Australian B2B SaaS Company: 3x AI Citation Growth in 4 Months
An Australian B2B SaaS company was completely absent from AI-generated answers despite strong traditional SEO, with competitors being cited in ChatGPT and Perplexity for critical buying-stage queries.
Published: March 2026 · Timeframe: 4 months
Company Overview
- Industry
- B2B SaaS / Technology
- Campaign Duration
- 4 months
- Primary Service
- Generative Engine Optimisation (GEO)
- Type
- Growth-Stage SaaS Platform
- Status
- Active Client
The Challenge
The client had invested heavily in traditional SEO, ranking on page one for dozens of category keywords, but as their buyers increasingly started research journeys in ChatGPT and Perplexity, the business was invisible. Buyers asking AI engines 'what is the best [category] tool' or 'compare [category] platforms' were being directed to competitors. There was no strategy for AI-generated search visibility.
- Zero citations in ChatGPT for 40 tracked buying-intent queries, competitors cited in 31 of them
- Perplexity brand mention rate of 0% across tracked industry queries
- Content structured for traditional search engines, not for AI extraction and summarisation
- Brand entity not established across knowledge graph sources that LLMs train on
- No digital PR presence on high-authority tech publications that AI engines use as primary sources
- Topical authority gaps: LLMs found no clear, authoritative content clusters to cite
Our Solution
Phase 1: GEO Audit & Entity Foundation (Weeks 1–2)
We began with a systematic audit of the client's current AI presence and built the entity foundation that LLMs rely on for brand recognition.
AI Visibility Audit
Ran 200 tracked queries across ChatGPT (GPT-4), Claude, Perplexity, and Google AI Overviews. Mapped which queries mentioned the client vs competitors, identifying 40 high-value buying-stage queries with zero client presence. This baseline established the priority targets for the GEO programme.
Brand Entity Establishment
Created and enhanced the client's presence across knowledge graph sources that LLMs index: Wikidata entity creation, Crunchbase profile completion, LinkedIn company page optimisation, and structured data markup across all key pages. LLMs need to recognise a brand as a real entity before they will cite it consistently.
Content Gap Analysis
Identified 34 topical areas where competitors had authoritative content clusters that the client lacked. These gaps directly correlated with queries where the client was absent from AI responses. Prioritised by query volume and buying intent.
Phase 2: Content Restructuring for AI Extraction (Weeks 2–8)
Existing content was restructured and new content created specifically for AI extraction, a fundamentally different writing approach to traditional SEO content.
AI-Optimised Content Architecture
Restructured 80+ existing pages to include clear, extractable answers to buying-stage questions. Added FAQ sections with direct answers, implemented structured data (FAQPage, HowTo, Product schema), and rewrote introductions to lead with the most citeable, direct statements rather than contextual preamble.
Topical Authority Content Build
Created 18 new in-depth content pieces targeting the 34 identified topical gaps. Each piece was built to be a definitive, citable resource, including original data, clear comparisons, and expert commentary. Structured with clear headings that match the exact phrasing AI systems use when looking for answers.
Comparison & Alternatives Content
Built 7 dedicated comparison pages structured specifically for AI citation. AI engines frequently cite comparison content when users ask 'what is the best alternative to X'. Comparison pages were written to be factually accurate, balanced, and structured for easy AI extraction.
Phase 3: Digital PR for AI Source Authority (Months 2–4)
AI engines weight citations from high-authority publications significantly. We ran a targeted digital PR campaign to earn mentions in the exact sources that LLMs prioritise.
Targeted Tech Publication Campaign
Identified the 40 high-authority tech publications appearing most frequently in AI citations for the client's category. Developed 3 original research studies and pitched them to each publication. Secured 28 features and mentions across DA 60+ tech media within 10 weeks.
Expert Commentary & Thought Leadership
Positioned the client's leadership team as expert commentators for tech journalists. Reactive PR to breaking industry news resulted in 14 additional high-authority mentions in publications that AI engines consistently cite.
Results & Impact
Across 40 tracked buying-stage queries in ChatGPT, Claude, and Perplexity. From 0 citations to being present in 31 of 40 queries by month four.
Measured via UTM tracking and GA4 referral source analysis. Perplexity and Claude referral sessions grew from near-zero to 1,840 monthly sessions.
Across buying-stage and category queries. The client is now consistently mentioned for 'best [category] tool' and related high-intent buying queries.
Demos attributed to AI-referred and direct brand search traffic grew 40%, with AI-referred visitors showing higher intent scores than average organic visitors.
"After DigiBlazon's GEO strategy, we're now consistently cited in ChatGPT and Perplexity for our key industry terms. AI-referred traffic grew 185% in 4 months and directly contributed to a 40% increase in qualified demo requests."
James Hartwell
VP of Growth, Australian B2B SaaS Company
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