The Gist
- AI in VSO. AI is central to transforming SEO for voice search, interpreting conversational queries and user intent.
- Content optimization. Businesses must tailor content to be conversational and answer questions directly to rank well in voice searches.
- Technical SEO. Speed, mobile-friendliness and structured data are crucial for optimizing websites for voice search queries.
As voice search continues to grow in popularity, driven by the rise of AI-powered assistants such as Siri, Alexa and Google Assistant, along with the prevalence of voice search on smartphones, the practice of search engine optimization (SEO) is rapidly evolving.
Voice search optimization (VSO) is now a critical part of the new SEO strategy, and AI is at the heart of this transformation. By understanding how AI helps interpret user intent and deliver more conversational search results, marketers can better optimize their content for voice searches and remain competitive in this ever-changing digital environment.
This article explores the role of AI in transforming voice search, its impact on SEO strategies and essential best practices for optimizing content for voice search.
Introduction to Voice Search
The rise of voice search has fundamentally transformed how users interact with search engines, sparking a shift in SEO strategies. With more consumers relying on voice-activated assistants like Alexa, Google Assistant and Siri, and more importantly, voice search on smartphones, the volume of voice-based queries has surged. This growth is driven by the convenience of speaking rather than typing, especially as people increasingly use mobile devices and smart speakers to search for information hands-free.
The growing adoption of these devices has had a profound impact on how consumers search for information.
According to data from Google, 20% of searches in the Google App are done via voice. Additionally, as of 2022, there were around 142 million users of voice assistants in the United States, a number that is forecast to increase to 157.1 million users by 2026. Voice-enabled smart speakers and virtual assistants are reshaping search behavior by encouraging users to make more natural, conversational queries.
AI is playing a pivotal role in shaping the future of SEO in this voice-first environment. Advanced algorithms such as Google’s BERT and its successor MUM analyze the context of voice queries to deliver more accurate and conversational results. AI helps search engines understand the nuances of natural language, enabling them to process voice searches with greater precision and relevance.
As a result, SEO strategies are evolving to accommodate this new search behavior, requiring businesses to optimize their content for more conversational, long-tail keywords that match how people speak rather than how they type. This shift marks a new era in digital marketing, where AI and voice search converge to redefine the practices of SEO.
AI’s Role in Understanding User Intent
AI plays a crucial role in interpreting user intent, especially as search queries become more conversational with the rise of voice search. Traditional search engines were designed to handle short, keyword-based queries, while AI-driven systems are now equipped to understand the natural language patterns and nuances found in spoken questions. When users speak, they tend to ask questions more like how they would in a conversation, often including extra words or context, which AI must decipher.
For example, a typed search might be “best pizza restaurant NYC,” while a voice search query is more likely to be, “What’s the best pizza place near me in New York City?”
AI technologies such as natural language processing (NLP) allow search engines to interpret these longer, conversational queries by analyzing the context and intent behind the words. AI can recognize important elements such as location, timing and user preferences to provide more relevant results.
Additionally, AI-powered algorithms can handle various accents, regional dialects and even background noise, making voice searches more accurate. This difference in how AI processes voice search queries compared to typed searches is a game-changer for businesses that need to optimize their content to match these conversational patterns. Instead of focusing solely on keyword density, marketers now have to create content that answers specific, spoken questions clearly and directly, improving relevance for voice search users.
Optimizing Content for Voice Search
To rank effectively in voice search results, businesses need to focus on crafting content that mirrors the conversational nature of spoken queries. Voice search queries tend to be longer and more natural compared to traditional text searches, which means optimizing for these nuances is crucial to improving search engine visibility.
Bogdan Krstic, founder and CEO at Krstic SEO, a local and affiliate SEO agency, told CMSWire that AI summarizations are essentially a more advanced version of Featured Snippets on Google, which attempt to provide an answer to the user’s question. “This position has already relied on scraping third-party data from other websites and then coming up with an answer the user won’t have to click for,” said Krstic. “The change lies in the conversational abilities of the new search engine results pages (SERPs).”
Featured Snippets, or “position zero,” are the quick answers provided at the top of many search results pages. Voice search often pulls answers directly from these snippets. To optimize for snippets, content must be structured in a way that answers questions clearly and concisely. Consider using headers for each question, followed by a brief, direct response, as this format increases the likelihood of being chosen by AI for voice search responses.
It is essential to structure content that mimics the conversational tone of voice queries, which often involves answering direct questions clearly and concisely. For businesses, this means integrating more long-tail keywords, leveraging FAQ-style content and focusing on local SEO, as many voice searches are location-based.
Scott Dylan, founder and CEO at investment company NexaTech Ventures, told CMSWire that the shift from keyword-based tactics to NLP is paramount when optimizing content for voice search. “AI now plays a critical role in interpreting not just the words used, but the intent and context behind them.”
Structured content that anticipates user questions — such as those commonly found in frequently asked questions or blog posts written in a question-and-answer format — helps AI better understand and prioritize that content for voice search. For example, instead of focusing solely on technical or jargon-heavy content, aim for clear, straightforward language that directly answers common user inquiries.
Voice search queries are often longer and more specific than traditional typed queries. These are referred to as long-tail keywords. “It is essential to structure content that mimics the conversational tone of voice queries, which often involves answering direct questions clearly and concisely,” said Dylan. “For businesses, this means integrating more long-tail keywords, leveraging FAQ-style content and focusing on local SEO, as many voice searches are location-based.”
Instead of just focusing on broad keywords such as “best restaurants,” target more specific, voice-friendly phrases, such as: “What are the best family-friendly restaurants in downtown Chicago?” Incorporating these long-tail keywords into website content helps match the more conversational tone of voice searches, increasing the chances of ranking higher.
As Dylan suggested, many voice searches have local intent, such as: “Where is the nearest coffee shop?” Businesses should ensure their content is optimized for local SEO by using location-specific keywords, claiming and updating Google Business Profiles, and including accurate address, phone number and business hours information.
Most voice searches are conducted on mobile devices. Therefore, having a mobile-friendly website is essential for voice search SEO, so brands must ensure that their site is responsive, loads quickly and offers a smooth user experience. Google factors mobile optimization into its ranking algorithms, so a slow or poorly designed site could hinder a brand’s chances of appearing in voice search results.
AI and Personalization in Voice Search
AI is playing a crucial role in delivering personalized voice search experiences by leveraging context, location and past behavior. This personalization allows voice search to provide more relevant and tailored search results based on user preferences, habits and real-time factors.
Dylan explained that, at its core, voice search optimization is about more intuitively understanding user intent. “With voice queries being longer, more conversational and often contextually driven, AI is becoming the linchpin in delivering accurate results that match user expectations. AI’s role in this exchange is set to deepen, particularly in how it analyses and predicts user intent. We’re already seeing AI learn and adapt to individual user preferences, providing more personalized results over time.” He suggested that this presents a significant opportunity for brands to create content that not only ranks well in traditional search but also aligns with the specific nuances of voice search behavior.
One of the key ways AI enhances voice search is by understanding the context in which a query is made. For example, when someone asks, “Where can I get coffee nearby?” AI not only processes the query but also factors in the user’s current location, the time of day and even past behaviors to recommend relevant results. This level of personalization enables AI to deliver highly targeted responses that cater to individual needs. For instance, Google Assistant might suggest a coffee shop the user has frequented or a highly rated café that’s open at that specific time.
Voice assistants also use AI to track and learn from a user’s previous interactions. Over time, AI refines search results based on the user’s preferences, such as their favorite restaurants or the types of products they frequently buy. For example, if a user frequently asks for Italian restaurants, future search results for “restaurants nearby” might prioritize Italian options. Additionally, ecommerce platforms like Amazon use AI-driven personalization to suggest products based on past purchases, allowing users to reorder items through simple voice commands.
A good example of personalized voice search is in smart home ecosystems. If a user regularly asks their voice assistant to set reminders, adjust home temperatures or play specific music, AI tailors future responses and actions based on these past commands. When someone says, “Play my morning playlist,” the assistant knows which playlist the user prefers based on previous choices.
By combining these data points — context, location and behavioral patterns — AI can create a highly personalized and convenient experience that transforms how users interact with voice search technology.
Technical SEO Considerations for Voice Search
As voice search becomes a dominant method of accessing information, ensuring that a brand’s website is optimized from a technical SEO perspective is critical. Three main factors — speed, mobile-friendliness and structured data — play an essential role in ranking for voice queries. These are elements that still play a role in traditional SEO, so emphasizing them for voice search will not diminish standard SERPs.
“One of the key challenges lies in balancing optimization for both traditional search and voice search,” said Dylan. “Brands need to adopt a dual strategy that caters to succinct, keyword-rich content for traditional SEO while also providing more conversational and contextual content for VSO. It’s about understanding that these two worlds are converging, and AI is central to that fusion.”
Page speed is a top priority in both traditional and voice search optimization because users expect instant results. Google emphasizes fast load times in its algorithm, making this a critical factor for voice search success. Additionally, mobile-friendliness is non-negotiable since most voice searches happen on mobile devices. Ensuring a responsive design that adapts seamlessly across devices helps maintain user satisfaction and improves ranking potential.
“I’ve seen firsthand how businesses can thrive by embracing these shifts,” said Dylan. “By focusing on how AI can be leveraged to interpret complex user intent and adjusting content strategies accordingly, businesses not only stay competitive but also offer richer, more relevant user experiences.”
Incorporating structured data (such as schema markup) helps search engines better understand the context of a brand’s content. For voice search, this is key, as AI algorithms and assistants need context to deliver accurate answers. Using schema.org, businesses can ensure that their data is organized, making it easier for search engines to serve relevant voice-based results like local listings or product recommendations.
Featured Snippets often become the spoken response to voice searches, so aiming for snippet placement is vital. Structuring content in concise, informative formats — such as using bullet points, headers and clear language — improves the chance of appearing in these coveted search positions. Incorporating FAQ sections that directly answer common questions is an excellent way to increase the odds of ranking as a Featured Snippet, especially for voice search queries.
Voice searches frequently have local intent, such as “restaurants near me” or “closest gas station.” Optimizing for local SEO by keeping Google Business Profiles up to date, using location-specific keywords and including structured data for addresses and business hours will increase visibility in these location-based voice searches. Ensuring this information is easily discoverable helps voice assistants deliver quick, accurate results to local queries.
Finally, one should keep in mind that VSO is still speculative, especially when AI is thrown into the mix. Even the concept of search optimization remains questionable today. Consider the position of Kaveh Vahdat, founder and president at RiseOpp, a fractional CMO and SEO services company, who told CMSWire that when it comes to SEO, there is a widespread misperception about the importance of content.
“SEO, more than anything, has always been about influence and authority — i.e., backlinks — much more than content,” said Vahdat. “The relative importance of backlinks over content has increased over time and will significantly increase in the age of generative AI. Essentially, generative AI has democratized content creation, making it 10x more easy to create quality content than before.”
Vahdat said that when it comes to SEO, Google has somewhat adjusted this in their recent algorithm updates and will adjust more in the future, meaning that less and less weight will be assigned to one piece of content, and more and more weight will be allocated to the popularity of that content — i.e., backlinks. “This is not only valid for Google Search but also for generative AI search engines, voice search engines and all others.”
Case Studies: Brands Bet Big on Voice Search
Domino’s Pizza is one of the most notable examples of a brand adapting to the voice search trend using AI. Through its Domino’s AnyWare platform, the company allows customers to order pizza through various devices using voice commands. Customers can use Google Home, Alexa and even smartwatches to place an order simply by speaking. Domino’s made sure its ordering system was fully optimized for voice search by integrating AI into its app, making it seamless for users to order pizzas via voice, increasing both convenience and engagement.
This use of AI-driven SEO allowed Domino’s to rank higher for voice search queries like “Order pizza near me” or “best pizza deals.” The focus on conversational AI and voice recognition has significantly enhanced customer experience and led to a competitive advantage in the fast-food industry. Recently, Domino’s partnered with Microsoft to collaborate on generative AI solutions for personalized orders and simplified store logistics, further enhancing its AI-driven innovations.
Beauty retailer Sephora leveraged voice search optimization by integrating its own voice assistant, Sephora Voice, with Google Assistant and Alexa, allowing customers to search for products, learn makeup tips and book beauty consultations using only voice commands. Sephora optimized its website content and FAQs with natural language, aligning with common voice search queries like “best foundation for oily skin” or “top-rated skincare routine.” This has enabled Sephora to appear in Featured Snippets and improve its ranking for long-tail voice search queries.
Sephora’s use of voice search aligns with its broader omnichannel strategy, blending AI and voice technology to enhance the shopping experience for beauty consumers across multiple platforms.
Capture Audience Attention With Voice Search Initiatives
As voice search and AI continue to reshape SEO, businesses must adapt their strategies to remain competitive. By focusing on conversational content, leveraging AI for personalization and optimizing technical aspects such as page speed and structured data, marketers can effectively cater to voice search users.
As AI becomes more sophisticated and voice search more prevalent, those who prioritize voice search optimization will be well-positioned to capture audience attention and drive engagement in the constantly evolving digital marketplace.
