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

Good morning, everyone. Welcome to today's session, How Salesforce Runs on Tableau. And thank you all so much for joining. My name is Natalie Goin, and I'm on the corporate marketing team here at Salesforce. Before we begin, I would like to cover a few quick notes about our webinar platform. Today's webinar will be available on-demand after we wrap up, and will be accessible through the URL that you're on now. Please note the slides will advance automatically throughout the presentation. [Operator Instructions] We've also added some additional resources, which are available through the resources window to the right of the slides, where you can find additional related content. [Operator Instructions] And with that, I'm going to hand it off to Jeff to get us started.

All right. Thank you, Natalie, and hello to everyone joining us today. My name is Jeff Chen. I'm a Product Marketer working on Tableau here at Salesforce based in San Francisco. And we're excited to bring to you some of our latest examples of how Salesforce runs on Tableau. So before we get started, I have to remind everyone that Salesforce is a publicly-traded company. So please do make your purchasing decisions based on the products and services that are currently available. Now I know we are all here virtually today, but I still want to take the time to thank everyone for being here. It is all of you, our customers, our partners, our prospects and the community that we are here today inhibiting for all of you. And so thank you for taking the time out of your day. We hope our presentation can spur conversations and thoughts on all the different ways that your organization can maximize the value through data. I'm joined by my fantastic colleagues, Ed Beaurain, RVP of AMER Enterprise Sales; and Mike Crook, Senior Director from our Finance Data Office, who you'll hear from later today taking us through their different use cases of using Tableau. And so at Salesforce, we say well, few things that we are our own customer, that we are customer #1 or 0, but all that's to say is that we use our own products. And so along the way, we've navigated our own data transformations and subsequently AI transformation as an enterprise organization ourselves. And so we've accumulated all these best practices and lessons learned, tips and tricks to show to you today. So these transformations over the course of many years can be depicted as waves. We've gone from reporting as specialized functions to reporting through spreadsheets, made even easier with natively built self-service analytics, to now being able to visualize anything and everything lowering that barrier to insights even more every step of the way. With the power of AI, this is really just the beginning that we'll see a new wave of personalization and reimagine analytics experiences. And that's because AI is fundamentally changing the way that everyone works. In our personal lives as consumers that changes the expectations of the tools that we expect in our work, right? It doesn't matter where you sit in an organization, your line of business or department or even industry, AI is here and is changing how we work at Salesforce as well. But what do you do when -- this is the reality that faces many enterprises, right? We -- there are over close to 1,000 applications to integrate and automate. And this means that only around 30% of individuals surveyed are using data to make decisions because of the time that it takes, about 36 hours to prep and get access to insights. Though this shouldn't hold us back from using data. In fact, this is where we need to be driving in data culture, and I'll tell you why. Think about all the decisions that you make in a day and times that by the size of your organization. If you were to visualize it, it would look like this where you have micro decisions that drives the business every single day, all the way up to high-level decisions that hinge on the company doing well, right? Decisions around marketing campaigns or sales strategies or even decisions around mergers and acquisition, right? Data is foundational and decisions needs to come from trusted data, not gut feeling or anecdotal statements. Now let's take the same pyramid and look at how data aligns an organization to ladder up to their mission and goals. With this visual, starting on the left, without data and a data-driven culture, everyone is making their own decisions based on various different references. You can look at this diagram and think chaos, right? With data, you slowly start to align your organization on harmonized trusted data, [indiscernible] decisions resembles more of a pyramid, organized, if you may. Then when you lay on metrics and KPIs, teams can start to align with shared goals. And with action and collaboration, your organization can achieve data Nirvana where individuals and teams are making decisions that are in lockstep with the business because it's not really just about the tools, it's the people, it's the processes, it's the product working together that truly makes the difference between using data and a data-driven culture, right? So people inherently gravitates towards data, processes help us enable on how to use data and products are the powerful tools that unlock these critical business insights. And so we've been on a journey of our own to bring data and people together by tackling this gap that has kept data out of reach for so many in disparate silos, resulting in this context and mistrust of data. And so we started by imagining a world where every user can get notified of a metric that they care about, explore the underlying context of what's happening given the why or the logic and analysis, then be able to ask all questions of their own in natural language and take action immediately in their flow of work. Tableau has really made this possible for Salesforce. As the leading AI analyst platform, Tableau has integrated nicely into our existing strategy, our tech stack, bringing everyone the ability to self-serve analytics with confidence using trusted data every day. And the important part is how open and flexible our platform is. So enterprises can scale because enterprises are inherently complex. So we at Salesforce are also complex, right? We have data everywhere. So it is important for Tableau to not be this walled garden and can handle the complexity of data connectivity, data preparation and deep analysis. And with our latest innovation, Tableau Pulse, which has accelerated even more analytics adoption since our deployment in February, not just in the amount of active users, but also in the time that it took to deploy and the time to value for our users. This reimagine experience brings personalized metrics with relevant contextual information and intelligent AI to everyone's fingertips. Tableau Pulse completes this data analysis journey by being always on, always available to keep track of what you care about with the ability to dive deeper with the click of a button. So what does this look like? Well, I'd like to first contextualize this for my job as a product marketer. We keep a pulse on the industry to bring to market innovations that matter to you. To do that, we take a look at metrics like marketing-driven pipe, customer acquisition costs, conversion rates, marketing qualified leads and so much more. So I need data, but by no means do I can serve myself a data analyst. For our sales team, it's all about boosting revenue and efficiency with managing pipeline, win rates, understanding contract values, customer retention and churn. Service. Service is hugely important to elevate the customer experience, so understanding our CSAT scores, number of abandoned calls, average wait times and resolution times. Finance keeps us all in check, so our business can thrive. So things like total revenue, gross margin, operating costs and T&E expenses. These are just some of the many ways that Salesforce is running on Tableau. And today, you're going to hear about our marketing, sales and finance use cases here shortly. So starting with marketing, and I will do that by jumping directly into Tableau Pulse. Can my team confirm that they're seeing Tableau Pulse?

Yes.

Yes, we are.

Awesome. Thank you. Now you're going to see Tableau Pulse demo a few different ways today. Here, this may not look like much, but that's intentional because I want to show you both the blank slate and the end state to explore the product together. Another experience are prepopulated metrics governed by lines of business or departments where you have out-of-the-box metrics for every user based on their role, credentials to jumpstart [indiscernible]. So this blank slate, however, is meant as an explainer to the different functionality that we'll come across. From here, it's super simple to start. Without any instruction, I can search for metrics that I care about. So let's type in marketing and see what comes up. There we go. So these are the metrics for marketing, and we can go ahead and follow month-to-date marketing qualified leads, month-to-date market-driven pipe and marketing-driven ACV. There we go. Now let's take a look at actual pipe as well and let's do actual ACV. Right, so I have my metrics followed. Another way to look at metrics is to explore all of them. Here, you can see all the metrics that have been created and governed. So any person in the org when they look at a specific metric, it is the same data across the entire company. And now this is the demo environment, but real product nonetheless. So you'll see things that may not be working properly, like this data quality warning, where it's always being transparent about what's going on with the data. But it sounds like that's something that the team will need to look into and check on. But going back to Pulse being my personalized homepage, I have metric cards now. Here is -- everything that I need to keep track of, what I care about. And on the top here, I have an AI-generated insight summary that is telling me what's going on with my data. And in plain language, it looks like marketing-driven ACV is up. So let's dive deeper by clicking into that specific metric card. All right. So here I get additional details of that specific metric and with its own AI-generated insight summary. And I can seamlessly filter by clicking into breakdown to understand at a deeper level, what's going on based on whatever tides I have within the data. So here, we have region, we have the different clouds, we have industry, campaigns and offer types. So AI will review all of this data and have additional questions. AI is already suggesting questions that I can ask of my data, but we can ask one of our own in plain language. So how about we ask, which campaigns decreased the most? AI is validating the question that I'm asking. And here are the results that I'm getting. So from this insight, I can make decisions on perhaps deprecating some of these lower-performing campaigns to reinvest in the higher-performing ones or net new campaigns. And I just did all this analysis in a whole new way that I can easily understand and navigate myself. And going back to my Pulse page here. Again, this being a personalized experience, if there's a metric that no longer need or need to follow, I can unfollow, the metric card goes away. Or let's just say, I manage a team, and I need them to follow and [indiscernible] around this specific metric, I can share this directly with them. And the best part is, I don't have to constantly click into Tableau Pulse because I'm able to get daily, weekly or monthly digest, I guess, sent straight directly to my Slack e-mail so I can manage my business on the go. So from Tableau Pulse, I can then go back to our [indiscernible] marketing dashboard. So to do that, let's go back to our slides. So here at Salesforce, we run hundreds of campaigns supporting our different products like Tableau, MuleSoft, Slack and whatnot. And we target different industry and regions across different mediums like social, digital, events, paid promotions. And so when I need to dive deeper into the analysis on performance or benchmarking across these different variables, say, for quarterly planning, this dashboard helps me understand at a granular level what's working and what's not such as individual offer type stuff we're promoting within campaigns to see how many conversions those offer types have brought in over time; or offer types such as individual cases of content or events, demos, trials, all the things that marketing develops and support. So by understanding our individual campaigns and offer types, we are working to scale those best practices across the marketing team. And on the flip side, again, if we're seeing something that's not quite working, we can dial back on resources. We'll potentially cut costs in those areas, ultimately driving up our marketing ROI. I can also dive into our marketing leads dashboard. And this is where we can analyze lead volume and revenue by lead source. So we can identify top opportunities that we need to be targeting with our sales team. It uses AI to surface what if scenarios, which helps us mitigate challenges and identify potential areas for growth. And best of all, the dashboard combines data from multiple marketing systems into one view so that we can analyze every step the customer takes in the marketing funnel. This kind of visibility and analysis journey between Tableau Pulse and traditional dashboards are dream for all marketers and is what promotes the confidence and the use of data in our day-to-day. So next up, I would like to introduce one of our amazing sales leader here at Ed Beaurain to talk about how he runs his business on Tableau. Ed, over to you?

Great. Well, Happy Wednesday, team. It is actually our final day of the quarter today. So I am in dashboards. I won't be showing you those dashboards. I'll be showing you some mockups of what we do use internally here. We're really grateful for the time. I've been with Tableau approaching 10 years. I lead our enterprise corporate sales organization, so selling into the North American enterprise customers across every department and vertical. I had the opportunity to see all use cases of our technology. And prior to being with Tableau, I was an analyst, and I love data, and I would -- couldn't be happier to be here at Tableau. So if you can go to the next slide. Our job here at Salesforce and within the 70,000-person organization is quite complex. We have 1 unified sales ecosystem across all different teams. So it's critical through the use of Slack, through the use of our CRM, obviously, in Sales Cloud, and Tableau that we're constantly communicating and leveraging data to make better decisions to improve our overall customer experience. Everything from solution engineers and field marketing to obviously our Tableau AEs, our ECS working with our core counterparts, our BDRs and SDRs, to also anything that needs to get done to get these orders over the finish line in terms of deal desk, order management, [indiscernible] and legal. So we really run our business on Tableau from everything from customer assets to renewals to their overall activity, anything that gives us a row and column of data, whether it's qualitative or quantitative to create a better customer experience, we're going to take advantage of that and visualize that in Tableau. Next slide? So what keeps our sales team up night? Well, I guess, last night, I didn't sleep much. My son had a nightmare about Saber-toothed tiger, so I slipped in his toddler bed, so that didn't work out. But I was also very focused on the quarter end here and taking a look at the dashboards to make sure that not only do I deliver revenue, but accurately forecast delivery of that revenue. Not just about top line growth, it's also about doing it in a profitable way, hiring and retaining top talent and ensuring that we're driving efficiencies with the right overall pipeline health and coverage. So let me walk you through how I use Tableau to go ahead and run my business. So Pulse has been a huge innovation for Tableau. What's super exciting about it is it's built for mobile. So a while here, I'm on my browser just because on this Elite studio, I wasn't able to go ahead and log in to my phone. But all the key KPIs and metrics that we are constantly looking at as a sales organization are highlighted here in Pulse, whether it's all -- the overall ACV, our pipeline being generated, our overall coverage versus our commit, the number of activities, average opportunity size. If you think about kind of senior sales leaders with an organization that are potentially living in Google Sheets or screenshots or PDFs or some outdated form of consuming information to make better decisions, Pulse is just a critical enhancement to our technology to go ahead and do that. And the beauty of this is, I can obviously jump in to Pulse and I can see additional metrics of what's happening with the information. I can see overall how we're trending, what's happening with the different reps. I can go ahead and ask which account increased the most, and it'll go ahead and let me know specifically where I might focus my energy. So the beauty of this is it uses natural language, it uses our acquisition of Narrative Science to take advantage of all this innovation that has happened, but doing it in a way that's accessible and intuitive for the masses. So while I live in dashboards and I manage them all the time, many people might not be willing to jump into a dashboard or overwhelmed by a dashboard. And Pulse is a great gateway to go ahead and get people more into data and more access there. Let me go ahead and jump into a different view, which is the dashboard that I used to run my business. And what's been exciting is since we've integrated with Salesforce 3 years ago, I think our dashboard usage within the company has only improved. In fact, I really run my business up of 3 dashboards, 2 of which I'll show you today and one of which I can't show you just yet because we haven't mocked it up for public viewing. But this one, I'm literally -- if you look at my other screen, this is what's up right now. And because my job is to, as we're kind of managing the business here on this final day and anyone knows in the world the software, a lot of deals here are closed at the way, way very end. My job is to figure out what are the deals that are coming in? What are the deals that are not coming in? How do I go ahead and mitigate those gaps and allocate my personal help or resources internally to go ahead and maximize the outcome? What's incredible about this is it really is an app. It's a forecasting app, and you can use it across all the different cuts of your business. So for this example, we can go across the different President, VP, AVP, RVP. I can also filter it to my business, ECS manager, which is important because we go ahead and work specifically with the field team. I would have my commit here, which is my overall call. I would call it in terms of what my overall growth would be. And what's nice about this is it takes things in Sales Cloud, but makes it intuitive. It takes my manager forecast judgment, which is whether it's in, up plus or up minus. It allows me to go ahead and review these opportunities that if these were real-live opportunities which show me the manager notes, the next steps, a link to the opportunity in Salesforce. It also show me their stage so I can understand, "Hey, is this opportunity represented accurately in the system and are we putting ourselves in a position to go ahead and close this business?" It doesn't just stop at reflecting active pipeline. It also provides assumptions on other types of pipeline. So for us, we have a lot of transactional business here at Tableau. So for some of those calls, I can't go down to a certain level and call each and every call, but we can now use things like expected value or machine learning or a manual input to call the rest of our below card-off business to go ahead and leverage the data, to go ahead and be more accurate in our overall call. This application also has a create and close component. The beautiful thing about create and close is it uses historical information to see what have you created and closed from this day forward so that you can go ahead and call the business that you haven't seen, but use the data of previous quarters and current trends to identify what's going to go happen. And lastly, we know that salespeople like to go ahead and put their deals in all different types of places and the accurate date because they don't want the inspection in those things or they have a deal that's a little bit risky and they don't want to put it outside of the quarter. We also have an aspect of this application for pull forwards that you can go ahead and say maybe all of our pull forwards on August 15, they have a less than 50% conversion rate, we're going to go ahead and put them into this view to go ahead and be able to fund the overall call. So this right here is that specific application. Another one is our Who's Hot View. This is around lead and lead management. So as all of you go ahead and consume this demo, you're going to go ahead and go through our system. And my hope is that our BDR is going to go ahead and call you with relevant information to go ahead and carry this on. Maybe you're going to say, "Hey, could I get this presentation live for my customer, my company?" I'm happy to do it, by the way. But when you go here, you're able to go ahead and see all the different leads that are coming into the business by the different accounts, by the different contacts. You can identify specificallywhat recent activity that they did. If it has a view here that is highlighted in blue, that means that they were followed up on. It shows you exactly what the e-mail content was and the information. You can also see your top campaigns that are trending. So for us, we see that Analytics for Everyone is a campaign that is trending. That's most likely on our website and inbound. It allows people to go ahead and then potentially use this proactively for their organizations. So our Tableau Desktop trial, someone's trying the new product, we want to follow up and have a guided evaluation with them. This is also a great partnership with Jeff and the team to understand what's resonating with our customers, but how do we take advantage of the investments that our marketing organization is doing and turn those leads into dollars through the use of something like this Who's Hot Dashboard. The last thing is Tableau is fantastic for ad hoc analytics. So for me, when I'm coming in here and I have additional questions that might not be focused on a dashboard, I can come in here and say, "Show me the average discount by state on a map." And I can use something like Einstein CoPilot, which we just went ahead and released in terms of beta, to go ahead and visually represent that data and use the advanced technology to go ahead and show this right here on a map. So this now allows someone like me who's a business leader, a third line leader, to go ahead and use things like Copilot to go ahead and do additional analysis. I might come here and say, "Okay, I actually rather see it specifically on to color." I might also do initial information. Maybe I want to look at my sales, look at my sales specifically over time, understand the seasonality of my business, break this across my different months, and see this maybe across my different categories, right? So now I really have the ability with Tableau to go ahead and do consumption of metrics overall in Tableau Pulse sent to me on my phone, on my device. Using dashboards, like I just shared, this analytic application for forecasting or for lead management or other things that I used to really understand high level what's happening with my business across my 50-plus sellers and obviously, a massive amount of customers. And lastly, with Tableau and Explorer, I get to do the ad hoc analysis that's needed to ask and answer questions that might not be built into a dashboard without me relying on an analyst to go ahead and get that answer for me because I'm an analyst. Sure, I'm a senior sales leader within the organization, but it's important that I understand the governed data sources that are available to me to ask and answer those questions to provide a seamless customer experience. So with that, I'd love to pass it over to Mike Crook, a fantastic vet of the Tableau space who's been leading on our finance side. Mike, over to you, let's see how we manage our T&E with Tableau.

Awesome. Thank you so much, Ed. As Ed said, I've been with the company for a while now. I joined just over 12 years ago. I was a customer before I joined Tableau. So it's been great to see just kind of the evolution of our product and just the opportunity that we have to help everybody see and understand their finance data. So at Salesforce, I now lead our finance data office, I'm responsible for driving data governance, data insights and enablement, but also being able to have opportunity to present to customers like you. So let's learn a little bit more about what our finance team is all about. So Ed mentioned Salesforce just to over 70,000 people, over 2,000 of those represent employees that are part of our finance organization. We're distributed over 40 different offices around the world and have 8 incredible leaders that are driving our internal audit, tax, FP&A, Investor Relations, and you can see some of those other groups. But what we're doing with Tableau today, it's been a journey. And it didn't -- we weren't able to just do this on day 1. When we think back to 2018, this was just prior to the acquisition of Tableau, our finance organization was just over 1,000 people. They were struggling, trying to get access to their data, to get insights, to make those data-driven decisions. And then we launched a multiyear program to try and land our finance data into a data warehouse or data platform that we then could get some real-time or near real-time insights on to that data. And this is shortly after that's when I joined the company to build out the finance data office. And this is where, again, we made that decision to move to Snowflake as our cloud enterprise platform. This is when finance was one of the early adopters. So not only were we trying to drive the adoption of a new cloud data platform for the organization, we're also trying to drive the use of Tableau in finance group. Now fast forward to 2022, finance is now over 2,000 people. Some of that has been driven through just hiring, but also through acquisitions of a few different companies. But now we had Snowflake as a single platform that we can have Tableau on top of to drive those insights. Now we're 2024 and beyond, we're trying to leverage the investment that Salesforce is making into their data cloud product, how can we now bring the data that is inside of the different sales clouds, the marketing clouds, service clouds as far as the ecosystem of Salesforce, but how do we then bring it together with some of our data that doesn't reside in a Salesforce org like our finance data. So on top of all this, we've created a number of different use cases. And so on this next slide, what we're showing you here is just as Ed has shown you how we're using it inside of sales and Jeff has shown you how we're using in marketing, we are trying every day to try and leverage our own products to drive insights into the company. So whether it's in our accounting groups or sales operations or FP&A, treasury and tax groups, these are a variety of different ways that we've been able to leverage Tableau to get insights into our data. And if you scan the QR code here, you'll be able to go out to our Tableau Public Gallery and be able to explore many of these service all of you. So what I want to do now is I want to jump into a demo, and I want to show you how are we using our product inside of finance. So the first place I want to look at is our management business review. Now think of this as you have your analysts inside of your FP&A teams. They are supporting a number of different departments across your groups. You want to make sure that they are using single sources of truth that we can make sure that we start the conversation with confidence and trust in the data in which they're using. So we don't want to have 4-year versions of this dashboard for each of different departments. We want to have one that they're all using to start that conversation and dialogue. So right now, our departments are filtered to all, let's toggle this so we want to look just at our development organization. The other thing that we're trying to bring with this visualization is we're trying to bring that modern visual approach of being able to see what the trends are in that. But we also know our finance professionals love their spreadsheets. They love to see their cross tabs. So we're trying to balance that visual aspect of the data to see the trends, to see the outliers but then also bringing them some of the data that they need. Now this isn't just the actuals data. We've also brought in our forecast data. So now our ability to see how are we doing, how are we trending? And then we -- but beyond just our financials or our expenses, we've also brought in our FTE counts. So now we've calculated a metric here on what is our cost per average to FTE. We brought in our revenue as well as an additional data source to calculate a percent of revenue, which, again, are common metrics that we're trying to do inside of our organization. But let's say we don't want to look at the second forecast of the year. Toggle that off, and now you'll see that all the forecast numbers have gone 0. Let's toggle that to the first forecast that we did and how are we doing. So a little bit of that scenario planning or our leaders have said, "Hey, we're expecting our revenue to grow. We're going to increase our expenses." When we did that reforecast it, in fact, is that what happened. But beyond just having physical filters on the dashboard, of course, we also want to make sure that we have action filters. That ability for the user to toggle into something and filter all of the data that's on there. So let's say, we look at travel and entertainment expenses. Now I've highlighted my line chart to be able to see how they're trending. I've broken this down by each of the months inside of the quarters. I recalculated all of those metrics just focused on T&E. Now Tableau is wonderful at handling dates. But if I change the date hierarchies here, which are available through the pluses and minuses, I'm now not going to have alignment with the axes of my metrics down below. So with this simple action filter here, I now can toggle it between my month view and then my quarterly view. So we've looked at our travel and entertainment expenses here, and we see that we have a bit of a problem. Let's double-click into those travel and entertainment expenses. So here what we're showing you is a dashboard that is built out of an extract out of our instance of Concur, which is where we're tracking all of our travel -- our T&E expenses. And the author of this dashboard is focused on what are the top 5 expense types. Now these are not surprises, right? You would expect your airfare and your hotel and meals to be some of your top spend just because of the nature of that business. We can see how is it trending on a 4-week moving average, and so we can kind of see again, we're starting to trend a little bit above that average. We're showing relative size as far as 28% of our total expenses are covering our airfare purchases. And then just as we have with the other dashboard is I want to be able to click into this I now can do a highlight action, I can see who are the top 25 employees that are incurring airfare expenses. I've now highlighted across the scatter plot, and I can see that I have an outlier here with Jazlynn. And so I can click on Jazlynn. It's now highlighted that not only where does she sit in the heat map down here below, but also where she sits in the rest of the scatter plot. But through this action filter, I now can also jump into the employee details. I can now see all of the transactions, all of the events that are behind that data point. Now I don't know if you guys have used Concur or other travel or T&E systems, but I can tell you that having this type of insight into your data inside of those platforms is very difficult. But by now landing all of this data and exposing it to us with Tableau, I now can start to see greater insights into that. Now I can hit on the tabs and go back. Right now, I have this go back button, which is going to take me back to the dashboard to see where do I want to go next in my conversations or my insights. Let's now look at some of our hotel expenses. One of the common things we want to look at is like how much are we spending per night. So through the scatter plot, you can start to see that total spend by average per night. There's a lot of clustering here, which we would hope. But of course, we do have some outliers out here. And so I can click on these data points, and now I can see how much have we spent at Menlo Park? How many nights have we stayed there? What is the average cost of spending there just as we're able to look at the employee details, I now can go to the hotel details and now I can see what is driving that -- those expenses? And then the last one thing I want to look at is our airfare. As we saw that on the first dashboard, that is one of the largest expenses that you're going to have inside of your organization from a T&E expenses. So it's going to be really important that you've set policies around your travel and entertainment expenses. How far in advance do you want to encourage your employees to be booking that travel? Right now, we've set the target at 14 days. But let's say that we want to be really aggressive and we want to say, "Okay, we are expecting our employees to now book their travel more than 21 days in advance." And now we can see what is the relative percentage of how many of our employees are, in fact, following our guidance and following that advice. And we can see here that over 70% of our employees aren't booking their travel within 21 days. That is incurring extra cost to the organization that we need to potentially drive down. Now just as you've seen with Jeff and you've seen with Ed is that we can do a lot of wonderful things with these dashboards, but what could we do if we looked at the same data through a Pulse metric? So now I have subscribed to 3 different Pulse metrics, and I have a summary up here of how that they're doing. I have my business travel expenses, we should be just looking at my travel expenses or I can now look at my employee expenses, which was similar to the dashboard that we were just on. So now if I click into this metric, I can now start to see how are we trending? Through AI, it generated this narrative to me indicating, "Hey, we have a little bit of a problem, we're kind of trending in the wrong direction." This is Jeff and Ed showed you, we have the ability to use some of the precans like, okay, which employee now has increased the most? We want to be talking with Nila and we want to talk to Xavier. We want to talk to Cayan and try and understand this or as a people leader, I want to understand why are these people traveling so much? Are they on our sales team, are they on my marketing team or are they traveling to events? Or maybe I want to see which expenses are the lowest. And so again, Tableau is offering these precanned questions for you, but just as Ed and so we are through we can ask questions of this as well. And the ability through the breakdown that right now, we can see what are the top cities. We didn't have to build a dashboard to look at this. We can just explore this data and go where is our curiosity. We can see who the employees are. We can see who the expense -- what the top expense types are. And again, no surprise that we're expecting that hotel would be that. So hopefully, there in the last couple of minutes, I showed you just some of the insights that you can now start to get with your finance data, whether it's through Tableau dashboards or leveraging the latest capabilities that we have with our Tableau Pulse product. I turn things back over to Jeff.

That's awesome. Thank you, Ed and Mike, those are some amazing demos and use cases. And as I sat here watching these demos come together for the first time, I know that's just how consistent the experience is with Tableau Pulse so that anyone can enable others on using data. And aside from driving our own teams and business, data helps build visibility across the entire company and that builds empathy and understanding and how we all have common goals, although we're in different functions that ladder up to the business doing well. And so now as we wrap up, we want to recognize that nothing is prescriptive because every enterprise is complex, like I mentioned, and every enterprise is unique. But the important thing is to have continued dialogue around transformation, right? This is the most tangible thing that you can do wherever you sit in your organization. So have conversations around driving adoption by advocating for AI to lower barriers to insights that is followed by user groups and build communities around data and using data. Conversations around change management and not shy way or delay just because change management is hard. We're in the age of AI, where the imperative for trusted data is renewed because your AI is only as good as your data. So although businesses have different regulations and data residency requirements and whatnot, get specific on finding use cases or datasets that can be migrated for cloud deployment because that is where AI inhibition is fast moving. And so that you can build that momentum in ground swell one step at a time because the more people that can use AI, the more demand to help move the needle on overall change management and migration. And don't forget about enablement. Enablement is not one and done. Have conversations with stakeholders to create programs around 2-way enablement where you have a feedback loop so that you can iterate on products through the user-driven advocacy that in turn inform how and what you need to refine enablement on. But also, we're here to have conversations with all of you throughout the various different teams and use cases that you've seen here, we're here to help you along your journey. Now we have some resources here to help you get started both from a product perspective, but also from a knowledge of the landscape. Our Tableau Cloud trial includes access to Tableau Pulse. So get your hands on it by connecting whatever data you have and experience insights in a whole new way. Separately, we have our research paper on our approach to trust AI as well as our state of data and analytics report, where we surveyed over 10,000 IT and business leaders for insights across the entire landscape. So prefer to scan the QR codes here. And at this time, we'll transition over to our Q&A with all the speakers here with us today.

So it looks like we did get some questions just around getting the recording of this webinar. Again, this will be available on-demand.

There is a question out there specifically around using predictive analytics. So I think we have common predictive analytics techniques that have been built into this regression models, clustering models, time series analysis where you can get on desktop and kind of do the forecasting of it. If you look on the walk-up dashboard, when I was kind of showing that, what's interesting is we use now with an Einstein machine learning models that are able to go ahead and predict the conversion rates of pipeline that was built prior to the quarter and bringing that in. So it takes things like average age, number of push dates, close rates, kind of closed loss staging and all those things. The machine learning model is able to go ahead and predict where we're going to finish. And what's fun with that is that we've gotten better. So as a sales organization, the machine learning model used to say we would convert a much smaller percentage of our pipeline than we are now because really, when you look at Salesforce and Sales Cloud, you can use staging for the expected value of those opportunities. But that's hard because staging is at the behest of the person who is managing the opportunity, and there's always risk involved. So I think the machine learning model plus the EV for those opportunities allows you to get a little bit tighter, again on how to accurately forecast and deliver that revenue. So I wanted to go ahead and answer that question specifically around predictive and share the link in there as well.

I also saw a question in there about the Tableau accelerators. So there's a couple of different options that you have there. So there are a number of different accelerators that are to support the finance area as well as sales and marketing, et cetera. Many of the dashboards that Ed and I showed you today aren't accelerators. But we have versions of our dashboards that are available on Tableau Public that you can download and reverse engineer. But there are like dashboards that are available as accelerators. So I would definitely encourage all of you to go out to tableau.com and explore those. And I'm also seeing a new question that's coming in here talking a little bit about, do we need to have Snowflake and Data Cloud or could we just have the Data Cloud? Again, it all depends on what the journey is and the transformation that's been going on inside of your organization. If you've already made a large investment in Snowflake and you already have all of your data, your sales data and your finance data and your marketing all in that platform, then obviously, you want to leverage that investment. But if you are just starting out and you haven't landed your sales data into Snowflake yet or you haven't landed your marketing data into Snowflake yet, then that's where you'd want to leverage the data cloud. So it really just depends again where you are in your journey and the transformation that you've made with your data platforms on whether or not you need both or you can just use one.

Yes, I think the data cloud piece is super interesting and exciting, right? If you think of what is the most people say data is the new oil. It's the air we breath, it's the water we drink. It's really about the value of that data. And I think if you look at everything that's happened with AI and the LLMs and those things, especially on kind of the public web, that's interesting, everyone has access to that. So LLMs end up being interchangeable. What's different is the data and there's no better leader when it comes to customer data than Salesforce. And data cloud and innovation that now surfaces up that data across all your different clouds for a singular view for the customer across their entire experience, visualize in Tableau. So encourage you as we come up to Dreamforce here happening in September. If you want to go ahead and take advantage of one of the biggest opportunities, not just in software but analytics in your business, especially if you are a big Salesforce shop, I would spend a lot of time in this specific area, investing time here because we're really excited what we're bringing to market here and what's going to be available for customers. In terms of making Pulse available for on-prem server customers, right now, it is only available on Tableau Cloud. And I think we'll provide updates. Now the good news with on-prem server customers is there's still many innovations that are happening. We just released 24 -- 2024.2. Multi-fact analysis is going to be a game changer. Viz Extensions is something where you can bring in like Sankey diagrams or Super Tables or things like that to visualize data in ways that have never been done before. That's still available on Tableau Server. So I do think it's important to call out that the innovations continue to happen there. What I would say is, is there a cloud instance that you would deploy almost from a prototype or POC perspective to give your access to Pulse for those people who need it because the beauty of Pulse is you're accessing a whole level of business users that aren't willing to jump into the dashboard, go through the filtering and do that. It's too overwhelming for them. So I don't think of a full on-prem environment to a full cloud environment, you might just start off with a pilot Tableau cloud environment, and we can go ahead and work with you to go ahead and make that as successful as possible. Want to hit, Mike, this Tableau have a workflow to take snapshots of the data and create a time series to show what data change when it comes to forecasting? Yes. So I don't have the exact answer to this one, but they can because we have kind of an analysis that happens of what are the snapshots in terms of stage management. So something that went from, let's just say, for example, today, there could be a deal that closes that was out specifically on 9/1, which isn't a date that we're managing deals on and went from stage 2 to close. And what's important of seeing that, Chris, for example, is that you're able to go ahead and analyze the progression of deals but a snapshot in time. So we definitely have that analysis. I don't know if we have a publicly facing piece of material that explains that, but feel free to reach out to me directly, and I'll be able to go ahead and connect you with some of the folks that have done that analysis. Mike, do you do any of that on the...

Yes, the piece I want to just make sure that we're -- yes, the piece I want to just make sure we're distinction is like, does the product itself, do you snapshotting versus are we creating snapshots that are then being consumed by Tableau. And again, it's more of the latter, where we've architected the snapshots of key data. And so obviously, the use case that Ed is talking about is a critical one, being able to see how our sales are progressing through their cycles. But we're also doing that, again, whether it's with some of our forecasting data, right, is essentially getting a snapshot and you have multiple versions of those forecasts that we want to be able to compare to each other. So we definitely are doing that type of analysis with snapshots to support forecasting and predicting what's going to happen.

Yes, especially think about open pipeline. Open pipeline always goes away at some point. But at some point, when I'm in the new quarter in Q3, I want to understand my open pipeline versus a year ago to understand the coverage I have and the health of that coverage. So that will be something that we can go ahead and follow up with. Any other questions from the group?

All right. Awesome. Thank you, everyone, for your time. Again, this will be made available on demand. Throughout this webinar, you should have seen a section to solicit for your surveys and feedback, we would love to kind of hear from you on what content you would like to see from us as we think about double clicking into some of the different pieces of Salesforce on Tableau around trust and security and how we deploy it and things like that. So please share with us your thoughts and feedback. Awesome. Thank you, everyone, for joining, and I hope everyone has a great rest of the week.

Thanks, team. Thanks very much.

All right. Bye.