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

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All Right. Thank you, Moya. Hi, everyone. Welcome to this webinar on how you can unlock and action data across your enterprise with MuleSoft and Data Cloud. And thank you so much for taking the time out of your day to join us. Before we get started, a quick note that we may be showing some forward looking slides and products during this webinar, but please make all purchasing decisions based off of what is already available. So my name is Jackie Wulfsohn. I'm a Product Marketing Manager here at Salesforce, and I'm joined by Ajay Kumar, who is a Director of Solutions Engineering at Salesforce. And we're also really excited to have Sean Donahue from Buyers Edge Platform joining us today, who we are going to introduce and get to know a little bit better in our fireside chat. All right. In terms of what to expect from today's webinar. So first, we're going to be exploring some of the data and integration trends that your business may be experiencing. And more importantly, we're going to go through how you can actually stay on top of these trends and really set yourself up for success. Then we're going to cover how MuleSoft and Data Cloud together can really unify all of your data to deliver trusted AI and personalized customer experiences. And then finally, last but certainly not least, we're going to get to hear from Buyers Edge Platform on how they're implementing Data Cloud using MuleSoft, and we'll get to explore some of their use cases and really see how they're improving both the customer experience and their business operations. So with that, let's dive right in. So right now, we know that there are many teams across your organization who are being asked to do more with less. And this is especially true for your IT teams who are constantly seeking ways to reduce cost, to save time, boost productivity, and this is amongst only a growing backlog of projects and requests. Fortunately, we have tools at our disposal. We have AI integration and automation, which are really proving to be powerful ways in which we can achieve these goals, and we're already seeing some great results. According to McKinsey, 79% of companies are reducing costs by using AI. Companies are also saving 67% of technology resources by using a unified data solution. And then finally, 77% of companies are saving more than 2 hours a week by automating repetitive tasks. And these are all great successes, but there's still more work to be done, and there's a lot more potential and benefits that can be unlocked. But as data volumes continue to grow, the challenge of doing more with less only becomes greater. We are living in an era where data is more abundant and is growing faster than ever before. So consider all of the interactions you have on a daily basis. Perhaps, you have an Apple Watch that's tracking your fitness. You're making purchases with your credit card across various different platforms. And all of this activity is generating customer data that has to be stored somewhere. Now today, companies are measuring data in hundreds of zettabytes. And just to put that into perspective, 1 zettabyte equals 10 to the 21st power or 1 trillion gigabytes, which is an incredible number. And this data is often scattered across many different systems. But really, to achieve success in this data-rich environment, companies really need to be able to learn to harness this data effectively and really use it to be -- to create exceptional customer experiences. But achieving this is much easier said than done. We know that data management is a really complex task, and it demands a lot of time from your IT teams. In fact, 36% of IT's time is actually spent designing, building and testing custom integrations across systems, and these custom integrations can create some challenges. They can be costly to maintain. They can be prone to breaking. And it's really important that they continue to adhere to security and privacy regulations that are just continuing to evolve. And this is only going to become more and more important as AI becomes more prevalent. But despite all of these challenges, this work is really essential because having access to data is really foundational for being able to deliver connected experiences that your customers have come to expect. So we know that companies need trusted data at scale, but integration challenges are often a major obstacle. So today, you may or may not be familiar with this stuff, but the average company uses nearly 1,000 different systems to track a single customer across various channels, and majority of these systems are disconnected. Yet to build lasting customer relationships and really meet the demands of this 71% of customers who expect those personalized interactions, companies really need a unified view of their customer. But to achieve this unified view, companies need a solution that can connect and harmonize data in realtime. And not only that, but a solution that can actually handle the incredible amounts of data at an unprecedented scale and actually make that data accessible across the entire organization, so that customers can have a consistent connected experience across every single touch point. So how can you actually harness all of your company's information? And this is where the Einstein 1 platform comes in. So Einstein 1 unifies all of your apps and data on a single integrated platform, so you can really deliver AI-powered experiences across your CRM and beyond. It brings intelligence into your workflows. You can automate and action insights across every application. But to deliver AI-powered experiences, you really need harmonized and unified data. So at the core of the Einstein 1 platform, our Data Cloud and MuleSoft, which are really those foundational components that make the predictive and generative AI capabilities across the Einstein 1 platform possible. And these elements really work together to integrate, harmonize and actually activate all of your data securely to really create those next-gen AI initiatives. So let's take a closer look at each one. So starting with Data Cloud, Data Cloud really serves as a central foundation for bringing all of your enterprise data into Salesforce, so you can really activate it across your CRM and beyond to power those intelligent AI solutions. So with Data Cloud, you can combine your engagement data from external sources like web and mobile applications with all of the rich customer data captured in your CRM apps. And by bringing this data together, you can create a true 360-degree view of your customers. But something you might be wondering is these are some incredible opportunities. But how can you really effectively implement and utilize Data Cloud to really bring this vision to life? And that's where MuleSoft comes in. So MuleSoft can really help enrich and secure your data, while enabling actionable insights across your business. And MuleSoft can really set you up for success with Data Cloud in 2 key ways. And the first way is that it opens up the universe of connectivity. So Data Cloud includes a native connectivity, including to a first-party data in Salesforce to major third-party sources like Amazon S3 and Snowflake and to many SaaS applications. But as we touched on before, we know that the reality is that companies have critical data that sprawl across hundreds of systems, 991 on average to be exact. And that critical data lives in industry-specific systems like Epic. It lives across legacy systems like SAP and Oracle. It's in homegrown systems like in your mainframe, and it's in other cloud-based applications as well. And MuleSoft is really that market-leading integration platform that can bring all of your data into Data Cloud to really fuel AI. And not only that, but to help you save additional time and cost, MuleSoft also includes prebuilt connectors to over 300 different systems. So with all of your Salesforce and third-party data sources connected into Data Cloud, Einstein now has richer contacts to ground your recommendations. And so this is where MuleSoft delivers on our next value proposition with Data Cloud, which is actually actioning these insights across your business. So within Data Cloud, you were going to generate some type of outcome. So this outcome may be creating a new segment or it may be using this data in Einstein Prompt Builder. And then MuleSoft can actually help you action these outcomes by distributing them in realtime to any external system or channel. So for example, this could include updating a health record in your EMR or it could even mean triggering multiple different systems and workflows to fulfill customer orders. So by bringing this together, what do you get as a result? Well, by bringing MuleSoft and Data Cloud together, you can really enrich the data sources that are natively available within Data Cloud by connecting its data across any system. You can action those specific segments from Data Cloud and insights from Einstein and actually create event-driven integrations and automations to interact with any downstream system in real time. And then finally, you can actually maintain visibility over and monitor all of your integrations under a single pane of glass to really keep that security and governance at the center of everything. So by leveraging one solution to connect all of your data to the Einstein 1 platform and action those insights in real time, you can really provide that best possible customer experience as quickly and efficiently as possible. So on average, MuleSoft customers can go to market 78% faster and reduce maintenance costs by 74% by really leveraging reasonable APIs and integrations. But now we want to actually double-click on the 2 primary ways in which MuleSoft makes Data Cloud better, which is connectivity and actually taking action. And to take us through that deep dive, I would like to pass it over to Ajay.

Thank you, Jackie. So we just saw how MuleSoft helps unlock and orchestrate data, and there are 4 different ways in which we can actually look at this. So let's double-click into each one of these type one by one. The first one I wanted to talk to you today is about on-premise. MuleSoft really makes it possible for you to connect to data on on-premise systems, which are running locally or probably from which our data is getting streamed to and from -- back from Data Cloud. And to solve these common challenges wherein there could be a lot of networking challenges involved, and when there's also systems involved that run on a private cloud or even public cloud that's deployed on a VM, especially if there's data being exchanged between back-end systems on a cloud platform or behind a firewall, you can imagine all those scenarios in which MuleSoft plays a very important role to unlock that on-premise data. The second one is transactional systems. And these systems are like your core banking systems, the ERPs, which hold your core business data, which is generated by the day-to-day operations in any enterprise, and it could be like things like sales orders or inventory adjustment orders. And from these systems, what you'll typically see is there will be some level of preprocessing of the data, which you'll need to do such as queuing, error handling or to even have some basic delivery controls, because the sheer volume of that data and the sensitivity around that data generated can be immense. And as customers, you'll probably have to deal with some preprocessing with MuleSoft before that data reaches Data Cloud. Let's take a look at what some of these preprocessing capabilities look like. So when we look at all that kind of different applications, which are both on-premise as well as transactional systems talking to each other, some of the preprocessing mechanisms, like queuing where we typically can guarantee that messages are delivered exactly once preventing data duplication or loss in the process. The second one could be like error handling, where we could automatically detect and manage for errors, therefore, ensuring there's a smooth flow of data even when the issue arises. Orchestration typically allows us to coordinate multiple services and APIs, which are talking to each other, and it's a normal scenario in any given enterprise and, therefore, enables the complex workflow of those systems to be executed seamlessly. With access, security and governance, we can help you define policies to protect the data and to manage those access control effectively, which is very important. And lastly, we were talking about the auditability and traceability of that data, which basically ensures all of that transactions which are tracked and could be locked, therefore, providing you with the necessary compliance and, therefore, also in the future for any troubleshooting capabilities. Overall, these preprocessing capabilities with MuleSoft helps you to take advantage of your transactional data in on-premise data that could -- to Data Cloud before it gets to Data Cloud. And finally, when it gets to Data Cloud, you can actually see -- you're able to harmonize this to create a unified profile of a customer or a single digital body language that you're trying to get to. And the next way I want to talk to you about is where MuleSoft enhances the connectivity for Data Cloud by providing the ability to ingest unstructured data. And we, from MuleSoft, have been dealing with unstructured data for a very long time. And typically, here, the unstructured data, you can think of it coming from key knowledge repositories like Google Drive, Confluence, SharePoint and many other such systems where you could be even extracting data from images and documents that are not in a machine-readable format. So let's dive into these 2 solutions that actually make this possible. So in April of this year, we actually launched our Intelligent Document Processing platform, also known IDP, which helps you to extract and classify data from a wide range of documents, formats, including PDFs and images, so that you can put all of that into your business processes to use. You can embed them as an invokable API action in your workflow to take action downstream into your systems like ERP or other legacy systems. We'll see some of that in action later when we get to the demo. And now with the advent of AI, you can actually look at how you can do bring pretrained models with the most common document type and also apply natural language tooling to this, therefore, minimizing the training and configuration time that you'll need to implement and, therefore, accelerate your release to market. So IDP also has this capability to perform OCR, which is very popular. So it can be used to extract data from images and other unstructured data types, so you can ultimately bring all of that data, ingest that data into Data Cloud. We're also very excited to be introducing a new solution for unstructured data ingestion. Introducing MuleSoft Direct for Data Cloud. This is only the first time we are talking about this into the public. So this is our new solution that makes it much faster and easier for you to tap into your organization's unstructured data. With MuleSoft Direct, you can seamlessly discover and deploy out-of-the-box integrations to connect to your organization's knowledge repositories to Data Cloud. This includes connectivity to systems like Google Drive, Microsoft SharePoint and Confluence and many other similar systems. By leveraging these prepackaged integration, you'll be able to simplify and accelerate the process of connecting your documents while completely adhering to the MuleSoft's well-defined industry-leading approach to connectivity. And you can activate all of these integrations without even leaving Salesforce. Once the data comes to Data Cloud, you actually think of using this to further ground your AI prompts for more personalized customer experiences, powered by our Einstein 1 platform, which is the most trusted Salesforce AI platform. We are excited to share that these prebuilt integrations will be available to open beta starting Q3 of this year, so let's see how this works in action. Let's say a customer service agent is interacting through Einstein Copilot. And basically, it's our Salesforce AI-powered sales agent. Asking if a customer in that journey is eligible for an account upgrade. Copilot today can search through Data Cloud Vector Database for relevant context across both structured and unstructured data. And some of this data is already available in Salesforce through the format of case data. And it can be used to ground -- increase the relevancy of the Copilot's response. But a lot of this data still is unstructured and still lives outside of Salesforce for most of the enterprises and many companies. It could be across your knowledge articles. It could be across your internal frequently asked question documents. So how do we bring all of that together? With MuleSoft Direct and IDP, we can now infuse Data Cloud Vector Database with additional sources and additional document types to connector. This is our easiest way to ensure that Copilot is able to access all of your organizational knowledge needed to provide the most accurate and reliable responses whenever you need it. And with that, we want to go back to our fourth use case, which is activation. So MuleSoft can respond to data events that you saw that Data Cloud has and then further orchestrate a series of actions in realtime to any downstream system. Let's explore how MuleSoft can facilitate these interactions. Think of this as anything that is at the tail end journey of Data Cloud. So the APIs that you use to connect to Data Cloud can also be reused to send data outside of Data Cloud. And to all the necessary systems to which this actually connects to, there could be a lot of insights and actions that you want to drive out of. Realistically, most of these systems and workflows traditionally sit outside of Salesforce and always need an integration platform like MuleSoft to reach them. And there are a number of ways in which MuleSoft can really help you extend the data and AI activations here. In a developer's perspective, a MuleSoft developer can actually invoke a MuleSoft Anypoint app to respond to a data event. And what this MuleSoft app can actually do is to respond to the data event changes in real time. And based on those multiple events across multiple systems, MuleSoft can help those developers take specific data out of Data Cloud and then send it downstream to the respective applications. If you look at through the lens of an administrator, they can use Flow Builder and Data Cloud-Triggered Flows to invoke an automation in Salesforce based on a data event. They can then further go on to invoke the engine that determines if the flow that has built the Flow Builder to update the record and synchronize that data and action system. Flow here serves as the rule engine that determines when and where to trigger those external systems. And finally, also, I want to highlight that administrators can still continue to use these MuleSoft APIs in Copilot to take action on those external systems directly from the Copilot's user-friendly interface without having to deal with the back-end systems of APIs. Ultimately, the value of Data Cloud here is being able to do something with the segments and insights that are generated and to be able to respond to those events in realtime and also being able to communicate with all the impacted concept systems, and MuleSoft facilitates all of this. And what you're probably seeing is Data Cloud is as good as the data it gets through ingestion, but it's also really valuable for you to take that insights and enrichment outside of Data Cloud to activate it downstream, and MuleSoft plays a very important role in this process. So let's see how this actually works in action. I'd like to take a use case of a financial services organization. Popularly, it's called as a bank, where they're trying to manage their customers' information and relationships. You've typically seen this where a customer comes to a bank, and if they've had a life-changing event where they have to manage a portion of their money, a bank like this, an organization can harmonize that data, which could be coming from multiple systems like Financial Services Cloud, which has a native integration to Data Cloud, of course. And this also could be across several banking and transactional systems from external entities, such as the core banking systems and AS400, which are typically the legacy systems. And from this, MuleSoft can really help you extract that data and send it to Data Cloud. So let's see a quick demo of how this really works. From Data Cloud's homepage, what we can typically see is a cumulus setup. We can actually activate the most active data streams to bring that data together from various locations. And here, you can add a new stream as well just by using few simple clicks, where native integrations to Salesforce Clouds, like, for example, in this case, Financial Services Cloud are available out of the box. MuleSoft further extends these capabilities with out-of-the-box connectors, and there are a lot of those which allow you to interact with the business systems available on Anypoint Exchange. If I go to the next example, which is typically the use case of activation. If we continue with our banking example, we can actually further see how an action that is generated can be further driven to take the base off our personalized customer action. After harmonizing the customer profile in a banking scenario like this, transactional data streams inside Data Cloud can uncover very valuable insights about like a segment of a customer. For example, in this case, I'm talking about a customer profile where we discover a segment where customers with having greater -- deposits greater than USD 10,000. And we can further take a look from how this bank can help those customers to make better financial decisions. Let's take, in this case, an incoming transaction kicks off a Data Cloud-Triggered Flow, which can then create a new opportunity in Financial Services Cloud. And MuleSoft, in this case, comes in handy to create a transaction where a personalized offer is created for this specific customer and send further downstream to market, which is an external system to Salesforce and to drive a marketing journey. So let's see how this actually looks like in a real world now. In this example, here we are typically looking at how we can actually send and who is typically a customer of that purchase a gift. Behind the scene, Data Cloud can act on this data change using a record-triggered flow in Flow Builder to create an opportunity. In this case, we're trying to create an opportunity for an investment account 529 in Financial Services Cloud. Alongside, what we're also doing is taking Data Cloud's actionabilities to third-party systems using MuleSoft. A separate MuleSoft app, in this case, is detecting a data change using the Salesforce platform event. And therefore, you can also apply that downstream action back into marketer, where a personalized e-mail is triggered back to a customer, providing them with very relevant offers in real time. So with this, you've typically seen how a data cloud journey looks like. And with this, I want to hand it off back to Jackie for next chat.

All right. Thank you very much. So I'm excited now to be shifting gears a little bit and getting to hear directly from Buyers Edge Platform and how they are delivering quality engagement with MuleSoft and Data Cloud. So Sean, welcome. Thank you for joining us today.

Thank you, Jackie. So just first, thanks -- thank you to Jackie and Salesforce team for allowing me to join and share kind of what we're doing at Buyers Edge Platform with both Data Cloud and MuleSoft. So I'm Sean Donahue. I'm the Chief of Staff at Buyers Edge Platform. I've been here 9.5 years, currently located in South Florida. And as the Chief of Staff, my main focuses are on key executives initiatives, new strategies and others as well as focused on some of our M&A activity with diligence and integration into our organization. And I also manage our entire operational organization for the company as well as our data teams as well. So a little bit about Buyers Edge Platform. So we are in the foodservice industry, mainly focused on 3 key stakeholders being the operators, distributors and manufacturers, being the key stakeholders in that ecosystem. We bring a bunch of different foodservice operators from independent restaurant operators, casinos, universities, hotel and lodging. Anybody that is in the foodservice industry, we focus -- we go and we sign those customers up. We focus on procurement and supply chain. And what we do is we have 4 business units. One is our biggest, which is called our digital procurement network in which we go and enroll restaurant operators in there. And they work with us, and we collect their invoice line item data on a daily or weekly basis. And we help them clean and normalize that data, provide them data insights as well as technology solutions to help them run their business more efficiently and understand what they're spending it on, where they're spending it on and from who. We also have a fresh division, which helps them manage their fresh produce purchases, all the way from the seed at the grower through distribution into the -- through their kitchen and onto the plate for the operator. We also have a division that focuses on providing consultive type of activities where operators will hire our team to help manage their procurement division within their organization as they're scaling their business. They're working towards being able to develop their own or we support an existing procurement team in that factor. And then we also have a technology or SaaS division, which is comprised of 2 different types of products, one, being an enterprise analytics type of platform, which helps bring all the data in for the larger operators and kind of gives the executive team at those operations insights into how compliant each location is being, what they're buying, what they've spent, are they being charged the right price that they should be and as well as helping them with their RFP processes, when they have to negotiate contracts with suppliers, whether that's a distributor, they want to go and negotiate their own direct manufacturer deals. We also have another solution, which we call our Back Office, which is -- helps operators manage their inventory, recipe costing. It also has a restaurant-focused accounting platform and payroll solution to help them with managing that, all powered through the data that we collect for -- on their behalf. So Buyers Edge Platform is a family-owned company. We got just over 1,200 employees and work with over 240,000 operator locations and are now expanding into Europe as well. And then so kind of just give a little bit of where we're going with our data. Obviously, we've done 26 acquisitions over the last 5.5 years, and we process over 400 million invoice line items and growing on an annual basis. That grows on about a 20% to 30% clip every single year. And so we got to bring -- we're bringing in a lot of data and we're cleaning and normalizing a lot of data and trying to map it. As I said, we have a few different business offerings for the operator to participate in. So bringing all that data into one -- and allow our teams to create action on it is where Data Cloud and MuleSoft has come in for us. And I will say, before we get started on the use cases, Data Cloud journey for us has been a 3-year journey. It was very -- took me a very long time to kind of wrap my head around it from a B2B perspective. I understand Data Cloud and the power of it for a B2C model and things like that where you're focusing on the actual individual in which you need to engage with, where our customer is really the operator at large, and there's multiple different contacts. So figuring out how to drive the actions there was -- has been key. So with Data Cloud, what we did was we evaluated kind of what data we needed to bring into Data Cloud to start and where we were going to get that from direct connectors with Data Cloud, and that being our Salesforce, CRM, core sales and service products as well as Marketing Cloud, Pardot. And we also have Redshift database, which is the database in which we ingest all of the different data in from all the different channels that we get it from, from our distributor partners as well as our distributors. And we bring that data in, we clean and normalize it. We map it, and we don't house that information in Salesforce on the line item detail level. What we do, keep it there in a roll-up perspective. And then MuleSoft, here we do -- because of all the different acquisitions, we've acquired a lot of different companies that have their own systems. And so we have a lot of different data in multiple different places and where we want to -- and everybody, as you acquire companies, nobody uses a consistent nomenclature to how they name their customers or things like that. So we have to go through a whole bunch of exercises to integrate them into the ecosystem of kind of normalizing their data to our kind of standards. So we're -- we'll use MuleSoft for -- to help us kind of bring all those systems together and push information into Data Cloud to help us find that unified profile for that customer across all the different platforms. We also have a lot of different customer-facing or stakeholder-facing products in which requires some data to be crossed system to system. And we also have wound up with a mountain of APIs that we will eventually want to manage through the MuleSoft's product as well as much enhancing native cloud. So kind of the first use case for us is the purchase data for the operators. All 3 stakeholders have a key need for this data, right? The distributor which is selling to the customer wants to know how much product they're selling to customer, how often the customer is placing orders. The operator wants to know what they're buying, what are they earning on their rebate dollars, where are they saving on our national pricing and where is there opportunity for us. So kind of the use case #1 for us was how do we utilize that purchase data once we synchronize and unify profile and bring in that Redshift data to empower actions off of that. So we'll trigger kind of through MuleSoft and feed into Salesforce kind of our operator report card to show the customer -- show our internal sales team what's going on with the customer, when is the last time we received their purchase data, when is the last time they received a rebate check, how much was it, what was their latest action with the team, latest engagement and things along those lines to help our client management teams and sales teams have better insightful conversations with the customer based on their actual behavior through data. And then we also will provide them where there's opportunities, right? So triggering action through Marketing Cloud as well to say, "Hey, you're buying this product that is not under contract. And the distributor in which you're purchasing this product also sells this product, which is under contract. And here's an opportunity. Would you like to set up a meeting, engage and -- along those lines?" And then looking at the customer as we bring it in and based on -- and utilizing our customer data and data points on our customers to say, "Hey, we've recently signed up this customer. We have an existing customer who fits a certain criteria of data that will trigger the team to initiate." Contact with them on the next best solution to -- for the operator to engage with us for opportunity to save money or find efficiencies in their operation where the labor in the restaurant industry is always hard, especially when we're talking about our independent restaurant segment, which is our largest group of operators from a number count. And so helping them find ways to initiating it based on the data, find ways to help them with the next best solution to help them with their pain points based on the data. And that will all be triggered through Salesforce Flows as well as Marketing Cloud, engagement and things like that. And then obviously, the purchase data being at the center of everything we do without the purchase data, we can't provide them with the insights or the know-how of what's going on with their business, unless we have that. So if we notice that there is a disconnect from their data, we will trigger in real time. So do it in 30-day segment, 30-day windows because we kind of can get reporting on weekly, daily or monthly basis. So we allow time to elapse. And if we haven't seen purchases in the last 30 days, engage, right? So either send them a notification, like, "Hey, just wondering if you -- did you make any purchase? Did you switch distributors? Did you stop buying from this operator?" And it also triggers an action to our internal teams to engage with that customer. So we can either do it through Marketing Cloud, send it through to our customer portal, which we call our Launchpad to engage messaging through there, to drive them to reconnect on their purchase, so that we can help them maximize why they joined our platform, to save and earn rebate dollars on the platform.

Well, thank you, Sean. So many great use cases. So much meat there, but it's really great to hear how you're able to bring together MuleSoft and Data Cloud to not only unify your data across so many different places, but really take that data, action on it and generate new insights for your customers. So that's all fantastic.

I would love to hear from you, what are some of the results that you're seeing? What are some outcomes that you're seeing now that you're in the thick of it?

So on the last use case, I can -- I know that one off the top of my head because that one recently came up for us. So on a quarterly basis, we do a big campaign or initiative for our teams and identify all the customers who have missing data for a certain period of time -- for a 3-month period of time, and we give them about a month to resolve it. And typically, we resolve about 75% to 80% of it in the 4- to 5-week window. We started our latest one, utilizing the segments that we created and based on the criteria through Data Cloud. And within the first 2 weeks of the initiative kicking off, we have resolved 38% of the customer on a positive route. So that we were able to engage with that customer and confirm and get that data reporting to us. And then also we have a lot of -- the other one that we are seeing a lot of positive around is identifying our milestones for our customers. You've been a customer for x period of time and giving them a shout-out and an acknowledgment and incentivizing them for being a member with us for 1 year, 5 years, 10 years, and kind of really driving that engagement with the customer to drive utilization of our customer portal up or increasing conversions to contracted manufacture items and things along those lines.

Some great results. Very exciting to hear some of the outcomes that you're starting to hear -- that you're starting to see. I'm sure there's a lot more greatness to come. And would love to hear if you have any best practices to share. Do you have any advice you would give to an organization who, let's say, is just getting started? Or if they're considering using MuleSoft with Data Cloud, what advice would you give them?

For us, it was less is more for me is kind of my mantra. I understand the sky is the limit. There's endless opportunities and countless opportunities to kind of dive into rabbit holes, as I would say. So kind of for me, it was really about focusing on, okay, what are the 3 to 5 biggest things that we're constantly going through that is driven by data, right, which is taking team members of ours or analysts to identify what we need to attack and where we need to attack and when from a sales perspective and marketing perspective and utilize Data Cloud to help us create those parameters, create that stuff and drive kind of more realtime insights into that. So it's not -- doesn't take us 3 weeks to prep for a campaign. It can kind of almost happen in realtime as we get it going. And then also for me, it is documentation, training. And then the other big piece for me was identifying my 3 to 5 key stakeholders in the project who are going to be the ones carrying the torch along the way and responsible for making sure that we hit the milestones that we wanted to hit along the way.

All fantastic advice, and it seems like you were kind of able to narrow down the huge landscape of opportunities into really impactful areas. So I think that's excellent advice. So thank you. All right. Well, Sean, thank you again for joining us today, taking us through your story. We're excited to see more of what's to come of all this. So thank you.

I appreciate it. Thank you.

All right. So I'm going to just wrap this up with a quick recap of kind of what we've heard during this webinar. So really by bringing MuleSoft and Data Cloud together, you can really improve operational efficiency by optimizing data flows and automating processes. You can facilitate that seamless engagement across multiple different channels. And the end result, personalized customer experiences that can really help you gain a competitive edge. All right. And we would love to continue the conversation with you all. We have a few resources to leave you with, where you can continue to learn more about all of the topics that we discussed today. So first, you can scan this link here to subscribe to our LinkedIn newsletter, which is called Technically Speaking. Here we share news about integration, automation, API management and AI across MuleSoft. So really great resources to hear kind of the latest and greatest. We also have a bunch of content on mulesoft.com, where we go through strategies, deep dive use cases into leveraging MuleSoft and Data Cloud. And then finally, Dreamforce is coming up. It is coming up in a month. It is the world's largest AI event. It's being held in San Francisco in September. We've got tons of amazing sessions and opportunities to get hands on with our products, and we would really love to see you all there. And with that, thank you so much for joining this webinar. We are going to -- happy to answer questions. So I'll go ahead and take a look at the chat and see if there are any questions that we can answer for you all. So to kick us off, we've got a question for you, Sean. Does Buyers Edge Platform have any plans to leverage AI in your MuleSoft and Data Cloud initiatives?

Yes. So that's part of -- a lot of these use cases are going to start powering that model for our sales team to engage. So we are actively in the process of launching out our Einstein bot within our Salesforce core product, which will allow our reps to ask certain information of the bot that will utilize the data from the Data Cloud kind of unified profile in order to engage with that customer. Or if they're on a business view with a customer and a customer asks them a question that they know is data driven, they can ask the question of the chatbot. That will hopefully be able to pull that information from the Data Cloud model to allow them to answer the question faster. So they don't have to tell the customer, "We will get back to you," and kind of really drive them to engage more insightfully. And then as well as utilizing it to write drafts for their followup e-mails and helping them with that as well based on the data that is kind of married in that unified profile.

Awesome. Some great productivity gains to be had there, I'm sure. All right. So it looks like we have another question. What external systems will be available through MuleSoft Direct? Great question. So, there are 4 initial sources that we will be supporting from the start through MuleSoft Direct. So that will be prebuilt integrations to Google Drive, to SharePoint, to Confluence and to Sitemap. And in case any of you aren't familiar with Sitemap, it is a blueprint for all of the pages on a website. So with MuleSoft Direct, you'll actually be able to extract and ingest a web page data using the prebuilt integrations to Sitemap and then you can leverage this data within Data Cloud. All right. And it looks like we've got another question. Let's see, for Ajay, maybe I'll send this one over to you. Someone asked how can you get started with some of the unstructured data ingestion for MuleSoft?

Yes. Well, as you rightly saw, with MuleSoft Direct, we are actually helping you unlock this unstructured data. And it is very easy and pretty straightforward for you to access all of this from within Salesforce setup and to use those prebuilt integrations that we just talked of at no additional cost to your Anypoint Platform subscription. So that's how easy it is for you to get started with this unstructured data ingestion journey. And well -- as we said, we'll share more details in the future sessions.

All Right. Thank you, Ajay. All right. Well, it looks like those are the questions that we had. So again, thank you all so much today for joining this webinar. We really appreciate it, and we hope you have a fantastic day.