Search and AI discovery: SEO, GEO and AEO strategy
A core depth area within my integrated marketing work: building compounding organic acquisition systems across search engines, conversational answer engines, and generative AI overviews, accountable to commercial pipeline.
Last updated: October 2026
What this solves
Siloed tactics might spike raw pageviews, but they rarely protect market share or build durable pipeline. We solve for commercial outcomes across both classical and generative search.
Poor organic rankings
Missing out on active commercial demand while competitors capture high-intent category searches and core purchase queries.
Low-quality traffic
High top-of-funnel visitor volume that lacks purchase intent, resulting in weak engagement and poor conversion overlap.
No pipeline contribution
Traffic numbers rise on vanity charts, but qualified leads, commercial applications, and attributable revenue remain flat.
Brand missing from AI answers
Synthesized summaries and answer engines answer high-value queries directly without citing your domain, eroding organic click share.
The approach
A cohesive framework aligning technical infrastructure, brand authority, generative discovery, and cross-functional governance.
Technical search health
Ensuring search bots and answer models can discover, crawl, render, and index core platform infrastructure efficiently. Encompassing crawlability, indexation controls, site architecture, Core Web Vitals, entity-level schema markup, and strategic internal linking graphs.
Content and authority
Building authoritative topic hubs mapped to verified searcher intent across the decision journey. Establishing topical authority, semantic entity relevance, and structured hub-and-spoke content models that demonstrate comprehensive subject matter expertise.
GEO and AEO (Generative & Answer Engine Optimisation)
Restructuring deep content with answer-first passage models and structured FAQs designed for automated synthesis. Amplifying brand citations, entity co-occurrences, and third-party authority across forums, discussion platforms, and verified review portals.
Measurement and decision infrastructure
Connecting organic search activity directly to commercial metrics through Looker Studio executive dashboards and CRM attribution, moving beyond vanity rankings into qualified pipeline contribution and customer acquisition efficiency.
Cross-functional operating model
Establishing clear search governance across marketing, content velocity, analytics, product, and engineering teams, ensuring organic search standards and technical requirements are integrated into sprint roadmaps.
How I measure AI visibility
As search behavior shifts toward conversational answers, tracking classical keyword ranks alone is insufficient. I report a dedicated AI visibility framework alongside organic traffic, engagement, and conversion:
Frequency of brand presence across answer engine responses for high-intent queries.
Total citations earned in generative summaries and market share relative to competitors.
Proportional prominence within synthetic answers across core commercial topics.
Frequency of inclusion in search engine overviews and AI snapshot blocks.
Contextual tone and factual accuracy of brand characterisation within generated outputs.
Direct click-through sessions originating from generative engines and answer interfaces.
All AI visibility metrics are integrated alongside organic traffic, user engagement, and Salesforce-tracked lead pipeline to maintain complete commercial transparency.
How a programme runs
A structured four-stage operating model delivering strategic clarity, technical execution, and commercial accountability with no invented delays.
Audit
Forensic evaluation of technical platform health, crawl logs, entity recognition, indexing bottlenecks, AI visibility baselines, and competitor market share.
Roadmap
Prioritised strategic plan aligning commercial search opportunities with engineering capacity, content resources, and leadership revenue objectives.
Delivery
Hands-on execution across technical sprints, answer-first content restructuring, structured data deployment, and cross-functional team coordination.
Reporting
Automated executive Looker Studio dashboards tracking pipeline metrics, CRM lead attribution, and AI visibility KPIs to maintain strategic investment.
Frequently asked questions
Clear answers on generative discovery, answer engine optimisation, and modern search measurement.
What is GEO (Generative Engine Optimization)?
Generative Engine Optimisation (GEO) is the discipline of optimising digital content and brand entity signals so that generative AI engines, including Google AI Overviews, Perplexity, and ChatGPT, discover, parse, and cite your domain in synthetic answers. Unlike traditional SEO which focuses primarily on ranking within blue-link result pages, GEO focuses on structured answer-first passages, semantic entity relevance, and third-party authority that encourage AI models to quote your brand as a trusted source.
How is AEO different from traditional SEO?
Answer Engine Optimisation (AEO) specifically targets zero-click searches and conversational interfaces that deliver direct answers rather than a list of search links. While classical SEO targets page-level keyword relevance and backlink volume to win top organic SERP positions, AEO structures information into modular question-and-answer formats, concise summary passages, and nested schema markup, making it seamless for both search engines and answer engines to extract and credit your content directly.
How do you measure AI visibility?
AI visibility is measured through a dedicated KPI framework tracking brand mention rate, citation count and share, AI share of voice, AI Overview presence, sentiment, and AI referral traffic. These metrics are evaluated alongside traditional organic traffic, user engagement, and CRM pipeline attribution to provide leadership with a comprehensive view of organic market presence in both search engines and generative models.
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