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The Best Way to Automate Product Content on Shopify

paula gould — Thu, 09 Jul 2026 13:51:53 GMT

What's the Best Way to Automate Product Content on Shopify(Without Spending Hours on Every Product)?

Launching new products should be exciting but for many online merchants, the mechanics and process of getting their products online is time-consuming and costly.

50 Product Attributes Every Fashion Store Should Have For Structured SEO and GEO – Catecut

Catecut Team — Fri, 13 Mar 2026 00:00:00 GMT

Fashion brands spend enormous effort improving product descriptions, photography, and marketing campaigns. But one of the biggest SEO opportunities in fashion e-commerce is often overlooked: structured product attributes.

Search engines, filters, recommendation engines, and on-store search all rely on structured product data. When important product and design attributes are missing or inconsistent, valuable product information gets lost, and never reaches the shopper, or search engines.

Many of these attributes are visually identifiable from the product imagery that the brands already produce, which makes the product images one of the brand’s most valuable assets, more than they may even realize. We’ll get back to that further along in this post.

In the mean time, here are 50 product attributes every fashion e-commerce store should have to best structure pages to improve discoverability, filtering, SEO and GEO.

Core Product Identification

These attributes define the fundamental identity of a product, and some are derived from visual features, while others are typically managed in the store backend.

Visually identifiable attributes

•Product type (dress, shirt, jacket, pants)

•Product subtype (mini dress, maxi dress, cropped jacket)

•Silhouette

•Garment length

•Sleeve length

•Neckline

•Shoulder style

Typically managed by the store

•Brand

•Season

•Gender

Attributes such as collection, SKU, and style name are usually handled in the store or PIM system rather than derived from imagery.

Fit and Structure

Fit is one of the most common ways customers search for fashion products.

Structuring these attributes helps both SEO and product filtering.

•Fit (slim, relaxed, oversized)

•Waist rise

•Leg shape

•Hem Typs

•Sleeve shape

•Collar type

•Closure type

•Waistband style

•Layering structure

•Garment construction details

These attributes describe how the garment is built and how it sits on the body.

Materials and Fabric Characteristics

Material searches are extremely common in fashion e-commerce.

Customers frequently search for products based on fabric type or feel.

•Fabric type

•Material composition

•Knit or woven

•Fabric texture

•Fabric weight

•Stretch level

•Lining

•Padding or insulation

•Sheerness

•Surface finish

Many of these characteristics can be inferred visually or combined with supplier data.

Visual Characteristics

Visual attributes play a huge role in both search and product filtering.

•Color

•Color family

•Pattern

•Print type

•Embellishments

•Distressing

•Wash type (denim)

•Transparency

•Shine or matte finish

•Surface texture (smooth)

These attributes are often clearly visible in product imagery but are frequently missing from structured product data.

Functional and Design Features

These attributes describe practical or design-specific features that customers often search for.

•Pockets

•Adjustable elements

•Belt loops

•Slits

•Layering components

•Reversible design

•Detachable elements

•Thermal or weatherproof properties

•Breathability

•Care instructions

These features help customers better understand how a garment functions.

Why Structured Attributes Matter for SEO

Most fashion stores store product knowledge across multiple places:

•Product imagery

•Design briefs

•Merchandising spreadsheets

•Manufacturer or Supplier documentation

•Product tags and shipping documents

•Product descriptions and titles

•PIM system

But search engines can’t easily interpret unstructured information.

When attributes are structured properly, product pages can rank for far more specific search queries. For example, instead of ranking only for black dress, a structured product page might rank for:

•Black satin mini dress

•Sleeveless satin evening dress

•Fitted black cocktail dress

•Black sleeveless party dress, or even

•Black satin sleeveless princess neckline mini dress with side zip closure and front slit pockets

Structured attributes enable thousands of long-tail combinations automatically.

The Real Challenge: Extracting Product Attributes

The problem isn’t knowing which attributes matter. The problem is capturing them consistently. Manually structuring dozens of attributes per product is time-consuming, especially for fashion brands launching hundreds or thousands of products each season. And much of the information needed to describe a product is already visible in the product imagery.

Where Automation Changes the Workflow

Instead of manually tagging products, new approaches to automation focus on analyzing product imagery. From product images, technology can detect attributes such as:

•Product type

•Garment length

•Sleeve length

•Neckline

•Silhouette

•Pattern

•Fabric characteristics

These attributes can then be structured automatically and returned directly to the store backend.This allows brands to structure far more product data without increasing manual work

How Catecut Approaches Product Data

Catecut focuses on turning product imagery into structured product attributes that can be used directly in e-commerce platforms. Instead of introducing another complex system, Catecut acts as a lightweight layer that:

•Understands fashion imagery

•Extracts visible product attributes

•Structures attributes into data and information

•Returns the data and information directly to the platform or PIM in the correct format

The result is faster product launches, richer product pages, and more consistent product data across the catalog.

The Future of Fashion Product Data

As fashion catalogs grow larger, structured product attributes are becoming increasingly important for:

•Search engine and generative engin optimisation (SEO / GEO)

•Filtering

•Internal search

•Personalisation

•Product recommendations

Brands that structure product data effectively create a strong foundation for discoverability and automation. And increasingly, the most scalable way to structure that data begins with something every fashion brand already has: product imagery.

The Real Bottleneck Behind Fashion Product Pages – Catecut

Catecut Team — Sun, 01 Feb 2026 00:00:00 GMT

When people talk about automation for product detail pages (PDPs) in e-commerce, the conversation usually focuses on generating content or SEO tags.

But anyone working in fashion e-commerce knows the real challenge isn’t writing product descriptions. It’s the process behind the product page.

The Hidden Workflow Behind Every Product Page

A fashion product page might look simple to a customer. But internally, it’s the result of a surprisingly complex workflow.

It often starts with product imagery. From there, information flows through multiple teams:

Merchandisers define product attributes

•Copywriters write descriptions

•SEO specialists add tags and metadata

•Product teams manage structured product data

•E-commerce managers prepare products for launch

Each team contributes a piece of information that eventually needs to land in the correct fields inside the store backend. And this is where the problems start.

Product Information Gets Lost

Because product information is created across different teams and tools, everyone from the manufacturer to the marketing team, and everyone in between, the process often becomes fragmented:

•Product attributes are stored in spreadsheets

•Tags are missing and terminology is inconsistent

•Descriptions are written without structured product data and details

•Valuable product knowledge never reaches the product page

The result is slower product launches and PDPs that fail to communicate all of the information customers need to make purchase decisions.

In fashion e-commerce, details matter. Everything from materials, fit, structure, and construction factors into purchase decisions, but also how those products show up in search, whether online or on the store’s filters. In short, missing information directly impacts product discovery and conversion.

Why Traditional Automation Doesn’t Always Work

The product content bottleneck leads many brands to introduce new systems and solutions, designed to manage product data, into their e-commerce stack.

But this often leads to unforeseen challenges for the online store.

The most common among these challenges are complex integrations and new workflows the e-commerce and content teams must learn. Likewise, additional operational overhead may emerge. The combination of these hurdles, means longer durations before their value is actualized.

For many brands, the cost and disruption of these integrations outweigh the potential benefits.

A Different Approach to Automation

Instead of replacing systems, what if automation could work as a lightweight layer on top of existing workflows? Starts with the product imagery brands already have, the solution layer can automatically:

•Detect product design attributes

•Structure them into product data

•Generate product and attribute tags, and

•Populate store product detail page fields directly on the backend.

The e-commerce and content teams transition into publishing teams.

No heavy implementation. No operational disruption. Just faster, more consistent product data and content.

The Future of Retail Software

Smart automation reflects a broader shift happening in fashion retail digital transformation. Brands can now integrate quickly, and their e-commerce creates value immediately with minimal operational changes and no long-term vendor lock-in.

Automation shouldn’t force companies to rebuild their workflows nor start from scratch when they move between platforms. It should simply make them work better.

That’s the direction we believe fashion e-commerce software is heading. And, it’s the problem Catecut is solving today.

Want to learn more about AI in Fashion Retail?

TGC Capital Partners invests in AI Vision and Product Content Automation Solutions Company Catecut – Catecut

paula gould — Wed, 05 Nov 2025 00:00:00 GMT

Reykjavik, Iceland (5 November 2025) Icelandic artificial intelligence company, Catecut (Sowilo ehf.), has signed an investment and cooperation agreement with multinational investment firm TGC Capital Partners. Catecut is quickly becoming a leader in developing AI Vision for automated product content for fashion e-commerce. Their solution addresses massive and costly product information accuracy and logistics issues, while expediting the ability of clothing brands and fashion marketplaces to get their products for sale online faster. Catecut is currently being used by several large international fashion brands.

TGC Capital Partners is the investment arm of the global software conglomerate Gateway Group of Companies. The company reviews over 300 investment opportunities annually. It specialises in investing in high-growth innovation companies that can have potential for tangible global impact, and can quickly capture their respective markets.

“Catecut has uniquely and strategically built its solution for the global e-commerce fashion market. We at TGC and Gateway believe in their vision for the future of fashion retail, and have the network and experience to support their ambitious goals,” says Ingi Björn Sigurðsson, Investment Manager at TGC Capital Partners. “We invest in entrepreneurs who have the perseverance and expertise needed to solve big global challenges while maximising value in their business sectors. That certainly applies to Heidrun Osk Sigfusdottir, the team she is building, and their technology.”

“It is invaluable to receive this support from TGC and Gateway to scale both our technology and provide the foundational capital necessary to bring our solution to fashion brands and marketplaces in markets worldwide,” said Heidrun Osk Sigfusdottir, Founder & CEO of Catecut. “We at Catecut have built our AI Vision engine into a valuable product content automation solution for the fashion industry, specifically to address the significant hurdles they face in staying competitive, while best catering to shopper needs during the shopping experience. The investment and collaboration with Gateway ensures that we have world-class experts immediately and can expedite our market entry strategy efficiently.”

Catecut automates the product content and information creation and distribution process using product imagery of clothing and accessories to identify design elements and attributes– in multiple languages. It then instantly creates and populates online store product pages with accurate, engaging product descriptions, care instructions, and important underlying metadata and search tags, saving brands and marketplaces valuable time and money. The result is faster product availability online and informed shopping experiences that drive better purchase decisions. Brands and marketplaces leveraging Catecut’s solution span North America, Europe, The Nordics, and Singapore. For more information, visit catecut.com or tgccapitalpartners.com.

ÍS

TGC Capital Partners fjárfestir í Catecut

Reykjavík, Ísland (5 nov. 2025) Íslenska gervigreindarfyrirtækið Catecut hefur undirritað samstarfssamning við fjölþjóðlega fjárfestingafyrirtækið TGC Capital Partners um samvinnu og fjárfestingu. Catecut er leiðandi í að þróa sjálfvirkar vörulýsingar fyrir föt sem eru seld í gegnum vefverslanir. Lausnin er byltingarkennd og er komin í notkun hjá nokkrum risa vörumerkjum.

TGC Capital Partners er fjárfestinga armur alþjóðlegu hugbúnaðar samsteypunar Gateway Group of Companies. Fyrirtækið sérhæfir sig í að fjárfesta í fyrirtækjum sem geta vaxið hratt inn á markað. Fyrirtækið hefur tekið ákvörðun að fjárfesta í Catecut, árlega skoðar fyrirtækið yfir 300 fjárfestingakosti gaumgæfilega.

“Lausn Catecut er framúrskarandi og við höfum trú á því með fjárfestingum og samstarfi við okkur þá getur lausnin vaxið á ógnar hraða. Okkar markmið er að fjárfesta í frumkvöðlum sem einbeita sér að búa til verðmæti fyrir viðskiptavini sína. Það á svo sannarlega við um Heiðrúnu og hennar teymi. Þrautseigja hennar hefur verið ótrúleg og er öðrum frumkvöðlum til eftirbreytni” Segir Ingi Björn Sigurðsson fjárfestingarstjóri TGC Capital Partners.

“Það er ómetanlegt að fá stuðning frá TGC og Gateway til þess að skala bæði tækni og útbreiðslu lausnarinnar á erlendan markað. Við hjá Catecut höfum verið lengi að og erum núna komin með lausn sem markaðurinn hefur verið að bíða eftir og viðtökurnar hafa farið fram úr okkar björtustu vonum. Fjárfestingin og samstarfið við Gateway tryggir að við höfum aðgang að sérfræðingum á heimsmælikvarða,” segir Heiðrún Ósk Sigfúsdóttir.

“Lausninni verður dreift óháð landamærum, við hjá TGC og Gateway höfum risavaxið tengslanet sem við ætlum að nýta til þess að koma lausninni sem víðast. Dæmi um markaðssvæði sem við ætlum að skoða með Catecut er Asía. Vandamál vefverslanna þar eru þau sömu og alls staðar, hvort sem það er á Íslandi eða Asíu, nema skalinn er mikið stærri inn á stærri mörkuðum. Við hlökkum til að vinna með Catecut á vegferð þeirra til vaxtar” Segir Ingi Björn Sigurðsson

Catecut sjálfvirknivæðir lýsingar á fatnaði með því að nota myndir af fatnaði og fylgihlutum til að bera kennsl á hönnunarþætti og eiginleika – á mörgum tungumálum. Kerfið býr samstundis til nákvæmar og aðlaðandi vörulýsingar sem eru sýnilegar á vörusíðum netverslana, ásamt leiðbeiningum um meðhöndlun sem sparar vörumerkjum og markaðstorgum dýrmætan tíma og fjármuni. Niðurstaðan er hraðara vöruframboð á netinu og nákvæmari vörulýsingar sem leiðir til betri kaup ákvarðana. Vörumerki og markaðstorg í Norður-Ameríku, Evrópu, Norðurlöndunum og Singapúr nýta sér lausn Catecut

Fyrir frekari upplýsingar, heimsækið catecut.com og tgccapitalpartners.com

What is AI Computer Vision in Fashion Retail and E-commerce? – Catecut

paula gould — Wed, 22 Oct 2025 00:00:00 GMT

What is AI Vision (Computer Vision, Image Prediction)? Why Is Highly Trained AI Important In Fashion Retail?

Think of AI Vision like the eyes and brain to your backend e-commerce processes. It allows for software to “look at” images or videos and understand what’s in them—just like humans do, except the analysis output can be vast and instant.

General AI Vision (AI models) can analyse and interpret an image with, say, a jacket, and return simplified attributes of that jacket.

However, highly-trained AI goes deeper, understanding that jacket in detail, down to:

🧥 The type of jacket, and its collar and lapel

👗 The silhouette or structural details (e.g. closures, fit, seam type, sleeve, cuff)

👖 The material (e.g., waxed cotton vs. denim vs. leather)

🌻 The pattern (e.g., plaid, floral, solid)/

🎨 The color palette

🪩 Even styling cues (e.g., business vs. casual vs. formal)

But, why does AI Vision matter for fashion retail?

For executives, merchandisers, and e-commerce managers, this is a game changer because it provides their teams with:

🏷️ Faster tagging and categorization of thousands of products

🔎 More accurate filtering and search results for shoppers (“show me high-rise flared jeans”)

🫶 Better recommendations (based on style, not just keywords)

ℹ️ Richer product descriptions and SEO (AI can generate content from image analysis)

🛍️ Higher discoverability and conversion—products show up where they should

Catecut built its own, custom AI Vision models. It leverages known general models to do initial categorisations, then uses its powerhouse proprietary AI to interpret clothing and jewelry within product imagery, identifying design attributes and structural details, spinning those details back out to a brand or marketplace’s online store to fully populate the store’s product pages with accurate, engaging information to best inform shoppers.

Catecut offers the ability to leverage longer descriptions and shorter descriptions, depending on the preferences of your brand, whether you offer stunning clothing collections or fine jewelry. Behind your fully populated PDPs (product description pages), your online store is simultaneously enriched with the search data and tags needed to make shopping on your store more precise and to draw new shoppers in. We know brands and marketplaces are on hunt for AI Vision to make e-comm more efficient. Often times, large language models and image vision solutions promise more than they can deliver. Our AI models are specifically hand-trained on the multitude of design elements of clothing and accessories.

We offer the granular identification you’ve been searching for, alongside the instant and fully populated product pages you need to get your products onto your store faster, leading to sales and searchability in seconds.

That’s what sets us apart!

How is Catecut Different

Catecut Team — Sun, 20 Apr 2025 18:12:10 GMT

Catecut welcomes retail executive, Aslaug Magnusdottir, to its Board of Directors – Catecut

paula gould — Mon, 14 Apr 2025 00:00:00 GMT

Reykjavik, Iceland (14 April 2025) Catecut, an AI-powered platform that automates product tagging and SEO optimization for fashion e-commerce, announced today that Áslaug Magnúsdóttir—founder of Katla, former co-founder and CEO of Moda Operandi, and Gilt Groupe executive—has joined its board.

“Áslaug is a highly respected innovator who has driven digital transformation in high-end fashion retail and e-commerce globally for 20 years, said Heiðrún Ósk Sigfúsdóttir, co-founder and CEO of Catecut. “She has already had an incredible impact on our company, lending her depth of fashion retail expertise to inform our strategies and help guide our market entry. We’re honored to have her serve on our board.”

“Catecut’s team has the experience and technology to truly shift fashion e-commerce by focusing on many of its most critical operational, customer experience, and business intelligence hurdles,” said Áslaug Magnúsdóttir.

Catecut released its automated product tagging solution earlier this year, introducing it to European fashion retailers at the Copenhagen International Fashion Fair in February, and to North American and European brands during Shoptalk in Las Vegas in March. Catecut was also previously selected as one of four startup companies to watch in retail, presenting on stage during the Total Retail Tech startup pitch event in North Carolina in the fall of 2024.

About Catecut

Catecut is an Icelandic technology company that develops solutions for e-commerce with the goal of shaping how fashion brands and retailers reach, service, and deliver efficiency and value to their online shoppers. Its AI-enabled deep tagging technology for apparel product imagery automatically creates more in-depth and precise product descriptions, provides valuable metadata, and strengthens SEO and GPT prompt performance. Catecut has been awarded a development grant, Vöxtur, from the Technology Development Fund at RANNÍS, and a marketing grant from the Women’s Employment Project Fund (Atvinnumál Kvenna Styrkur). For more information, please visit catecut.com.

(Íslenska)

Catecut býður Áslaugu Magnúsdóttur framkvæmdastjóra smásölu velkomna í stjórn

Reykjavík, Ísland (14 Apríl 2025) Catecut, sem hefur þróað öflugt gervigreindarlíkan sem greinir eiginleika fatnaðar út frá aðeins myndum og skilar sjálfvirkt vörulýsingum og SEO-merkingum á vörusíður fatasala, tilkynnti í dag að Áslaug Magnúsdóttir hafi tekið sæti í stjórn félagsins. Áslaug er stofnandi tískumerkisins Katla, meðstofnandi og fyrrverandi forstjóri Moda Operandi og fyrrverandi stjórnandi hjá Gilt Groupe.

„Áslaug er einn virtasti frumkvöðull tískuheimsins og hefur leitt stafræna breytingu í lúxustísku og netverslun á heimsvísu síðustu tvo áratugi,“ segir Heiðrún Ósk Sigfúsdóttir, meðstofnandi og framkvæmdastjóri Catecut. „Hún var jafnframt valin ein af 50 valdamestu konum í tískuheiminum af vefritinu Fashionista. Hún hefur nú þegar haft jákvæð áhrif á stefnumótun okkar með innsýn sinni í alþjóðlegan tískuiðnað. Það er okkur sannur heiður að fá hana í stjórn.“

„Teymið hjá Catecut hefur þá reynslu og tækni sem þarf til að umbreyta netverslun með fatnað með því því að leysa margar raunverulegar áskoranir í rekstri, og upplifun viðskiptavina,“ segir Áslaug Magnúsdóttir.

Catecut kynnti sjálfvirka vörumerkingarlausn sína fyrr á árinu og hefur þegar vakið athygli á alþjóðlegum vettvangi. Lausnin var kynnt fyrir evrópskum tísku vörumerkjum á Copenhagen International Fashion Fair í febrúar og fyrir norður-amerískum og evrópskum vörumerkjum á Shoptalk í Las Vegas í mars. Á síðasta ári var Catecut einnig valið eitt af fjórum efnilegustu sprotafyrirtækjum í smásölu og tók þátt í startup-vettvangi á Total Retail Tech ráðstefnunni í Norður-Karólínu.

Um Catecut

Catecut er íslenskt tæknifyrirtæki sem notar myndgreiningu til að bera kennsl á fatnað og merkja eiginleika fatnaðar sjálfvirkt, sem skilar sér í dýpri vörulýsingum og bættri leitavélabestun (SEO) fyrir netverslun með það að markmiði að draga úr ósamræmi í vöruupplýsingum, miklum tilkostnaði við handvirka skráningu og skapa betri og notendavænni netverslun.Lausnin samræmir efni, bætir leit og síun, og veitir kaupanda mun betri lýsingu á vörum.

Catecut hefur hlotið þróunarstyrk Vöxt frá Tækniþróunarsjóði RANNÍS og markaðsstyrk úr Atvinnumálum kvenna.

Nánari upplýsingar er að finna á catecut.com.