Leave a Nest: Turning Data to a Profit Multiplier | Dreamforce 2025

So I'm here with my friend Takeshi. Could you please just introduce yourself and your role at Leave and Nest?

Thank you. My name is Takeshi I work the Sorry I work at the Levanist knowledge so let me introduce my company Lebanese have a mission about advanced science and technology for the global happiness. We have six offices Singapore, Malaysia, the Philippines, United Kingdom, United States and Japan and we connect academia with company to solve the social issue together. So we have many conferences. Let me introduce two main components. First left side Science Capsule Conference this conference is research conference for high school student connecting high school student with academia expert. You can see in this portal hundreds of students gather to present their research Next Hyper interdisciplinary conference or HSE HSE Connect different industry with company to solve social issues together these conferences share same goals Science classroom connecting students with academia expert or experienced researchers hic Connect different industry with academia so this conference we make opportunity create new relationship thank you.

Thank you so much for that important work to connect academia and industry that's building the leaders of tomorrow. It's super important and we're excited to support you on that mission. So why did leavenows adapt Tableau next Adopt Tableau next and Slack well, Leaven us is facing some challenges that we see from many of our customers. We see that most insights today, despite a long time working on this problem, are most team decisions and actions are taken without insights and without data. If it's easier for me to use my intuition than to access the insights, I will just use my intuition. We also see that most teams continue to communicate in silos including around analytics. Even though sales, service, marketing, et cetera may share a lot of the same metrics such as customer satisfaction. They don't necessarily understand how they're working together and how their upstream and downstream partners are impacting their own work. In addition, the analytics team might struggle to connect with the business team and really understanding how their work is impacting decisions on a day to day basis and they want to better understand how the analytics are being adopted. Ultimately, this results in lost opportunities. There's gaps in the analytics resonating with the team because they're not in the flow of work where users are taking decisions and collaborating together and because they're not very accessible. If I can't easily find the insight again, it's easier for me to use my gut to make that decision if I'm looking through a dashboard with complex visualizations. As a business user like a marketing leader or a sales manager, I'm not an analyst. That's not my primary job. So digging through all of that data is not something I'm going to naturally do and I might not even know how. So ultimately this means there's lost opportunities for the business. Levinest wanted to revolutionize how their team collaborates around analytics and increase that adoption and they said they wanted to do that with Tablet X and Slack. So about a year ago we started working together and this is even before most of these things existed and you had this great vision. Can you share the vision that you had for how your team would interact with analytics?

Thank you, Austin. So we've revolutioned with Tableau Next. So in other words, how could we make this dream come true? This is harbor 2.1 is enable an analytics agent to provide trusted answers with tableau semantics. Point 2 Enable adoption though tableau Next and Slack.

All right, I love that two part plan. It's very simple and it basically says if we've got an agent where people are working, we think it will really change how the team collaborates. So to do that, first thing we needed to do is to enable an analytics agent that could provide trusted answers. And I'm really impressed. Leavenest has actually created an agent that is providing trusted answers now to 100% of the business. You've rolled it out to the whole company. So a round of applause for that. That's amazing accomplishment. So how did Leave and us do this? Well, it's really important that the data was ready. We know that most AI projects will actually fail without AI ready data. In fact 60% of them. So how did we achieve this? Despite some complexities for Leave and Establish, can you share some of these complexities with the audience? Of course.

So Levernist Lab Salesforce Platform so Levonist has customized Salesforce for over 10 years. We have a lot of custom objects and a lot of custom insight. Of course these objects have a lot of business context, a lot of business story, a lot of context. So these objects complicate other complex to understanding by analytics agent. Let me introduce about Lebanese system architecture. So everything built on Salesforce platform you can see the right side. We use three main business apps. Sales cloud and marketing cloud and the custom apps on Helc. These apps make a lot of data every day Revenue, customer engagement, campaign and more. So agent, force analytics agent will understand these data. But it is very very difficult complex. But now AgentForce can access the semantic layer. This is Tableau semantics. Tableau semantics doesn't just store the data, it provide a lot of meaning to these objects for analytics and agent. So now Agentforce can understand about what this revenue mean. What is customer engagement mean by my our Salesforce apps? So Salesforce can understanding our business data because by tableau semantics. Thank you.

That's great. The semantic layer is like the agent's guidebook for how to understand the customizations that your team has made over many years. And we were able to actually create the semantic models and enable that trusted agent over the course of just a few months as we built that out for the whole business to use. So that was really exciting to see when those answers started to come in correctly because the agent knew that context. So that was part one. And then the second part was let's enable adoption for that agent. And Leave and us wanted to do this in slack. With our tabletX and Slack integration, the whole team can rally around live data and the flow of work in a way that's natural and intuitive. In my existing team channels that my team is already having conversations in, I can share live analytics either through messages or through a team canvas, a collaborative document where we can view the latest together. In addition, Analytics Agent is a new team member in Slack. It feels like another person that I can reach out to, except they're always available and they know how to answer the data questions. So with this approach, Leave and S enabled the agent for 100% of the business. But let's see what that might have really looked like. In this demo environment, we're simulating a very similar agent experience that the Leave and S team members use every single day. Here we can see in my sales team channel, one of my team members has shared that our total sales are off track to reach our quota. So let's imagine I'm a team manager and I'm trying to understand why are we off track and what can we do about it. Well, first of all, for me to understand what's going on with total sales, there are other related metrics that I need to gain an understanding of to have the complete picture. This is where we have this team metrics canvas always available to us. And I can see the latest in this team canvas. My team can collaborate, write together, add images, workflows, lists, actions. There's so many things that can happen in this canvas, but now another thing that we can do is include metrics. So all I need is a link to a metric. I paste that link and choose to embed it as a card. When I choose card, it automatically turns into a visual that my team can engage with, including with tooltips. This is really tableau native in Salesforce or native in Slack. So in this experience now I can see that while total Sales is off track, my other metrics are actually looking pretty good. Maybe pipegen's a little bit lower than it should be, but I think I want to drill into Total Sales in particular to understand what's going on. When I'm doing that, this is normally where I start to take my gut well, actually, probably I hadn't even seen the data before at all. But at this point I understand the baseline, I understand the value, but I need to drill in to understand what's really going on. It has to be a deeper insight for me to take action. And normally this is where I might reach out to my analyst team. But what if the analyst isn't online? What if their queue is full of requests? What if, what if it takes three days or longer for them to get back to me? That won't work for me. As a business team, we need to take action immediately. So how can we drill in to understand what's going on? Thankfully, we have a new analytics agent in Slack ready to collaborate whenever we need them. My team member Harry has already started this conversation. He's asked Analytics Agent what's driving changes to total sales. I think I'll also chime in and ask Analytics Agent to break down total sales by industry and I'll say for this year. So when the Analytics Agent is providing an answer to this question, it's looking through that tableau semantic layer like we were talking about. It's looking for the trusted governed data that is AI enabled with all of the business context about my business that it's drilling through and providing an answer that actually is relevant to my team and respects my own permissions. Analytics Agent is actually respecting all of my Salesforce permissions automatically. I had no setup required. As a business user, my Salesforce and Slack accounts are seamlessly mapped and authenticated. So the Analytics Agent has come back with my answer. Total sales broken down by industry. It looks like energy and utilities as well as manufacturing are two of the key industries that I might want to focus on. In addition, Analytics Agent always leaves me in control. Analytics Agent came back with a message that's only visible to me so I can take a look, check out the sources, and then decide to share it back with the team once I feel confident in the response. Now that I've shared it back with the team, the whole team can access that visual and and the response and have that conversation to take action. But when we're taking action again, I don't want to leave Slack. So how can I take action right from within Slack? And how can I gain a bigger context about the upstream and downstream work that might be happening that could influence how I should take action? Well, if I click on the metric or any analytics shared into Slack, I can see all of the conversations across my own private channels and the public channels that are happening about that analytics object. So here I see the conversation in this team channel, but I can also see other conversations, such as from our marketing team, where they're understanding what campaigns might be relevant for us to increase total sales this quarter. Matt on my analytics team has actually shared that there is a manufacturing campaign or sorry, on our marketing team has shared that there's a manufacturing campaign that might be driving an increase to total sales for a lot of accounts like this one. But this particular opportunity has been in the negotiation stage. What you're looking at here is called a Salesforce channel. It's a channel that my team uses to discuss a particular account or opportunity or other Salesforce objects. In this place, I can actually update the record directly, such as changing the opportunity stage or even trigger workflows. In this case, I'll create a new task to give this account a call because I think this one might be one that could help bring total sales back up. So that's what it looks like for me to take insight to action all within the flow of work in Slack, with an analytics agent on my team available whenever I need it, and marketing and sales working together to drive action. But there's another Persona that I'd like to talk a little bit more about. What if I'm an analyst? If I'm an analyst, I live in Tableau. But collaboration is also super important for me today. When I create analytics, often I put them out into the world and I don't even really know what conversations are happening about them or how well it's resonating with the business. Not anymore. With Tablet X and Slack, I can look across all of the conversations happening with this data. Also from my flow of work in Tableau, or if this were embedded in Salesforce. Even as a business user, I can also access that in my flow of work from Salesforce. Even better, I can actually view oh, click the wrong button, let's keep it here. Even better, I can view the conversations and respond to them live. So here I can see this message that Matt had just sent and I can say, hey team, if I send that message, it's actually a live conversation going back and forth where my team and I are Having that conversation together. So this is a live bi directional collaboration experience from Tableau and Salesforce where my team can stay in the flow of work wherever they're working. All right, so we're super excited about that experience and Leavenst team is loving it. So I want to hand it over to you to share what does this mean for your team since you're often on the go.

Thank you. So Leavenist team member love Slack. So in other words, Lebanese team member living in Slack. So for example, Leibniz member will serve search anything. At first they will try to search on Slack but you know, you can see this photo. Japanese train is very, very close during rush hour. So we have to hold on the handle on train so we can only one hand is free. So we couldn't open the tableau, we couldn't open the check the data on tableau but now we can check the data and insight by my hand. Only one hand by Slack. So Slack and Tableau next change our data culture and make a new habit. Checking data inside every morning. It's an amazing product. Thank you.

That's awesome to hear. I mean, there's so many gaps in our day where we could be doing something valuable such as on the train to and from work. And I know that's a very common experience, especially in Japan. So having that moment where you can just actually with one hand getting the answers you need is a totally new way of doing analytics. I don't think we've ever enabled that before without an analytics agent. That's super exciting. And now let's talk about what that has resulted in for your team. Now that the insights are always at your team's fingertips and collaborating around insights is natural and intuitive. We've seen some amazing results at Leavens. So I just want to show off your success a little bit. It's really remarkable. You're leading the space here. So Leavens has now enabled 90% accuracy for the agent in Slack through tableau semantics. That means the team trusts analytics agent, which is very important. Once they trust it, they love it. They're seeing amazing adoption. At Leave and s we're seeing 10% to 80% adoption, an increase from 10% to 80%, which is truly revolutionary. So a round of applause for that.

Amazing.

So now every day it's a habit you mentioned earlier, like maybe even when they're brushing their teeth, they could be checking their data. I love that story. So in addition, that means there's a lot of saved time. That's one to two hours every day. You said that we used to be drilling through dashboards trying to understand complex insights. Now we can just ask an agent and get an answer right away. That's saving a lot of time and it's also saving you time as an analyst leader for the business as well. You don't have to create a new dashboard or new use case for every single request. Analytics Agent is there to extend your impact and ultimately this has a big impact on the business. I'm super excited to see how the increase in event attendance and sales and everything that is resulting from the analytics leading to better actions as a team. So that's tableaux and slack. It's generally available. Everything that we shared today, please give it a try. It's available if you have tableau and we're really excited to see how this transforms collaboration around insights for you and your team. And thank you again for leaving us for being wonderful partners and thought leaders. It's been great building this experience together with you.

Thank you Austin, from giving me the amazing products. Thank you.

Awesome. Thanks Steve.