Yext's Agentic Marketing Capabilities

TL;DR: Yext is an enterprise agentic marketing platform that helps brands improve visibility across AI and traditional search. Scout identifies where your brand is losing visibility, the Knowledge Graph provides the verified data AI systems trust, and Action Center is where AI agents execute across listings, reviews, and social.

Most marketing software still stops at advice. It watches your data, ranks what's wrong, and hands the list back to you. You still have to open each tool and make the change yourself. Agentic marketing is the shift from that model to one where the software does the work, within limits you set.

"Agentic" only matters if it helps brands get work done, and that requires more than AI. It requires competitive intelligence to guide decisions, verified data to power every action, and AI agents that can execute across listings, reviews, and social, all with human oversight.

Does Yext have agentic marketing capabilities?

Yes. Yext is an enterprise agentic marketing platform for multi-location businesses that is powered by three tools working together. Scout provides the competitive intelligence, Knowledge Graph holds the verified source of truth, and Action Center enables a team of agents and humans to create and distribute brand content across every surface that matters.

What separates Yext from reporting tools is action. A dashboard shows you what happened. An agent does something about it. Yext's agents can update an incorrect listing, respond to a customer review, and fix a brand visibility gap in AI search before you realize there's a problem.

What is agentic marketing, and why does it depend on verified data?

Agentic marketing is the practice of using AI agents to carry out marketing work toward a goal, not just generate suggestions.

The difference between an AI assistant and an agent is the difference between a copilot and an autopilot. A copilot sits beside you and helps when asked. An autopilot knows the goal and flies the route, checking in at the points that matter. Generative AI is a copilot: prompt it, and it writes a draft, then waits. An agent is an autopilot: give it an outcome, such as "keep our hours accurate across every location," and it works toward that outcome, using the tools it needs along the way.

That autonomy is exactly why the data an agent relies on matters more than the agent itself. An agent acting on stale or conflicting information doesn't fail quietly. It executes the mistake confidently across every location, which is worse than not acting at all. If one source says you open at 9 and another says 10, an agent working from that conflict will publish the wrong hours everywhere. Trusted agentic marketing depends on a foundation of verified facts and clear human governance.

What can AI agents automate for multi-location brands?

A brand with hundreds or even thousands of locations, with dozens of signals to manage for each, throughout all 52 weeks of the year, faces several hundred thousand manual actions annually just to keep location data current.

A review sits unanswered for two weeks, a photo goes stale, a location stops posting on social media, hours change and nobody updates them. These are all distinct tasks that directly impact whether your brand and locations get discovered at all.

No marketing team is able to get this done by hand. And the proof is already here: more than a million agentic actions have already been completed by Yext's agents, returning over 11,000 hours of manual work to multi-location marketing teams.

The three layers of Yext's agentic platform: intelligence, verified data, execution

Agentic marketing only works when intelligence, trusted data, and execution are connected. Yext brings all three together in a single platform:

• Intelligence: Scout analyzes where you're winning and losing across AI and traditional search, down to the individual location.
• Verified data: the Knowledge Graph is the structured, verified source of truth that agents read from and AI systems cite.
• Execution: content generation and distribution agents create and syndicate brand content across listings, reviews, social, and pages using that verified data.

Together, these capabilities create a closed loop. Scout identifies what needs attention, the Knowledge Graph provides trusted data, and AI agents take action from the Action Center. Instead of surfacing problems for marketers to solve manually, Yext helps brands identify, prioritize, and act from the same verified source of truth.

A deeper look into how that loop works: It starts with a signal - a Scout competitive scan, a check inside Listings or Reviews, or a real-world change like a new review landing. That signal becomes a recommended action, usually with a written explanation of what will happen and why. You approve, edit or reject it, and the agents themselves are configurable, so they take on the jobs you actually want done. As trust builds, more of the work completes on its own and Action Center becomes the place you review rather than the place you work.

How Scout gives agents competitive intelligence to increase AI search visibility

An agent is only as good as the intelligence it relies on. Point an agent towards a vague goal, and it produces confident, generic work. Give it depth, breadth, and competitive context, and it produces action you can defend to your CMO.

Scout is the intelligence layer. It analyzes 10 billion signals across four AI models (ChatGPT, Gemini, Perplexity, and Claude) for more than 12 million business locations, surfacing 150 visibility metrics and benchmarks against 19 competitors per location. That depth is what turns "improve our brand visibility" into a specific, sourced instruction an agent can carry out.

Two Scout metrics anchor the scoreboard:

• Win rate: how often your brand beats local competitors across the searches Scout tracks, trended over time and measured against a benchmark.
• AI Visibility Score: how often your brand appears in AI answers, measured across AI search specifically rather than traditional rankings.

Because Scout reports at the location level instead of nationally, it delivers the nuance a brand-level dashboard hides: the company looks healthy overall while individual locations quietly lose visibility to a local competitor. That is the signal an agent needs to act precisely.

How the Knowledge Graph gives agents a verified source of truth

Intelligence says what to do. The verified source of truth is what the agent acts on when it does it.

The Yext Knowledge Graph is that layer: structured, schema-mapped brand data kept current for every location. Data agents in the Knowledge Graph connect information across sources, verify it at scale, and resolve conflicts before they reach a customer. The result is a single record of verified facts (hours, addresses, services, attributes) that both your agents and external AI systems can trust.

Those verified facts don't sit in a database. They push through Yext's Publisher Network, a set of direct integrations to more than 200 endpoints, including Google, Apple Maps, Yelp, and the large language models behind AI search, with no aggregator in between. What your agent publishes is what AI actually sees and cites. That direct distribution is why the Knowledge Graph is more than a data store: it's the citation layer for how your brand shows up in AI search.

What kinds of marketing agents does Yext have available right now?

Yext runs several kinds of marketing agents: data agents that maintain the verified source of truth, content generation agents that create on-brand content, and distribution agents that syndicate it. All agents work the same way across every channel, always from the verified data in the Knowledge Graph.

• Listings agents keep every location accurate across the Publisher Network, updating a changed phone number or set of hours everywhere at once and suppressing duplicates, so listings management stops being a manual, location-by-location chore. The Listings agent also corrects addresses, fills missing hours and categories, and resizes photos to each publisher's spec.
• Knowledge Graph agents work alongside them, keeping each profile complete without a manual audit. It enriches photos, hours, categories, attributes, and descriptions, and refreshes a stale gallery when a location carries fewer images than nearby competitors.
• Review agents draft and post responses at scale and read sentiment across locations, turning review management into a workflow a person governs rather than types out by hand.
• Social agents produce and schedule localized social content for each location, so a brand can run local social media management across hundreds of profiles while a person holds the brand standards.

The Action Center is where these agents connect insight to execution. It's the layer where a diagnosed problem becomes a completed fix rather than one more item on a to-do list. An agent that only recommends leaves the work with you, but Yext's agents close the loop.

Yext Agent	Action Center capabilities
Listings	Rewrite descriptions to publisher spec, fill missing categories and hours from comparable locations, correct addresses, strip characters that break sync, resize images to spec, and flag broken publisher connections
Reviews	Draft responses matched to sentiment and brand voice; trigger review invitations when velocity, volume, or sentiment trails the local competitive set
Social	Create Google posts when a location goes quiet or falls behind competitors, localize brand posts per location, turn 5-star reviews into posts, and draft replies to comments
Knowledge Graph	Fill missing hours, descriptions, phone numbers, and attributes through enrichment with approval; add missing cover and profile photos; refresh stale galleries and close photo or video gaps against nearby competitors

How teams work with Yext's agents: inside Yext, through MCP, or on the APIs

Agentic marketing doesn't look the same for every enterprise, so Yext offers three ways to engage.

• Work inside Yext: Use the ready-built agents in the platform to run listings, reviews, social, and visibility work directly.
• Bring Yext into your AI: Connect Scout's intelligence and the Knowledge Graph to your own models through the Model Context Protocol (MCP), so your AI stack reasons over Yext's verified data. What Yext MCP gives marketers is a dashboard-free way to ask and act.
• Build on Yext: Use the APIs to integrate Yext data and agentic distribution into your own products and workflows.

The through-line is that all agents run on the same verified source of truth. Whether an agent lives inside Yext or inside your own LLM, it acts on the same trusted data. That's exactly why AI agents don't work without competitive intelligence and a verified foundation.

Who stays in control when agents do the work?

Autonomy does not mean no one is watching. Trusted agentic marketing gives brands control over which tasks an agent can act on alone, which loop in a human, and which route to full review. Those permissions can change over time.

In practice, human governance means guardrails are built into the source of truth rather than bolted on at the end. Think of it as a kill switch that stops an agent, approval logic that routes sensitive changes to a person and limits on what an agent can do on its own. Because the agent only acts on verified facts, it can't post an address that's out of date or an offer that's expired. For regulated industries such as financial services and healthcare, wrong data at scale is a legal exposure, so this governance is the entry ticket, not a nice-to-have.

The marketer's role shifts with it. The job moves from doing the tasks to governing the goals: setting outcomes, drawing the guardrails, and stepping in on genuinely new decisions. Managing the system beats managing every task by hand.

Governing well also means knowing what not to hand over. Marketers hold the decisions and agents hold the execution. Some examples of decisions that always stay on the human side of the line:

• Strategy and prioritization: an agent can tell you that forty locations are behind on review volume, and it can complete the work for all forty. What it can't tell you is that twelve of them sit in a market you're exiting this year. Which locations deserve investment, and in what order, is a business decision that sits above the agentic action queue.
• Crisis response: a review left during a genuine incident reads to an agent like any other negative review, and a fast, on-brand reply is exactly the wrong move. Sentiment is not context. When a response carries legal or regulatory exposure, or when the right answer is to say nothing yet, that call belongs to someone who knows what actually happened.
• Any claim not yet in the verified record: because every agent works from the Knowledge Graph, none of them will invent a price, a new service, or a product detail that isn't there.
• Brand building: agents can apply a brand standard, not set one. Localizing an approved post, matching an established voice, keeping a description on-message: these are all applications. Deciding what your brand should say about itself, or how a new campaign should be framed, always lives with the marketers.

How to measure agentic marketing success: Win Rate and AI visibility

Traditional marketing metrics were built for a world of clicks and rankings. Agentic marketing needs a scoreboard built for AI search, where the question is whether your brand shows up in the answer at all.

Two Scout metrics lead. Win Rate measures how often you beat local competitors across tracked searches, and it's the headline number, trended over time, and benchmarked. New Yext Research across 600,000+ physical locations for 500+ brands found that locations in the top competitive Win Rate decile drive roughly 3x the customer actions of those in the bottom decile. That is what makes Win Rate the best number to chase: it moves with the customer actions you are actually trying to produce.

Finally, AI Visibility Score measures how often your brand appears in AI answers across ChatGPT, Gemini, Perplexity, and Claude.

Together, they replace the old habit of reporting raw rankings as a read on presence and competitiveness in AI search. An agent watching those two metrics by location can act the moment either one slips, closing the gap between measurement and fix.

Ready to see Yext's AI agents in action? Book a demo to learn how Yext's Knowledge Graph, Scout, and Action Center work together to help your brand improve visibility across AI and traditional search.

Frequently asked questions

Do I need to pay extra to use Yext's AI agents?

No. Agents come with the Yext products you already own, so a Reviews customer gets review agents and a Listings customer gets listings agents, at no additional cost. Scout adds the competitive layer on top, telling you which competitor you are behind and why a given action matters. Free Scout shows limited competitive context, and paid Scout shows the full picture.

Do I have to configure the agents before they start working?

No. Every agent runs out of the box with a default prompt, and the core behavior is locked, so there is nothing you can break by leaving it alone. Customization is worth it for the Social agent, where a few brand-voice instructions make posts and replies sound like your locations rather than a template.

Can I turn off an individual Yext agent?

Yes. Each action type can be toggled off on its own, so you can run review responses agentically while keeping listings changes manual, or the reverse. If you would rather not use agents at all yet, the whole feature can be switched off for your account and turned back on when you are ready.

How do I see what the agents have actually done?

Every completed action is logged. Action Center reports actions completed and total time saved, and each agent carries its own performance view covering time saved, accuracy, and reliability. That log is what makes the work auditable, which matters when someone asks what changed across a thousand locations last quarter.

How do Yext's agents work for regulated industries like financial services and healthcare?

Compliance is built into the workflow rather than added at the end. Review responses can run through attestation, supervision, and disclosure steps with a full audit trail, so a response is defensible as well as fast. Agents in these industries are enabled deliberately rather than by default, so your team decides when to switch them on.