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DSW Multi-Brand Footwear Catalogue & Size-Width Stock Dataset

Q: Is width captured separately?

It is captured inside Size as “9 - Medium”. We can split size and width into separate columns on a custom feed at no extra cost.

DSW is one of America's largest footwear retailers, and this file captures its catalogue at size and width level — 31 columns covering list price, final price, discount, stock flag, brand, merchandising tags, ratings and images.

It is a multi-brand shelf — Vince Camuto, Brooks, Birkenstock, Kelly & Katie in the sample — and a heavily promoted one: 41 of 50 rows were discounted, up to 46% off, with half the size rows already out of stock.

This data is available for download immediately after purchase

The file already exists, because this pipeline runs once a month whether you buy it or not. Most vendors start collecting after you order — which is why they quote a lead time. Here the most recent file is in your account within minutes of payment, with an API key issued at the same time.

$1049.00per month

All prices are in USD · GST or VAT added on the invoice

Every style, size and width by size and width

31 fields, all listed below

This dataset was last updated on 02-Oct-2026

Delivered monthly · cancel any time

Excel and CSV included · JSON and Parquet on request

Please download the sample first and check the fields against what you need. Data files are not refundable once delivered.

VISA · MASTERCARD · AMEX · UPI · NET BANKING

Fields Sample rows Coverage Historical FAQ Add to cart · $1049.00

What you get, in plain terms

Four things. Many brands, deep size runs and constant promotions in one file.

Size and width on the row

Size reads “9 - Medium”, so width is captured alongside size — the dimension most footwear feeds drop and most returns come from.

List price and final price side by side

Price is the list price, Final Price what a shopper pays and Discount the saving in dollars, so markdown depth is a subtraction, not a guess.

Brands you can compare

Vince Camuto, Brooks, Birkenstock, Crown Vintage and DSW's own labels sit in one file, priced and stocked by the same retailer.

However you want it

Direct download, REST API, Amazon S3, Google Cloud, Snowflake or SFTP. The API key comes with the dataset.

Fields included in this dataset

All 31 columns, in the exact order they appear in the file — taken straight from the sample, not from a brochure. The free sample ships with a data dictionary giving an example value for each one.

S.No.WebsitePIDName Short DescriptionDescriptionCategoryImage URL PricePrice CurrencySale PriceFinal Price DiscountIsOnSaleIsInStockKeywords BrandManufacturerMPNUPC or EAN SKUColourGenderSize Varint_PriceAlternate Image URLsLink URLNum Ratings Average Ratingshash_idpage_path

Sample rows from the real file

Real rows from the sample file, not an illustration. The supplied sample has 50 variant rows with all 31 columns.

Sample is free, no signup and no card. Check the fields before you buy — files are not refundable once delivered.

Coverage

Captured monthly across dsw.com. One row is one size-width-colour variant, identified by its SKU, with the style in PID.

Metric	In the supplied sample	What it tells you
Variant rows	50 across 7 styles	Pumps, runners, clogs, sandals, boots
Brands	Vince Camuto 15 · Brooks 10 · Birkenstock 10	Plus Kelly & Katie and Crown Vintage
Discounted rows	41 of 50	Savings of $20 to $40
Deepest cut	46% off	On a dress style
Out of stock	25 of 50 size rows	Half the sampled size-widths gone
Ratings	On all 50 rows	Average 4.42

Only tracking a brand you sell through DSW, or one category? Send the list and we will price a narrower file.

Historical data

The last 30 days come with the dataset. Beyond that we hold DSW records from February 2025 onwards.

Ask about historical data

Need more data points?

We can extend this dataset beyond the standard 31 columns — size and width split into separate columns is the most requested change, along with a clean single-category field.

Request custom fields

“We sell into DSW and against it. Size-and-width level data every month is how we see which of our widths they actually reorder.”

Grace Tan · Wholesale AnalystUS footwear brand · downloaded the sample, bought the same month

What people use this dataset for

Retail and brand pricing teams

Benchmark list prices, markdown depth and timing against a competitor's live catalogue.

Merchandising and planning

See assortment width, size depth and what is already out of stock, category by category.

Marketplace and resale sellers

Track which styles, colours and sizes disappear first to shape your own buys.

Data and AI teams

Train product matching, attribute extraction and pricing models on clean, structured catalogue data.

No procurement cycle. Card payment, invoice on the spot. Most buyers are querying data the same afternoon.

Maintenance is ours. When DSW changes its layout, the file you receive does not change shape.

Analysis-ready. Loads straight into Excel, Power BI, Tableau, BigQuery or a pandas notebook.

Cancel whenever. The feed runs to the end of the period you paid for, then stops. No notice, no fee.

About DSW catalogue data

DSW (Designer Shoe Warehouse) sells hundreds of footwear brands alongside its own labels, online and in stores. For a brand, it is a major wholesale customer; for a retailer, a direct competitor. Either way its live catalogue is the benchmark.

Width is part of the size

Every row records size with width — “9 - Medium” — so the two can be analysed together. Half the sampled size-width combinations were out of stock, which is where a size curve actually breaks.

Promotions are constant

41 of 50 rows carried a discount, with savings recorded in dollars ($20.01, $34.02, $40.02) and the deepest cut at 46%. Tracked monthly, the pattern shows which brands DSW promotes hardest and when.

Two things to plan for

Category is a long merchandising tag string — “Dress Shoes/Shoes/Block Heels/Heels/Pumps/Gifts/Fall/Seasonal/Mother's Day” — rather than a clean hierarchy; split it on the slash and treat the entries as tags. page_path is an internal archive reference to our stored copy of each page, which we strip on request.

Is collecting this data legal?

Collecting publicly visible product and price information is generally lawful in most jurisdictions. Actowiz collects only public pages, respects robots.txt and platform terms, holds no personal data, and aligns with GDPR and CCPA. We are ISO 9001 and ISO 27001 certified, and this dataset carries documented provenance so your legal team can review the source before you buy.

Frequently asked questions

It is captured inside Size as “9 - Medium”. We can split size and width into separate columns on a custom feed at no extra cost.

DSW tags each product with every merchandising bucket it belongs to — occasion, season, gift guides. Split on the slash to use them as tags, or ask us for a single primary category.

Once a month. Each file is a fresh capture of the catalogue, which suits assortment, range and benchmarking work. If you need markdowns as they happen, weekly and daily versions of this feed are available.

Immediately. The pipeline runs on its schedule whether you buy it or not, so the current file is in your account within minutes, with an API key. Most vendors start collecting after you order, which is why they quote a lead time.

Yes. Real rows with every field and a data dictionary, no signup and no card. Checking the fields against your own requirement takes five minutes and prevents almost every problem we see.

Excel and CSV are included, UTF-8 encoded. JSON and Parquet are available on request at no extra cost — JSON suits the nested fields best.

Yes, and the key comes with the dataset at no extra charge. It is unmetered for the data you have bought, with a fair-use rate limit documented in the API reference.

Yes. Send the categories, brands or a list of products you track and we will price a narrower file, which costs considerably less than the full catalogue.

Data files are not refundable once delivered, which is why the sample matters. One exception: if a delivered file does not match the field list on this page, that is our error and we fix it or refund that month.

Any time from your account. The feed keeps running until the end of the period you have paid for, then stops. No notice period and no cancellation fee.

We email you 30 days before any field is added, renamed or removed, and we never remove one inside a period you have already paid for.

The last 30 days are included. Beyond that we hold DSW records from February 2025 onwards. Ask and we will confirm exactly what exists for the categories you care about.

Internal use across your whole organisation with unlimited seats. Redistributing the data, reselling it, or embedding it in a product you sell needs a separate licence — tell us what you have in mind.

Of course, though nothing on this page requires it. If you would rather have a call before buying, use the contact form and ask for the datasets team.

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DSW Multi-Brand Footwear Catalogue & Size-Width Stock Dataset

What you get, in plain terms

Size and width on the row

List price and final price side by side

Brands you can compare

However you want it

Fields included in this dataset

Sample rows from the real file

Coverage

Historical data

Need more data points?

What people use this dataset for

Retail and brand pricing teams

Merchandising and planning

Marketplace and resale sellers

Data and AI teams

About DSW catalogue data

Width is part of the size

Promotions are constant

Two things to plan for

Is collecting this data legal?

Frequently asked questions

Is width captured separately?

Why is the category so long?

How often is the file updated?

How soon can I download the data after paying?

Is the sample really free?

What format does it come in?

Can I get it as an API instead of a file?

Can I get only part of the catalogue?

Is it refundable?

Can I cancel?

What if the fields change?

Do you have historical data?

What licence do I get?

Can I speak to someone first?

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