Markdowns, sizes and new drops, tracked by style.
Fashion competes on newness, sell-through and the timing of markdowns. We track styles from brand web stores and fashion marketplaces at colour and size level, so merchandising teams can see what competitors launch, discount and sell out.
What makes this industry hard to track.
Style, colour and size variants
One style can carry dozens of colour and size combinations. Data needs to be captured at variant level and rolled up cleanly to the style.
Short product lifecycles
Styles appear and disappear within a season. Tracking has to pick up new arrivals quickly and keep history after a product is removed.
Inconsistent attributes
Materials, fits and categories are labelled differently by each brand. Attribute mapping is needed for any assortment comparison.
Regional pricing
The same style is often priced differently across countries, with separate sale timings in each.
Eight data points our clients rely on.
Full and sale price
Original price, current price and discount depth per style and colour.
Markdown timing
First date a style is reduced and each subsequent price step.
Size availability
Which sizes are in stock, as a proxy for sell-through.
New arrivals
Styles first seen in each capture, with launch price and category.
Assortment depth
Number of styles by category, price band and fit.
Material and attributes
Fabric composition, fit, occasion and other listed attributes.
Colour palette
Colour names mapped to a standard set for trend comparison.
Delistings
Styles removed from sale, with their last seen price and sizes.
An illustrative extract.
| Date | Source | City | Style | Full price | Sale price | Currency | Sizes in stock |
|---|---|---|---|---|---|---|---|
| 2026-07-03 | Brand store A | Dubai | Linen blend shirt, relaxed fit | 229.00 | 159.00 | AED | S, M |
| 2026-07-03 | Fashion marketplace B | Sydney | High-rise straight jeans | 119.95 | 119.95 | AUD | 6, 8, 10, 12, 14 |
| 2026-07-03 | Brand store C | New York | Cotton poplin midi dress | 98.00 | 68.60 | USD | XS, L |
| 2026-07-03 | Fashion marketplace D | Santiago | Leather ankle boots | 79990 | 55990 | CLP | 37, 38 |
| 2026-07-03 | Brand store E | Paris | Merino crew-neck jumper | 89.95 | 89.95 | EUR | S, M, L, XL |
Illustrative rows. Sources, markets and fields are agreed with you during scoping.
How teams put it to work.
Markdown cadence analysis
A timeline of competitor price reductions by category and region, so you can plan markdown timing and depth with a view of the market.
Assortment architecture
Style counts by category, price band and fit across competitors, to show where your range is thin or crowded.
Sell-through signals
Size-level availability tracked over time, indicating which styles and sizes competitors are selling through fastest.
Relevant solutions
Related industries
Do you capture data at size level?
Yes. We record availability per size and colour where the site exposes it, then roll up to style level. That keeps both views available for analysis.
How do you compare attributes across brands?
We map each brand's category, fit and material labels to a shared taxonomy agreed with you. Unmapped values are flagged so the taxonomy can be extended rather than forced.
Can you keep history for styles that are removed?
Yes. Every style keeps its full price and availability history after it disappears from a site, with a last-seen date. This is often where the most useful sell-through evidence sits.
Can you collect product images?
We can collect image URLs and, where appropriate and permitted, image files for internal analysis such as colour classification. Usage is agreed at scoping, taking each source's terms into account.