generative engine Optimisation (GEO) is no longer a future concern — it’s a live ranking factor. AI-powered search experiences from Google, ChatGPT, and Perplexity are already reshaping how users discover businesses. Our team is actively retooling client strategies around AI citation tracking, local keyword validation, and content optimisation that serves both traditional SERPs and generative answers. Here’s what we’re implementing right now and why it matters.

Key Takeaways

• New websites need a strict 90-day SEO sequencing plan that accounts for AI answer visibility from day one.
• Local SEO keyword research must now validate intent across Google Search, Maps, and AI-generated responses.
• AI visibility tracking tools give agencies a concrete way to measure whether client brands appear in generative answers.
• Content optimisation in 2026 demands a dual focus: human readers and large language model citation.
• Competitor-level AI visibility gap analysis reveals exactly where brands are being outperformed in generative search.

Sequence Your First 90 Days to Include AI Answer Targeting

Launching a new site without an SEO sequencing plan is wasted effort. We follow a phased approach — pre-launch technical foundations, post-launch indexation checks, and structured content rollout — to build authority fast. The critical addition in 2026 is ensuring new pages are structured for AI citation from the start. Schema markup, clear entity definitions, and concise answer-ready paragraphs are non-negotiable in our builds. We align every new project with the sequencing framework for new website SEO published by Semrush, adapting it to each client’s sector and competitive landscape.

Validate Local Keywords Against AI-Generated Results

Local SEO keyword research has changed. It’s no longer enough to find high-volume terms and map them to service pages. We now run a six-step validation process:

• Identify seed terms from Google Business Profile insights and customer language.
• Expand using autocomplete, People Also Ask, and competitor gap data.
• Check intent alignment across organic results, Maps pack, and AI overviews.
• Filter for terms where AI answers currently cite competitors but not our client.
• Prioritise based on conversion potential, not just search volume.

This mirrors the step-by-step local SEO keyword research methodology outlined by Semrush, which we’ve integrated into every local campaign we run. The difference it makes is measurable: clients gain visibility in both traditional and generative results simultaneously.

Track AI Visibility With Purpose-Built Agency Tools

You can’t improve what you don’t measure. Our team now monitors AI citations alongside standard SERP rankings. Tools like Semrush, Otterly AI, and Peec AI each serve different use cases — from brand mention tracking in ChatGPT responses to citation frequency analysis in Google AI Overviews. We select tooling based on client needs, as recommended in this breakdown of the best AI visibility tracking tools for agencies. The key metric we watch: citation share versus direct competitors in AI-generated answers for target queries.

Optimise Content for Readers, Search Engines, and LLMs

Content optimisation now serves three audiences. Pages must satisfy human readers, rank in traditional search, and earn citations in AI-generated responses. We apply a set of 20 tactics covering structure, readability, entity clarity, internal linking, and freshness signals. Concise definitions, well-labelled data tables, and FAQ blocks all increase the likelihood of LLM citation. Our content team works from the content optimisation tactics compiled by Semrush as a baseline checklist, then layers in client-specific authority signals.

Run Competitor-Level AI Visibility Gap Analysis

The fastest route to AI visibility gains is identifying where competitors get cited and you don’t. We run prompt-based audits — testing the exact questions potential customers ask AI tools — and map which sources appear in responses. Where a competitor is cited and our client is absent, we create or restructure content to fill that gap. This process follows the AI visibility gap analysis workflow detailed by Semrush, and it’s now a standard part of our quarterly strategy reviews.

GEO is not a bolt-on. It’s embedded in how we build sites, research keywords, create content, and report results. Agencies that treat AI visibility as separate from SEO will lose ground quickly. We treat them as one discipline.

Frequently Asked Questions

What is Generative Engine Optimisation (GEO)?

GEO is the practice of optimising web content so it gets cited in AI-generated search answers from tools like ChatGPT, Google AI Overviews, and Perplexity. It builds on traditional SEO by adding structured, entity-rich content that large language models can easily reference.

How do web designers build new sites for AI visibility?

They implement clear schema markup, concise answer-ready content blocks, and strong entity definitions from launch. A phased 90-day sequencing plan ensures technical foundations and AI-optimised content are in place before scaling traffic acquisition.

Why does local SEO keyword research now include AI answers?

AI tools increasingly surface local business recommendations in response to user queries, pulling from the same content that ranks in Maps and organic results. Validating keywords against AI-generated responses ensures businesses appear in all the channels where customers are searching.

How do agencies track whether a brand appears in AI Search results?

Agencies use purpose-built AI visibility tracking tools that monitor brand citations across ChatGPT, Google AI Overviews, and other generative platforms. These tools measure citation frequency and share of voice against competitors for target queries.