SEO & GEO case study: how to make a fashion brand visible beyond its name

The challenge: growing beyond loyal customers

The site ticks every box: 78/100 for SEO, content quality rated 85/100 and more than 2,000 product pages. Customers who already know the brand find it with no trouble.

But a fashion brand does not grow on loyal customers alone. It grows thanks to shoppers searching for "a long dress for vacation" who do not know it yet, on Google or through an AI. The starting question: does the brand exist for those shoppers?

To answer it, the audit combined two sources: classic SEO, using real Google data, and GEO (Generative Engine Optimization), meaning the ability to be cited in AI answers.

The diagnosis: 3 findings

Finding 1: on Google, traffic comes almost entirely from the brand name

The Search Console data (March to June 2026) leaves no doubt. The homepages capture most of the clicks, and their top queries are all variations of the brand name. Product pages, on the other hand, are almost invisible.

In other words, Google knows the brand, but almost never shows it to someone simply looking for a dress.

Finding 2: in AI answers, it is worse: zero citations

REVVDA analyzed 1,350 answers from GPT-5 mini, Claude Sonnet 4.6 and Gemini 2.5 Flash to buying questions. The result: 819 brands cited, and never the client's.

Yet when the brand is named, AI models know it at 99/100 and have nothing bad to say about it (+47). They describe it as chic and relaxed, made for vacations. Their reservations: price, availability and sizing.

What Google cannot see, AI will not recommend.

A telling detail: on queries such as "satin" or "cotton dress", AI models mostly cite… fabric retailers. The words the brand uses are not the words its customers use.

Finding 3: pages that machines cannot read

1. 01

   No usable structured data (0/25). 318 pages do not tell search engines what they contain: product, price, FAQ, breadcrumbs. (How to audit schema.org coverage across a large catalog.)

2. 02

   Weak HTML structure (7/15). The content is not marked up in clear sections that AI models can break down. (How to fix weak semantic HTML once, at template level.)

3. 03

   Few quotable sentences (6/20) and few facts (3/15). A typical product page has 571 words, but not a single measurable fact or trust signal.

4. 04

   SEO basics to fix. Missing or duplicate H1s, missing or overly long meta descriptions, images without alt text, and 20 empty or placeholder pages to clean up.

Lack of facts was also the main blocker we found at an e-commerce coffee roaster missing from 3,415 AI answers.

The solution: prioritize with real Google data

This is the audit's great strength. Actions are not ranked "on instinct", but according to real demand measured in Search Console. You start where there are already impressions to turn into clicks. (How to use Search Console data to choose which keywords to work on.)

Step 1: the quick wins that reach the most searches

Step 2: make the brand readable and quotable

• ●Structured data everywhere: Product, FAQPage, BreadcrumbList and Organization schemas, delivered as ready-to-use code.
• ●Quotable proof blocks on key pages: fabrics, fits, care, in short, factual sentences.
• ●Comparison content to position the brand against the names AI models cite instead.
• ●The customers' vocabulary: "long dress for vacation" rather than fabric names alone.
• ●A reference guide to the long dress, written in the brand's tone of voice and scored 97/100 before publication, with its own FAQ.

What does a fix look like?

Every action becomes a ticket with the before, the after and the rationale. Example on a product page title tag:

• ●Before: "Model name – Color | Collection | Brand".
• ●After: "Model name: black embroidered cotton long dress | Brand".

The product is finally described in the words a shopper would actually type. (How to fix missing meta descriptions, H1s and titles across thousands of pages.)

Key takeaways

1. 01

   A well-known brand is not a findable brand. If your traffic comes from your name, you only reach your loyal customers.

2. 02

   Google and AI fail for the same reasons. Poorly marked-up pages, no facts, none of your customers' vocabulary: SEO and GEO must be worked on together.

3. 03

   Prioritize with your data, not your gut. Start with the pages that already have impressions to convert.

FAQ