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

Thanks so much for joining us here. Delighted to be welcoming Salesforce to the conference. Very fortunate to have Bill Patterson here, Executive Vice President and GM of Customer 360 Applications. Bill, thanks for joining us.

Thank you for having me.

Great to have you here, and I've got some questions we'll kind of go through and look forward to the discussion.

Wonderful. Thank you.

Awesome. So Bill, why don't we just start with your -- a little bit of background on yourself and your role at Salesforce?

Okay. So hello, everybody. Thank you for having me here today. I'm Bill Patterson. I'm the Executive Vice President and General Manager of our CRM Applications at Salesforce. So I'm responsible for some of our largest cloud businesses, our Sales Cloud or Service Cloud, our emerging businesses like our field service offering, our commerce businesses. So really been at the organization now 6 years. And prior to that, we had a shared background, we spent time at Microsoft and just learned that a moment ago.

Absolutely. Yes. Great. Well, awesome. Why don't we just start with the concept of Customer 360. Could you perhaps illustrate how the platform enables that with Salesforce? So give us an idea of the platform, underlying all the different clouds and applications, whether it's Service Cloud, Sales Cloud and Marketing Cloud, Tableau, Slack. I mean there's a lot of offerings here. What are the kind of underpinnings if you will, that enable that 360 view?

Yes. First off, in sort of the raw sense or most primitive sense, what Customer 360 is, is the world's most sort of popular customer relationship management platform. So it really provides line of business computing for sales teams to drive growth, service teams to drive retention and sort of drive customer satisfaction; marketing teams to really drive and amplify the brand of your offerings; commerce teams to drive digital transactions. And those are really the 4 big sort of application workloads that we run. Across those applications, it's built on a platform that really is a cloud-based declarative software technology that allows the solution to be adapted to different sizes of business, styles of business, industries of business for use across our organization. And Customer 360 also encompasses some of our technologies like our integration with MuleSoft, our Slack technologies for collaboration and engagement and productivity as well as our Tableau technologies for driving analytics and intelligence for enterprises at large.

Great. And maybe some examples of a customer who has really embraced Customer 360, maybe a use case, if you will, a cohort of a customer that -- or a customer or 2 that have been with Salesforce for a longer period of time and really embrace that 360 in the technology. And what does that footprint look like? How are they generating ROI?

What makes Salesforce unique is really the diversity of the customers that sort of run on this platform to power their operations and their business. And I think everything from big companies and small companies are -- really use this technology at scale to run their operation. I'll give you 3 examples. Companies that are sort of in the physical business, like Siemens, use our technology for driving not only kind of frontline sales operations, working with their selling partners, their distributors, their suppliers, kind of keeping everyone on the same page. But they also use our technology for service to maintain all of their buildings, their building management software kind of connected through their offering. So an organization like Siemens is very much kind of in the physical domain. That's kind of one example. A company like DocuSign uses our technology also to not only drive online service and support, they use us for helping to sort of configure and optimize their solutions when they're actually selling to customers. So they're a good company that's sort of in the digital domain. And then you think about a company like Marriott, who kind of operates in the experiential domain. They're another organization who runs our technology for powering all their guest relations, guest services, et cetera. So I think, again, what makes Salesforce very unique is it's not dominated by one industry. It's not dominated by one company size. It's not dominated by sort of one geography. We're incredibly global. We are incredibly diverse in terms of the customers that we sort of operate with and have the elasticity to sort of scale and stretch to different styles of business based on sort of their needs.

Wonderful. Now that's great to hear. And when we think about the Salesforce stack and Customer 360, I think of the big 3: sales, service and marketing. Those 3 really need to be integrated. Then you have these other kind of horizontal categories like Slack for Communications and Tableau for Visualization. How well integrated are the big 3, if you will? Is the work -- is the heavy lifting done there such that you really have that single source of the truth on a common data platform? And these other ones, there's incremental effort to integrate these. I mentioned those 2 with Commerce Cloud as well.

Right. Well, first off, sales and service were organically built inside of Salesforce based on our platform that we kind of underpin that technology with. We acquired Marketing Cloud, I think, in around 2016 with the acquisition of a company called ExactTarget. And one of the things that we've been doing since that time is really embedding that technology really into the core of how sales and service operate because what we really find is that sales teams and marketing teams turns out they actually want to be on the same page and have the same kind of level of data . So our technology platform that we've created, which now we call our Data Cloud, underpins all of those technologies and allows the data to seamlessly run and feed all the departments that run on the Salesforce platform in that clear and consistent manner. And that's ultimately what has led to that product, which we call Customer 360, single source of truth to utilize in every line of business that kind of offers that information through.

Wonderful. And then maybe some perspective on R&D. What are the key investment priorities? I imagine one of them is going to start with an A.

Well, first off, I'll start with data actually because data is the foundation. That's the lifeblood of what turns into great AI kind of innovation. So our innovation strategy is pretty much threefold. First off, it's about data and unlocking data in a clear and consistent manner, so it really works across an organization and even intra organization, so you can share that with your trading partners, et cetera. AI is sort of the next horizon. And I think once you ground that data specifically with the customer data, the customer intelligence, the business policy, the business brand, tone of voice, the unlocking the specialness of what makes up the CRM data structures, applied with great technology like generative technology really makes it special and powerful. And then lastly, it's still -- we have a lot of room to run in the CRM category. And so as we kind of think about how to help businesses either save money or drive growth or sort of resuscitate their business in this post-pandemic era, there's a lot of innovation going in the CRM domain, that's also really about helping companies sort of thrive in today's macroeconomic environment.

Great. Why don't we shift to AI while we're on the topic of R&D priorities? How does Salesforce think about the AI opportunity? What is the company doing to build AI into the offering? I know there's already some available today, but just love to get your perspective on kind of the state of the stack with AI and where it's heading.

Yes, generative AI is really the most profound opportunity of our lifetime, I think, around sort of enterprise software, around business services, et cetera. And so we, like many, are really accelerating kind of our innovation efforts around the AI domain. What I'll tell you is we do things a little bit differently at Salesforce than maybe some other technology companies do. First off, one of our core company sort of values is running a trusted operation for our data and our policies around company's data because customer information is really the lifeblood of an organization. And so one of the things we really set out when we -- before we even wrote a single line of code, it said was we are going to continue to operate on this foundation and this platform of trust to really run this operation with. And we've seen a lot of stumbling already in the early days of generative AI about people using public models or publicly available consumer services really in the wrong, inappropriate way, sharing information with these models that now becomes part of the model for the future even if it's sensitive information, if you will. So first off and foremost, it is about a platform of trust for us around how we think about AI as a foundational service across our applications. Second, the reality of most enterprises today, it's a very large and diverse landscape of technology that often makes up the way in which an organization operationalize its customer experiences. I take customer service, for example. Oftentimes, the service organization has 20, 30, 40 different systems in use that manifest that customer experience or that operations like a contact center. It is not sustainable for an organization to have 30, 40 different AI strategies to try and kind of manifest a consistent experience for their customers. And so our approach with -- starting with the trusted foundation said, okay, first and foremost, we want to make sure that the data stays resident and secure and safe. Second, we really want to help organizations leap into this AI era by not trying to have all of these different diverse of landscape of models that are just flying around inside the organization. I want to make that more cogent, more coherent, more simple to utilize across every center of interaction the company does. And finally, I think the last horizon of sort of AI really becomes, how do you think about the application of AI, specifically in how you serve, how you sell, how you market, how you digitally transact with organizations? And that's really kind of the last horizon we're thinking about is how do we really think about fundamental new ways to break through the marketing domain or the service domain or the selling domain with those areas. So 3 horizons of how we think about AI. And I think Salesforce is taking, one, a very responsible way of bringing this forward; and two, a real focus on applying AI for the purpose of transforming customer experiences.

Wonderful. And there's a debate across software categories as to where is AI additive, where could it potentially be deflationary. I would love to get your perspective when you think about the Salesforce end market. What's your take on that?

Yes. Yesterday, I was in Chicago talking with 130 service leaders, of the same question. Because I think what's been fascinating is for service teams, customer service is one of those domains and disciplines that I think a lot of people are forecasting will have a large amount of labor disruption associated with kind of the use of generative AI and generative AI practices. And so I was there in a meeting just like this, talking to customer service leaders. And the question came up, like, okay, so does that mean that we're going to have less people working in the service center? The reality is that what -- for software companies and for software technologies like what Salesforce offers, it means the software actually gets more valuable because we can make the users of that domain more productive, more sort of intelligent around how they drive interactions and actually drive more scale that's there. So I think first off and the foremost, while there may be less labor employed, the value of the software actually gets more a premium value associated with that. Second horizon of that is, I think that we still cannot keep up with the demands of what consumers are generating in terms of brand expectations for sales, marketing service interactions. And so AI, in an always-on kind of experience, actually gives new ways to drive growth for companies like Salesforce because what we're going to do is build technology that's in an always running, always on manner, even when your employees are not at work. So I think that gives another kind of horizon. And then last, when you think about sort of kind of value creation, what companies are actually looking today to companies like Salesforce for is help to drive growth or savings. And the opportunity to use the software to participate in the growth and savings of how the sort of business revolutionizes itself, I think just becomes another growth lever for a company like Salesforce. So I think our energy is very much at an all-time high. I think there's a lot of excitement around the innovation in this category at large.

Wonderful. Great. And when you think about the defensive competitive mode, if you will, that Salesforce has against potential LLMs taking on more of sales and service functions, what are those, in your opinion?

Number one, it's the data. That's why I started there from an innovation kind of standpoint. Today, if you can go out to a large language model like ChatGPT and get a really great compelling sort of narrative written for you or a trip plan for you online, but what you don't get is a personalized sort of response. You don't get something tailored to you as an individual or to your needs or to your kind of unique circumstances. And so first and foremost, the data that sits inside of the CRM system, not only about customer profile, customer history, but also around your policies as a business, your operational policies, your -- the way in which you communicate in your brand and your sentiment or what you allow to happen in a regulatory environment that sits inside the CRM kind of core today. So the ability to combine the CRM data structure and do it in a safe and secure way, along with this genre of technology, it ultimately creates this incredible flywheel of innovation, but also a longevity of value for a platform like Salesforce to keep serving companies into the future with a more AI-first manner of how they interact with their customers.

Wonderful. And Marc, on the earnings call, last week, he alluded to some AI features coming with Slack and Tableau. Would love to get some color on that and what he was referring to.

Yes. Well, we do have an event next week. So won't steal all that thunder that was coming. But really, I think around Tableau, specifically, the way in which what has been so beautiful about use of Large Language Models, and I think we've been really deeply inspired by, is the way in which kind of users can inter-operate with data or information has never been kind of more simple than it is today. And so we really took a lot of inspiration from what we've seen around the use of Large Language Models and now applying it to Tableau are really allowing sort of an information worker to be able to talk to data like never before. And allowing the data that sits inside of a Tableau kind of visualization technology to really be queried and questioned and even asked more data to -- more clarification to all in that conversational language. So that's sort of on the Tableau side. Slack is another opportunity for us and really it's a goldmine of opportunity for enterprises because a lot of unstructured policy or unstructured decision or unstructured resolution to common problems actually sits in the Slack platform today. And so when you actually think about the opportunity to utilize a Slack GPT to summarize conversations going on across your organization, or summarize kind of commonly, maybe, resolutions to big problems that occur, these are really where I think we can help bring organizations forward to work faster really with the combination of generative intelligence working alongside those platforms.

Great. Great. And lately, we're seeing Salesforce take on a much more open approach to data. Genie was launched last year at Dreamforce, integration with AWS, SageMaker, Snowflake, let's just bring more data into Salesforce. How significant is that in kind of your road map towards data and AI?

Yes, we today announced a partnership with Google on Vertex AI as a good -- another testament to this validation of sort of opening up our platform and our ecosystem. The reality is, as you go into the enterprise or you travel around the world, the only thing that's consistent when you work with the organizations of size and scale is they're very diverse in terms of their technology landscape. And what makes it very difficult is, if you say, okay, in order to access only the Salesforce AI, you have to move all of your legacy investment over to this platform. That's just not a reality for people. And so what we've done is really, really over the last, I'd say, 5, 10 years, is start to open up the Salesforce platform for more diverse landscape of technology and also more deeper ecosystem partnerships with the likes of Amazon, Google, even Microsoft, really to think about ways to kind of remix this innovation together. And again, what we want to do always is listen to our customers. Our customers have these kind of unique needs and the ability for us to sort of open up our technology so it fits into the environment that our customers have really kind of makes it even more enduring proposition for us.

Great. And then maybe we could touch on Einstein GPT. What data are feeding that? I think there's OpenAI in there. There's Salesforce own models in there. There's third-party data sources. So that's a lot. But it's consuming potentially. So if you could just help us understand kind of the data feeds for Einstein.

Yes, first off, as we looked at kind of in building on the last question you just asked around kind of a diverse technology landscape, when we approach the generative AI world, what we've realized is there will not be a future, where kind of a one-size-fits-all model is going to be perfect for everything. In fact, what we've seen now really in as sort of time has progressed is there are great models for general purpose needs. But there's also now these industry-specific needs or vertical-specific or even customer-specific models that are starting to be created to really kind of even go further acute into the value that they provide. And so what we built with Salesforce's Einstein GPT technology is what we call a gateway to really access multiple models or the model of choice for a customer to really register alongside their customer data and customer intelligence activities. And so the foundation of what Einstein GPT is, is really an open gateway for people to participate in the CRM kind of use cases with the models that they've served. And so we have great partnerships with OpenAI. We have great partnerships with Anthropic, Cohere, You.com, a whole ecosystem of providers really that specialize in different types of models can work with the Salesforce ecosystem. We also asked a question about our own models. We're also building our own models for really generating workflow or business process, things that really comprise the enterprise application. We can make enterprise software easier through a lot of the models that we've created, and that's definitely kind of on our horizon is to actually help companies just get more from the technology they have from us.

Wonderful. Why don't we pivot to multi-cloud deals? It's a...

Great pivot, by the way.

Yes. Since we went from AI, let's just go to multi-cloud.

Multi-cloud.

It's been an ongoing driver in the business. We're seeing this trend where customers are committing to more clouds, both new and existing customers adding more. What are some of the combinations that you're seeing resonate more, sales plus service plus marketing, in the core 3? Or are you starting to see some of these other solutions like Commerce and Tableau and Slack coming in increasingly onto that, layering on top there?

Yes. I think increasingly so, organizations really care more about getting better business outcomes than they care necessarily about sort of the line of business department that enabled the outcome to happen. And so as a trend really originating from the Customer 360 strategy, it's more companies that use more Salesforce software get better results. Because they actually can drive more cohesion around the way in which you market or sell or serve or digitally transact all from that one platform. And it allows organizations to save time, save money and actually work in a much more agile manner. So definitely, the trend is for more organizations to combine more of these line of business sort of offerings together. But you're also now starting to see with technologies like Slack and Tableau reaching into more user communities inside of an organization by bringing the power of our data to more information workers, by bringing the power of engagement into more professionals. And so I think that as sort of as your question was getting at, you're going to see more multi-cloud. And in fact, maybe live in a future where they're not even call multi-cloud. It's just we really run more of the front-office computing platform for organizations because they're all working now in service of customer, customer demand, customer needs and our technology just facilitates that opportunity to make that happen.

Wonderful. Thanks for that, Bill. Why don't we go to industry clouds? 13 of them. Salesforce offers an out-of-the-box solution for a number of verticals. Which ones are you seeing traction in? Where is the incremental traction from here?

Yes. Well, first off, the strategy on industry computing is all about providing a clear and opinionated set of technology that builds upon the special uniqueness of how market -- how companies market or sell or serve or digitally transact kind of into the industries that they operate within. And the kind of transactions you do in banking are very different than transactions you do in health care or in retail consumer goods, for example. And so our industry technology layer is about kind of going that last mile of time-to-value acceleration for companies to find a purpose-built or fit-for-purpose technology to really speak to their unique needs. And what we experienced with our industry cloud is a higher premium in terms of the value that we arrive at for users who use those clouds. We see a greatly accelerated time to value for companies who deploy those clouds. And finally, when you think about this world of AI, we see even more acute and value-driven intelligence that we can because we have industry demand understanding really into the technology layer that's there. The question you asked about what industry is kind of we're seeing a lot of growth from -- in our first quarter, you saw a lot of sort of kind of vulnerability around technology and financial services, just due to macro sort of environment situations. But you saw a lot of kind of resurgence around the retail consumer goods kind of area. Travel and hospitality starting to invest their way back to growth. And so those become the areas that we're really excited about continuing down more of our industry strategy around. Automotive is another good example, this whole kind of move towards electrification. A lot of companies are doing it on the Salesforce platform, which is really cool.

That is very cool. Maybe back to AI. I mean just if we kind of step back a little bit and you think about the opportunity to monetize AI. Philosophically, how does the company think about AI? Is this -- are these features that are embedded into the clouds the core offerings? Or are these different -- these premium SKUs, where there's added functionality here, how are you thinking about that?

Yes. When we talk about multi-cloud, we talk about the more companies that use more Salesforce software, they run better. When we talk about AI, the more AI that we can bring into the world of our users, the more productive and more sort of efficient or effective they can become in their jobs. And so our strategy for monetization on AI is really still emerging, but really starts to look at the following. One, we want to bring AI to every information worker in the world. That's very clear. Two, we want to use AI to drive a transformational way to engage with brands even in a self-service manner that maybe aren't necessarily human-driven or human labor-driven kind of interactions. And then finally, I think AI is going to create even new value-driving opportunities like, hey, if I can become -- if I can get a higher margin on these transactions I do, maybe there's a participatory economic model that actually can arise there, sort of like our commerce business runs today. So I think there are a lot of horizons of growth that AI sort of represents. We're in such early innings of what this kind of world is starting to look like. But I feel very confident that it starts always with the foundation of bringing more AI into our applications because ultimately, we want to help our companies achieve more with the software that they use from us.

Absolutely. A big effort for the company is sales efficiency. And from your perspective, how is that effort? Where is the focus? There's obviously go-to-market efficiencies, but there's also product efficiencies in order to enable an efficient go-to-market product, needs to be integrated. So to the extent you have visibility into kind of the go-to-market, from your observation, where is the incremental effort there to drive that sales efficiency?

Yes. So in my role as a product leader inside the organization, I have deep accountability to helping ensure that our products find the right routes to market, find the right sort of sales blueprints to market. As well as ensure that our products and our packaging are optimized for a sort of more lean and higher productive kind of selling force, if you will. So the first and foremost, kind of from my vantage point, deep focus around product prioritization, deep focus on packaging simplicity and deep focusing on sort of pricing optimization. That's sort of horizon one that we've been thinking about around sort of our restructuring opportunities and activities. As you've kind of all seen, we also completed a relatively sizable, meaningful restructuring to our go-to-market sort of organizations, which really was about -- less about sort of micro businesses and more about maximizing for the whole of the Customer 360 strategy. And so a lot of growth that we've seen with Salesforce over the past had come through acquisitions, had come through sort of areas, where teams where maybe we're operating kind of in an individualized basis. What we've done is restructuring a way to really focus on the buyers and the roles that really matter most to our future. And that allows us to become more efficient, allows us to become more agile, allows us to actually deliver higher value for our customers because we're focusing now on really taking Customer 360 to every industry as opposed to necessarily maybe some of the legacy businesses that we would have acquired.

Great. And if you could help us understand a little bit kind of what stage you are in that effort. Is this a multiyear effort? Obviously, the reduction, those aren't easy, I'm sure. But where kind of are you on that journey, if you will?

Yes. First off, any restructuring of size is difficult. So thank you for sort of recognizing that. And there are a lot of great people that kind of love their time at Salesforce. And obviously, we see them on to their next horizon there. But where we are, we've completed our initial restructuring around sort of the activities that we have. But we now are really -- our energy is focused on higher performance, higher productivity, higher sort of efficiency within the organization that we've created. And that's still an ongoing process that we've been working through. I think Marc has really brought back an incredible culture of performance into Salesforce. And I think that we'll continue to optimize, especially as the new world of AI-driven CRM start to emerge.

Wonderful. We've got a couple more minutes here. Maybe just to -- and the conversation on the core business. Sales and service have been nice, steady growers. What's driving that? I mean it's been -- when you...

I do manage those businesses. So I don't want to say me.

Yes, I'm sure it's all you. But yes. Just curious to get your perspective. I mean you see the core business lagging the overall growth rate of -- but in this case, that's not.

No. I think well, first and foremost, that turns out, companies still want to drive growth. And they want to drive growth more efficiently, more durably and also with higher economic yield back to their shareholders. And so Sales Cloud, really, our original cloud has continued to outperform a lot of expectations because we now have really kind of expanded into new market categories, things like sales enablement, things like configure price quote technologies, things like higher revenue intelligence, pricing optimization, really to help companies continue to beat that growth from around their organization. Same thing on service. I think service technologies today, the reality of the service centers, as I mentioned earlier, is it is -- there's way too much technology that is all bespoke in the service center that your poor customer service agent has to deal with to try and kind of perform a routine interaction. The inventor of alt tab actually never spend a day working in customer service because it just is not efficient for them to try and kind of manifest a clear and easy interaction that way. And yet, so service has the same opportunity to keep growing by making smart adjacency expansion around the technology landscape that we're sort of providing to expand into higher units of productivity for customers that we serve. And so while kind of these two little engines that could keep growing, it's because customers need our help really to keep growing and thriving in this era of where they find themselves in the lifespan of our relationship.

Wonderful. Well, Bill, on that, we're going to end. This is a great discussion. Thanks for coming. Great to have you here.

Thank you so much. I appreciate it.