Get your collections recommended by AI assistants

What you’re looking for when you search “AI visibility for fashion brands”

You run a fashion or apparel label and your customers now ask AI assistants what to wear and where to buy it: “linen shirts made in Europe”, “jeans that fit curvy hips”, “what to wear to a summer wedding”. The answer names a few labels and retailers, and shoppers rarely look further. You want to know whether your label is among them, whether the assistant gets your fabrics, fit and sourcing right, and what to change on your site. Behind that search sit four questions:

• Is my label named when shoppers ask AI assistants for pieces like the ones I make?
• Do the answers describe my fabrics, fit, sizing and sourcing correctly?
• Which labels and retailers are named instead, and which magazines or forums do the answers quote?
• Which style and fit content should I publish so assistants have something accurate to cite?

What Rankfender does for fashion labels

Rankfender sends the style and where-to-buy questions your customers ask to 8 AI assistants (ChatGPT, Claude, Gemini, Perplexity, DeepSeek, Grok, Llama and Mistral) and records every reply. For each one you see whether your label appears, its rank in the list, the sentiment and the magazines, forums or retailers cited. Breakdowns by topic and buyer profile show which customers you reach and which you miss. The audit checks that product, size guide and collection pages can be read, and the writer drafts fit and style guides from real sources.

• How often your label is named for each style question, per assistant, next to the labels named instead
• The exact words assistants use about your fabrics, fit and sourcing, with the pages they drew on
• An audit of product, collection and size guide pages: crawler access, Product schema, sitemap and orphan pages
• Fit guides, fabric explainers and style articles written from a keyword, with a Sources list