Knowledge Center

Direct Answers

What are direct answers, and why are they significant in the AI search landscape?

TL, DR: As search shifts to AI-driven experiences, customers now see (or hear) direct answers to their questions and prompts. Instead of seeing a list of web links (bye-bye 10 blue links), customers now encounter conversational, direct answers. The impact? Branded and unbranded search visibility are changing the shape of the customer journey. To stay visible and competitive, marketers have to develop new strategies that treat AI as a customer, too.

What is a direct answer?

A direct answer is a quick, clear, and straightforward response to a question customers pose in a traditional or AI search.

Direct answers can provide specific information, likeNAP data. More commonly now, they also answer conversational questions, including questions from voice search. Direct answers should not be confused with other types of generative AI answers. Direct answers are not robust, conversational research results or interactions withAI agents.

Instead, direct answers are concise. They appear frequently in Google AI Overviews (AIOs) and other AI search results. Direct answers may also appear in a box below AIOs. Customers can also spot direct answers within direct answers when AIOs highlight information to draw extra attention to it.

Here are three examples of direct answers and the queries that might prompt them:

Query: "Brooklyn Public Library Sunday hours"

Direct answer: "Most Brooklyn Public Library branches are open on Sundays from 1:00 PM to 5:00 PM, according to the Brooklyn Public Library. The Central Library and the Park Slope branches are also open on Sundays, but the Central Library has different hours (1:00 PM - 5:00 PM) than the Park Slope branch (10:00 AM - 5:00 PM), according to the Brooklyn Public Library."

Query: "Beach closures in Orange County"

Direct answer: "In Orange County, California, ocean and bay waters are closed when an immediate health hazard is identified, such as a sewage spill Currently, there is a closure in effect for a stretch of coastline in Huntington Beach and Newport Beach due to a 4,000-gallon sewage spill. The affected area spans from the Talbert Channel outfall at Huntington State Beach to the projection of Grant Street in Newport Beach, according to the OC Health Care Agency."

Query: "Movies opening this weekend at mall of america"

Direct answer: "This Friday, June 20, 2025, at the Mall of America's B&B Theatres Bloomington 13, several new movies are opening, including "How to Train Your Dragon", "Lilo & Stitch", "Ballerina", "Karate Kid: Legends", "Final Destination: Bloodlines", "DAN DA DAN: Evil Eye", "Mission: Impossible - The Final Reckoning", and "Thunderbolts."

Direct answers replace SEO keyword matching and guide intent-driven discovery

In this new era of search, direct answers replace keyword matching and Google's 10 blue links. Customers expect instant, authoritative answers everywhere they search, every time they search. This shift in technology and consumer culture means that brands have to adapt, too. For marketers, SEO used to mean search engine optimization. Now, it means search everywhere optimization. So, how do you create content to make sure you're seen in direct answers, no matter where customers are searching? It's all about publishing your content with structured data using schema markup in knowledge graphs.

How to show up in direct answers in search

AI-driven search experiences (like AI Overviews, Gemini, ChatGPT, and other AI models) aren't just crawling indexed web pages. Instead, AI search often pulls from a wide range of sources and delivers quick, informed, and conversational answers to questions (and customers trust what AI search shares).

For brands, this means two things:

#1 – If your data isn't structured and accessible in a knowledge graph, AI search might not find you. With AI-driven search use growing fast, that's a problem. A knowledge graph makes sure your machines can read, understand, and contextualize your brand's information, such as store hours, services, product details, and FAQs. Without a knowledge graph, brands won't show up in AI and voice search when customers need answers. The stakes are even higher when you compete with other big brands in the same local market.

#2 - Brands need to extend and diversify their digital presence well beyond a static Google Business Profile and basic listings. As AI search continues to evolve, customers will expect more from direct answers in local search. To stay relevant and competitive, brands need to optimize their listings to make sure they're accurate and robust. Listings management is key. So are local social media management and review management.

How AI search engines generate direct answers

There are three foundational factors impacting how AI search engines generate direct answers: structured and unstructured data inputs, RAG quality, and FAQ strategy.

Structured and unstructured data inform semantic search and NLP, so direct answers are accurate and relevant

Semantic search is a search technology that understands the words of a query in context and produces results that are relevant to that context. Semantic search is possible thanks to natural language processing (NLP) and knowledge graphs filled with structured data.

Structured data helps AI root out the facts to share in a direct answer. It's structured because brands create behind-the-scenes entities, schema markup, and other types of tags to codify their information.

Meanwhile, natural language processing helps AI grasp the context and relevance of information shared in unstructured data. This includes blog posts, social posts, reviews, and FAQs.

NLP helps AI understand the intent behind the brand information and the intent behind customer questions. technologies work together, super fast, to deliver direct answers to customers.

RAG relies on a knowledge graph to communicate direct answers that are authoritative, specific, and accurate

RAG, or retrieval-augmented generation, is a type of generative AI. It relies on accurate, meaningful data sources to communicate direct answers. So, RAG — and your brand's direct answers — can only be as good as the data that informs them.

Retrieval-Augmented Generation (RAG). This groundbreaking AI technology relies on pulling data from reliable sources to generate accurate and meaningful responses. But here's the catch: RAG can only be as good as the data it retrieves. That's why a well-organized, comprehensive knowledge graph is the backbone of effective RAG. Without it, even the smartest AI systems can struggle to retrieve the right information and deliver precise answers.

FAQs impact search visibility and deliver AI-generated answers based on intent

FAQs are dedicated sections or pages in a brand's website that give customers clear, simple answers to their most frequently asked questions. The best FAQ pages succinctly answer the most important questions from customers and share the most important information first. Whether a customer is looking for parking instructions, the seasonal menu, or how to prep for an upcoming appointment, FAQ pages house easy-to-digest answers in one central place.

Brands with high-performing FAQ pages also perform well in AI search since the unstructured data in FAQs speaks to both AI's technical needs and customer intent. To increase relevance and prominence in direct answers, brands should regularly update FAQs. FAQs should also be both short and specific. They can also be effective if they're written so they speak to long-tail questions in a conversational way that mirrors how customers actually search. It helps to supplement the most common questions with the latest questions, too. Brands must also write FAQs based on competitive gaps and emerging opportunities they see through competitive benchmarking.

Takeaways

Brands can't compete if their information doesn't show up in direct answers. And they can't show up if they don't operate with a knowledge graph filled with clean, up-to-date, structured, and connected data. It's key to staying visible and discoverable in this era of AI search.

Yext prepares brands to win in AI search. With scalable data infrastructure, content strategy support, and direct integrations, brands can align data strategy with content strategy with AI strategy.

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