Video: Yext's Vision for the Future of Agentic Marketing | Duration: 2308s | Summary: At Envision, we unveiled our transformative vision for marketing in the age of AI agents — centered on empowering marketers, not replacing them. In this keynote session, Mike Walrath, Jeanette Simisky, Matt Hupman, and Paige Saunders demonstrate how Yext is evolving its Scout platform into a "multiplayer agent harness" that enables teams to scale their work by 10–30x while maintaining strategic control and judgment.The presentation challenges the prevailing industry narrative that AI will automate marketing jobs away. Instead, Yext positions its platform as a system that augments marketers' capabilities by unifying three critical types of context: brand context (your knowledge graph, locations, products, voice), market context (competitive intelligence, reviews, visibility data), and working context (shared memory across team conversations and decisions).Key takeaways:The Scout Harness: A shared workspace where your entire marketing team — including agencies and partners — operates on unified context, eliminating "slop grenades" (disconnected AI outputs) and enabling seamless collaborationReal-world demonstration: Organic Crush, a multi-location health food brand, used Scout to create hyper-local marketing plans in under 3 minutes — a process that traditionally takes daysFlamel AI acquisition: Yext announced the acquisition of Flamel.ai, a platform for executing localized paid campaigns across Google, Meta, and ChatGPT, bridging the gap between Scout's strategic intelligence and campaign executionMemory, skills, and connections: Scout's "harness" is powered by episodic memory (past decisions and preferences), repeatable marketing skills (workflows like competitive analysis), and integrations with Yext's knowledge graph and external platformsMultiplayer capability: Teams can collaborate in real-time inside Scout, with agents and humans working together — all grounded in shared brand standards and market dataLive demo highlights: Scout generated a $10K hyper-local paid media plan for five Organic Crush locations in 2 minutes 16 seconds, tailored by neighborhood demand and competitive positioning. | Chapters: Welcome & Recap (0s), Building for Marketers (161s), Three Context Types (305s), Local Marketing Challenge (462s), Marketing Harness (541s), Multiplayer Agent Harness (665s), Real Customer Demo (766s), Scout in Action (860s), SCOUT Platform Overview (1103s), Scout Harness Demo (1195s), Conversation Threads (1402s), Live Scout Demo (1530s), Paid Media Execution (1756s), Flamel Acquisition (1859s), Live Campaign Launch (2009s), Closing Remarks (2151s) Video: The Perfectly Personal: How AI Redefined "Best" | Duration: 1570s | Summary: In this video, Christian Ward, Chief Data Officer, explores how AI is fundamentally transforming search from a finite, transactional model into an infinite, personalized conversation—where "best" is no longer based on ratings alone, but on context, memory, and real-time relevance to the user. Ward introduces the concept of the "perfectly personal" era, where AI agents understand individual circumstances—insurance coverage, availability, location, preferences—and filter results before the user even asks. Unlike traditional search, which ends with a list, AI search is an ongoing dialogue that learns and adapts with every interaction. This shift means stale or outdated data is no longer acceptable; real-time updates and comprehensive facts are essential to staying visible. Key takeaways:AI search prioritizes context over keywords—what matters is "best for me," not "best rated"Your AI knows your insurance, schedule, preferences, and filters out irrelevant options automaticallyBusinesses must supply rich, structured, real-time data at every level—brand, regional, and localOver 83% of AI answers cite controllable sources like websites and listingsActively managing location data can double platform visibility and drive significant increases in clicks, calls, and directionsUpdating content frequently (4+ times per month) signals trustworthiness and improves engagementTools like Corvo, Yext's AI marketing agent, allow small business owners to manage data and updates via simple text messages | Chapters: Welcome to Envision (0s), Contextual Search Ranking (63s), Perfectly Personal AI (129s), Finite vs Infinite Games (164s), Contextual AI Intelligence (203s), AI Context Levels (289s), AI Data Study (496s), Contextual AI Search (638s), Active Data Management (781s), Engagement and Usage (844s), Real-Time Data Strategy (938s), Corvo Demo Conclusion (1261s) Video: From Local to Brand: The Launch of Brand Scout | Duration: 446s | Summary: In this video, Melissa Tedisco, Senior Director of Product Marketing at Yext, explains how brands can close visibility gaps in AI search by managing both brand-level and location-level presence. She emphasizes that AI search requires a fundamentally different approach than traditional channel marketing — one that prioritizes an ecosystem of consistent, fresh information across multiple sources rather than focusing on a single platform. Melissa introduces Yext's enhanced Scout product, which now integrates brand-level visibility management following the acquisition of Go Shine, allowing marketers to monitor, optimize, and act on AI citation gaps in real time. Key takeaways:AI search strategies differ from traditional channel playbooks — visibility depends on an ecosystem of sources, not a single platformLocation-based citation research shows that websites, location pages, and listings are top AI sources, not just PR or social platforms like RedditYext Scout now manages both brand and local visibility in one system, following the acquisition of Go ShineScout's AI agents analyze top citation sources, generate GEO-optimized content briefs, and track visibility lift by topic and queryReal-world results: Yext improved visibility on "agentic marketing" in two weeks; Play2Go doubled inbound leads and gained brand awareness at trade showsChris Johnson from Janney shares insights on using Scout for brand-level visibility in regulated, multi-location environments See the slides. | Chapters: Welcome and Introduction (0s), Closing Visibility Gaps (12s), AI Search Complexity (103s), Brand-Level Visibility (157s), Agent-Driven Content (220s), Results and Proof (307s), Case Study Introduction (394s) Video: Yext Research: Four AIs, One Question, Four Different Answers | Summary: In this presentation, Anthony Rinaldi examines the inconsistency of AI model responses and what it means for businesses trying to optimize their online presence. Drawing on research analyzing over 500,000 queries across multiple AI models (ChatGPT, Claude, Gemini, and Perplexity), he reveals a striking discovery: these models agree on their top recommendation only 14% of the time for the same location-based business queries. Nearly half the time, they provide completely different answers. This "disagreement amongst friends" highlights a critical challenge for businesses navigating AI-powered search optimization. Key takeaways:AI models agree perfectly on business recommendations just 14% of the time when asked the same question48% of the time, four major AI models give completely different answers to identical queriesModels typically return only 7 results on average when asked for "top 10" recommendationsEach AI model has a different "citation diet" — Gemini favors first-party content, Claude emphasizes reviews, ChatGPT prefers directories, and Perplexity takes a balanced approachBusinesses with location pages are 3x more likely to be recommended by AI modelsThe median rating for AI-recommended #1 businesses is 4.8 stars, though 11% of top picks have ratings below 4 starsBusinesses that achieve unanimous agreement across all models have 30x more reviews than those that don't appearDense urban markets show less AI consensus than rural areas due to more business options | Chapters: Introduction and Setup (0s), Predictive Text Magic (51s), Response Variability (125s), Research Findings (198s), Inconsistent AI Results (311s), Model Inconsistency Analysis (396s), AI Ranking Criteria (537s), Model Ranking Differences (647s) Video: One Platform. Every Perspective. | Summary: In this session, Mike explores how modern enterprise organizations—particularly in healthcare—can move beyond using Yext as a single-function marketing tool and instead leverage its data platform to drive outcomes across multiple business units. He discusses the evolution from traditional listings and reviews to a holistic, AI-powered approach that supports brand, demand generation, patient experience, and strategic growth initiatives. The talk emphasizes the role of Scout and MCP in transforming billions of data signals into actionable insights for diverse stakeholders. Key takeaways:Organizations are shifting from siloed marketing use cases (listings, reviews) to enterprise-wide applications of Yext data—supporting brand teams, demand generation, patient experience, and strategic planning.SCOUT provides visibility into how brands are represented across AI and traditional search, generating 2.3 billion annual signals—but the real value comes from making that data actionable via the MCP.Real-world example: A Fortune 5 healthcare system used SCOUT + MCP to identify that only 3.5% of negative patient feedback related to provider care—most issues stemmed from phone interactions and parking signage, prompting operational fixes.Demand generation optimization: By analyzing keyword performance and competitive spend in emerging markets, the client achieved $43 per conversion and generated 900 appointments in weeks.Competitive intelligence: Identifying which competitors are bidding in specific markets allowed content teams to create targeted content around those services and specialties.Healthgrades review syndication: By pushing first-party review data (scrubbed of PHI and profanity) to third-party platforms, providers went from 10 reviews to 50+ overnight, improving visibility on channels they don't fully control but can influence.Strategic planning use case: Overlaying census data and projected orthopedic/cardiology trends in Texas and Florida helped the acquisition team identify coverage gaps and decide whether to hire, acquire, or expand—demonstrating how Yext data can inform long-term business strategy. | Chapters: Introduction to Yext (0s), SCOUT Data Insights (116s), Data-Driven Insights (201s), Market Analysis Strategies (384s), Data-Driven Strategy Expansion (517s), Business Growth Strategy (699s) Video: A Love Letter to Marketers | Summary: In this video, we explore a marketer-first approach to AI and automation, challenging the industry narrative that agents should replace marketing teams. The speaker argues that AI should amplify marketers' judgment and strategic thinking—not eliminate it—enabling teams to scale their output 10x to 30x while maintaining competitive advantage in an evolving landscape.Key takeaways:Why AI agents are the next platform shift—similar to SEO, social media, and user-generated content in past decadesThe difference between automation and leverage: agents without judgment create "negative leverage"How every major platform shift (search, UGC, social) gave early adopters a temporary edge—until everyone caught upWhy judgment and context are the lasting competitive advantages when technology becomes commoditizedThe vision for AI-powered marketing: scaling human expertise, not replacing it | Chapters: Empowering Marketers (0s), Agents as Edge (65s) Video: Yext's Multiplayer Harness | Summary: In this video, Michael Walrath, CEO at Yext, explores how modern marketing systems must bridge the gap between global strategy and hyper-local execution — a challenge that grows exponentially with every new location, agency, or franchisee. The core message: great marketing has always been local, but until now, marketers lacked a unified system to see and act on that reality at scale. This is where Yext's innovation comes in, introducing a powerful "marketing harness" designed to make localized marketing scalable, reliable, and effective.The concept of a "harness" — borrowed from engineering and AI — refers to the structural framework that makes complex systems trustworthy and actionable. Yext has been building this harness for over a decade through tools like the knowledge graph, supervision, compliance frameworks, and brand facts. Now, these components are evolving into agentic applications that operate within a unified workspace, allowing marketing teams to manage listings, reputation, social media, and more from a single platform.Key takeaways:Why global strategy often breaks down at the local execution levelHow Yext's "marketing harness" unifies data, context, tools, and memory to enable scalable local marketingThe role of structured data, compliance, and human oversight in building trust with AI-powered agentsWhy a multiplayer harness matters: one system, one shared context, enabling the entire marketing team to collaborate effectivelyHow this approach provides operating leverage across search, maps, social, reviews, paid media, and web content | Chapters: Introduction to Yext (0s), Marketing Harness Evolution (45s) Video: Corvo: Agentic Marketing Tool for SMBs | Summary: This video introduces Corvo, an AI marketing agent designed specifically for small business owners—particularly solo operators like plumbers, contractors, and home service professionals. Christian Ward explains how Corvo meets these professionals where they already work: their smartphones. Instead of forcing users to log into yet another software platform, Corvo operates entirely through text messaging, making marketing accessible and frictionless for busy service providers.Key takeaways:Corvo targets ultra-small businesses (single-person operations) who rely on mobile devices for invoicing, scheduling, and marketingThe platform uses AI-powered local market research (via Scout) to analyze competition and provide hyper-local marketing recommendationsMarketing strategies are customized by geography—what works for a plumber in Roswell, Georgia differs completely from strategies needed in ManhattanUsers can manage their entire marketing strategy via SMS, eliminating the need to learn or log into traditional marketing softwareCorvo's core philosophy: marketing should understand your specific market first, not apply generic templates | Chapters: Welcome to Envision (0s), Contextual Search Ranking (63s), Perfectly Personal AI (129s), Finite vs Infinite Games (164s), Contextual AI Intelligence (203s), AI Context Levels (289s), AI Data Study (496s), Contextual AI Search (638s), Active Data Management (781s), Engagement and Usage (844s), Real-Time Data Strategy (938s) Video: Brand-level Scout Launch | Duration: 108s | Summary: In this video, Melissa Todisco, Sr. Director of Product Marketing, announces a major product update: the acquisition of Go Shine and the integration of brand-level visibility and GEO content optimization into Scout. The platform now enables businesses to manage both brand and location-level visibility, with a focus on competing effectively in Google AI overviews and search results. The demo highlights how QSR brands can identify gaps in their competitive positioning—such as losing in delivery and rewards categories—and use AI agents to close those gaps through targeted content creation.Key takeaways:Scout now supports brand-level visibility tracking, allowing you to compare performance against competitors on key topicsAI agents analyze the top 20 citation sources for specific queries to identify what content LLMs prioritizeThe platform generates content briefs and articles aligned with your marketing guidelines and GEO best practicesScout connects published content to visibility metrics, so you can measure which pieces are driving the best resultsAgents continuously rescan and adapt as LLM algorithms evolve, ensuring your content remains optimized | Chapters: Brand Visibility Announcement (0s), Agent Implementation & Tracking (66s) Video: Yext Acquires Flamel AI For Multi Location Brands | Summary: CEO Michael Walrath shares that Yext has signed a definitive agreement to acquire Flamel.ai, a platform specializing in localized paid campaigns for multi-location brands. Flamel enables brands with hundreds or thousands of locations to run automated, brand-compliant campaigns across Google, Meta, and ChatGPT, with centralized control and location-level reporting. The acquisition, expected to close in Q4, will integrate paid media capabilities into Scout's existing platform, creating a unified solution for both organic and paid visibility management.Key takeaways:Flamel.ai acquisition announced — closing expected in Q4Platform designed for multi-location brands to run localized paid campaigns at scaleSupports Google, Meta, and ChatGPT advertising channelsBrand teams set campaigns once; platform adapts them for each local marketIntegration will add paid media to Scout's existing channels: search, listings, reviews, web pages, email, and socialEnables brands to act on competitive insights and drive more foot traffic Video: How AI Predicts An Answer | Summary: In this video, Anthony Rinaldi, VP of Data Strategy, shares his initial experience of using ChatGPT and how it felt like magic—prompting many to assume it was all-knowing. However, they quickly realized that AI doesn't actually "know" answers; instead, it predicts them much like predictive text on a smartphone. Anthony illustrates this with the phrase "killing two birds with one stone," showing how the AI becomes more confident as it receives more context, but can still occasionally produce unexpected or incorrect completions.Key takeaways:ChatGPT and similar AI models predict responses rather than truly understanding or knowing informationAI prediction works similarly to predictive text on your phone—building confidence as more context is providedEven with high confidence levels (e.g., 98%), AI can still produce unexpected or incorrect outputsUnderstanding how AI generates responses helps set realistic expectations about its capabilities Video: The Way to Monitor and Act on Visibility Gaps at the Brand Level | Duration: 82s | Summary: In this video, Melissa Todisco, Sr. Director of Product Marketing, shares why traditional channel-focused marketing strategies fail in the age of AI search, highlighting critical differences between brand-level and local-level visibility tactics. Melissa reveals how location-based research challenges the assumption that Reddit dominates AI citations, showing that local searches prioritize websites, location pages, and listings instead. This insight underscores the need for a fundamentally different approach to visibility in AI-powered search environments.Key takeaways:Brand-level and local-level AI visibility require different monitoring and optimization strategiesLocation-based citation research contradicts the Reddit-dominance narrative for local searchesTop AI citation sources for local queries: websites, location pages, and business listingsTraditional channel-selection playbooks (like choosing between platforms) don't apply to AI searchAI search success depends on maintaining consistent, fresh information across an entire ecosystem of sourcesEvery AI model, location, and prompt can generate different answers from different source combinations | Chapters: Brand vs Local Visibility (0s), AI Search Ecosystem (45s) Video: AI's Shift from Search Volume to Contextual Knowledge Utilization | Summary: In this video, Christian Ward, Chief Data Officer at Yext, shares a shift in how we think about SEO and search behavior in the age of AI-powered discovery. Christian challenges the traditional reliance on search volume metrics, emphasizing that personalized, contextual AI interactions create infinite variations of user intent that can't be measured through conventional keyword research. Instead of focusing on search volume data, marketers must trust that their knowledge and content are being ingested and utilized by AI systems — even if traditional tracking methods fall short.Key takeaways:The traditional SEO approach of optimizing for search volume is becoming less relevant in an AI-driven discovery landscapeContextual variations in user experiences create infinite query possibilities that don't show up in volume metricsSuccess now depends on ensuring your content and expertise are accessible to AI systems, not just ranking for specific keywordsTracking AI-driven engagement requires new measurement frameworks beyond traditional search analytics. | Chapters: Welcome to Envision (0s), Contextual Search Ranking (63s), Perfectly Personal AI (129s), Finite vs Infinite Games (164s), Contextual AI Intelligence (203s), AI Context Levels (289s), AI Data Study (496s), Contextual AI Search (638s), Active Data Management (781s), Engagement and Usage (844s), Real-Time Data Strategy (938s) Video: How Yext Used GoShine to Gain GEO Traction | Summary: In this video, Melissa Todisco, Sr. Director of Product Marketing shares how Yext leveraged GoShine immediately after acquisition to rapidly improve their generative engine visibility. Melissa explains how Yext identified a competitive gap in the marketing category and closed it in just two weeks by publishing two targeted pieces of content. This example highlights the speed and agility of GEO (Generative Engine Optimization) compared to traditional SEO, where results typically take months to materialize.Key takeaways:Yext tested GoShine across multiple product categories post-acquisitionInitial analysis revealed they were trailing two competitors in marketing-related queriesPublishing just two pieces of content shifted their position to category leader within two weeksGEO delivers measurable results in weeks, not months like traditional SEOImmediate action in GEO can produce fast, tangible competitive advantages Video: How Often Do AI Models Agree on The Number One Recommendation? | Summary: In this video, Anthony Rinaldi, VP of Data Strategy shares inconsistencies in how four AI models respond to the same queries, revealing surprising patterns in model agreement and behavior. Through data-driven analysis, he uncovered that these models rarely align perfectly—and even more surprisingly, they often fail to deliver on explicit instructions like returning exactly 10 results when asked for a top-10 list.Key takeaways:The four AI models agreed perfectly only 14% of the timeNearly 50% of the time, all four models provided completely different answers to identical questionsWhen asked for "top 10" lists, models returned an average of only 7 items—despite abundant available dataThis suggests models may struggle with instruction-following and consistency, even on straightforward tasksThe findings raise important questions about AI reliability and decision-making in production environments Video: Real-Time Data: The Essential Fuel for AI Success | Duration: 15s | Summary: In this video, Christian Ward, Chief Data Officer at Yext, shares a critical shift in data strategy for AI applications: real-time data is no longer optional—it's essential. The era of tolerating stale or delayed data has ended, as AI systems require instantaneous access to current information to deliver accurate and effective results.Key takeaways:The acceptance of stale or slightly delayed data is obsolete in modern AI applicationsReal-time data access is now a fundamental requirement for AI systems to function effectivelyOrganizations must prioritize immediate data availability over legacy approaches that tolerate latencyThe competitive advantage now lies in systems that deliver instantaneous data to AI models | Chapters: Welcome to Envision (0s), Contextual Search Ranking (63s), Perfectly Personal AI (129s), Finite vs Infinite Games (164s), Contextual AI Intelligence (203s), AI Context Levels (289s), AI Data Study (496s), Contextual AI Search (638s), Active Data Management (781s), Engagement and Usage (844s), Real-Time Data Strategy (938s) Video: Using One Marketing Strategy to Unite Thousands of Independent Franchisees | Duration: 1475s | Summary: Getting found is only half the battle for multi-location brands. Customers are discovering businesses through countless platforms, including the traditional ones like Google and Apple Maps, but add in AI assistants and agents, and the discovery points are endless. But what happens when the information they find is outdated, inconsistent, or simply wrong? And how do you get thousands of local franchisees working toward the same goal?In this episode of The Intelligence Brief, Chris Brownlee (SVP of Product, Yext) sits down with Lisa Hake (Chief Marketing Officer, Winmark) to discuss what it takes to modernize marketing across 1,750 independently-owned franchise locations.Lisa shares how Winmark, the parent company of Plato's Closet®, Play It Again Sports®, Once Upon a Child®, and more, is tackling these challenges head-on. From discovering that roughly 80% of its Apple Maps locations had never been claimed to using competitive visibility data to motivate franchisees, she explains how Winmark is bringing consistency to its franchise brands' digital presence without losing what makes each local business unique.This episode breaks down:How national brands can align marketing priorities across thousands of locationsWhy inaccurate business information can cost brands thousands of potential customersHow Winmark has brought together business listings, local pages, and reviews to help customers find accurate information everywhere they searchWhy showing local business owners how their visibility compares to competitors is more effective than just asking them to update their listingsHow automating repetitive tasks can help marketers on small teams focus on more impactful workIf you're a marketing leader managing multiple brands, locations, or franchisees, this episode offers a practical look at how to turn fragmented information into a more consistent customer experience — and make it easier for local teams to act on the insights that matter. Video: How Community Fibre Wins Local Search in the Age of AI | Duration: 1284s | Summary: People don't choose a broadband provider on price alone. They search for the fastest network in their neighborhood, read what customers say about the service, and, increasingly, turn to AI to decide which brand they can trust.For Community Fibre, a London broadband provider with more than 450,000 customers, that shift is already showing up in the numbers. About half of its sales now come from digital channels, and a 4.7 Trustpilot score helps it stand out in a market where customer experience is often a pain point.But Chris Williams and his team found that being visible takes more than a strong rating. By pairing local landing pages, personalization, reviews, and help and support content, Community Fibre turned neighborhood-level searches into a growth engine.In this episode of The Intelligence Brief, Chris Brownlee (SVP of Product, Yext) sits down with Chris Williams (CIO, Community Fiber) live from Envision in New York to discuss how the company is adapting to the way customers find and evaluate brands.During their conversation, Chris shares how Community Fibre has optimized for AI search since the early days of its Yext partnership, why helpful content is often a prospect's first touchpoint with the brand, and how his team is applying AI across the business — from procurement to customer service. This episode breaks down:How customers are shifting from traditional search to AI search to find and vet local providersWhy reviews are becoming a core part of how AI engines evaluate and surface a brandHow local landing pages and personalization help a London-based brand compete with national players, borough by boroughWhy help and support content doubles as a brand awareness channelHow Community Fiber is using AI to work more efficiently, and what its leadership expects the next 12 months to look likeIf you're a marketing or digital leader managing a multi-location business, or competing for customers in a crowded local market, this episode offers a real-world look at how reviews, local content, and AI-ready experiences work together to drive visibility and growth. | Chapters: Introduction to Community Fiber (0s), Customer Discovery Shifts (127s), AI-Powered Search (252s), Content Discovery Strategy (433s), AI Implementation Strategy (613s), Envision Event Takeaways (859s), Rapid Development Pace (1010s), Future Outlook (1090s), Closing Remarks (1247s) Video: Build a Page for It: QSR and Intent Pages | Duration: 365s | Summary: In this video, Zach Herriott demonstrates how QSR brands can win high-intent, hyperlocal search moments using Scout analytics and intent-specific landing pages. He reveals that traditional metrics hide critical market-by-market performance gaps, while AI-powered search now returns single answers that either recommend your location or direct customers to competitors—making structured data and targeted pages more crucial than ever. Key Takeaways:National performance metrics often mask local visibility problems—individual locations may be losing to nearby competitors on critical searches like "lunch specials near me"Location pages with structured data are 2.9× more likely to be cited by AI than profiles without themIntent-specific pages receive 70% more traffic from targeted queries compared to generic local pagesScout provides market-by-market visibility into exact queries, competitors, and AI recommendation patternsThe Yext MCP server enables custom dashboards combining national performance, AI visibility, and regional comparisons in one viewIntent pages target unbranded, high-intent searches—capturing new customers who haven't decided on a brand yet | Chapters: Intent Pages Introduction (0s), Scout Map Overview (76s), AI Answer Dominance (123s), Implementation & Tracking (199s) Video: One Provider, Three Truths: Healthcare (and Anyone with Reviews and Surveys) | Duration: 273s | Summary: In this video, Reya Arora, a solutions engineer at Yext, examines the critical disconnect in healthcare reputation management — where marketing teams, patient experience teams, and AI-generated outputs each tell a different story about the same provider or location. She demonstrates how fragmented data sources create blind spots and explains how Yext unifies reviews, survey data, and AI/LLM insights into a single operational view for smarter decision-making. Key Takeaways:Healthcare marketing teams rely on public star ratings, while patient experience teams focus on private survey feedback — creating siloed insightsAI and LLMs often generate incomplete or incorrect provider information by pulling from inconsistent third-party sourcesYext integrates first-party reviews, third-party platforms, and survey tools (like Press Ganey, Qualtrics, NRC) to surface the full patient sentiment pictureScout technology validates AI-generated content by running direct queries across the patient journey phasesThe unified action center prioritizes the right interventions — e.g., fixing scheduling issues instead of launching reputation campaigns when survey data reveals operational gaps | Chapters: Healthcare Reviews Disparity (0s), AI Data Accuracy (57s), Unified Data View (109s) Video: The Art of the Possible | 3 Brands Asked 3 Different Questions | Duration: 1231s | Summary: In this video, Javier Fabrega, VP of Data Strategy at Yext, demonstrates how structured data from the Yext platform can be combined with third-party datasets—such as census records, international student populations, USDA spending data, and physician revenue benchmarks—to unlock powerful market intelligence. Through three real-world case studies spanning grocery retail, healthcare, and logistics, he illustrates how businesses can identify where to expand, quantify visibility gaps, and maximize ROI by structuring data for AI-driven discovery. Key takeaways:Grocery Retail: By analyzing Texas census data, household spending (USDA), and location performance, Fabrega identifies high-demand counties like Dallas and Harris, revealing potential revenue opportunities of $140M–$420M through strategic store expansion.Healthcare System: A Nevada health system with 344 entities and a 42% win rate can bridge visibility gaps in AI-powered search. By fixing listing issues and leveraging population growth projections (Clark County growing to 2.4M by 2030), the system could capture $7.9M–$32M in additional revenue.Logistics Network: With 50.3M foreign-born residents and 61,000+ international students in Florida, intent-driven pages (e.g., shipping golf clubs, surfboards, or luggage) can meet high-intent queries and improve LLM citations, compounding structured data for better discoverability.The Compounding Data Effect: Core listings (name, address, phone) are table stakes. Intent pages around specific services and products—structured and nested under location pages—are what drive citations in large language models (LLMs).Actionable Questions: Where would a scored map change your next decision? What visibility gap can you quantify in dollars? Which customer questions have no landing page today? | Chapters: Introduction and Overview (0s), Data Integration Sources (45s), Growth Strategy Analysis (133s), ICP Fit Models (167s), New Chapter (184s), Market Analysis (254s), Geographic Growth Patterns (307s), Revenue Projection Models (348s), Healthcare Case Study (474s), AI Data Optimization (514s), Data Optimization Strategy (592s), Revenue Growth Projections (624s), Compounding Structured Data (819s), Closing Remarks (1123s) Video: Defend Your Territory: Retail and Franchise | Duration: 763s | Summary: In this video, Kait Thompson demonstrates how distributed retail networks can leverage Scout to uncover AI visibility performance at the local level—and how integrating third-party data via the MCP transforms marketing strategy. Using a real-world example of an 80-year-old retail brand with nationwide locations, she explains how Scout helped identify why traditional SEO tactics failed in rural markets—and what they did instead.Key Takeaways:Scout revealed a 78% overall win rate but significantly lower AI visibility in rural locations—despite strong Google performance (93% win rate)Local-level insights showed competitor sets and customer behaviors vary dramatically by region, invalidating one-size-fits-all marketing campaignsLayering US Census data (e.g., households online, median age) via MCP exposed why review-generation and social campaigns weren't working in Amish and rural marketsThe brand shifted to offline marketing—country fairs, door-to-door, pamphlets—and empowered franchisees with Scout dashboards to "defend their territory"Results: A hyperlocal marketing model that adapts to market-specific customer behaviors rather than relying on national-level assumptions | Chapters: Scout Introduction (0s), Local Competitive Analysis (97s), Local Market Adaptation (169s), Data Integration Strategy (253s), Rural AI Gap (330s), Small Town Markets (406s), Owner-Level Activation (519s), Location-Level Campaign Insights (634s) Video: Find the Formula: Financial Services | Duration: 461s | Summary: In this video, Caroline Bello shares how financial services marketing teams can streamline operations across thousands of locations and professionals while maintaining compliance and driving measurable success. The presentation focuses on unified digital presence management, AI visibility optimization, and compliant engagement strategies — essential for advisors, agents, and branch managers navigating today's AI-driven customer journey.Key Takeaways:Unified knowledge graph architecture enables "update once, update everywhere" for branch, ATM, and professional data across AI platforms and search enginesScout platform provides AI visibility metrics including win rate analysis — measuring how often your brand ranks above competitors in AI-powered search resultsTalk to Scout feature allows natural language queries for program performance (e.g., "How are our Houston branches performing?" or "Who are top competitors in Atlanta?")Compliant agent workflows ensure all marketing automation adheres to regulatory guidelines with approval-based executionGamified scorecards for individual advisors show personalized performance metrics, review sentiment, and local competitive positioningEnd-to-end attribution tracking across the AI search funnel — from consideration to conversion — with brand query monitoring capabilities | Chapters: Marketing Challenges (0s), Yext Unified Ecosystem (81s), Scout Platform Overview (156s), Talk to Scout (237s), Data-Driven Optimization (287s), Field User Experience (361s), Wrap-Up and Summary (435s) Video: Reviews as an Operational Signal: Retail and Real Estate | Duration: 582s | Summary: In this video, Nina Sunderland demonstrates how retail and multi-location businesses can operationalize reputation intelligence to improve their digital presence and AI search visibility. She walks through how reviews, response rates, and sentiment themes directly influence rankings in Google and generative AI assistants—and shows how fragmented feedback across platforms can be managed at scale using Yext's MCP and AI-powered Action Center.Key TakeawaysReviews now serve as ranking signals in both Google and AI search engines, influencing whether your location gets recommendedNegative sentiment themes buried in reviews can prevent properties from appearing in AI-generated recommendations—even if overall star ratings are strongYext's MCP integration with Claude allows marketers to build live dashboards that surface review themes, AI visibility metrics, and operational issues across all publishers in one viewThe Yext Action Center uses AI agents to prioritize high-impact tasks like responding to reviews or amplifying five-star feedback on social—helping teams close the loop between engagement and visibilityFuture enhancements will expand orchestration across reviews, social, email, and SMS for unified, multi-channel reputation management | Chapters: Introduction to Reputation Intelligence (0s), AI Search Results (71s), AI Visibility Challenges (164s), Dashboard Overview (230s), Dashboard Deep Dive (316s), Action Center (417s), Future Vision (540s) Video: Yext Envision 2026 | Duration: 60s | Summary: <p>Check out everything that happened at Envision in New York!</p> Video: Cut the BS with Yext | Duration: 91s | Summary: Outdated business hours. Expired promotions. Incorrect amenities. Bad information can lead to frustrated customers, lost opportunities, and damage to your brand's reputation. AI isn't necessarily trying to mislead your customers. When your brand data is incomplete, outdated, or inconsistent, AI can surface inaccurate information from old websites, business listings, and forgotten directories. That's BS. Bad Signals. Yext helps brands cut the BS by managing and distributing accurate, verified business information across the digital ecosystem, so customers and AI search platforms can find more reliable answers. Stop letting outdated data speak for your brand. | Chapters: Cutting the BS (0s) Video: How Organic Krush Uses Yext Scout to Turn AI Insights Into Action | Duration: 239s | Summary: What if AI could do more than tell you how your brand is performing? What if it could help you figure out what to do next — and get it done? Meet Organic Krush, a multi-location business on Long Island using Yext Scout to turn AI-powered insights into real marketing action. With Scout, Organic Krush can identify opportunities to attract more customers, build location-specific marketing plans, coordinate work across teams, and measure what's actually driving results. From launching local pages that connect customers directly to online ordering to publishing social content and improving AI search visibility, Scout helps turn marketing goals into coordinated action. See how Yext Scout helps businesses:Identify local search trends and opportunities across locationsBuild marketing plans tailored to each neighborhoodCoordinate AI agents and human teams to execute marketing tasksImprove visibility across AI search and traditional searchLaunch local pages and distribute content across digital channelsTrack location-level performance and connect marketing activity to results In just three weeks, Organic Krush began seeing growth and gained a clearer picture of how its marketing efforts were contributing to business outcomes. The future of marketing isn't just about insights. It's about action. | Chapters: Meet Michelles Business (0s), Scouts Planning Process (43s), Scouts Adaptive Planning (86s), Results and Growth (134s), Results and Growth (163s) Video: The Future of Agentic Marketing | Yext Envision | Duration: 116s | Summary: The future of marketing isn't just AI-powered. It's agentic. For more than 20 years, Yext has helped brands deliver accurate information wherever customers search. Now, as AI transforms how people discover brands, make decisions, and take action, the next era of marketing is here. Welcome to Yext Envision, where we're exploring the future of agentic marketing.Imagine a world where:AI doesn't just answer customer questions — it takes action with the right guardrails.Brand data doesn't become outdated — it's continuously enriched to power smarter experiences.Insights don't sit in dashboards — they inform decisions and drive meaningful action.Marketers don't work alone — human teams and AI agents collaborate to accomplish more with less effort. From AI search visibility to intelligent marketing automation, Yext is helping brands prepare for a future where accurate data, actionable intelligence, and agentic AI come together. The future of marketing is agentic. Let's Envision what's next. | Chapters: Yexts Journey (0s), Agentic Marketing Vision (58s)