Yext, Inc. (YEXT) Earnings Call Transcript & Summary

Hello, everyone. Has everybody got their seats? Good afternoon. My name is Nils Erdmann. I lead Investor Relations here at Yext, and welcome you all to Investor Day 2025. Before we get started, let me read off a couple of legal disclaimers, particularly for the benefit of those listening in via live webcast or for those who prefer a summary of the information contained on this slide. Our presentations today will contain forward-looking statements, including statements related to our future financial performance, expectations regarding the growth of our business, our outlook for future periods, our strategy and estimates of financial and operating metrics, capital expenditures and other indications of future opportunities. These forward-looking statements are subject to certain risks, uncertainties and assumptions, which are discussed in our reports filed with the SEC and that we encourage you to review. They reflect our views only as of today and are subject to a variety of risks that could cause actual results to differ materially from expectations. Yext is under no obligation to revise any of these statements to reflect changes that occur after this presentation. Throughout the day, we also refer to certain metrics, including non-GAAP financial measures. Definitions of these metrics and reconciliations of non-GAAP financial measures with the most comparable historical GAAP measures are available in the Appendix section of the Yext Investor Day 2025 slide presentation, which is available at investors.yext.com. For a discussion of the material risks to our business, financial condition and operating results, please refer to our Form 10-K for the year ended January 31, 2025, and other filings that we may make with the SEC. Our filings are also available on the Investor Relations section of our website, and we will make a replay of this presentation available after we conclude the event. Let me briefly run through an agenda for today. Our first session will cover our company strategy, market dynamics, platform overview, product innovation, data science. And you'll hear from our Chief Executive Officer and Chairman of the Board, Michael Walrath; our data alchemists and scientists, Christian Ward and Michael Misiewicz; our Chief Technical Officer, Jason LaFollette; and our Head of Product, Chris Brownlee. Following these presentations, we'll have a Q&A session and then take a short break. In the second session, we'll delve into our go-to-market, customer success and financial strategies with Chief Revenue Officer, Thomas Nielsen; Chief Operating Officer, Yvette Martinez-Rea; and our Chief Financial Officer, Darryl Bond. We'll conclude with another Q&A session with these presenters and Mike. At the conclusion of the presentation, we invite everyone to join us in the adjacent room for a cocktail hour and product demonstrations. And it is now my pleasure to introduce Chairman and CEO, Mike Walrath.

This is dangerous, but I'm going to do it. Thank you, Nils. Welcome, everyone. I'm thrilled to kick off our 2025 Investor Day and share how Yext is evolving to meet this moment and to lead in the next. We've come a long way in a short period of time. Today, we're going to show you how far we've come and where we're going and why we believe Yext is built to lead in this next chapter. You'll hear directly from the team about the steps we've taken to transform the company, the opportunities we see ahead and how we're executing with more clarity, more focus and momentum than ever before. So let's get started. Over the last few years, we've done a lot of hard work rebuilding Yext to strengthen the business and set a stronger foundation for what comes next. The transformation of Yext is focused on 3 critical areas. First, our task was establishing a more efficient cost structure. Over the past 12 quarters, we have rebuilt the operating foundation of the company. We have optimized our resource allocation. We've improved efficiency across all functions, and we've streamlined how we operate. We are leveraging automation wherever possible and making strategic decisions about where to invest for maximum impact. Step 2 was sharpening our focus on the core business and customers. We have refocused on our highest value products and the parts of our platform that drive the most impact for our customers. That meant reinforcing customer support, investing in R&D to meet evolving customer needs. And now with a stronger foundation in place, we're accelerating our pace of innovation. We focused our road map around what customers need, and we're building momentum for long-term growth. We are anticipating what's coming, aligning with our customers and leading through change. I'm proud to say that Yext is a much stronger company today than we were 3 years ago by every measure. So let's start with the numbers. Over the past 3 years, we have transformed the financial foundation of the company. We've demonstrated a remarkable improvement, moving EBITDA margins from negative 3% to a robust 22%. This journey has been about more than just financial improvement. Yext is leaner, much stronger, faster with reduced complexity and more focus. We have optimized cost while maintaining quality customer service through process improvements and technology. We've improved operational efficiency and focused execution to maximize value delivery, and we focused on our highest margin products and services. This improvement in EBITDA margin gives us greater financial flexibility. It allows us to reinvest in the business to pursue strategic opportunities and to deliver more value to all shareholders. It also signals our customers and partners that we're building a sustainable business that will be here to support them for years to come. Looking ahead, we are committed to maintaining and gradually improving this healthy EBITDA margin as we continue to grow. Another clear signal of our progress is our improving gross retention rate. As you can see, we've made a strong recovery in this metric in fiscal year '25. And as of the end of Q4, we are back into our historical range in the high 80s. This trend is particularly encouraging. It reflects the success of our efforts to enhance customer satisfaction and deliver ongoing value to our clients. It demonstrates the stickiness of our products and the integral role that they play in our customers' operations. And it provides a stable base of revenue that we can build upon with upsells and cross-sells as we introduce new products, some of which you'll see today. These improvements didn't happen by chance. They are the result of several targeted initiatives and trends. First, enhanced customer success programs have ensured that our clients are fully leveraging the capabilities of our platform. Second, we are driving continuous product improvements based on customer feedback and market trends. And third, digital presence fragmentation trends are underscoring how important our products are to our customers. We'll get into this more throughout the day. And while we're pleased with the progress, we see a clear opportunity to push this metric into the 90s. To understand how we are reigniting growth, we need to look at our product history. From 2009 to 2016, we built the foundation of the company, launching Knowledge Graph, listings, pages and reviews. These products were deeply connected to our customer needs, and they fueled a period of incredible growth for the company. From 2016 to 2023, we expanded our view. We shipped some smart, ambitious products, search, studio and chat. I'm proud of the work the team did with these products. They are ambitious, innovative, and we've seen some success, particularly in certain highly localized search use cases like find a doctor, find an adviser, store locators and similar solutions. In hindsight, the solutions we were trying to build were too far from our core ideal customer profile. These products didn't achieve broad product market fit, and they weren't fully aligned with the priorities of our ICP. In mid-2023, we hit reset. We got really clear on what we do best. We reconnected with our core mission and rebuilt our road map around a single powerful idea, digital presence. We trimmed complexity. We refocused our teams and accelerated our work to build the platform our customers need, a connected scalable platform to manage how they show up across an increasingly fragmented digital world. That clarity sparked a new wave of progress. In the past year alone, we've launched Yext Social. We launched new AI-powered features, including listings, recommendations and reviews response, automated review response. We've made 2 significant acquisitions with Hearsay Social and Places Scout, which expanded the capabilities of our platform and accelerated our road map. At the same time, we started building the foundation for our most disruptive innovation yet. This wasn't about shipping more features. It was about building for what comes next because as we retooled the platform, we saw what was coming next. AI is changing everything and the digital presence is going to look radically different in the future. So let's talk about why a refocused and customer-obsessed Yext is positioned to win big in the future. There are 2 powerful shifts underway that are driving demand for the exact capabilities Yext is built to deliver. The first is fragmentation of search, something we've been tracking and talking about closely for years. The second is the rise of AI agents, a shift that's only beginning to take shape, but one that we believe will fundamentally change how brands think about their digital presence. These trends are moving really fast. They're already creating new expectations for how businesses structure and distribute information online. What they have in common is this. They both highlight the growing importance of clean, authoritative and structured data and a consolidated set of tools to manage, optimize and distribute data in all forms. That's the foundation we spent more than a decade building, and that's why we're confident in where we're going next. So let's start with search fragmentation. Search continues to evolve. The current shift is the most disruptive yet. About 3 decades ago, many of us will remember this, we started with traditional index search. You typed a few keywords into Yahoo! or Alta Vista, and you got a long list of unfiltered and often irrelevant links. Then came the Google era with keyword search and link strength at its core, ranking became more intelligent, search became more useful, but users still had to click, scan, compare, search again, jumping between pages to find a clear answer. Now we've entered the AI phase. Users ask a question, they get a direct answer. No links, no browsing, just a synthesized response from a large language model. Ask what is a Roth IRA today, and you'll get an AI-generated summary or a generated answer. No clicks, no attribution and often no visibility for the brand behind the information. That shift has enormous implications. It changes who gets seen, what gets prioritized and how trust is established. These models are not ranking websites. They're interpreting data. They don't show you what your brand published. They synthesize what they can find about your brand, and this is exactly where Yext comes in. We help our customers deliver the kind of data that AI systems depend on, clean, consistent and reliable. Without it, results are flawed. With it, brands get discovered and win. At the same time, search fragmentation is revealing the risk of overreliance on any single platform, particularly Google. Competitors who built around that dependency are struggling to adapt. Yext with a diversified platform and deep investment in structured data is built for this moment. So now let's talk about what's coming next. A second wave of digital transformation based on the absolute requirement to make your brand, products and services visible to AI agents and experiences. For the last 20 years, brands have invested trillions of dollars building digital experiences for humans, websites, content, social media campaigns, landing pages, all of it is designed to attract and convert human beings. This is how humans consume data. AI agents do not and will not interact like humans. They don't browse or click. They don't read your content, they go straight for the data. They want structured, lightweight, machine-readable data. They want it to be comprehensive and relevant right now. That's what they use to generate answers, make decisions and shape what surfaces. This shift is just beginning to take hold, but it's going to be profound, and it requires a different approach. Structured data becomes the storefront. Data strategy becomes the marketing strategy. Yext is always focused on structured, authoritative distributed data. That foundation, what has always been a strength, now becomes essential. You'll hear this more than once today. Your AI strategy is your data strategy. And that belief is exactly what led us to build what you're about to see. Let me introduce you to Scout. [Presentation]

Scout is built for the new reality we just talked about. Throughout the day, you'll see more of it. Search is no longer centralized. Discovery is happening across dozens of fragmented surfaces. And more, it's being handled by AI agents instead of people. In this environment, brands need to understand how they show up across the entire digital ecosystem, not just in one place, but everywhere customers and increasingly AI agents are looking. That's what Scout does. It gives our customers a full picture of their digital presence at the location level. It benchmarks them against competitors. It highlights gaps, surfaces insights and offers clear data-driven recommendations. It is a direct response to the complexity that AI is creating and a foundation for how brands will manage visibility going forward. For our customers, it brings clarity, for Yext, it's a strategic foothold. It gives us a new entry point, a strong retention lever and a clear way to prove value in every conversation. This is what the future of digital presence looks like. This is what it means to be building and leading end-to-end digital presence platform. Every product, every signal, every insight is connected. Everything you're hearing about the rise of AI agents, the complexity of search fragmentation, the need for structured trustworthy data, it all leads here. This is what we've been building toward. Scout sits at the top, acting as the intelligent layer. It helps brand understand how they're showing up across traditional and AI search, experiences where they're strong, where they're falling short and what to do about it. Beneath that, we're building the next layer, automation, turning insight into action, connecting Scout to every product in the platform so that customers can close gaps and optimize performance in real time and at scale. And across the full customer journey from awareness to loyalty, we have the products that matter. Listings, pages, social, reviews, search, relate and action, all working together, all powered by the Knowledge Graph we've been building for over a decade. This isn't a collection of point solutions. It's a connected platform built to help brands show up everywhere, everywhere that matters with confidence, consistency and control. It's how we simplify digital presence in a world that's only getting more complex, and it's why we believe Yext is well positioned to lead in this next chapter. When they write the book on Yext, I want them to say 3 things. We operated better than others with discipline, efficiency and results. We innovated more by focusing on our customers, staying one step ahead of where the market was heading. And we allocated capital better, investing where it mattered with a long-term view. Our plan is working. And today, you're going to hear about how we're sticking to it. The team is going to take you deeper into our data strategy, how we're deploying R&D investments to drive future growth and how we continue to operate with a relentless focus on efficient growth. And we'll leave plenty of room for Q&A as well. Chris and Jason will take you through the product, how we're increasing adoption and building what customers want. Christian and Michael will take you deeper into the data driving our advantages. Tom and Yvette will show you how we're delivering real value, both strategically and operationally, and Darryl will drive much deeper into our financial performance and outlook. So let's get started. I'd like to invite Chris and Jason to the stage.

All right. You've heard a lot about the opportunity and our history behind us. But Jason and I are here to show you how we plan to seize this moment before us. Yext is the tool a multi-location brand uses to manage their online presence. We manage how they appear in Google, in the local search pack or on maps through our listings product, how a brand creates, manages and optimizes their websites and how they manage their online reviews anywhere a customer might leave a review about them and how they interact with their customers on social media. But at the heart of Yext is our Knowledge Graph. It gives brands a unified comprehensive format to communicate with search engines and AI empowers all of our products. Through it, we can centralize a brand's online strategy. Yext customers need to understand how they're performing before they can execute a strategy. We've always been best-in-class in the solutions to help you manage a brand's digital presence. We have a suite that helps you execute and manage how a brand and all of their locations appear online. But our customers have had to use other platforms to monitor the wider market and to try to determine where to focus. This has left a gap that our customers have demanded for us to address for them. And with the acquisition of Places Scout, we now have the data and capability to provide those market and ROI analytics and turn that into customer insights and recommendations and connect that with our solutions to manage your presence. And with this new capability, we're able to address the 3 most important questions that every marketer has ever wanted to have answered. How am I performing against myself, against the market, against my competition? Where can I improve? And most importantly, what can I do next? What are my best next actions? Where should I apply my time? These are perennial questions and the solutions to address them must always be evolving as the space is always evolving. Algorithms change, behaviors shift, tactics need to change with them. And sometimes you have groundswell changes that rewrite the game altogether. And we have one of those groundswell changes happening today, the type that rewrite everything. If we come back to Mike's slide here for a moment, for the past 20 years, Google has controlled what consumers see when they search for a product or service or offering. Within this world, marketers have had a lot of control over their information. They can measure how many people are seeing their brand, who click through and how this changed over time. But this is all changing. Let's double-click into that last box. So AI search, as a marketer, it's a black box. There's no dashboard to update your information. There are no metrics to measure your performance. So how does a marketer survive in this new world? AI search and their LLMs still need the web. The web and its data are the fuel they run on. All of the information the LLM is storing and sharing with your customers comes from the web from Google to Yelp to Apple to TripAdvisor. But what we're also seeing is that each LLM picks up on different data. We're seeing sources like YellowPages and MapQuest and Hours.com, things that are really deep and very niche sites are rising up and surfaced in this citation data. And each LLM favors different data sets. In this new world, Google is only one data point against the backdrop of the entire web that these LLMs are leveraging. And so how is a marketer going to control their presence in this new paradigm? As I said earlier, Yext is the most powerful tool for managing your digital presence. We're connected to more web publishers than any other solution in the market. We help brands manage their reviews and social presence across the web, and we help brands firmly establish their first-party websites as a source of truth. And so what we can see now is that your AI strategy is your digital presence strategy. And now we have Scout. Scout gives you insight into how you're performing, where you can improve and what you need to do next in traditional and AI search. So welcome to the next generation of search intelligence. Scout is your search and competitive intelligent built for this new era of search, and I'm going to hand it over to Jason LaFollette, our CTO, to walk you through Scout.

Thank you, Chris. I'm going to walk us through some of the user experience and key features of Scout. Thousands of hours have gone into the planning, design and engineering of this product, and we think we built something pretty compelling. Scout is already in early access preview with our development partners. But today, we're excited to launch a publicly available trial experience of Scout, enabling anyone to demo a subset of key features and generate a report for a single business location. We're going to hold that launch until about 1 minute after today's event, so no one gets tempted to generate a report and misses out on all these great slides. So let me show you how the trial experience works. All we need to run a Scout report is a business location. You can start by typing the name of the business and the city or street name where it's located. Scout will auto complete your search and can ultimately find any location with a Google business profile. In this example, we're going to report on a fictional brand, Oakmere Outfitters, located in North Bethesda, Maryland. Once Scout knows your business location, it can infer the correct business category, relevant search terms and the proper geolocation, everything necessary to conduct a comprehensive scan of AI and traditional search apps. In this case, Scout recognizes that Oakmere is an outdoor sports store. As soon as the user presses continue, Scout will begin scanning AI and traditional search platforms, assessing visibility for the brand at the chosen business location. This is where Scout immediately starts to differentiate itself from general SEO keyword tracking tools. Scout can track visibility down to the level of individual ZIP codes. That means visibility and competitor data is collected at the local level, enabling tailored insights and recommendations for each location. This is especially powerful for multi-location brands. In a few minutes, all the scans Scout has kicked off are finished, and we're ready to report on the business. First, Scout reveals the business' AI rank within search generative experiences. This metric is analogous to search engine result page or SERP ranking in traditional search. In this example, Oakmere is doing quite well in Google Gemini, but other local businesses in the same category are outranking it on Grok, OpenAI and Perplexity. Next, Scout analyzes brand sentiment from generative AI conversations about this business location. To power this feature, our data science team has helped us leverage well-tested sentiment analysis algorithms used in Yext's review product. Our outdoor store is receiving a mix of positive and negative sentiment, leading to an overall neutral rating. Brands can also see their standing in traditional Google search. Oakmere Outfitters is doing great here, ranking #2 in the local pack. We also gained visibility into which local competitors ranked near this Oakmere location. In this case, Bearhaven, Trailspire and Ironwood Supply are also showing up in search results. Scout goes well beyond purely reporting performance metrics like AI rank, sentiment and Google search rank. It performs deeper analysis by examining indirect nonperformance metrics for your business and for up to 40 local competitors. These nonperformance metrics are all the signals that traditional and AI search uses to rank your business and ultimately determine how it will perform. Here, you're seeing Google profile completeness, a nonperformance metric for Oakmere versus their competition. It looks like they've done a great job staying competitive in this area, ensuring their profile has a 100% completion score. Scout also collects information about how each location is managing its Google photos. Brands can see how many photos have been uploaded by their customers versus the brand itself, how recently new photos have been added and whether cover photos, profile photos and other specific phototypes have been uploaded for the account. We'll also show the same information for each of the brand's competitors. It looks like Oakmere is lagging the competition a bit when it comes to photo count. Next, we have competitive data about reviews. Scout tracks 26 different metrics related to review count, recency, frequency and sentiment. Here, we can see that Oakmere is doing a decent job with reviews, but really needs to work a bit harder. Bearhaven has over 4x as many reviews. Profile completion, photo count and review count are the 3 metrics we highlight in the trial experience, but Scout is capable of scanning and extracting over 150 nonperformance metrics about your locations and your local competitors. Finally, Scout combines these performance and nonperformance metrics to provide actionable insights and clear recommendations. These insights are crafted specifically to help brands surpass their competition and improve their visibility where it matters most. Our outdoor store is lagging behind its local competitor, Bearhaven Outdoors, in Google search ranking. Based on a predictive ranking machine learning model built by our data science team, we were able to advise Oakmere that focusing on Google reviews is their best opportunity to increase SERP ranking and overtake Bearhaven. Now let's move from the trial experience to the full Scout platform. This is Scout. You're viewing real data with business names and street addresses, again, anonymized as our fictional retailer, Oakmere Outfitters. Oakmere is an outdoor clothing and equipment store with over 1,000 locations across the continental United States. The colored hexagons on the map show how Oakmere is ranking in Google search when a user geolocated inside that hexagon searches for outdoor store near me or types in a similar search with local intent. The black circles with numbers inside them represent clusters of locations where Oakmere has a high density of stores. The smaller white circles represent individual locations. Let's drill into the local level. Just like any other map experience, you can zoom the view in or out to see a wider or more narrow set of locations and associated performance data. Now we've zoomed into an area showing a few Oakmere Outfitters locations in the Maryland suburbs just north of Washington, D.C. We can use this view to see aggregate performance metrics about the 4 store locations in the area. Now that we're zoomed down to a neighborhood level, the contiguous sets of hexagons approximate the outline of ZIP codes where Oakmere has a store location. Color coding shows at a glance which locations are performing and which are struggling with local visibility. Users can click on a location pin or a [ hexafied ] ZIP code to filter the performance details on the left-hand side bar. The drop-down in the top right corner of the screen allows users to switch between different performance metrics for AI and traditional search. Let's see how Oakmere is performing in AI search for brand sentiment. Looks like Oakmere is seeing more consistent performance in AI brand sentiment across these store locations. Unfortunately, all these locations seem to have mixed or neutral sentiment. There's no green on this map. So we definitely have some work to do. Once a user is ready to take action, they can click the insights and metrics view icon to see detailed insights, competitive analysis and recommendations. Let's see what that looks like. Here's the insights and metrics view for one specific Oakmere Outfitters location, one of the locations that we were just viewing on the map there. The insights and the metrics view mirrors the scope and selections made on the map view. If no individual locations are selected, users will see aggregate statistics and a priority ordered list of recommendations for all locations that were visible on the map. In this case, we've selected a single location on which to focus. The top part of the screen shows the same performance metrics visible on the map, but in a bit more detail. As we scroll down, we see a section with a light blue heading labeled, how can you improve visibility. Here, Scout is surfacing insights ordered by relative opportunity to increase SERP ranking. Each insight has a link at the bottom of its card to learn more about that insight. Let's drill into the first insight card about encouraging customers to leave reviews. Here, we can see more details about the insight, why it was triggered for this particular location, concrete recommended actions and information about how taking these actions will impact performance. Each piece of content on these insight detail screens is tailored to the circumstance of an individual business location and the unique competitive landscape around it. Scout is like having an analyst who constantly reevaluates how to best optimize and outperform the competition at each location a brand owns. Let's jump back to the insights and metrics view. The final section to point out on this screen is the table view at the bottom. In the first and second column, brands can see all of the metrics Scout is tracking for their business locations. Right next to that, you can see columns for competitors who are ranking above or below the brand location and precisely what each competitor scored for every metric. So looking at this chart, it becomes easy to zero in on the gray and red color-coded metrics in the second column. These are the areas where this brand's location is close to or already falling behind localized metric benchmarks. And if you want to do your own analysis, the export icon at the top right of the table view will export all the competitive analysis data in CSV format to pass on to your own business intelligence team. Now let's jump back to the map view to wrap up this walk through. We've seen how Scout provides deep location level intelligence. I also want to highlight how seamlessly the map view can handle Yext customers who manage hundreds or even thousands of locations. Scout's vector-based map and hierarchical spatial grid of hexagons supports nearly limitless levels of Zoom. It's the perfect way to view performance data for a brand, whether it operates within a single city, spans multiple states or extends across the country. Scout's map view provides a simple way for marketers to see patterns and digest a high density of performance data much more intuitively than trying to make sense of a giant data table, spreadsheets or reports. At a glance, you can zoom out to identify broad performance trends, pinpoint areas requiring immediate attention or drill down to focus precisely on a single location. Scout transforms complexity into clarity, empowering your brand at every level. That's it for the walk-through. I'll hand it back to Chris.

Okay. Now we get into the growth flywheel. As we've seen, everything a brand needs to manage their online presence is already in Yext. And now we have the tools to answer those critical questions, how am I performing? Where can I improve and what do I need to do next? And we will connect the dots for our customers to show how interconnected their entire digital presence is from their listings, pages, websites, reviews and social. We've always known and now we can demonstrate to our customers that their digital strategy is not made up of independent components. The more fragmented your tool stack, the more fragmented your strategy. There's a symbiosis across a brand's web presence. Each piece of your digital strategy impacts the other. Now let me walk you through a fictional example with Oakmere Outfitters again. So I asked ChatGPT, what are the latest trends in outfitting shops and it said avalanche equipment. So I'll use that for my demonstration here. So first, what I want to do as Oakmere Outfitters is add this to my listings. I might update my description or add new keywords or categories. But that's not enough to actually perform. I have to have my offering be discoverable by customers as well. I need to manage this across the entire web. And we, as Yext can help automate this process across a band thousands of locations. So next, Yext will help make this update to every one of my locations that has this new product line to amplify this change. Yext will create well-crafted pages that are optimized for the consumer and even more importantly, are optimized to be found by web crawlers and other AI agents. Each of those locations needs to be posting social content about avalanche equipment now tailored for their local region to give it impact in order to drive further discoverability. Social is also a great place for creating ephemeral content about new sales, offers, other promotions that can also be picked up by AI. And as you've seen in our data by using the same keywords in your review responses, we see a further impact to drive discovery, further boosting your rankings and listings. Through all of our interconnected products, we can maintain and manage these strategies for you across your brand, regions and down to your individual locations, something that's nearly impossible to do with people today at that level of scale. And for customers that use Yext across their strategy, it creates a growth flywheel for your brand to drive up your visibility and conversions and help you outperform your competitors. Through Scout, customers will come to understand that they need to be active, present and engaged across all touch points and across all Yext solutions. And we can bring it all full circle today and tomorrow, all thanks to Scout. So with that, I'll hand this off to our Chief Data Officer, Christian Ward; and our Director of Data Science, Michael Misiewicz, to walk you through a little bit more of the science of these things.

Thank you. Hello, everyone. My name is Christian Ward, I'm Chief Data Officer here at Yext. And I'm joined today by Michael Misiewicz, our Data Science Director. Thank you for all being here. Today, we're going to walk through 3 key examples showing how data and insights come together to really enhance our customers' ability to rank well, as you've seen both in classic search and in AI. Now before we jump into those examples, it's important to set the stage. As discussed earlier, we are seeing significant fragmentation in the AI and search landscape. And we believe this trend is only going to accelerate in the coming months. Think about it. In just the last few weeks or days, we've seen a ton of new updates, a new Gemini model, a new image model from OpenAI, as well as a web version of Claude. These advancements are happening incredibly quickly. Now for the last decade or so, we've really been in more of the low agency, low intelligence area, sort of the annoying chat bots. And we've moved into easily sort of the low agency, high intelligence area where these models are very strong, but the trajectory is clear. We're headed into this high agency, high intelligence area. AI agents won't just respond, they're going to act. And these agents will become far more impactful than today's conversational interfaces. So what does that mean for businesses? As we often say at Yext and you've heard already today, your AI strategy is fundamentally your data strategy. What this means is AI technology is going to continue to evolve at a dizzying pace. But for most businesses, the most critical strategy is getting your foundational data right. We're talking about the core information about your brands, your products, your services, your locations. Getting all of that information into a structured format where AI can understand and use it to optimize the customer journey is the critical next step. So we can see a future where classic search and AI search are increasingly going to merge, adapting based on the type of question that's being asked of the platform. This isn't -- there isn't some separate secret data store for AI systems that isn't available to classic search. In fact, all of the effort businesses have put in over the years into search engine optimization has perfectly prepared us for this new AI-based search experience optimization. There are 4 major channels of that content and data. The first, obviously, your listings, which is your data across the whole network; the second, your website content and information; the third, your reviews and reputation; and lastly, your social media content. And with tools like Scout, our customers can see exactly how those data elements impact their performance and they can see it of their competition. So building on that foundation of data strategy and key signals, let's look at 3 concrete examples about data science insights often surface through Scout are creating real market opportunity for our customers. Michael, why don't you kick us off the first one?

Thanks, Christian. So our first stop is going to be the classic Google search. As you know, this has been around for a long time. And consumers do spend a lot of time still on classic Google, even though AI search is growing very quickly. And thanks to Scout, we're able to ingest these search engine result pages or SERPs at a large scale. And the first thing a data scientist is going to do upon receiving this wonderful new data set is to fit a model to it to see what are the factors that are affecting businesses rank in Google. And we were able to get this working. And our result was that 80% of the difference in ranking was determined by the distance between the user and where the business is. So that's a great result. However, not necessarily super helpful for a marketer because you can only move your business maybe once every 10 years once your lease is up or something. So we need to understand what are the other features in addition to location that are going to be important for Google in your ranking. We have known for a long time that Google values relevancy over anything else, and this is exactly confirming that result. So we know we're off to a good start. So let's take a look at some of these model outputs. All right. So right here, this is a feature analysis of the first model we fit. before we applied the distance calculation. And if you look at these features here -- distance correction, excuse me, if you look at these features here, you can see that the most important one by a wide margin is the distance between -- from where the user is located and where the business is in meters, by the way. And we also find that reviews are pretty important. So the difference in the number of reviews will determine whether someone's ranked higher or lower and as well as the rating photos. And finally, at the very bottom, we have whether or not the user search query happens to match the category the business is in. But we wanted to apply this distance correction mechanism. And so after applying a clever modeling trick, we reorganized our data so that we could train a model that would be very resilient to the difference in distance. And after applying that trick, we find the following. So one of the things I want to call your attention to here is how these have been reordered and also the order of magnitude of differences between them is quite a bit larger. So we find after applying this that review count is the most important thing and followed by rating. So reviews, huge deal. After that, it's photos. And even still, we still find that distance has an important impact. Even a distance as small as 5, 10, 15 or 20 meters will cause a difference in Google's propensity to rank. So that's a really cool result. And we see that the category mapping still kind of remains at the bottom. So seeing this result, we're extremely happy because it means we have the building block that we need to build recommendations for scale. If we can get this working, we can tell you what you need to do to make things better.

Thanks, Michael. As Michael demonstrated, gathering data across massive numbers of locations, categories, geographies allows us to build systems that can accurately account for and debias in this case, the distance factor. But it's also important to keep in mind that, that same wealth of data helps us uncover other shifts in ranking factors as the market evolves and algorithms change. One particularly interesting change we're observing is how AI search seems less bound to a simple major point in algorithm like location. Location has always been absolutely critical in terms of distance, but AI is more open to using other tools. And you can see as it uses more information like memory or context, it changes the way these businesses will show up in search. AI average also leverages additional context. And what we're seeing is the more data we can feed to the AI, the more likely that, that context will help a business be discovered. So we're going to continue to track the performance in both classic search and AI search for both all of our customers and their competition, and that will give us the data necessary to find more of these insights. Back over to you, Michael, for the second one.

Thanks, Christian. So we've got another really interesting one here. The first question that everyone asked about as soon as we got all the Scout data online is how are we comparing to the other digital presence management platforms out there. And so one of the first things we did was we ran that analysis, and I'll show you in this table what we found. So reading this figure column by column or row by row, if you wish, you're looking at the percentage likelihood of appearing in the Google local pack as a function of your -- the tool you're using to manage your local -- your digital presence. What's pretty interesting here, we see Yext versus Yext, no change in probability, that makes sense. Next one down, we see that if you are not using an identified digital presence management tool or doing it yourself, then you are 6.7% less likely to appear in the local pack than those who use Yext. And lastly, if you're using one of our competitors' products, you're 13.7% less likely to appear in the local pack, which I can see from the reactions that there's obviously a lot of interest in this result. We thought the same thing. This is based on an analysis of over 12 million businesses over a 30-day period. So the first question we asked about is we wanted to know is like why is this happening? This is a very surprising result. And we have a couple of hypotheses here. So one hypothesis is that maybe the businesses that are not using any tooling at all are perhaps single location businesses or maybe mom-and-pop businesses. Maybe they don't rely very much on digital presence to drive their revenue. It's a possibility. Maybe it's the case that Google gives mom-and-pop businesses a boost. Certainly could be what it is. Another one might be that maybe they are using -- they are putting effort into managing their digital presence, but it's not using an identified tool. Maybe they're using an agency or they have a team that works on it in-house, and it's just -- it doesn't show up as a competitor to us because it's just totally bespoke. That's a possibility and maybe what it is, but there is maybe another possibility as well.

So our primary hypothesis is one that supports something that we have contended for years. Many of you know that over the last several years, our competitors have positioned their products as like Yext, but not as good. They've made claims that getting listings right at scale just wasn't as important. They use inferior approaches to data management, and they charge a fraction of the cost to win the business. Typically, this is done using data aggregator solutions, which we actually know tend to cause inconsistency in the data that platforms like Google and others have access to, but they also cause data frequency problems of updates because they do not update in real time. They take an enormous amount of time. It's hard to fight the good enough pitch in any market when you don't have the data. With Scout, we now have the data. Our hypothesis, the size of the Yext network, our real-time APIs, the update frequency that we can provide, the depth of data that we can provide and our platform consistency across that entire data ecosystem delivers the strongest signals that algorithms recognize, trust and value. Our competition, on the other hand, sends mixed signals on a delayed basis, ultimately causing performance well below actually just the don't do anything bucket. This is an exciting data set to explore, and we'll continue analyzing what works, what doesn't and what advantage does our platform complete with Scout data, what does it advantage our customers over our competition. So let's move on to our last example, starting with some background on just how important source data is to large language models, namely citation data. Now to understand brand presence and the impact of source data in AI, we need to track different types of questions. Think about questions along 3 axes. You have sort of this branded versus unbranded question, which is pretty well understood. We have objective questions versus subjective questions. And lastly, we have simple versus complex questions. And each one is a different flavor of a query by a human to a particularly type of large language model. Now most real queries aren't just one type. They're actually a combination of these different dimensions. So for example, if I say what time does the Apple store open in Chelsea Market, that's clearly branded to Apple. It's objective. I'm just asking what time they open. It's a factual element. And then it's relatively simple. Now if I were to flip that to something a little more difficult is catch stake a good restaurant near Chelsea Market. What has happened is I've gone from an objective question to a subjective question. When you do that and you ask good restaurant or good anything, you're getting a little more complex, but you're also looking for more nuanced information and different opinions. So the source data will change. And one more, what's a good restaurant for a business dinner near Chelsea Market. And this time, the query is unbranded. So it's going to look at all the competition. It's still subjective because I'm looking for a good recommendation. And it's also complex. So when you ask something that has the context of something like a business dinner, it has to think and analyze yet another suite of sources of information or citations. In each case, both classic search and AI search are leveraging this different source material, and they share those content citations in their platforms. You can actually click through and see where they're getting the data based on the question types. So those citations are absolutely critical to finding answers from brands, but for also understanding what sources of information should you be focusing on updating more or engaging with, listings, pages, reviews or social. So as we've seen, understanding these query types is crucial because it connects directly to where AI systems will pull the information. Ultimately, trust is the currency of AI and the citations of the receipts. They show the work and they build credibility. And now I'm going to hand it back to Michael where he can discuss how Scout enables us to do more of this.

So we know how important these citations are. And one of the things that we've been doing with them has been analyzing the citations at scale and also figuring out how -- what's in those citations has an impact on what the models know about different brands. And I'm going to take you to 2 examples of some financial services companies that show very differently as a result of these different citations. So -- the first one here, these are the words produced by an AI search system when you ask about a financial services company. This particular brand is focused very much on physical locations. So they emphasize in their marketing materials, they emphasize hours and convenience and where they're located and being open on Sundays and things of that nature. And when you look at the words that the LLM has learned to associate with this particular brand, you see some pretty interesting results. We see locations. We see branches. We see hours. We see today, street access, stores. It's all about where can you get access to a physical location. So these AI search systems have learned from the citations that this is what this brand is all about. Very interesting result. But let's flip to a different brand. This one, different company. They have a very different strategy. So they're much more focused on personalized service on nice, friendly agents that are knowledgeable, that have really good -- that people have really good satisfaction with. They're positive. It's a very different sort of fingerprint of this brand compared to the first one. The fact that we can pick up these signals in the output of AI search systems is a phenomenally exciting result for the team. We are able to apply this right now, this is nationally. We could expand it regionally. We can slice it in many different ways. There's basically an unlimited opportunity here to start to understand at scale how this is all working. It's all powered by what's in these citations.

So let's bring this all together. The data from Scout can help Yext customers optimize their approach. But as we started with fragmentation, it's also important to recognize that AI isn't just carving up an existing search market. It's significantly expanding the entire pie. AI search moves beyond this classic search box that we've all known to love over 20 years into entirely new context. Like think, for example, of your commute in your car every morning, all that time or in your home with smart home connections to conversational interfaces. All of these open up a much larger opportunity. The Yext platform with the addition of Scout, helps our customers monitor these changes to search and AI, not only for themselves, but across all of their competition at the local level. This helps them understand how they can best excel in their market. With that, I'm going to hand it back to Nils, and we'll continue the discussion.

Thanks, Christian. At this time, I'd like to invite Mike W, Christian, don't go anywhere. Mike M, Chris, Jason, back to the stage to conduct our first Q&A session. For members of the audience, please raise your hand and wait for me to bring you a microphone or for Holly to bring you a microphone if she's -- you're on that side of the room and wait to ask your question into the microphone for the benefit of those who are watching this via the live webcast. We will also be taking questions from the live webcast. So Holly will be monitoring that, and we'll call on her if we get questions virtually.

Naved Khan, B. Riley Securities. So Scout looks pretty impressive. And maybe just maybe talk a little bit about the foundational elements of that. How much was the acquisition of Places Scout kind of central to building this? And what are the things kind of unnecessary? What I'm trying to get to is from a competitive standpoint, how easy or difficult it might be for somebody to build this kind of a tool?

Yes. I'm happy to start, but you've got the actual experts here, so I'll be quick. The best way to think about this is Places Scout was, in our estimation, the best tool in the market for gathering the intelligence around the search engine results page and the review information. We had our own initiative running inside the company around all of the AI visibility and ranking metrics that you saw today. It was a perfect combination where we could take an existing tool with existing capabilities around the search engine, the traditional search, if you will, and combine it with a significant R&D effort that we had been running for quite some time internally around AI visibility and that sort of tracking. And this group is much better suited to explain the nuances of those things.

So I would also say -- so Places Scout was well known in the industry of the local level of understanding performance metrics. And that's one of the ways that it really immediately made sense. One of the things that's really special about it is, generally speaking, most of these performance metrics are at a very high level. They're almost like brand level. By getting it all the way down at the location level, it's a completely different way, and we haven't seen anyone in market doing anything similar to what they were doing. And the reason why we say that is if you're a doughnut shop or a chain of doughnut shops in a town with only 10 doughnut shops, you're going to rank on the first page of Google. There's -- like you're going to be somewhere in there. There's things you can do to do better. But if you're one doughnut shop in a town of 500 doughnut shops, it's a completely different approach that you have to be taking in order to rank better in those systems. So that level of granularity is what's particularly interesting because we can now see it as demonstrated at that much higher level, but zoom in and out across classic search and the AI models to understand what can this business be doing better. And that's a huge advantage that up until this point, really the market didn't have.

I think another thing that's really important to point out here is while we've been developing all these models and algorithms, we've been combining features from different sources in our business. So the Places Scout gives us an enormous new set of data to work with, but we're also able to join it in with all the data we've had historically for everyone in listings. And given the size and complexity and depth of our network, I don't think that would be easy to replicate.

Yes. Totally agree. When we did the technical evaluation of Places Scout, we saw kind of to Christian's point, we saw the marriage of 2 feature sets. We have the SEO feature sets, which go a lot deeper. They hit a lot more performance and nonperformance metrics. But then they also just have the general scanning capability. I think the general scanning capability is something you can find out in the market. In fact, Yext already has partners that we use for general scanning that power our prior competitive intelligence platform. We just couldn't get nearly the depth of information that we needed, and we didn't see that anywhere else in the market.

Tom White, D.A. Davidson. Just sort of a follow-up to that last question. The competitor product slide was interesting. And maybe you could just explain a little bit more simplistically for me. I guess, why you think maybe that delta in the performance was there, whether it's sustainable? And I don't know, is that sort of a sustainable competitive advantage for your offering? And then just kind of more broadly on Scout, it seems like you guys are kind of redoubling back to the core, which is kind of listings visibility and I guess you're calling it digital presence management. What does that mean for some of the other kind of ancillary products like chat and pages? Where do they fit in?

I'll start with the first piece. How this works on a technical level. When we get a SERP back from Google, we're able to look at each of the links in there, and then we can go crawl those and find out who's hosting that page. So we'll know all the named competitors based on some characteristic fingerprints. What you're looking at in this presentation was a snapshot. So we're going to be able to monitor this over time and make sure we're staying on top of everything. I can't wait. It's going to be so exciting.

It's also very likely that by region or by potentially industry type, we're going to see a lot of nuance in why we're performing better than the competition. This was a study on roughly 12.6 million businesses. And probably the most exciting thing about this is we've always been able to compare people that use Yext against other people in the same industries that use Yext. We had the data for both. And with the size of our client base, that yielded really great data science insights into how we were performing and how to best use the platform and best practices. Now we have the data on everybody that's not using Yext. So we can actually see all the way from the start to the very worst ranking all the way up to the top by industry, region, market cap, any of those factors. And so it really gives us that opportunity to your question of, yes, I think it's certainly -- I think that performance was there. We're just now able to see it more obviously. But the real fun part is every time we run one of these analyses, let's say, on a monthly basis, we can see who's moving up, who's moving down, why? What did they do? What did they do different? It gives us an enormous way to go back and analyze the time series of these changes. So that gives us an edge on improving any of the products, all the other products to help basically drive that higher ranking.

Yes. And I'm just going to be a little more direct about that even. Scout is an extraordinary product. Kudos to this team and their teams for not just developing it, but the pace at which it has been developed is extraordinary, and we're just getting started. So there will be companies trying to aim for where we are today. We'll be long gone by the time they get there if they get there at all. What it does to be really direct, it provides value to our customers so that they can understand the value of the different products that they use. And the recommendations that it provides virtually all of them will be supported by the products that we sell. So one of the things that we've seen anecdotally looking at customer data, Christian and I were on a call with a major health care system yesterday, is the website pages information, the structured data of the website is extraordinarily important when it comes to for -- certainly in certain categories, how they rank. And so if your pages aren't right, you're going to struggle to rank no matter how good your listings information and your reviews and ratings are. And that's going to go across those -- that entire set of products. So the way we talk about this internally is Scout is of tremendous value to our customers in and of itself. One of the things that it does is it also shows you the value of our other products, and it frankly will sell our products to our customers who aren't using those core products. And we're going to talk a lot about sort of multiproduct customers later today. But that's one of the reasons why you hear so much bullishness from us is unpacking these value insights has been one of the -- you talk to our customers, you guys -- you do market checks. You hear all the time, hey, we all believe Yext is sort of a better platform, but it's hard to demonstrate it. We're now able to demonstrate it.

Mike, maybe in the KPIs, you chose EBITDA margin and gross retention rate. And in there, I think you mentioned that you think you can get gross retention rate into 90s. Maybe unpack that a little bit. What are the drivers behind that? What you can control and what externalities are there?

Yes. So I think there are externalities. I think, obviously, to the extent that businesses are shrinking, not growing, that's going to be a headwind. I think the flip side of that is that the more value you perceive in the platform, the less likely you will be to leave. And I think one of the things that we're beginning to be able to demonstrate much more effectively is when you leave and go to another platform for 20% or 30% off or I'm not even sure sometimes the spreads are that big, you're not -- you might be saving a little bit of money, but you are hurting yourself from a visibility standpoint. That will only get worse as the fragmentation that we're seeing continues. And so we believe that one of the earliest things that we'll see from the robustness and the capability of Scout is that it will improve our gross retention rate because you're just -- once you see it, it's very difficult to justify going somewhere else. And it's -- I'd like to say sometimes we spend more in R&D annually than most of our smaller competitors have in revenue. And so our pace will continue to accelerate, and that's something that I think also drives those. So we're obviously being cautious about how we're forecasting the business and projecting the business, but we're seeing a lot of green shoots around that metric in particular. The second part of that, when we talk about accelerating growth is obviously attaching more products. So the other message you should take away from this is gross retention creates the base. Net retention clearly comes from being able to attach more products to that customer set. And with now 7 or 8 products that we can distribute across the unified platform, we're feeling really excited about the future there.

And about the trial, the Copilot trial that you guys talked about AI search, CoPilot, that sounds exciting. What are your expectations from having a waitlist and maybe talk through the commercialization and the monetization plan of the new product?

They're not going to touch that one. But I will. Yes, we're really excited with -- we're not talking publicly about pricing and things like that. I think we're in a really great place with our development partners today and moving into a beta phase here. You'll get to see, I think Jason said it 501 today. You'll be able to see the public demonstration. And it's great to see sort of a wait list for access. We -- I don't know that we've had a waitlist for access for a product in quite some time. So -- and that's really a testament to the quality of the work that the team has done. So we're not going to make predictions about the revenue or ARR momentum at this point, but we'll be happy to show it to you over the next couple of quarters. I know you [indiscernible] I wouldn't respect you if you didn't.

Ryan MacDonald with Needham. I wanted to maybe ask a little bit about how you envision productization of Scout. It seemed like in some of the initial sort of examples and use cases, it kind of felt like a very sort of in the hands of the customer, self-service using the platform, gathering insights location by location, doing that analytical work. But in the data section, it felt very consultative that it's something that Yext can do to then go into whatever QBR to talk to a client about and sort of find better ways to monetize. How do you think about productizing Scout given sort of the vast amount of data and the variability you have there with the flexibility of the product?

I'll take this one. It is definitely meant to be a much more self-serve model. Coming back to those 3 questions I was talking about, those are the things that you as a digital marketer need to be able to go to your boss and prove what's happening. How are we performing? How are we comparing? What do we need to do next to get more ROI. And so we're making it so that, that's available not just when you have your QBR, but you can go and self-serve. And then you can very clearly say, what are the things you're doing and then coming back as we can mark this over time, we can help show that as they took action on these recommendations, obviously, hopefully, they get up into the right kind of trend happening as they start to take those actions, which should just build more trust into the system and again, hopefully help to show the importance of needing to use all of the solutions together to really get a cumulative strategy out of it. But yes, we're really excited to make it much, much more accessible to hopefully a wider market by making it so self-serve as well.

We've also seen in some early demonstrations of the data with clients. The clients are very quickly telling us how they could action on the data. And so the feedback loop has been phenomenal. One of the ones that Mike and I were on early on was looking at a large financial adviser company, and we could actually see very big differences between people that took care of their digital presence, even things like head shots. And that made a real big difference in Florida, but did not make a difference in New York. I don't know why. But it's one of those things that we're just starting, and they had already identified they wanted to show internally not just them against their competitors, but all of their people against each other, which is a completely different data view, but is really insightful if you want to compare that with, let's say, growth in assets under management or something for an adviser. So there's so many ways to look at this, but I expect that the clients will be one of the best helps in actually productizing and giving us some priority.

Yes. And I'll give you 3 points on this. So Christian and I were on a call yesterday with a customer looking at urgent cares. They have -- we looked at 2 different urgent cares, a number of them, lots of them. We looked at 2 that were probably 10 or 15 miles apart. And the prescription for improvement for those 2 businesses run by the same marketing team, same tactics were completely different, right? For one, it is we need more reviews and better reviews. For the other one is we have plenty of reviews and the reviews are great. We need photos. We need better website data. It's shocking, right? Because you wonder how does it -- now imagine the challenge for a marketing team who's managing 5,000 or 10,000 or more global locations trying to figure out my one size fits all, hey, I need to manage -- do a better job with reputation management. That's only true across a subset of their locations. This is the first time that they've ever seen something that visualizes that and then allows them to drill in and actually do something about it and say, okay, stop focusing on more and better reviews for this location. They don't need them, right? Focus instead on a better web presence. Over here, we definitely need more and better reviews, right? And those things -- I mean, 2 locations, 15 miles apart. It's extraordinary. The last thing I'll say about this is I've been here for everyone knows, I'm old and I've been here for a long time. I have never seen a product at Yext before that we can walk into the C-suite with and show them the product and have them immediately go, oh, yes, that's the product. right? Because this visual interface, this ability to see your entire digital presence across different vectors, color coded by performance is what they're desperate for. And so I think that's actually a really profound and underappreciated element of this product. We've built the best-in-class products for -- since the beginning -- since we invented this category. Those products are sold to and used by highly technical users within the system. This allows us to come in and have a much higher level conversation in the C-suite. And as I mentioned before, the product, the Scout product sells the rest of the products. And that's the flywheel we're really excited about.

How much data is there to validate the recommendations that Scout provides? How long does it take the customers to see the results of those recommendations? And then lastly, is there a tool today that automates the execution of those recommendations?

I'll start by talking about the size of the data set, very large. I don't know if I can give you the exact number, but it's huge. In terms of what it takes to train a model or any of the models, we can usually get through them pretty quickly, but that's like on the development side. It's a huge data set, way bigger than we could possibly imagine. And we couldn't be happier as a data science team with it.

Yes. And I'd say, number one, his team is very excited about it. Number two, I'd say, because it's retaking a snapshot and looking at all these across all of the clients and their competition on an ongoing basis, what you're also getting is you're getting the movements in between of both rank and what people are doing. So it helps us decode some of those changes. And so that obviously gets much bigger very quickly. And so the data set will continue to compound as we run Scout analysis for each of the clients given their category, their ZIP codes, all that kind of thing. So we'll just keep getting bigger, which will give us more confidence to go back and then align what the recommendations are. So recommendations will not only come out from the cross-section, but they also will come out from the temporal view of the data over time of what's actually changing.

Which enables back testing, randomized control testing, AB testing, like all of that is a couple of key strokes away now.

Recommendations don't result in [indiscernible]

So it's too early to say what percent of the recommendations because obviously, we're sort of launching today. But as you go through over time, we'll be able to see that because we can see did rank change, did rank not. But I do want to point out one interesting thing, which is we expect we'll be able to find those, but the algorithms change, too. So for the first time, now we can also say that was working. Why isn't that working anymore? And so it's a way for us to also help our clients react as I'm sure everyone has seen, search fragmentation, not just in Google, it's also causing big algorithmic changes in Google. They are, let's say, for example, whenever they added Reddit and suddenly Reddit was the first result on every nonbranded question I had. That's the type of thing that you're going to see where we can see those changes happening. So it's sort of -- I can't tell you which one worked the best, but I can tell you over time, which ones have a high propensity or directional accuracy, and then we can see when that changes.

And who's coming up on your tail fast and why? That's a really important piece, right? If you're holding that #1 spot, you're great. But if somebody is zooming up from 15 to 12 to 10 to 8, you want to know what they're doing because eventually, they're going to eat your lunch. Your automation question, I think, is an important one. So we have already launched numerous -- several things within the platform, listings recommendations, which will become part of the suite, obviously, AI review response, and there's plenty more in the pipeline there. I think that's an interesting question because I think it has to do with business behavior more than it has to do with technical capability. So human in the loop, human supervised or kind of machine recommended and human implemented very likely will go on -- will exist longer than -- let me say this differently. The behavior will change slower than the technical capability to automate much of this. In the end, our vision is that everything that you do inside the product over time or very much of it will be automated, and you will eventually trust the automation enough that it will save tremendous amounts of time and energy.

I'll add just one data point. We launched a listings recommendation tool late last year, and we've been able to see in the data that customers who actually use it, act on these recommendations, they're getting an 11% bump in just overall impressions and an 8% increase in people actually converting. And so those are some of our most basic first out of the gate recommendations that we've been able to do. So we've already got a lot of compelling data to know that we can effectively do this for our customers.

I have to say a detail on that. It's so interesting. That's within Yext customers. So the signal we're resolving is within people who are already the best at managing their listings. Now we can run these recommendations on everyone who's not a Yext customer too. It's going to give us so much more power.

Right. Maybe a piece of context too on the data size. So the reason why Scout is so different from all the SEO tools out there is instead of going out and monitoring a few keywords and running a few searches, every single location that we're monitoring for a customer, we're also monitoring 40 or potentially more nearby competitors. So if I'm monitoring 1,000 locations, I'm going out and executing 40,000 scans to collect that data. It's a massive amount of data. It takes roughly an hour to go out and collect 1,000 locations by 40 competitors worth of data, scan their website, scan deeply into everything Google knows about them, scan all of those AI search providers about them. It's pretty incredible...

And hard to do.

A quick follow-up. All that was already done in Scout? Or is this something that you're launching as part of the new product? Just a quick clarification.

A lot of it was already part of Places Scout, where Places Scout provided that deep scan ability. I think we have worked a lot of workflow around the Scout platform to be able to take that and spider out and understand how we want to direct those scans.

The best way to think about what Places Scout had, and it's an excellent platform, it was really for the professional. And so you would occasionally run a scan on a major client. What we are doing is now running it on everything. And so it opens up a much larger data set with that time series analysis. So it really gives us a much different view than people that had used Places Scout before because very rarely, they might run 1 or 2 scans, 3 scans a year, but it was much more of a point of service use model. This, it's baked into the platform.

And the scans overlap.

Yes.

So the data just gets incredibly rich, right? So every time you run a scan for anybody in a category, you're going to capture a lot of information about everyone in that category. This is another underappreciated. We've been giving our customers insight into how their -- how they perform against industrial benchmarks of other customers who use Yext for years, right? It's kind of like selling someone a Ferrari and then having them go out on the track and race it against another Ferrari. It's not as impressive, right? What we have -- what we're now able to do is we're able to show them how that Ferrari performs against a 1986 Ford Escort, which happens to be a great car in 1986 if you're on a budget, but it's not going to solve your digital presence problems today.

We have time for 1 or 2 more questions for the first half session. I see one here.

Just given the massive amount of data you are collecting, how does that affect the cost you have to incur to kind of get that, process that and all of -- I don't know if you're going to -- if you have plans to pass it on to the end user or end customer? Or how should we think about that?

I mean these aren't going to be -- I'm going to -- this is probably -- I mean, there's probably a [indiscernible] question in here around COGS and gross margins, which I'll let him answer. But I think the shortest version is we don't expect an impact to those. These are not free products, and they are high-value products. And so we're -- there is real cost. We think that's a great moat. We're going to do things that others won't be able to do. But we're not concerned about margin compression or COGS at this point. I mean if that PLG demonstration plug goes absolutely bananas, maybe we'll have a little bit of a quiver, but I think we would accept that at this point.

I'd also point out from a technical perspective, we're in a good sweet spot here with the evolution of a lot of data warehousing platforms where collecting this amount of data can be done very cost effectively. And then the data that we're processing, pre-aggregating and pushing back into the operational systems, that's going to be a fraction of the size. So we're definitely feeling good about the economics there. And yes, not worried about that.

One more upfront here.

For the present. So you mentioned there is a huge data set here, right? So how do you like verify the information? [indiscernible] more like [ fick ] data? How do you combat this?

So in terms of the scan data, we actually can take a snapshot of where the data is coming from. So we can go back in time and look to verify the data. But it's also that every time you run a scan, as Mike just pointed out, so if I run a scan on insurance agents in an area, I'm getting all of their data. The next day I might run a scan for insurance agents that they compete with that is also a customer, and I'm going to see the data again. So there is an enormous amount of overlap that allows us to analyze if we see any sort of anomalies in what the data is. So the way the system is designed, almost think of it as an overlapping fabric where we can see every single day additional adds to the overall data set. So that helps us. But really, we have the auditing all the way back to when was it run, what did we grab, where did we see it, all those tools. So that gives us that audit feature, which helps a ton.

Great. At this point in time, we're going to take a short intermission, and we'll be back in about 10 minutes.

Yes. And if you have -- just a commercial, if you have more data product questions, I think these guys are all going to be hanging around for the cocktails afterwards. So you can really get into it then. [Break]

Okay. Hi, everybody. So my name is Tom Nielsen, and I lead sales here at Yext. Thanks for being here today. I'm excited to take you through what we're seeing in the market, how we're executing in the field and where we see the next wave of growth coming from. So let's start by picking up on the story that Mike shared earlier because the opportunity in front of us couldn't be larger. So earlier today, we shared how Yext has evolved into an end-to-end digital presence platform. That story is anchored in listings, reviews, pages and social, and it mirrors the shift that we're seeing in the market. Search is fragmenting. Listings are no longer a nice-to-have. They are a must-have. AI is changing discovery, and marketing teams are under pressure to deliver more with fewer resources. That's exactly where Yext fits in. Over the past year, we moved from a multiproduct company to a unified platform strategy. We launched Social. We acquired Hearsay. We partnered with and then acquired Places Scout. These weren't isolated activities. They reflect a clear go-to-market approach, listening to our customers and delivering on a platform that scales. Today, I'll walk you through how our strategy, based on search fragmenting and our digital presence platform, will deliver results this year. Let's start by digging into Scout, Yext Social and Hearsay as the first set of growth drivers. So as you learned earlier, Scout is unlocking intelligence opportunities that fit hand-in-hand with what our customers want: more insights, more actions and better results. For customers, Scout is an intelligence agent. For us, it's a conversation starter. We've had over 300 conversations with our customers about Scout in just under 1 month, and we've already run live data for 100 of those customers, prioritizing our larger renewals and our near-term expansion targets. The reaction has been consistent that this is what is missing and what they've been looking for. So Scout is also helping our sellers. It doesn't just show a snapshot of a digital brand performance, it reveals what they're missing and what to do next, whether that's stronger reviews or more structured content. As our customers ask us to pinpoint the value of Yext, Scout is the conduit that provides that information to us. That means our AEs, they're walking into conversations with our customers with something they've never had before, which is brand-specific, data-backed recommendations that drive urgency. And we've seen that Scout has applicability across 100% of our customer base. So since launching our interest page on March 3, we've had 646 sign-ups, which is going up every day. That includes existing customers, new prospects and even some churned accounts who value innovation in our space. The feedback we're hearing again is consistent, that this is what they've been waiting for. One of the largest hotel brands in Europe told us, "We need to be your first beta customer immediately." A major national retailer said, "Scout is lighting up the SEO community." And a global health system shared that they're finally able to unlock the insights that they've been chasing while clearly showing the value of the hard work that they've been putting in. And with the PLG flow launching today, we expect the momentum to continue growing as brands see firsthand the powerful insights that Scout can provide. Secondly, Yext Social. Yext Social is also becoming a key part of our platform motion, 6 months into launch and adoption is growing, especially through our reseller channel. But the value of Social goes beyond the ARR that we're hoping it contributes this year. It's also a driver of retention. We are no longer at risk losing to competition because we lacked a social offering. It's strengthening our platform defensibility and it's part of our retention strategy. Next, Hearsay. So our acquisition of Hearsay has created a unique advantage with our financial services customers now, which is our largest vertical with revenue. Together, Yext and Hearsay deliver something no one else has: a single compliance-enabling platform that helps financial advisers and agents do three things: first, to show up in AI-powered search; next, to build trust through verified reviews and content; and lastly, engage prospects directly to convert interest into action. We're capitalizing on this by running coordinated sales plays across our joint base, where 2/3 of our customers are only using one solution. We're also leading with Hearsay Relate to enter new businesses like wealth management, insurance and retail banking. One of our major differentiators here is our ability to scale. With one of our largest FINS customers, we took them from 3,000 to 14,000 agents in under 9 months, demonstrating the speed at which we can expand value. We also have a large opportunity with increasing the awareness of Hearsay Actions. This turns digital interest that may come in through social channels and connections relate into solutions such as scheduling and confirming appointments, speed to lead. We've signed our first 4 major customers, and the momentum is building. One final point I'll leave you with on Hearsay is we have much, much more up for renewal this year than we did last year with Hearsay. So for us, that's plenty of at-bats with our customers telling these stories and converting. So as you'll see, these aren't just individual products in isolation. Together, they represent a modern digital presence platform, one that is built based on how customers search, decide and engage today. Search fragmentation is an advantage to us, and we're executing with focus to turn that advantage into growth. So we discussed how we're going to grow through Scout and also how we're going to grow both Yext Social and Hearsay. The channel that may benefit the most from this is our reseller channel, and we expect to build on the growth that we started in the second half of last year. We serve over 1,500 active resellers who embed Yext into their offering and then power the digital presence for their hundreds of thousands of small businesses globally. These resellers are uniquely positioned to deliver scaled reach and long-term revenue growth. And here's how we're turning that potential into results. First, the rebuild last year. We took deliberate steps to reverse previous decline in this channel. We restructured our team, we streamlined account coverage, we aligned incentives, and we improved the reseller onboarding. We've stabilized this channel today, and we are already seeing improvements in the numbers. Our gross retention rate amongst our top 10 global resellers is 97%, and we also activated over 175 resellers last year. Secondly, a multiproduct adoption strategy within reseller. Today, more than 70% of our resellers sell more than one product. And we've seen an opportunity for meaningful ARR expansion as they adopt more of the Yext platform. Two key innovations are accelerating this momentum. First, Yext Social. So our resellers were the first to adopt the social product, and they're now the largest channel for social activations. Secondly, Yext Scout. Early feedback on Scout has been overwhelmingly positive. Resellers see it as a way to deliver proactive insights and real ROI to their small business customers. So let there be no doubt, we are committed to our reseller channel. Today, we are also much, much easier to do business with than ever before, and you can see that in the growth of our uncommitted revenue in this channel. So we've laid the groundwork. The results are coming into focus. And in FY '26, we expect to continue to grow this channel. So shifting from our resellers back to our direct channel verticals. We continue to have 5 key verticals that we service best. You'll notice one key change since we last spoke 2 years ago. Financial services now accounts for 35% of our revenue. So what are we doing to protect and grow this? We've invested in 25 dedicated sellers across Yext and Hearsay just servicing financial services. We have 20 CSMs just servicing financial services. We have 10 professional services team members just doing implementations in financial services. 30 of our largest financial services customers are mapped to executive sponsors. So we have about 50 direct customer-facing roles in financial services and over 100 if you include the support teams and the enablement teams. So this is a strategic investment to protect and grow our largest vertical, and it's working. Next, health care is another key area of focus for us. We now serve nearly 60% of the top 100 U.S. health systems, and we're seeing steady growth in this segment. Our Find a Doc solution, which is powered by Yext Search, continues to perform well. And again, early interest in Scout is really, really strong in health care. We have also seen interest for Hearsay Social in health care, which is a signal to us that the opportunity extends beyond just FINS. So together, financial services and health care account for more than half of our total revenue, and we are doubling down to deepen our advantage here. Okay. Let's talk about execution. Over the past year, we rebuilt our go-to-market motion. So sales, marketing, customer success and product are all acting as one connected engine now. So what's changed? First, we tightened our focus on the right accounts. You heard Mike earlier talk a little bit about our ICP. So we went deeper into the opportunities that align with our ideal customer profile where the fit is strongest and the potential is highest for growth. Second, we shifted to a full funnel execution model. We're delivering programs that support the entire life cycle from first touch all the way through renewal and expansion. Every motion supports sales priorities and is connected to pipeline. Third, our field teams are more unified than ever. Field marketing, BDRs and ops are all operating in lockstep with sales. We've centralized our insights and our accountability. It means we can move faster, we can respond smarter. So all of this work is an effort to result in much, much more qualified, high-quality pipeline for our sellers. So when we spoke 2 years ago, we spent a lot of time talking about productivity. We talked a lot about pipeline, talked a lot about product innovation. And productivity continues to be a major focus area for us. Last year, we saw AE productivity up. In fact, it was up 21% over the period from FY '23 to FY '25 when we last met. We also continue to focus on the efficiency of our sellers. Today, our teams are smaller, there are better spans of control, and there is much more opportunity per AE. As we look to this year in the sales strategy that we outlined, innovation, specifically with Scout, with Social and with Hearsay are going to have to lead us to greater productivity this year. So to close, we have the sales strategy that reflects where the market is going, and it's built for growth. We continue to invest in our vertical teams and solutions. And while search fragmentation will remain a central driver of our sales strategy, we're also watching what's coming next, specifically agentic experiences. So in these emerging AI interactions, your brand data isn't just discovered. It's acted on. Your brand data strategy now becomes central to your organization and one of the most important topics that we're having with the C-suite right now. This shift raises the stakes for digital presence and Yext is uniquely positioned to lead. So with that, I'm now going to hand off to our COO, Yvette, to take us through how we've redefined customer success at Yext.

Thank you, Tom. All right. I'm the last thing standing between you and Darryl, and that's who you guys really want to talk to. So I'm going to try to move really fast. My name is Yvette. I'm the COO. And as part of my remit, I get to oversee the customer success journey at Yext and the teams. And that's actually a huge privilege for me. I love being close to the customer and thinking about the customer and how we create better experiences for them. I'm going to talk to you today about all of the changes we've made in the last 2 years around our customer success model. The reason that's important is that the world has changed quite a bit in 2 years, but mostly because we have had a renewed vigor at the company, and I hope you've already felt it today, around listening to the customer because we know that if we drive success from the customer, that's how we turn new customers into long-term partners, it's how we create expansion opportunities, it's how we drive retention and ultimately, customer lifetime value, which is what you guys all want to hear, right? All right. So let me tell you where we were, so you can understand how far we've come. So 2 years ago, we, like many in our category, were experiencing a lot of pressure: customer budgets were shrinking, downsizing was more common, churn was ticking up. And not really because customers are losing belief in Yext, but mostly because they were starting to lose faith in the criticality of digital presence strategy in a world of search monopolization. And our largest partners were also telling us that the products we were bringing to market at that time just weren't resonating against the real immediate needs they had in front of them. And our cross-sell motion was just not aligning to what they needed. Internally, we were not very well aligned to the customer. We had a lot of teams that were charged with serving them, but we weren't acting in a very coordinated fashion, which created a lot of friction. And then externally, our competitors were aggressively bundling, they were aggressively pricing, and they were sending the message that good enough and cheaper prices was all a customer needed. So we heard all of that. And we said, "What do we really need to do to become a customer-led organization?" And obviously, the first thing is we have to listen to the customer. And we did hundreds of meetings, all of us, with customers all over the world. And we boiled down everything we heard really to 3 key themes. The first we were hearing from customers is "Show me how I'm doing. Give me a better clarity. Help me understand my performance relative to my peers, to my market, to my goals and do it in an easy way, not only for me to understand, but so I can show my franchisee, all the way down there, how they're doing. In other words, give me insights." The second is they were saying, "Tell me what to fix. I don't want dashboards. I want actual concrete, actionable guidance that actually delivers results immediately." In other words, they want strategic value. And third, "Help me do more with less." Our customers' teams are shrinking and they're under pressure to do more faster, and they look to us to give them more partnership and not just try to sell them more. So we heard them very loudly and clearly, and we took a step back and said, "We've got to think of this completely differently," and sort of start over. And so what we did is we took apart and rebuilt end-to-end our entire customer success model, and we call it the Yext Customer Experience System now, a fully coordinated function across customer success, support, services, concierge, et cetera, et cetera, all fully aligned towards the same goal, which is really to keep that customer in the center. What I'm more excited about is not just pulling all of these teams together, but we connected this wheel to the rest of the company, to R&D, to sales, to marketing, to finance. So now we are really orienting the entire company around a customer-first mentality, and that's made a huge difference. All right. As we did this shift, there were really 4 immediate things that we focused on right away. First was making sure we were much more efficient operationally. So we restructured the post-sales organization to be leaner, faster, more aligned. We focused on accelerating product innovation that the customers wanted today so that they were getting the things they need today, but also making sure that we were pulling them closer and getting their feedback closer into our innovation loops. We changed our support packages to address a lot of their asks for things that give them more flexibility in how they work with us and how we augmented their teams. And then we strengthened our partner ecosystem, which is important because it gives us more ability to reach more customers globally and also gives customers more options to work with partners when they want to. So I'm going to talk a little bit about each of these. So the first move we made was structural. We put all the post-sales customer teams under one organization, common goals, KPIs, you guys know that drill, very important. It did reduce our CX costs significantly year-over-year. But more importantly, it created more operational, just streamlined operations, more clarity of ownership. And now the customers could know exactly where to go when they need us. The thing I think I'm most excited about is when we did this, everybody was like, "Oh, gosh, we're going to break everything. We actually did the opposite. Our outcome has actually gotten better after we did this. So our average resolution time has dropped by nearly 2 business days. Our implementation times have gotten faster, which means customers get to value much faster. Our ability to take in and action their feedback, we used to have customers say, "We've been telling you for years that we need this thing," or "We need this feature," "We have this problem," we're now able to close that loop really quickly for them and come back and say, "This is when you're going to see it. This is when you're going to get it." And then we continue to achieve a CSAT score across all of our programs of 96%, even as we've sort of put all this change into the system. So there's no question in my mind that we're operating at a much higher standard and that we're a much more highly efficient organization and that that's paying off for customer experience. The next thing, and this is probably the thing that's really the most satisfying when you're talking to customers, is we started to be able to demonstrate right away that we were listening and we were giving them the features and the products that they wanted. And this is kudos to our R&D team who have been producing at a crazy pace. So the customers told us, you've heard, "Give me insight." You've heard a lot about Scout. So I'm not going to tell you much more about the product. But what I will tell you that I get excited about is that our teams who are actually on the inside thinking about the customer, this is a tool for them now. So now our CSMs, our services teams, can use Scout to say, "Hey, how do we get ahead of something that's happening that maybe even the customer isn't seeing yet?" And so they're already better equipped and it's much faster. What used to take hours and hours and hours, literally 6 to 18 hours, to prepare a detailed analysis for a customer is now taking an hour. Customers also said, "Tell me what to fix." So managing your digital presence is a very complex thing. And they wanted something that was simple and that allowed them to really zero in very quickly on what to do. And so we launched Listings Recommendations. All that is really is being able to point out to the customer where they have incomplete or low-quality data and then offer them an automated suggestion to say, "How about you change this word or you fill in this field?" And then a click of a button, they can do that, and they can do that across thousands of locations. So made it much easier for them to do that. They wanted us to help them do more with less. And so we launched Yext Social. So now brands can post across hundreds of locations with just a few clicks. And more importantly, they were asking for this because they wanted fewer discrete point solutions that they had to manage with other competitors. I have one customer who told me that this saves them 175 personnel hours a week. And then finally, to make reputation management easier, we introduced third-party review generation and AI-powered review response. Customers using this are responding to 50% more reviews, 80% faster. And I think you heard earlier, reviews are a really essential element of actually having your rankings perform. The best part for me of all of this is I know every single conversation that happened with customers where these were the things they were asking for, and we were able to go back to those customers and say, "Your insights, your feedback to us is something we've responded to and we've given you," and we can really say to them now that we are a much more responsive organization. All right. The third area, this is the re-envisioning of our success models. So what we were hearing from customers is their businesses were changing, and they needed more options for how they engage our teams. Some customers want us to do everything for them. They will hire a bunch of us to go do all the implementations, do all the changes. Some customers want very little support. Really, we did not have very flexible models before. So we've introduced more options for them. So our enterprise customers now have more options, and they are able to even adjust within those much more than they could before. We also launched a new model for our mid-enterprise and smaller customers. So we took the best of the high-touch model and then applied a bunch of automation, scaling and guided engagement so that the smaller customers are getting more support, more recommendations, but we are able to do it more efficiently. And we're seeing great impact. We have 99% of our top 200 customers have a CX package. We have, as I said, held a 96% CSAT score across all of our programs. And we're seeing faster resolution times and more proactive engagement than ever before with our support and services teams. Finally, and this one is really close to my heart because this was not true a few years ago. We have a really robust now partner ecosystem that we've continued to grow and continue to invest in and really partly to give customers more flexibility in how they work with us, but also allowing us to serve many, many more customers globally, specifically through our reseller channel. So we work with a diverse set of partners, global resellers, Tom talked a lot about that. We have implementation and delivery partners now. We have digital agencies we work closely with, and we have other strategic alliance partners. This helps us scale intelligently. It helps us serve more markets and bring Yext to more customers. What this actually doesn't show, and I realize that as I was walking up here, it doesn't show the hundreds of publishers we also work who are also really key partners. Such key partners, they often come to us before they introduce new changes to their listings or their products in order to have us give them our expertise. And what I love about that is it's just such a symbol of partnership. Many of these partners, especially our resellers, are always in the early stages of every product beta, helping us shape and make the product better. And I just see this as such an incredible part of why we succeed. All right. All of this is delivering results. Super happy about it. We have a strong NPS here, 41 for Yext with our largest customers and 54 for here. They're trending up, and we're going to keep focused on these. Just for fun, does anybody know where NPS comes from? I have to say this because this is my fun fact. So some dude at Bain takes credit for it. But actually, it comes because Enterprise -- the original founder of Enterprise Rent-A-Car, one of my favorite customers, actually used to ask the customers, "Would you recommend Enterprise to a friend?" And then a dude at Bain picked it up and he named it NPS, and he gets credit for it, but it's actually the Enterprise founder. You can look that up. All right. Gross retention. So NPS is really important, but gross retention is really our key metric that we think about. So we're pushing towards a goal of over 90%, and we're making steady progress. Our rate has improved sequentially for the past 3 quarters. So we started to make all these changes. Everything is going in the right direction after the changes. So it's a clear sign that what we're doing is working. I love this, but I love something even more. the tone of the conversation with the customer is dramatically different in 2 years. So we work -- as you guys know, we work with the largest global brands in these industries. What is changing? A, we're talking to higher-level folks. The senior leaders at these companies are leaning in -- not out, in -- to say, "Please come help us understand this changing landscape, help us understand how we get ahead of it." And not only that, we're being asked again and again and again, "Come talk to my broader team." So we'll have a meeting with a CMO or a CEO. And next thing we know, these guys are on the road, specifically Christian, on the road presenting to a much larger part of their organization because they're saying, "Hey, we need you to help our teams explain how to get ahead of what's changing." What I see is instead of them saying, "Hey, you guys don't get us," what they're saying is, "You're back to being the organization that is going to lead us through the complexity." And the recognition of Yext expertise and best-in-class solutions is allowing us to add new logos, expand the existing relationships. But my favorite is win back a bunch of customers that used to be with us. All right. I'm going to wrap it up. We are very focused on keeping this momentum going. This -- I'm super happy at the work we've done in the last 2 years, but we have a lot to still do. So we're going to keep focused on retention improvement with a goal of returning to over 100% NRR. We're going to continue now -- now that we've really focused on the enterprise, we're going to extend that focus to our mid-enterprise segment to make sure that we're continuing to scale support and recommendations and insights and everything there because those are the customers that are going to grow, and we want to grow alongside them as their partner of choice. And then we're going to continue to leverage data science and intelligence with tools like Scout to make sure that our customers are seeing and feeling the ROI that we know we can deliver. And what I'm really, really excited about there is, you saw this, we can now definitively show customers why using the combination of products that Yext offers is actually paying off for them. And then finally, my favorite part as the COO is we're going to keep focused on making sure we're not slowing down our progress and becoming an operationally highly efficient, highly scalable team that can flex with the needs of the customers and the products that we want to bring to market. All right. With that, I'm going to let you have Dale.

Thanks, Yvette, and welcome, everyone. Today, I'd like to cover 3 key areas: our fiscal '25 performance, the strategic opportunities ahead and our long-term objectives. This comprehensive look will give you a clear picture of where we stand financially and where we're headed. Let's start by looking at our financial performance for fiscal '25. Our fiscal '25 results, which we reported 4 weeks ago, showed positive growth. ARR grew to $443 million, representing a 13% increase from last year. Revenue reached $421 million, a 4% year-over-year increase. The increase in ARR and revenue was primarily due to the Hearsay acquisition. This growth was accompanied by a net retention rate of 93%, which excludes Hearsay's ARR as it was not in our ARR last year. We've improved our non-GAAP profitability and efficiency. Our non-GAAP EPS reached $0.35, and we achieved a 16% adjusted EBITDA margin. Our operating expenses were 66% of revenue, an improvement of about 400 basis points year-over-year. On the capital front, we generated $50 million in operating cash flow. We also repurchased 2.7 million shares, representing 2% of our total shares outstanding. We ended the year with a strong cash balance of $123 million. Now the last time we hosted Investor Day was 2023, shortly after reporting our Q4 results. Since then, we've achieved significant progress. Our improvements are evident across a number of metrics. ARR, revenue, adjusted EBITDA, Rule of 40 and free cash flow have all improved, and we've launched a number of new products. We set out to accomplish a number of strategic objectives at that event, and I'm proud to be able to highlight our accomplishments. Over the past 3 years, our total ARR has increased from $398 million to $443 million. This growth is primarily driven by the addition of Hearsay. And we're encouraged by the trends in ARR, and we will continue to provide granular ARR reporting, which we believe to be the best measure of future revenue growth. The challenges in fiscal '22 through fiscal '24 that Yvette mentioned also impact net retention. As a direct result of the work we've done, gross and net retention have been improving throughout fiscal '25. This reflects our success in retaining customers. The improvements are a strong indicator of customer satisfaction, the stickiness of our platform and our ability to deliver increasing value to our customers. Our gross margins have consistently remained within our target range of 75% to 80%. This is an indication of our efficient cost management. We have adequate buffer during slower economic periods and more resources to reinvest in growth activities. We also have the ability to scale operations without proportional increases in costs. We consistently work to improve our operating efficiency. Our operating expense as a percentage of revenue have decreased significantly from 81% in fiscal '22 to 66% in fiscal '25, demonstrating our commitment to streamlining the business. Much of the improvements were driven from reducing sales and marketing in response to the challenges we face in go-to-market, product and customer success. We've increased investment in research and development to accelerate our pace of innovation. We've achieved this while continuing to invest in growth, highlighting the leverage in our business model. Our EBITDA margin has seen substantial improvement, growing from 1% in Q1 of fiscal '22 to 22% in Q4 Of fiscal '25. This consistent upward trend in our EBITDA margin demonstrates our ability to drive profitability as we scale. It's a clear indication that we're not just growing, but growing efficiently with a focus on sustainable, profitable expansion. We've also continued to make progress in reducing dilution. The impact of share issuances related to employee compensation has decreased significantly. And with the increase in PSUs in fiscal '25, we've signaled our continued focus on reducing issuance dilution. At the same time, our share buyback program has been a key contributor in offsetting dilution. This focus on managing our share count demonstrates our commitment to maximizing shareholder value and our confidence in the long-term prospects of our business. We will continue to opportunistically repurchase shares. Now that we've reviewed our fiscal '25 performance and financial progress, I'd like to shift gears and focus on the growth opportunities ahead. These are rooted in our ability to expand platform adoption, drive upsell and cross-sell initiatives, improve retention and capitalize on strategic acquisitions, Hearsay and Places Scout. Together, these initiatives position us to unlock significant ARR growth and long-term value creation. As you've heard from most of the other speakers today, we believe Scout presents us with significant growth opportunities. First, Scout serves as a compelling land-and-expand product, enabling us to attract new logos with a high-value, low-friction point of entry. Its insights and recommendations demonstrate immediate ROI and pave the way for platform expansion. Second, Scout is relevant to 100% of our current customers and its utility and ease of adoption make it an ideal attach product. And third, it is a catalyst for cross-sell acceleration, acting as a gateway to our broader platform and naturally surfacing the need for listings, reviews, pages and social. Our initial pricing strategy for Scout is to charge per location per month, similar to Listings. By way of comparison, approximately 98% of our customers are using Listings, accounting for over 40% of our total ARR. We believe every customer can benefit from Scout as it will provide insights on local ranking and recommendations on how to improve discoverability. The acquisition of Hearsay has also unlocked significant opportunities for Yext. The combination of Yext Financial Services customers with Hearsay's financial services customers creates a powerful cross-sell opportunity. We also see significant potential in introducing Hearsay Relate to Yext customers. Combining Hearsay's social capabilities with Yext's core platform creates a compelling value proposition for financial institutions looking for integrated solutions. By leveraging our complementary offerings, we can deepen relationships with existing customers and expand our footprint within the financial services sector. There are over 100 Hearsay customers that we obtained through the acquisition. Some of Hearsay's largest customers were Yext customers as well. However, almost 75% of these customers do not currently use Yext products. Just as compelling, there are over 400 enterprise and mid-market financial services customers only using Yext. These customers represent a significant opportunity to introduce Hearsay's offerings. Finally, I would highlight the adoption gap where less than 25% of the Hearsay-only customers are using Relate. This signals an untapped opportunity to showcase the value of Relate as a key tool for our customers' communication strategy, driving better engagement and outcomes for their business with a compliant solution. By bridging these gaps and presenting a united Yext plus Hearsay front to our FINS customers, we position ourselves as a trusted partner that delivers tailored and effective solutions. Greater platform adoption not only increases revenue, but also strengthens customer retention and loyalty. As customers integrate more products into their workflows, switching costs rise and the perceived value of our platform grows, creating a virtuous cycle of engagement and recurring revenue. To maximize this opportunity, we are prioritizing strategies that encourage multiproduct adoption, such as targeted upselling campaigns and bundled pricing initiatives. By doing so, we can unlock substantial ARR growth and become a valuable partner to our financial services customers. The third significant opportunity that I want to touch on is our core platform. As customers integrate more Yext products into their operations, they are likely to become more entrenched, leading to higher retention rates and sustainable long-term growth. To drive platform adoption, we will leverage our strengths. We have the most complete end-to-end digital presence platform in the market. We provide the broadest publisher network of any listings provider, a network that includes AI platforms. And our platform empowers brands to seamlessly manage and distribute structured data, ensuring accuracy, consistency and discoverability across both traditional and AI-driven search experiences. These features equip our customers to not just weather the market dynamics created by search fragmentation in agentic AI, but to thrive in this new environment. By empowering businesses with tools to enhance discoverability, streamline operations and deliver accurate information across channels, Yext can help customers improve efficiency, strengthen customer trust and drive growth in a rapidly evolving digital landscape. And despite efforts to expand multiproduct adoption, progress was limited due to a focus on products that struggled with broad customer adoption. With Scout and Social, we've added several new products that we believe achieve product market fit, and we believe a large and significant opportunity exists for our core products as well. With 76% of our direct customers using only 1 or 2 of our products, we can see a clear path to driving adoption across the platform. We have a lot of customers, but not a lot of them are using 3 or more of our products. The more products the customer uses, the stickier that customer becomes and, of course, the higher the ARR. This chart demonstrates that opportunity, and we believe Scout could help further product adoption. These initiatives position us to unlock meaningful growth and broaden our reach into new markets. Now that we've explored the immediate opportunities ahead of us, let's look at how these initiatives align with our longer-term objectives. In just the past 12 months, we've increased the number of products on our platform to include Social, Relate and Scout. This expanded portfolio increases our addressable market while enhancing our ability to meet diverse customer needs across industries. This broader platform brings an expanded sales pipeline as we leverage comprehensive suite of solutions. We strongly believe that capital allocation is a cornerstone of sustainable business growth and shareholder value creation. Our approach is balanced, focusing on both organic and inorganic growth opportunities, while maintaining flexibility for shareholder returns. It's also adaptive, ensuring that we are always optimizing our resources for the maximum benefit. We are committed to returning value to shareholders. We had $32 million available for future share repurchases as of January 31, 2025, which was subsequently increased by an additional $50 million in March of 2025. This gives us flexibility to enhance shareholder returns, particularly when we believe our shares are undervalued. Our progress toward achieving Rule of 40 has been steady and deliberate. Improvements over the past 3 years have been due to the operating efficiencies we've created in our business. Looking ahead to fiscal '26, at the midpoints of our Q1 revenue and adjusted EBITDA guidance ranges as of March 5, 2025, we expect to achieve a Rule of 40 score of 26%. This trajectory reflects both our commitment to driving revenue growth and continually improving our profitability while also reinforcing our long-term financial health. In closing, I want to thank you for your time and attention today. As you've seen throughout this presentation, we delivered strong financial performance in fiscal '25. We're capitalizing on exciting strategic opportunities across platform adoption, upsell and cross-sell initiatives with Scout and Hearsay, retention improvements and new product launches. We're executing against clear long-term objectives that position Yext for sustained growth and profitability. We remain committed to delivering value for our customers, employees, partners and shareholders as we continue building on this momentum into fiscal '26 and beyond. That concludes my prepared remarks. And now I'd like to invite Mike, Yvette and Tom back to the stage to conduct our second Q&A session.

So maybe the question is for Darryl or maybe Mike. So in terms of just the 2026 outlook, curious what you're baking in, in terms of contribution from Scout. You did kind of talk about how pricing might work. But even though we don't know what exactly it will be, just give us your thoughts there.

Yes. I mean when we provided our EBITDA guidance back in March, we based that guidance based on what we could see at that time. And if you think about back then, we had just closed the Scout acquisition about a month prior. So we haven't baked in any meaningful contribution into the full year EBITDA guide for Scout. Now obviously, we're excited about the opportunity. And Naved, you've known us for a while. We're just not going to get ahead of ourselves and sort of predicting what the future may look like, but the excitement is significant, and we've got a nice opportunity to execute against.

Yes. It's also one of the reasons, and we've talked about this, I think it's generally been received pretty well, why we didn't want to give a full year guide. We've got multiple new products. First full year with Hearsay, Relate, that cross-sell opportunity that Darryl has been talking about, Yext Social has really only been in market for about 6 months now, and Scout is obviously 501, so just there's a lot of opportunity there. I think trying to guess how much of it is going to show up this year with all the economic uncertainty and everything, so again, effectively short answer, not really anything baked into that number.

As we think about the time line on Scout here, so you said 501, obviously, early preview here, how long do you anticipate being in preview before sort of Scout is generally available? And then how do you -- and Tom, maybe how do you think about what the sales cycle looks like for Scout given that it seems like it's going to be providing quite a bit of value to customers pretty quickly off the bat here?

Yes, I'll take the first part. I just want -- I want to be super clear about this. There are -- you saw two things today. You saw a bunch of screens that demonstrate what is going live at 501 today, and that is our PLG demonstration. That PLG demonstration flow is a limited set of data around a single location. It proves that the product is capable of doing this in real time. It will lead to a waitlist sign-up. And then Tom can talk about how we'll work through that demand flow. The second thing you saw, which Jason went through in quite some detail, was the internal workings of the full product. So Jason mentioned, we're showing 3 or 4 metrics in the PLG flow. There are 150 nonperformance metrics that we're collecting that can be brought to bear in the full product. So I think there will ultimately be two pieces to this, a level of PLG acquisition over time, and then a lot of that will be to generate interest and demonstration around the full product. And then Tom can talk about how we're engaging with customers.

Yes. On the sales cycles, first off, they've already started. Now when we say that we have spoken to 300 customers and pulled 100 customers' data, we can manually pull the data. We can put it into Tableau reports. And so we've done that. And as I said, the excitement is certainly there. As it pertains to our sellers, there's two motions they're going to run. We're going to sell -- we can sell Scout stand-alone. And as I said, when they see that data, I think Darryl shared a little bit of pricing and how we're going to do that. But it also pinpoints where to go with other parts of our platform. So when it shows you things like, "Maybe you need more structured pages," or "Maybe your listings aren't performing that well." And I think Christian said earlier, it does it for both Yext customers and non-Yext customers. So it really becomes almost a BDR, if you will, for our sales force.

I particularly like the notion of having customers who decide to go to a different platform use Scout because it will show them exactly what the cost of leaving is.

I guess that case study around financial services, Tom, that you talked about 100 people, now you have that as the largest vertical. How replicable is that to retail, to health care? Is it a function of putting an army of people behind those verticals and having those 4 functions fleshed out? Or is there something special about financial services that you thought you're successful in and it's hard to do in retail and health care?

Well, I think we have the demand there. I think we have the revenue there, and we continue to expand the use cases, that's for sure. And whether we see it in insurance with agents or we see it in financial services with financial advisers, we have the demand there. Remember, previous to Hearsay, we had a pretty substantial financial services practice as well. So we certainly have beefed that up. Now when you start to -- so you get this cross-pollination, and we purposely cross-pollinated the teams. So we have 2 leaders of those teams. It's not Hearsay and Yext, right? There's some traditional Hearsay people on the team. There's Yext folks on the team. So there's a lot of knowledge share going there. And I think when we go to market, if we have a Relate opportunity, we have folks on the team that know a lot about Relate even if you were previously with Yext. And so we're seeing that, I think, that progression where social customers and that discovery become Relate customers and you make those connections. And then I think where the big play for us and we're really focusing this year is on actions, and that's where you really can solve business problems.

I think one thing that makes financial services distinct is that it's often many companies within a company, right? So when you're working with selling and supporting a financial services institution, you're actually often working with multiple entities who are not necessarily all talking to each other within their own organization. I personally don't see that as much in some of the other verticals. When you're dealing with a health care system or you're dealing with a retailer, often you don't have that same dynamic. So I think in some ways, financial services is always going to be, let's just say, a more resource-intensive vertical, I believe.

So on the product attach and the ARR chart that you showed that, once someone gets to 4 products, the ARR is significantly higher. Curious how that chart looked like maybe 3 years back, what's the progression like when people went from 1 -- or customers went from 1 to 2 to 3? And do you think the low-hanging opportunity might be to get customers from 3 to 4 because that's kind of the multiplier there? Or is it getting more customers from 1 to 2 and 2 to 3 maybe?

I think it's the progression along -- from my standpoint, it's the progression along the curve. And so if you rewind a couple of years ago, we had listings, reviews, pages, search. Those all had some significant or large market traction. And then as I discussed in my comments, we were launching new products. And I think as we've learned, those products were less applicable to a lot of our customers. And so I think when you look at that data, we haven't made a lot of progress in the last couple of years on expanding 1s to 2s and 2s to 3s and 3s to 4s. And I think that has a lot to do with the fact that the products we were releasing, again, were not -- just weren't what our customers wanted. And this has been the big reset and the big refocus across the entire company. And it's where this energy is coming from of we're bringing product now. I mean, Hearsay was a -- which is 2 new -- at least 2 new products, Hearsay Social and Relate, and then Actions we talk about, which is their lead generation product tied back to their sites and our Pages product. That's really 3 additional products that we can bring to customers and expand beyond the financial services vertical. Yext Social is today the same product. And eventually, we do believe there's probably a time line to merge those products, and then Scout. So Darryl and I were talking about today, 2 years ago, we really had 4 products that we felt were well suited to our customers, and we had some moonshots. Today, what we have is 8 products, and we have a lot of belief that those 8 products are well suited. But 4 out of the 8 products have been introduced to our sales team and our company in the last, let's call it, 8 or 9 months. So we expect to make a lot more progress, let's say, in the next 2 years than we did in the last 2 years.

Maybe a question on Hearsay for Tom and Yvette. So you mentioned, Tom, that this year, there are much, much more renewals for Hearsay coming up. Kind of curious, one, typically, when you have some M&A, there's always disruption. And so how, you two, have partnered to sort of minimize that disruption for existing customers? And then two, sort of what the sort of strategy here to sort of take Yext from maybe a retention story to an upsell expansion story with those Hearsay renewals and how you -- whether you're leading with, say, like Hearsay Social versus Yext Social, to the point Mike just made.

I can start on the first one, which is Tom and I partner's very closely. And I think what I would say, and I think he'll agree is the way we've minimized that disruption is really by listening to the customer. We were very lucky right to have some very some mutual customers when we made the acquisition who are familiar with both sets of products, both sets of teams. And those customers will tell us. We like this motion that you have on this success thing. We like in this report that you do over here. So we're able to really take that in and say, okay, now we're going to really design that together. And the teams have been wonderful at sort of figuring out how to work that. So I would say that's really the way we're doing it.

And on the renewals and the more up for renewal. I mean we've learned a lot from Hearsay as well, and I'm sure they've learned a lot from Yext. But what Hearsay did really well was multiyear deals, okay? 3-year deals, 4-year deals, 5-year deals, right, very long deals. It just so happens that a lot of them are expiring this year, which is great for us, in my opinion, because that's a lot of [ FS ], as I said, that's a lot of conversations with customers where we can do the cross-sell and the upsell. And it really depends on the opportunity. The customer that I had referenced in here that went from 3,000 to 14,000 agents as an insurance company didn't have Yext Listings. They were using somebody else. They now have Yext Listings. So that's when Darryl said that there's only 21%, 22% or so that have both. And that's a huge amount of white space for us.

I just want to underscore a point here, which I think is maybe best describes the transition that we've made in this company over the last 3 years is that for any software company, the renewal is either scary or exciting. And I think here, Yext for the last -- for much of the last 3 or 4 years, the renewal has been a scary thing. I think where we're sitting today and Tom's comments, having a big chunk of that Hearsay book up for renewal this year is a huge opportunity for us. It gives us an opportunity to get in there and talk about a lot of value that can be driven through these. And I think it's at the heart of a lot of the positivity that you're hearing from us in spite of the fact that we know that the environment stuff out there, and we know that there's a lot of uncertainty this organization has transformed around the customer, and we relish the opportunity to go into these cycles and compete.

On Darryl's slide about all the growth opportunities you have and if there is any way to frame a timetable or scale of growth to the Yext when you can around Scout, Hearsay and even the core as you're going to give us some more data. In terms of -- you talked about Scout has ARR potential pricing. Yours feels like just more cross-sell. I don't want to oversimplify and core has more products to sell. But as you ran out of these 3 and maybe just break it down in a better grid for us in terms of potential or to the extent you can give any color, that would be helpful.

Yes. Look, I mean, like we did the Hearsay acquisition. We closed that in August of last year. I think we launched the Yext Social product in September of last year. and we launched Scout, I guess we will be doing that at 501 today. So the sales cycles are long, as you know, right? We've been talking about this. It's 6, 9 months, sometimes even 12 months for large enterprises. So we're excited about the opportunity, but we're not going to break down what we think that opportunity could be piece by piece because it's a joint go-to-market motion. As Tom, I think, mentioned in his presentation, there's a go-to-market flywheel that's happening. And we're going to go to market with those products, but then Pages and Listings and Reviews and Social where we have got white space and we've got customers that haven't adopted those products. So we don't really think about it in ARR contribution product by product. We look at it at how can we further penetrate customer or go get new logos.

Yes, and bundle and packaging together. And we're not -- I mean, I guess we are sort of ducking the question, but get a credit for 2 questions that most obviously duck. I think what we've tried to do is we tried to give you the most robust possible view of the ARR, including increased disclosures so that you can really see what's coming. And that's the best indicator. And obviously, we all know that the second half of the year is typically a lot heavier when it comes to bookings and things like that. So -- but I just would point you once again to that's the place to look. And as we get into the middle of the second half of the year, that's where you'll start to see -- we expect to start to see growth appear.

I think Yvette's comments kind of implied that kind of solved the enterprise customer now going to go after the midsized and what's the scope of improvement there? And how much of your ARR is made up of enterprise versus midsized?

Yes. We haven't -- I don't think we've separated out enterprise versus mid-market. The sort of lines between those 2 get a little bit blurry, and they can get reset over time as we change go-to-market motion. So it's not something that we've separated, but we just look at that as our direct business. Yvette can talk about how we're servicing the lower end of the more customers.

Yes. I think one of the things that we recognized is that we needed to adjust some of our practices and customer success to grow alongside the mid-market cohort that are often sort of at different levels of resourcing internally. They have different levels of ability to apply focus our products, and so we may need to lean in a little bit more closely. They may need more support and learning how to engage their franchisees, et cetera. And so what we're really recognizing is a large enterprise may be different resources to bear, which may allow them to be more successful in a different time frame, we need to think about how to help the mid-enterprise folks do that since then they grow, which ultimately obviously benefits us as they grow alongside us. And so we're going to just enhance our attention to that. distinction in their needs.

Not one M&A question?

Maybe on Scout moving forward as you're kind of going through the evaluation process. This obviously at least places Scout was sort of a more consumption-based pricing model episodic, if you will, versus sort of now you're bundling it in as more of a subscription into the core product. What do you need to prove in terms of ROI? Or what kind of feedback do you think you -- are customers going to be asking for to maybe justify, I assume is maybe an increase in pricing for that functionality moving forward?

Yes. I mean I think every -- in this environment, and it's been this way for a few years here, you don't sell anything without belief that there's value in and then proving -- and you don't keep that business without proof of value. So we're very accustomed to that. One of the things that we've been -- we were bullish on and we've been pleasantly surprised by is that there's not a lot of explaining required at the customer for them to see the ROI of having this level of data and insight and actionability, and there is nowhere else where they can get it. We're very confident of that today. And so it's very early to talk about how we're going to price it and again, what the revenue opportunity is from that and it's multifaceted. It's the product itself and then it helps sell the other products and value dealer products. But yes, we're really comfortable that the value proposition is there.

Safe to say that as of now, there's just value in being able to see that data and be able to measure it versus greater evaluation over time of whether or not the recommendations result in sort of that improvement in search rankings, et cetera?

Yes. I mean -- sorry, just some sometimes value is holding your position, right? So if you're sitting at #1, you're not going to improve, right? But you're really, really focused on holding that position.

I've just been in a dozen of these meetings just in the last month. And I would tell you that the value that I say immediately in the customers' eyes is actually not about them. It's about their boss or their boss's boss because for the first time, this digital presence listings management is complicated and their CMO is like, "I don't get it. I don't get what we're doing and why we're spending and why you need more in our team." And all of a sudden, we show them these reports and they go, "Oh, I can take this right stairs. And I'm justifying now my job, my budget, my strategy," like so -- and that's the most pleasant part for me is when you just see their job just got easier.

And I wouldn't discount our reseller channel either. I mean you're -- now you're talking about us giving them a new product for them to sell, which we probably haven't done in quite a while, and they are our largest sales force.

Yes. When you look at -- when you go check out that PLG demonstration later today, think about how valuable that would be to any large organization selling to marketing services to SMBs, right? And so we are going to actively discuss with our key partners how do we give them that exact same functionality. It's not something that we're going to keep here near inside Yext because they are a channel to day to the SMB market.

20 minutes until it actually goes live, but we do have live demos that are staging outside as we speak, and one of those demo stations will actually feature Scout. In addition, we'll have stations outside that are showing the Relate product, Social as well as another station that's showing Listings, Pages and Reviews. So with that, I want to thank you all for attending. And that concludes today's presentation. Thank you.

Thank you.