Customers

Case studies (the honest kind)

We are in open beta and do not have named customer testimonials yet — and we will not invent any. What we can show today: our own self-experiments on the live product and anonymized patterns from real beta scans, each clearly labeled.

Self-experiment — our own product

RankedByAI, scanned by RankedByAI

The question
We are a new SaaS in a new category ('AI visibility monitoring'). When someone asks an AI assistant for tools that check whether ChatGPT recommends a business, do we appear at all?
What we did
We run our own weekly monitoring on the production system — the same Monitor plan customers get. The scan samples buyer questions for our category across all three channels and tracks which competitors are named alongside us.
Where it stands
The public demo dashboard on this site is that real, living scan — not staged data. It also drives our own roadmap: citation-gap analysis on our scan told us which comparison and educational pages to write first (several now exist on this site).
Open the live demo dashboard →
Anonymized beta scan — local services

A local service business discovers it is invisible

The question
A typical pattern from our beta scans: a well-reviewed local business (think plumbing, dental, legal) with solid Google rankings scores an F on AI visibility — zero mentions across all sampled questions, while 2–3 competitors are recommended repeatedly.
What we did
The scan's competitor extraction shows exactly which rivals the AI names and which sources (directories, review sites, local news) the answers cite. The prescription engine then lists the concrete pages and content the business is missing.
Where it stands
The diagnosis is the product: instead of guessing, the owner gets a ranked list of citation gaps — the specific third-party pages and on-site content that AI answers in their city actually draw from. The sample report below shows this exact report format on real scan data.
View the sample report →
Self-experiment — content strategy

Testing whether targeted pages move AI answers

The question
The core promise of GEO is that the right content changes what AI recommends. Before asking customers to believe that, we test it on ourselves.
What we did
Using our own citation-gap data, we published targeted educational and comparison pages, then let the weekly monitoring loop measure mention-rate changes over subsequent scans — the same fix-verification loop that ships in the Optimize plan.
Where it stands
This experiment is running now and the numbers will be published here — including if they are disappointing. We would rather show a real, slow curve than an invented hockey stick.

Your story could be here

If you are using RankedByAI during the open beta and it helped you find (or fix) an AI visibility gap, we would love to feature your story — with your permission and your real name, or anonymized if you prefer. Email support@zalize.com with what you found.

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