Our Approach to Local SEO in an AI-Driven Search World

We’ve talked a lot recently about GEO (Generative Engine Optimisation) and how AI is changing the way people search for information online. But there’s a massive piece of the puzzle that often gets overlooked: local search.

It’s easy to assume that people only use AI tools like ChatGPT or Google’s AI Overviews to answer complex questions or write code. But user behaviour is shifting fast. Searchers are now asking conversational, highly specific local questions like, “Which digital marketing agencies in the North West have the best reviews for web design?” or “Find me an accountant near me who specialises in corporate tax.”

If your local SEO strategy relies purely on stuffing town names into your website footer, an AI engine isn’t going to confidently recommend you. AI wants context, undeniable proof of location, and authoritative sentiment.

At Platform81, we’ve had to evolve our local search playbook to ensure our clients aren’t just ranking in the classic “10 blue links,” but are actually being cited as the go-to answer by AI. Here is a look at our approach and how we put it into practice across different regions.

1. Feeding the AI with Context (Not Just Keywords)

AI engines don’t read web pages the way older Google algorithms did; they look for “entities.” An entity is a clearly defined concept: a specific person, place, or business. If you want an AI to recommend your local business, you have to spoon-feed it absolute clarity about who you are, what you do, and exactly where you operate.

We do this through highly advanced structured data (Schema markup). It’s the behind-the-scenes code that acts as a direct translator for AI bots.

The Strategy in Action

Take a recent manufacturing client of ours based near our head office. When developing their Stockport SEO strategy, the goal wasn’t just to rank for “manufacturers in Stockport.” We needed AI engines to understand their specific capabilities.

We implemented a deep LocalBusiness schema, detailing their exact coordinates, service areas, operating hours, and specific industry accreditations. By structuring their site data so cleanly, when a searcher asks an AI for a “reliable, accredited manufacturer in the SK postcode,” the AI doesn’t have to guess. It has the exact, structured data to confidently cite our client as the answer.

2. Optimising for Conversational “Near Me” Queries

Because people speak to AI in full sentences, the era of “caveman search” (typing “plumber manchester cheap”) is evolving. Users are dictating full paragraphs into their phones, expecting the AI to do the heavy lifting.

Your content needs to answer these conversational, long-tail queries directly. If a user asks an AI a highly specific question, and your website has a clean, concise paragraph answering that exact question, the AI will pull your content directly into the search overview.

The Strategy in Action

This conversational shift heavily influences how we handle campaigns in highly competitive, saturated cities. For instance, when running a Manchester SEO campaign for a client in the B2B services sector, we knew we couldn’t just build a single generic “Services in Manchester” landing page. Instead, we audited the actual questions their sales team were being asked.

We then built out comprehensive, Q&A-style content silos answering highly specific, long-form queries about their industry in the city centre. We ditched the marketing waffle and provided direct, expert answers. Now, when an AI model scrapes the web for the best local answer, our client’s content is the most easily digestible source to pull from.

3. Mastering Sentiment Analysis

Here is a slightly scary truth: AI engines read your reviews. All of them. And they don’t just look at the star rating; they use natural language processing (NLP) to analyse the sentiment of what people are writing about you.

If someone asks an AI for a “highly recommended solicitor,” the AI will scour Google Reviews, Trustpilot, and local directories to find businesses where the text actually mentions words like “professional,” “quick,” and “helpful.” If your reviews mention “late,” “rude,” or “expensive,” the AI will actively filter you out of its recommendations.

The Strategy in Action

Local reputation management is now a core pillar of off-page SEO. We applied this exact focus when managing the Bromsgrove SEO strategy for a regional client operating out of Worcestershire. We didn’t just help them generate more reviews; we helped them generate better-context reviews.

We guided them on how to ask clients to mention the specific services provided and the areas served in their feedback. By cultivating a digital footprint packed with positive, keyword-rich sentiment, we turned their customer feedback into a powerful trust signal that AI engines simply cannot ignore.

The Takeaway

The rules of getting found locally have changed. AI doesn’t care about how many times you’ve hidden a town name on your homepage. It cares about structured data, conversational expertise, and undeniable local trust.

At Platform81, this isn’t future-gazing; it’s what we do every single day. If you want a partner who builds strategies for where search is going, not where it’s been for the past 15 years, then get in touch with our seo team today.