Local SEO is a digital marketing strategy designed to help brands rank higher in local search results for a specific geographic area. In the past, brands could rank in the Local Pack by optimizing their Google Business Profile, local keywords, citations, and reputation. Today, that approach still matters, but it's not enough.
With the rise of AI search, voice assistants, map apps, social as search, and hyperlocal platforms, brands need to evolve their local SEO strategy. Urgently. That strategy must combine local SEO optimization with structured data, real-time insights, and local SEO tools.
The biggest challenges in local SEO strategy
Digital marketers have a lot to say about the challenges of local SEO. Especially now, when customers are searching everywhere from Google to TikTok to ChatGPT:
"Our listings are accurate, but traffic is declining."
"AI search tools are surfacing our competitors, not us!"
"We need competitive intel to improve our local business marketing."
"How can we outperform competitors in a specific region?"
"We've never focused on unstructured citations before. Is that a problem?"
"Managing our local presence across multiple platforms is overwhelming."
"We have hundreds of locations and need a local SEO strategy that scales for them all."
Some marketers are still trying to figure out how to measure the business impact of their local SEO strategy and tactics, too. (Hint: it's not just impressions. It's also clicks, bookings, and conversions.)
Whether you're overhauling or fine-tuning your local SEO strategy, this post shares the details you need to get real results in an AI-driven world.
How to build a local SEO strategy that's AI-friendly and scales across business locations
Use structured data that speaks to AI's large language models (LLMs)
Local SEO is bigger than just ranking in the Google Map Pack now that visual search and AI search. Think Google Gemini, ChatGPT, and other AI-driven search experiences on the rise.
Unlike traditional search engines, AI models don't just source links from major directories and brand websites. They're sourcing information about local businesses from a wide range of sources. To turn that data into conversational interactions with customers, AI-driven search references structured data (which is best organized in schema markup and centralized in knowledge graphs).
AI also responds to brands that regularly update their web pages and listings. Think about changing up featured products and seasonal menus. Add new providers and enrich their bios. Add events, freshen up images, FAQs, etc. After all, if your financial services brand has just welcomed a new "tax advisor near me who speaks Spanish", you want Siri, Alexa+, and Bixby to know about it. These AI platforms are, directly and indirectly, your new customers.
Centralized structured data is easy to update and easy for AI search to discover.
Publish structured local citations everywhere
At a minimum, make sure you're publishing your NAP data accurately, wherever it's listed. To be most competitive, extend your publisher network so you're reaching the largest network available.
It's not enough to operate with an optimized Google Business Profile or publish only on major platforms. You want to make sure you're hitting niche directories and every industry-specific directory (like ZocDoc or OpenTable) as well as emerging AI-driven platforms. It's this diversity of coverage that drives discoverability, clicks, and conversions.
Make sure you're creating content with more informal or unstructured citations, too. Mentioning NAP data in social posts, review responses, FAQs, online press releases, blog posts, etc., can also raise visibility.
AI prioritizes brands with clear, consistent reach and hyper-relevance.
Share ratings and reviews on your local pages
Reviews impact traditional search in a number of ways, and they tie into Google's ranking criterion, "prominence." Prominence is, in part, determined by your brand's online reputation. It's informed by the volume, quality, and recency/history of reviews that imply your brand or location as "the best…near me."
Prominence is measured and communicated a little differently in AI-driven search. But it's still important.
For example, AI search relies less on keywords and more on the meaning AI interprets in reviews. In AI search, "best onion rings in town" might be discovered thanks to a glowing, authentic review that reports "life-changing onion rings." They can note click-through rates or time spent on a page and see it as more important than backlinks from high-authority sites.
With AI search, prominence may even take a back seat to "relevance." Relevance in AI search is measured by the accuracy and usefulness of the results:
Is this a retail brand the customer has interacted with before? Recently? Did they share positive feedback about the brand?
Are there reviews that suggest the restaurant is ideal for high-intent searches for kid-friendly, blind dates, or happy hour?
Does this healthcare provider have compelling educational videos and FAQs that imply the five-star reviews are authentic?
Does the brand actively and consistently respond to reviews in personalized ways?
Use a tool like Yext with a Review Monitoring feature so you can track what customers are saying about your brand in real-time. Yext also helps you generate first-party customer reviews, then add them to the location pages on your website.
Manage reviews: they send a very strong trust signal to customers and AI.
Centralize local SEO content management for scalability
It can be overwhelming when you're managing local presence for hundreds, even thousands, of brand locations. Especially when you're managing that presence across countless channels. Especially, too, while optimizing local SEO for both traditional and emerging search experiences. Knowing where to prioritize your efforts is key.
When you combine tools like Yext's Listings and Pages, you can keep NAP data updated and synced everywhere — from your own website and Google Business Profile to 200+ key citation sources, maps, apps, directories, search engines, and social media networks across the digital landscape.
Local SEO management doesn't have to be an inefficient risk or cost center.
Add rich content to enhance your listings
On average, business listings receive 2.7x more views than a brand's owned website (including local store pages and directories). So, it's worth enhancing those listings with rich content to try to gain attention and increase high-intent clicks.
Rich content extends beyond contact information, parking advice, and directions. Rich content includes images, videos, descriptive details, and more. Rich content is also a proven way to inspire customer engagement. Brands that include rich content pick up 416% more listing views compared to brands that don't. Meanwhile, 76% of customers will click listings when the images reflect their wants and needs.
Customers trust and engage with rich content, so use it to stand out.
Collect intelligence on your own (and your competitors') local SEO performance
Until Yext Scout came on the scene, most brands had no way to track how they appear in AI-generated search results. Local SEO strategy for AI-driven search has been full of guesses and finger-crossing, with no way to benchmark impact.
Scout is the first and only tool that gives brands the power to benchmark their brand against competitors in AI search. With Scout, digital marketers can finally measure and guide local SEO strategy:
See how your brand appears across both traditional and AI search, identifying bright spots and gaps
Find out who's outranking you and why, so you can quickly take (back) the lead
Get AI-powered recommendations to quickly improve location visibility and customer sentiment
Instantly turn insights into action directly from the Yext platform (no extra tools, spreadsheet toggling, or manual reporting required). With Scout, local SEO now has an intelligence layer that cracks the code in AI-driven search.