Case Studies — AI Search

What it actually looks like when AI starts recommending your brand

Real outcomes. Real citation growth. No guesswork.

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Results Overview
340%
increase in brand mentions inside ChatGPT & Perplexity answers
12-week campaign average
5.2×
ROI on AIO investment vs. equivalent paid search spend
Cross-client portfolio average
91 days
average time from campaign start to first measurable AI citation growth
Across active client engagements
B2B SaaS

From invisible in AI answers to 14 target queries cited in 90 days

increase in inbound leads from AI-referred traffic
Challenge

A B2B software company was invisible in AI-generated answers despite strong Google rankings. Prospects were opening ChatGPT to ask for tool recommendations and receiving competitor names in every response. The client's SEO performance gave no advantage where buyers were actually making decisions.

Approach

AI Search Lab conducted a citation gap analysis to identify exactly where competitors were being cited and why. We restructured key service pages with entity-rich content, published a suite of authoritative FAQ content aligned to AI query patterns, and built a structured data layer to make brand entities machine-readable and trustworthy.

Result

Within 90 days, the brand appeared in ChatGPT responses for 14 target queries — up from zero. Inbound leads from AI-referred traffic increased 3×. The client now has a defensible citation presence that compounds with each passing week.

Professional Services

From zero AI presence to cited across 8 advisory topics in 60 days

client enquiry volume from AI-referred sessions in Q1
Challenge

A Hong Kong-based consulting firm had deep subject-matter expertise and a strong offline reputation — but zero presence in AI answers. When prospective clients asked Gemini or Perplexity about key advisory topics, competitors were named. The firm's brand was absent from the AI's knowledge graph entirely.

Approach

We developed a topical authority content programme targeting the firm's eight primary advisory domains, created Wikipedia-adjacent reference content to anchor the firm's entities in AI training data, and built a citation trail across high-domain-authority publications that AI engines use as trust signals.

Result

Gemini began citing the firm in 8 advisory topics within 60 days of launch. Client enquiry volume from AI-referred sessions doubled in Q1. The firm is now positioned as the default AI-recommended authority in its primary practice areas.

Our Process

A systematic approach to AI citation

01
Citation Audit

Map where you're cited, where you're missing, and where competitors are outranking you inside AI answers. This is the foundation for every decision that follows.

02
Entity Optimisation

Structure your brand, key people, products, and content as AI-recognisable entities. Disambiguate your identity across knowledge graphs so AI systems can reference you accurately.

03
Authority Content

Publish content that AI engines use as reference material — structured, authoritative, entity-rich. Content that answers the exact questions AI models are trained to retrieve.

04
Citation Building

Place your brand in AI-indexed sources: Wikipedia, press coverage, high-DA publications, and structured reference databases that AI training pipelines prioritise.

Ready to become the brand AI recommends?

Start Your AI Search Audit