Examples

GEO Examples

The following scenarios illustrate how GEO improves AI citation rates across different business types. The specific numbers and implementations are representative — the underlying patterns and techniques are consistent with real GEO work.

Example 01

Local service business: accountancy firm

A regional accountancy firm serving small businesses was appearing in 0 of 20 AI test queries. Competitors in the same city appeared in 14 of 20. The firm had a functional website with good SEO rankings but had done no GEO work.

Gap analysis

  • Service pages used long narrative descriptions with no direct question-and-answer structure
  • No FAQPage, HowTo, or Service schema on any page
  • The firm's name appeared consistently on their own site but nowhere else — no directories, no press mentions, no independent citations

Fixes implemented

  • Rewrote each service page to lead with a one-sentence definition, followed by 3–5 explicit Q&A pairs
  • Deployed FAQPage schema on all service pages and HowTo schema on the onboarding process page
  • Added Organization schema to the homepage with founder name, service area, and service types
  • Submitted the firm to 12 relevant business directories and secured two editorial mentions in local business publications
0/20
Before
AI queries cited
7/20
After (6 weeks)
AI queries cited
Structure
Primary fix
Content + Schema

Example 02

SaaS tool: project management software

A project management SaaS had strong domain authority and ranked well for long-tail SEO keywords. Despite this, it appeared in only 3 of 25 AI test queries for phrases like “best project management software for agencies” — while two less-known competitors with weaker SEO appeared in 18 of 25.

Gap analysis

  • Content was optimised for engagement and keyword density — not for direct answer extraction
  • Competitors had invested heavily in third-party review sites (G2, Capterra, Trustpilot) where AI models frequently sourced answers
  • The SaaS had no structured comparison content — no explicit "who is this for" or "how does it compare to X" pages

Fixes implemented

  • Created a dedicated "best for" landing page with explicit positioning: 'Best for agencies managing 5–25 clients'
  • Added SoftwareApplication and FAQPage schema to core product pages
  • Ran an active review acquisition campaign on G2 and Capterra to increase citation frequency on platforms AI models source from
  • Built a comparison content series: 'Tool X vs Tool Y for agency use'
3/25
Before
AI queries cited
16/25
After (10 weeks)
AI queries cited
Citations
Primary fix
Reviews + Comparison

Example 03

Marketing agency adding GEO as a service

A 6-person digital marketing agency wanted to offer GEO to their existing client base without hiring a specialist. They used GEOhelp as a white-label execution partner, starting with an Agency Enablement engagement to build an internal playbook, then moving to a monthly retainer for their first two GEO clients.

Structure of the engagement

  • Month 1: Agency Enablement — GEOhelp built a custom playbook with prompt templates, schema checklists, and citation-building frameworks for the agency's specific client types
  • Month 2: First GEO client onboarded — GEOhelp ran the full cycle (audit, fix, retest) while the agency account manager handled client communication
  • Month 3: Second client added — agency team ran the audit phase independently using the playbook; GEOhelp handled execution
  • Month 4 onwards: Agency retains GEOhelp for execution while managing client relationships and reporting internally

“We went from having no answer when clients asked about AI visibility to having a repeatable process in 30 days. The white-label setup meant our clients never knew we were using a partner — it just looked like we'd built the capability in-house.”

— Agency Director, 6-person digital marketing agency

What these examples have in common

  • Every case started with a prompt audit — no GEO work was done without first establishing what the baseline was
  • The gap type (structural, technical, authority) determined which fix to prioritise first
  • Schema and content fixes produced faster results; citation building took longer but produced more durable improvement
  • AI visibility and Google rankings moved independently — fixing one did not automatically fix the other

Read the full tactical guide: How to Rank in AI Search →

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