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Ecommerce: Apparel and fashion

Best SEO and GEO agency
for apparel and fashion brands.

Shoppers ask whether your jeans run small, what to wear to a fall wedding and which merino tee survives a week of travel. Passionfruit makes your brand the one named in those answers, on Google and in ChatGPT.

Fashion shoppers ask about the body, not the brand

  1. Sizing is the first search

    Queries like “does it run true to size” and “best jeans for short legs” come before any brand name. The page that answers fit honestly gets cited.

  2. Occasions spike and vanish

    Wedding guest, graduation and holiday party searches rise for a few weeks a year. A collection page built in the week of the spike is already too late.

  3. Resale and dupes sit in the answer

    AI answers now mention Poshmark listings and “dupe” alternatives next to full-price brands. Your own pages have to explain why yours is worth it.

Questions shoppers type before they try anything on

Fit, fabric and occasion questions like these lead fashion search. We run them across ChatGPT, Gemini, Perplexity and Google AI Overviews and record which brands and retailers get named.

  • Do these jeans run small or true to size?
  • Best linen pants that don’t look wrinkled by noon
  • What to wear as a guest at a black-tie optional wedding
  • Merino wool t-shirt that lasts more than one season
  • Petite-friendly workwear brands for women under 5’3”
  • Cheaper alternative to a $200 cashmere sweater

The fashion listings standing between you and the buyer

Retailers, marketplaces, editors and resellers all rank for searches that should be yours. Each listing has a gap, and that gap is where we take the ranking and the citation.

Department store listings: Nordstrom, Macy’s, Revolve

Their gap
Their category pages carry hundreds of brands and one line of copy about each.
Your opening
We build your collection and fit pages with the measurements, fabric weights and styling detail those grids leave out, so Google ranks you and AI quotes you for the fit and occasion questions.

Marketplace listings: Amazon Fashion and Zalando

Their gap
Marketplace product pages follow a generic template and often carry thin or inconsistent sizing data.
Your opening
We make your product pages the complete record for materials, care and fit, with structured data engines can read, so the answer points to your store instead of a reseller.

Editorial roundups: Vogue, Who What Wear, GQ

Their gap
Many “best of” lists are written once and refreshed rarely, so their picks drift out of stock and out of date.
Your opening
We publish current, specific buying pages for those same queries and earn your pieces a place in the next edit, so you win the answer either way.

Resale listings: Poshmark, The RealReal, Depop

Their gap
Resellers rank for your brand and style names once a piece sells out.
Your opening
Evergreen style pages on your own site keep those searches, sending buyers who ask for a past favorite to its current version at full price.

See who AI recommends instead of you.

Book a call and we will run these searches live for your brand.

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Where AI looks to judge fit and quality

Engines lean on these sources when they recommend clothing. We work on each one.

  1. r/femalefashionadvice and r/malefashionadvice

    Long threads on fit, fabric and value get cited constantly. We find the threads about your category and contribute disclosed, useful answers.

  2. r/BuyItForLife

    The reference for durability claims. We surface your materials, construction and repair policies where those threads ask for lasting basics.

  3. Your own reviews and fit data

    Fit summaries such as “runs small” are quoted from review widgets. We structure reviews with Review schema so engines read sizing feedback correctly.

  4. Fashion editorial roundups

    Vogue, Who What Wear and GQ lists are cited for “best” prompts. Clear specs and linkable pages make your pieces easy for editors to include.

  5. YouTube try-on hauls

    Try-on videos are cited for fit questions. We map which creators cover your category so your team knows where seeding matters.

Search problems only apparel catalogs have

Fashion sites break search in ways other stores rarely do.

  1. 01Size and color variants that split authority

    One dress in eight colors and six sizes can become dozens of near-identical URLs. We set canonicals and variant handling so one strong page ranks and every color is still findable.

  2. 02Seasonal styles that sell out

    Sold-out pages get deleted and their rankings go with them. We keep evergreen style URLs, redirect retired products to their closest successor and bring back pages when a style returns.

  3. 03Vague fabric and fit language

    “Soft” and “relaxed” tell engines nothing. We rewrite product pages with fiber content, weight, rise, inseam and model measurements, the facts AI actually quotes.

Find out which of these is costing you most.

Book a call and we will rank them by the revenue at stake on your own site.

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The fashion search calendar

Demand in apparel follows the season, and the pages need to be indexed before each peak.

  1. January to February

    Resolution activewear and Valentine’s Day dressing. Publish activewear and date-night pages in early January.

  2. March to June

    Wedding guest, prom and graduation outfits. Occasion pages should be live by early March.

  3. July to August

    Back-to-school and college basics, plus the first fall transition searches.

  4. September to October

    Fall layering, outerwear and denim refreshes, the heaviest category searches of the year.

  5. November to December

    Black Friday, holiday party outfits and gift searches for sweaters and accessories.

Every part of the program, cut for fashion

Fashion sells on fit, fabric and occasion, so each part of the work is built around those three questions.

Fit guides, occasion edits and fabric explainers written from the questions shoppers ask before they buy, like what to wear to a fall wedding or whether linen wrinkles. These are the searches department store grids answer with a product carousel and no advice, which is why a brand guide can outrank them.

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Why Passionfruit for apparel and fashion

We work with apparel brands where the hardest search problems are structural: thousands of variants, styles that sell out every season and fit questions that decide the sale. Our platform audits your catalog daily, so duplicate variant URLs and dead product pages are caught as they appear, not at the end of the quarter.

The content work starts from how people really shop for clothes. We pull the fit and occasion prompts buyers ask AI, read which retailers and editors get named, and build the collection and product pages that answer those questions with measurements and fabric facts instead of adjectives.

Results are reported by collection and season in GA4, so you can see whether last spring’s wedding guest page paid for itself, and what to build before the next drop.

What we measure

  • Collection and season revenue earned through organic and AI search
  • How often your brand is named on fit and occasion prompts
  • Rankings for non-branded fit queries ahead of each seasonal peak
  • Product pages holding rankings after a style sells out
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Questions

Can we outrank Nordstrom and Revolve for our own products and categories?

Yes. Your own brand and product names should rank first, and complete product pages get you there. For category terms, we take the fit, fabric and occasion searches where retailer grids say the least, then widen from there.

How should we handle color and size variants for SEO?

Usually one indexable product URL with variants selectable on the page, plus separate pages only for colors with real search demand. We set the canonicals and feed rules to match.

What happens to rankings when a seasonal style sells out?

Keep the URL live with a back-in-stock option or redirect it to the closest current style. Deleting it throws away the rankings and links it earned.

Can we show up when people ask AI for a dupe of a more expensive brand?

Yes, with honest comparison content that lists materials, construction and price side by side. Engines quote specific differences, not marketing claims.

Do fit reviews really affect AI answers?

Yes. Engines often summarize sizing from reviews and Reddit threads. Structured reviews with fit fields, and clear size guides, make those summaries accurate.

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Get found and chosen in AI answers.

Book a call and we will show you where Google and AI answers leave you out today, and what we would ship first to get you in.