Zoom RevenueOS Unifies the End-to-End Revenue Motion (Full Transcript)

[00:00:02] Speaker 1: So, what if your CRM, your pipeline, and your forecast all told the same story? Today, I'm going to take you through how that's possible with Zoom's Revenue Operating System. But first, let's take a look at the state of the market. Nearly every tool in the stack added AI. Signals got smarter, sequencers got smarter, calls got summarized, deals got scored, forecasts got a confidence number. But six sets of intelligence that don't share context isn't an advantage because they're all isolated. Each platform holds only a fragment of the same customer. And the insights stay siloed. This isn't just a tooling problem. There's an architecture challenge underneath it. The integration layer stitching all that together? It's your team. That's a problem because all that critical intelligence could get lost in the seams. The signal fires Tuesday when a customer engaged on a webinar, but the rep might not hear about it until next Monday, if at all. Discovery happens in one system, the follow-up sequence gets drafted in another, notes get retyped into the CRM, or they don't, and the record quietly stops being true. The forecast is assembled last, built from whatever survived all those handoffs. Signal platforms see an anonymous account researching, not a person. Nothing builds campaigns off of that anonymous signal. Sales may never see it. And the platform never learns whether the deal closed because it stopped at the handoff. Conversation platforms start at the first captured call, but everything that got the buyer there, the campaign, the content, the webinar, it's invisible. The CRM holds what someone typed and not what happened. And very few platforms see the full arc. We think that model needs to change. Revenue teams don't need more AI features. They need a system that understands the arc of the buying journey. And the answer isn't yet another app with better AI. It's one revenue operating system that learns as you go. So why Zoom? Not because we built more features. It's because of where we sit. Zoom is different because we're already in the room, meetings, webinars, phone calls, they're already happening on Zoom. We can capture conversation intelligence natively without requiring an external recording tool. That's a structural advantage that's difficult to replicate through integration alone. And RevenueOS builds outward from that position. The next era of revenue software won't be won on features alone. It'll be won by teams with a unified system, one designed to surface the full buyer picture, help orchestrate the right actions and improve with every deal. That's RevenueOS, and we're just getting started. So let me break down how we're building a revenue operating system, a unified foundation that helps teams identify high potential opportunities, orchestrate recommended actions, and support the revenue motion from pipeline generation through coaching, close, and renewal. Here's how it's built. Layer one at the bottom here is the shared context. One place with all of your buyer intelligence, conversation intelligence, and CRM data all unified in a single foundation every motion reasons over. Layer two is the orchestration. One orchestration layer where operators turn signals into repeatable plays. The system does the stitching. And layer three is the application experience. The surfaces where revenue teams actually work through the phases of the buyer journey with a tool for identification, engagement, coaching, and closing, and forecasting with one login, one UX, one data model. And running underneath all of it is a continuous learning loop designed to write outcomes back. So the system is built to improve over time. That's hard to replicate with disconnected tools. Let's dig into shared context a bit more. Six data types, identity, enrichment, buyer signals, conversations, engagement, and deal context all in one foundation. One profile, not six different records across apps. People and accounts are designed to resolve into a single view every motion can reason over. That means less middleware, fewer dashboards that disagree, and best of all, manually stitching these things together isn't required. Read and write in the same place. Every surface, coaching, forecasting, sequencing, reads from and writes to this shared foundational context. And the learning compounds. Each closed deal helps sharpen what the system knows about how your company wins. Adjentic systems are only as trustworthy as the context underneath them. We're continuing to invest in data accuracy, enrichment quality, and the intelligence layer that powers everything above it. Because a strong foundation is essential to everything built on top of it. But context without action is just a dashboard. Once you have that end-to-end context, orchestration kicks in. An account plan drafted from signals already in the system requiring no manual research. Messaging is shaped by what actually happened in the meeting, not a template. A sequence that adjusts what the buyer just did, configurable by rev ops, repeatable across the team. This is where signal becomes a play and where operators define the model. Human to human, human to agent, agent to agent. With governance and control over how the pieces come together. This is the compounding effect. And it's what separates revenue OS from a collection of tools. Outcomes are captured and shared back into that shared context. That means a closed deal doesn't just close, it teaches the system. Who responded, what worked, where the deal stalled. That intelligence flows forward. Targeting gets sharper, coaching gets more specific, forecasts calibrate based on what actually happened, not what reps remembered to log. And it spans across buyer intelligence, conversation data, and the CRM, all feeding the same loop. The more your team uses it, the more data feeds the system and the more useful it becomes. Winning starts to feel less like a streak and more like a system. So let's make it real here. The goal is to get more qualified pipeline and win more revenue. So here's how it works. A target account starts showing intent. A person is researching competitors, engaging in a community, and let's say they attended a webinar and asked a question while they were there. Common Room by Zoom captures that signal and dozens more like it from product usage, marketing activity, web research, social engagement. It aggregates all of it and maps it to the account. So you're not chasing just a single data point, you're seeing a much fuller picture. And then it asks the questions a good rep would ask. Is this a fit? Who's involved? What have they researched? What's worked in similar accounts in the past? It identifies the right people so you can reach them at the right time. That's the power of Common Room by Zoom, bringing buyer intelligence to life, aggregating signals across channels, mapping them to accounts and individual people, and connecting the dots from customer actions to customer outcomes. And now that we know who to engage, when, and why, Engage kicks in to orchestrate outreach. Engage delivers high-volume, structured, multi-channel outreach and sequencing. Reps get a prioritized daily action list, email tasks pre-fill from a sequence template, and leads are pulled in straight from CRM. The result is that teams can work more accounts, they can miss fewer follow-ups, and they drive more pipeline. No separate tool is required, and you can keep that lead moving right through your sales funnel. Now, say that prospect got an email after their webinar, then a text, and maybe now the rep is ready to make a phone call. So using click-to-dial right from Engage, they connect, they do some discovery, and boom, the meeting is booked. Now that we've got the qualified lead, it's time for the rep to practice for that next conversation. And they can do targeted practice, so they walk into that next meeting already knowing the customer context and the intel. In fact, they can practice with simulations before prime time with sales role play. So using all of that context and intelligence that we've collected so far, sales role play can give them even more confidence. They can automatically input the actual conversation from the deal. They can give details on the persona, put in the scenario they'd like to practice, and any other areas they'd like to focus on. And by the way, managers and enablement leaders can prescribe these too. So they're targeting specific skills and key growth areas that are aligned to that broader company strategy. So the rep is prepared and ready for the pitch, and it's time for the meeting. The seller is feeling confident, the play is ready to run. And during the meeting, an objection comes up that they're not quite sure how to answer. But that's okay, because there's a real-time coach on the call with them. Let me show you Sales Assist, a live coaching assistant that's proactively surfacing insights and actions for the rep. A relevant response, battle card, or discovery prompt surfaces automatically inside Zoom right when it's needed. And it helps ensure that reps follow your chosen sales methodology too, prompting them to follow the playbook to collect any missed criteria or critical steps. So they handled the pricing objection and ace the rest of the conversation. Things move forward fast, and the deal is ultimately won. Eventually a win-loss report is generated and fired off to the team and leadership so that everyone's on the same page. Not only that, but the forecast was being updated in real time throughout so that the entire team from rep to CRO could stay in lockstep, dig into any portion of the deal at any stage, and understand how that influences their overall numbers. So now there's even more confidence that the CRO can go defend the projections with evidence, not just gut feel or outdated spreadsheets. And most importantly, the system learns with each step. With every sequence, coaching call, meeting recap, closed opportunity, and forecast update. Those answers don't just get reported, they're designed to inform the next accounts targeting, the next sequence, the next coaching recommendation, the next forecast. And that's the loop. That's what makes this a system, not just a scorecard. And it's not just one deal. It's a full system across all your deals. And guess what? Reps, managers, and leaders can continue to ask the big questions anytime with Ask ZRA, which lets you ask plain language questions across all your customer conversations, deals, and accounts. So leaders can just ask, where are we losing deals? Or managers can ask, what's working for my top reps? And sellers can ask, what are the top objections coming up across my conversations? And they all get answers instantly, straight from your actual customer conversations. Now I framed that walkthrough around pipeline generation, but the same architecture, the same context, the same orchestration, the same learning loop, powers deal execution, seller performance, forecasting, expansion, and renewal. One system reasoning over the full revenue motion from first signal to close deal to renewal. And because RevenueOS is composable, we're enabling an ecosystem where developers, ISVs, integrators, and RevOps practitioners can build customer-specific revenue systems on top of our platform. We're not just building an application. We're building a foundation for others to build on too.