWS. Big company, big scale, ran all marketing for them, then left and went to Oracle, big company, big scale. He sees Salesforce as the future of where he wants to spend his time in his career. That's a great sign for all of us, a great sign for our existing employees, a great sign for our investors that people want to be part of this organization, that this is a fast -- the margin piece of this has been hard for us to sort of get through. We're through it now. And now we're in this vision for where the future is going to take us. And so we're very excited about the opportunity to bring back these boomerangs. It's an indication for all of us that it's the place to be.

You said that we have a bright future. Just want to expand -- I'm not going to use the expression double-click and segue, but I'm intrigued by that. So why do you feel the way you do about the future of the company?

Well, 24 years in, I still have a lot of passion about being at this company. Core values of the business remained very strong and consistent over the many years. This vision for where we want to go, the opportunity we have to make a huge impact for our customers, our vision for becoming the most successful enterprise software company in the world, that gets people inspired. People want to be part of a winning team, and it's why we're seeing so many people come back to this organization right now.

That's great. Fantastic. Any questions [indiscernible], guys? We've got a few minutes. Yes, there's one raised hand here at the center of the hall. Before the mic gets to you, you can just speak up and I'll try to...

[indiscernible].

Yes. Are you building your own LLMs or buying it off the shelf?

Good question.

So there's a second part, too, sorry, which is -- so one is kind of how you're powering your own gen AI, right? Is it using some sort of proprietary LLM or one of the off-the-shelf ones? And then the second is, in a world where generative AI capability, the one API call away, how do you handicap the risk of your customers just using the data that they have in Salesforce or in any one of your clouds and generating their own applications on top of that. Because while, to Kash's point, you do have a lot of data, ultimately, the customer owns their own data, and it's not that difficult for them to pass it to an API call, to OpenAI or somebody else, right? So how will you capture that value versus the customer being able to capture themselves?

I got the first question, I'll answer that and then hopefully, I got the second one. We are building our own LLM models and have built them actually. We have some that exist today. But we also believe in being open where you can bring your own model to Salesforce. You can embed it and plug it into the work you're doing on the generative side. We believe there will be models that are specific to industries that will require us to be open. Certain market segments, some geographies are going to want their own models, certain compliance-related issues. So we're going to be an open framework for models going forward. Your second question, I couldn't quite grasp, but I think it was something around, hey, how do you get value if people are passing data to other LLMs. Is that -- was that your question?

Yes. [indiscernible]

Yes. I think it's a good question. Again, I go back to where are you getting -- where is the action happening? You can get the insight, but how are you creating the value for your company? Is it through a better selling motion, a better success motion, a better marketing motion? We believe the value is derived not only from the data but also from what you do with that data, the insights that you have. Do you get better outcomes for your business because your sellers are better, your service people are better, your marketing campaigns are more effective? That's where we think a lot of the value will be derived from these LLMs and the insights on generative AI.

With that -- on that note, thank you so much, Brian. Thank you, everybody.

Thank you.

Thank you all. I really appreciate it. Thank you so much.