How visible is Sussan in AI?

How often each AI engine names Sussan when buyers in Australia ask about women's everyday fashion, where Sussan ranks against other brands in each Radar market it appears in, and which websites those engines cite in the market’s answers.

The share of an engine’s answers to a market’s buyer questions that name the brand. Each question is asked once to each engine. It describes how often the engine names Sussan, not Sussan’s position in the market itself.

Within one market and one engine, brands are sorted by mention rate; Sussan’s place in that list is its rank. Every rate carries a 95% range, and when the ranges of two brands overlap, treat their ranks as tied rather than one ahead of the other.

Each engine is trained on different data, reads different live sources and weighs them its own way. Radar measures and ranks every engine on its own and never averages them, so a gap between engines shows where Sussan is visible and where it is missing.

Each market has its own buyer questions and its own set of competing brands, so the same brand earns a different rate in each. This page covers only the markets Radar has published; a market where the brand is not in any engine’s published top list is not shown.

A link to a website that an engine shows as a source with its answer. The sources on this page are counted across all of the engine’s answers in the market, not only the answers that name this brand.

Engines recommend brands based on what other sites say about them. Associations, publishers, retailers and platforms are cited far more often than brand sites, so a brand can be named in an answer whose sources are all third-party pages.

Every market is a dated measurement — the women's everyday fashion figures on this page were collected in Oct 2026. When a market is measured again, the numbers and the date on the page change together.