See how AIRank.au’s approach plays out across different Australian industries. The scenarios below are illustrative — representative of the work and outcomes our methodology is designed to produce.
Illustrative scenario: professional services firm, Sydney
The challenge. A mid-sized advisory firm found that when prospects asked ChatGPT and Perplexity for “the best firm in Sydney” for their service, competitors were named and they weren’t.
The approach. An AI Visibility Audit mapped the gap, followed by a GEO programme: tightening entity data and schema, publishing answer-shaped content for the firm’s key services, and building citations on trusted industry sources.
What success looks like. Over successive measurement rounds, the firm begins appearing in AI recommendations for its core service prompts, with recommendation share tracked month on month as authority compounds.
Illustrative scenario: e-commerce brand, national
The challenge. An online retailer was invisible when shoppers asked AI to “compare the best brands” in its category.
The approach. Structured product and brand data, AI-optimised category content, and a ChatGPT lead-generation funnel to capture AI-referred shoppers.
What success looks like. The brand starts being named in comparison answers, and a measurable share of new enquiries can be attributed to AI-referred traffic arriving ready to buy.
Illustrative scenario: local service business
The challenge. A trades-and-services business wanted to be the one AI recommends for its city and suburb.
The approach. Local entity clarity, consistent listings, review and citation building, and location-specific answer content.
What success looks like. The business becomes a consistent AI recommendation for local buyer prompts, turning AI visibility into booked jobs.
The common thread
- Start with a clear benchmark of where AI names you today.
- Fix entity clarity, structured data, content and citations.
- Capture the resulting demand with purpose-built funnels.
- Track recommendation share and compound the wins.
Want to see your own starting point? Run a free AI ranking report or book a strategy call.
Why there are no client case studies here yet
Because we have not earned them. AIRank.au is a new brand, and the scenarios above are illustrative — they show the shape of the work and the kind of gap an audit typically finds, not results we have delivered for a named client.
We could have written case studies anyway. Plenty of agencies do, and an invented recovery figure is impossible for a prospect to check. We would rather you judge us on the method, the transparency of the pricing and the quality of the thinking on the rest of this site.
What we will publish, when we can
When we have client outcomes we are permitted to share, they will carry the things that make a case study checkable rather than decorative:
- The client’s name, with their written consent to be named. No anonymous “a Sydney firm” attributions.
- The prompt set that was measured, so the scope of the claim is clear.
- The baseline reading and the later readings, including the runs that did not move.
- The period over which it was measured, and what else was happening — a rebrand, a new site, a change in spend — because attributing everything to one intervention is rarely honest.
- What we got wrong. Every engagement has something.
How to judge an AI visibility provider without case studies
Useful questions to ask us, or anyone else in this category:
- Can you show me the actual prompts you will measure, before I commit?
- How do you handle the fact that AI answers vary between runs and between users?
- What specifically will you change on and off my site, in the first month?
- What will you report, and will I see the raw results or only a score?
- What can you not control? A provider who claims to control model behaviour is describing something that does not exist.
If the answers are vague, the case studies would not have helped you anyway.