AI and local search: The new rules of visibility and ROI in 2025

Local search is no longer just about maps and directories. 

What began as a game of citation consistency has grown into a dynamic, intent-driven ecosystem shaped by real-time data, customer intelligence, and AI-powered personalization.

Today, AI is redefining how people discover, evaluate, and interact with local businesses – reshaping the rules of visibility, experience, and conversions across every channel.

This article:

• Breaks down the evolution from Local 1.0 to Local 3.0.
• Explore how AI is transforming the future of local search and what it means for marketers, brands, and businesses in 2025.

The evolution of local search

These shifts in local search have occurred in three interconnected phases, each building on the last, shaping the current landscape.

Local 1.0

This phase focused on ensuring data accuracy and consistency across channels, with citation management services emerging to help brands maintain correct local listings at scale.

Local 2.0

Last year, I wrote about Local 2.0, which was about discovery, relevancy, authority, experience, engagement, and conversions.

In 2024, local search emphasized engaging conversations across all touchpoints, moving beyond simple listings management to prioritize customer experience and relevance.

I shared why businesses should focus on: 

• Discovery through comprehensive listings and rich content. 
• Relevancy via authoritative and localized conten. 
• Customer experience by delivering a seamless and consistent personalized experience. 
• Active customer engagement and conversions through using strategies like optimization, paid, and personalization, etc. 

I emphasized the importance of a rock-solid platform, topical, and entity-rich content, and optimized digital assets, among other strategic priorities.

Local 3.0

This year, I see local search through the lens of AI. 

While the overall framework remains the same, AI is playing a pivotal role in modernizing customer discovery in local search. 

Why AI is the driving force behind Local 3.0

At the heart of Local 3.0 is AI’s ability to understand and match user intent with unprecedented depth and context. 

AI-driven search is becoming more personalized and context-aware.

Crystal Carter, head of SEO Communication at Wix, shared: 

• “AI-powered search experiences, driven by models like ChatGPT and Google’s Gemini, are creating hyper-personalized, agentic interactions. These conversations are built around understanding and addressing customer intent at their core. Unlike traditional searches, users now benefit from extended context windows, allowing for deeper, more focused interactions that incorporate their specific needs and goals. Tools like ChatGPT also have memory capabilities, which enhance relevance by maintaining context over multiple exchanges, making deep searches more meaningful.”

The impact you’ve likely seen:

• Increase in zero-click searches. 
• Decline in organic traffic.
• Brands’ concerns about “What’s going on?”

The five pillars of Local 3.0

AI has transformed micro-moments by:

• Enabling hyper-personalization.
• Automating workflows and journeys.
• Leveraging multi-agents.
• Delivering real-time information and dynamic pricing based on demand and external factors. 

Over the past year, we’ve observed how AI fundamentally changed the entire local search journey across all channels for both location-based businesses and large brands. 

1. Discovery

The essential ingredients for discovery are consistency, accuracy, and real-time discovery. 

With the rise of large language models (LLMs), the accuracy of business information within these models has become a foundational necessity. 

Data accuracy and real-time discovery of the most relevant and authoritative content are vital, especially given the high cost of computing resources. 

The role of images and videos in local search is evolving with technologies like Google MUM and similar models from OpenAI. 

These enable LLMs to understand connections across media types using embeddings and vectors, making topical relevance not just limited to text. 

This allows brands to engage users at different stages of the journey:

• Capturing attention with images.
• Fostering interest through videos.
• Building desire with articles.
• Prompting action via social posts across various media formats.

Recommended strategies

Brands should: 

• Audit LLM presence.
• Implement deep nested schema for enhanced content discovery.
• Manage schema drift.
• Create hyper-personalized landing pages with fresh, localized content.
• Regularly update content to ensure data remains consistent, current, and relevant across all touchpoints.
• Deploy IndexNow via your CMS or CDN to improve real-time discovery.

Dig deeper: Why entity search is your competitive advantage

Local SEO expert Will Scott highlights this when talking about consistency: 

• “Today, LLMs can give you wrong information. Disambiguation through context is critical. So when they are building their ontologies – their map of relationships of knowledge – consistency matters a lot.”

2. Experience 

Traffic to websites from organic search is expected to decline due to the increasing prevalence of AI-influenced searches, including AI Overviews on Google.

User expectations have shifted due to AI-powered search experiences.

Focusing solely on download times and metrics like Google’s Core Web Vitals (CWVs) is no longer enough.

Hyper-local and hyper-personalized content is now essential to boosting engagement and conversions.

Website traffic from organic search is expected to decline as AI-influenced experiences, like Google’s AI Overviews, become more common. 

At the same time, user expectations have evolved. 

To drive engagement and conversions, brands must now deliver hyper-local, hyper-personalized content tailored to each user’s context and intent.

• “As AI assistants become more agentic, customer loyalty will be absolutely critical. Businesses with a strong understanding of their customer relationships and loyalty will be greatly rewarded because users will input their preferences for their supermarket, airline, or shoe brand of choice, and that will form part the training knowledge for the agent,” Carter said.

Customer loyalty will be crucial as AI assistants become more agentic (using agents to retrieve information). 

Businesses that understand and nurture their customer relationships, primarily through loyalty programs, will be rewarded, as user preferences will become part of the AI’s training data.

For example, if a customer has a loyalty membership with an airline or hotel, the AI will prioritize that preferred airline in travel queries. 

AI-generated images are no longer performing well in search, says Joy Hawkins. 

Google introduced a quality filter earlier this year that significantly reduced the visibility of AI-created visuals, Joy Hawkins highlights. 

The ranking gains and image traffic were reversed when Google rolled this out. 

If you added AI photos to your website, check your image traffic in Search Console for 2025. 

If you see a drop, you might want to consider pulling back on that strategy.

Strategies to deploy

Key focus areas include:

• Enhancing page experience. 
• Auditing UI/UX.
• Leveraging hyper-personalization based on audience data.
• Implementing real-time content orchestration across all touchpoints. 
• Doubling down on social engagement and community forums, which will be especially vital for emerging businesses investing in brand advocacy via influencers. 

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3. Relevance and authority

Relevance and user intent have always been central to local search. 

With some LLM tools now capable of “remembering” past searches, they can personalize answers to an unprecedented degree. 

AI transforms the customer journey by enabling real-time intent matching, where highly topical, entity-rich content with strong topical authority and expertise performs best. 

Strategies to deploy 

Consider: 

• Conducting content audits to identify and optimize underperforming pages.
• Ensuring content is topically and locally relevant, fresh, informative, and marked up with schema to enhance discoverability.
• Establishing clear quantitative and qualitative metrics to evaluate content quality and performance.
• Leveraging brand mentions across social media and reviews to strengthen relevance and authority.
• Monitoring engagement across all channels – including Google Business Profiles, social platforms, and your website – to gain a complete view of user interaction.

Dig deeper: How to safeguard your content strategy in an AI-driven search landscape

4. Conversions

Speed and CWVs directly impact conversion rates. 

When visitors land on your site, many are already primed to take action, so it’s critical to deliver a seamless, high-performing experience with minimal friction. 

We also want to leverage AI to perform AB testing, CRO, and user experience testing. In 2025, local is about experience. 

Strategies to deploy:

• Site speed optimization.
• Conversion rate optimization (CRO).
• A/B testing.
• UI/UX audit.

5. Performance

Many factors influence local search results. Real-time, actionable insights based on current engagement are crucial. 

Key metrics include:

• Engagement rates.
• Appearances in zero-click searches.
• Impressions.
• Conversions.
• Listing-specific metrics such as:
  • Website clicks (Listings and LLMs).
  • Phone calls.
  • Driving directions.
  • Direct user interactions that connect to specific business goals.

Local SEO metrics

• Listings
  • Impressions.
  • Actions such as:
    • Phone calls. 
    • Website clicks.
    • Driving directions.
• Location pages
  • Views.
  • Engagement rate and engaged sessions.
  • Event count and conversions.
  • Video engagement.
  • User stickiness.
  • Internal link clicks. 

• LLMs
  • Accuracy.
  • Consistency. 

Dig deeper: 13 digital marketing trends you should plan for in 2025

Conclusion 

We are entering a new era of discovery where traditional search results are being replaced by conversational AI like ChatGPT, Perplexity, and Google Gemini. 

Instead of browsing links, users now expect direct answers, comparisons, and recommendations. 

Part revolution and part evolution, AI-powered search, predicted years ago, rapidly transforms the user journey. 

Soon, users will express their intentions, and AI will handle all the research, returning only the most relevant answer, rather than a list of links. 

Websites will serve more as data repositories for AI consumption than traditional sales tools.

Local search results may increasingly become part of AI Overviews or AI-generated search results, as Google introduces AI modes within search. 

Brands must prioritize data accuracy and a consistent, hyper-personalized experience across all channels. 

This shift has profound implications: marketers must optimize for an answer-first world, and builders can create AI-native customer experiences where the next buyer may be an AI agent. 

Local 3.0 is no longer just about features; it’s about rethinking discovery, experience, and purchasing in an AI-first landscape. 

I’d like to thank the many contributors to this article – Will Scott, Crystal Carter, and Joy Hawkins – for their valuable insights. I’m also grateful to the my team for their support with data and visuals, especially Tushar Prabhu, Elmer Boutin, and Brett Dugan. Your efforts helped bring this piece together – thank you.

#local #search #rules #visibility #ROI