Paz for fashion and apparel brands
Fashion catalogs change every season and shoppers ask precise questions: fit, fabric, length, what to wear it with. Paz handles the product-information work behind product-page SEO, AI visibility, content and feeds for apparel brands. Our experts agree the priority collections with you, fix what the data can fix and track the result.
What you get: Size, fit, material and color details complete on every priority style, variants that stay eligible in Google Shopping through the season, and more of your products in the answers shoppers get when they ask ChatGPT or Google AI Mode what to buy.
What gets in the way
The product-information problems we see most often in fashion catalogs.
Fit and size questions go unanswered
Shoppers ask whether a jacket runs small, how long an inseam is or whether a fabric stretches. When the product page and feed leave that out, search and AI answers quote a competitor that filled it in.
Variant sprawl in the feed
One style can mean forty SKUs across sizes and colors. Missing color, size, size_type or item_group_id values on part of the range leave single variants disapproved or grouped wrongly in Merchant Center.
Seasonal drops outpace the catalog team
New drops land with supplier copy, placeholder titles and no material or care attributes. The pages that matter most in the first weeks of a season are often the least complete.
Titles written for the line sheet
Internal style names and codes in titles mean product pages rarely match how shoppers search, such as wide leg linen trousers or petite wool coat.
The work on one product
From a signal on one product to the next check, the way it runs on every priority product in your catalog.
The signal
A priority collection of women’s coats is missing from AI answers to “warm wool coat for a petite frame”, while a competitor with thinner stock is named every time.
What Paz reads
Paz reads the product records, the feed and the stock in your ERP together. The coats carry a fabric composition and a petite size run in the PIM, and the product pages and feed show neither.
What our experts ship
Our experts add the wool percentage, lining and petite sizing to the product pages, map the size_type and material fields in the feed and rewrite the titles to the fabric and fit shoppers search for.
What we check next
The tracked question is checked again across ChatGPT, Google AI Mode and Perplexity, Merchant Center status is verified after the next sync and clicks on the coat pages are compared with the baseline.
What's included
The work a Paz expert carries for you, month after month.
Priority styles agreed
Collections, seasons and margins decide which styles get attention first.
Fit and fabric completed
Size, fit notes, material, care and color filled from your PIM, supplier data and samples.
Variants kept eligible
Size, color and item group fields corrected so the full range stays in Google Shopping.
Titles that match searches
Style names rewritten to the garment, fabric and fit shoppers type.
Shopping questions tracked
Fit, occasion and fabric questions checked across ChatGPT, Google AI Mode and Perplexity.
Season reviewed
Appearances, disapprovals and clicks reported against the baseline, next drop planned.
How it runs
Start with your priorities
Collections, margins, seasons, buyer personas and the questions that matter. One Paz expert is your point of contact.
Paz reads your systems
Catalog, Merchant Center, analytics and search data read together, against those priorities.
Our experts ship
Within your approved guidelines. Anything that needs your attention comes to you first.
We measure and go again
Every change is tracked against the baseline, and what happened shapes the next round.
Frequently asked questions
How does Paz handle a new seasonal drop?
We agree the priority styles before launch and complete fit, fabric and sizing from your sources as the products land, so the pages and feed are complete in the first weeks when the drop gets the most attention.
Can Paz work with our size guides and fit notes?
Yes. Size charts, fit notes and material specifications from your PIM, supplier sheets or product team are the sources we write from. If your sources disagree, we check with you before changing anything.
Which fashion questions do you track in AI answers?
Questions built from your buyer personas and collections, such as fit, fabric, occasion and budget. We report which products appear, which competitors appear instead and what changed after each round.
Put Paz to work for your store.
Tell us where you need help with SEO, AI visibility, product content or feeds. We’ll discuss your priorities and recommend where to start.
Services: Ecommerce SEO · AI visibility · Product content · Product feeds