Data Purl
  • Platform
    • Coverage400+ retailers across the US, UK, Europe and Asia, history back to 2013
    • Shelf IndicesFree monthly price and discount indices by category and country
    • Brand headlinesQuarterly prices and markdowns for 84 consumer brands
    • Custom dataResearched extracts scoped to your sectors, brands and dates
    • MethodologyHow we collect, classify and map brands to 1,900+ listed companies
    • ValidationCollection success, quality screens and backtests
    • Not sure what you need?Talk to the founders
  • Solutions
  • Pricing
    • ResearchFindings tested against the shelf, and brand studies
    • BlogWhat the online shelf showed this month
    • GlossaryDefinitions of retail and alternative-data measures
Client loginStart free
  • Platform
    • Coverage400+ retailers, history back to 2013
    • Shelf IndicesFree monthly price and discount indices
    • Brand headlinesQuarterly prices for 84 consumer brands
    • Custom dataExtracts scoped to your sectors and dates
    • How we build it
      MethodologyHow we collect, classify and map brands
    • ValidationQuality screens and backtests
  • Solutions
  • Pricing
    • Research
    • Blog
    • Glossary
Not sure what you need?Talk to the foundersClient login
  1. Home
  2. /Use cases
  3. /Using markdowns as an early inventory and gross-margin signal
Use case

How do you spot excess inventory at a retailer or brand before it shows in reported results?

Excess inventory is usually cleared through discounting, and discounting is visible on public websites weeks before it appears in reported gross margin. Rising markdown breadth, deepening discounts and in-stock rates that stay high while prices fall, all measured against the same weeks last year, are the standard early signals.

For:Public market investorsConsultants

Last reviewed 24 September 2026

The three signals to watch

  • Markdown breadth: more of the range on sale than at the same point last year.
  • Discount depth: bigger reductions on the products that are on sale.
  • In-stock rate: products staying available even as prices fall, which suggests demand is not clearing stock.

Reading the signals correctly

Seasonality dominates retail discounting, so the comparison that matters is the same fiscal weeks in prior years, not last week. Promotional calendars also move: a sale that started a week earlier this year can look like a deterioration if the calendars are not aligned.

Channel matters as well. A retailer discounting a brand's products heavily while the brand holds price on its own site points to a wholesale inventory problem rather than a brand problem.

A practical workflow

  1. 1Map the company to its brands and retailers and choose the categories that drive margin.
  2. 2Track markdown breadth and depth weekly, aligned to the company's fiscal calendar.
  3. 3Compare with the same weeks in the prior two years to set a baseline.
  4. 4Cross-check with in-stock rates and new-product share to separate clearance from planned promotions.

Metrics used

  • Markdown breadth: The share of each product's in-stock sizes and variants selling below full price, averaged across products so each product counts equally.
  • Discount depth: The average percentage reduction from full price across products that are on sale.
  • In-stock rate (availability): The percentage of a brand's or retailer's listed products that are available to buy.
  • New-product share (new entrants): The percentage of a brand's live assortment that was first seen within a recent window, such as the last 13 weeks.

How each measure is built: methodology.

See the data for your coverage

Start free in the analytics portal, or talk to the founders about the full dataset delivered to Snowflake or S3.

Start free Talk to the founders
Data Purl

Data Purl is an eCommerce pricing and assortment data provider that follows every brand across the retailers that sell it: SKU-level price, discount, availability and assortment history across 400+ retailers back to 2013, compared like for like, with brands resolved to their owners, public or private, and listed owners mapped to tickers.

+44 20 8125 3010 (UK)+1 212-660-0780 (US / International)

Product

  • Platform
  • Coverage
  • Retailers
  • Custom data
  • Methodology
  • Compliance
  • Validation
  • vs AI web scraping
  • Choosing a data provider

Solutions

  • Public market investors
  • Private equity
  • Consultants
  • Investment banking M&A
  • Venture capital

Use cases

  • Pricing power
  • Markdowns and inventory
  • Commercial due diligence
  • Brand distribution
  • Category inflation
  • Portfolio monitoring
  • Tariff pass-through
  • Holiday promotions
  • Private label
  • Assortment cuts
  • Earnings previews
  • Product launches
  • Choosing a data provider
  • Build vs buy

Resources

  • Plans and pricing
  • Research
  • Blog
  • Shelf Indices
  • Brand headlines
  • Use cases
  • Glossary
  • FAQ
  • About
  • Privacy policy
  • Terms of use
  • Start free
  • Talk to the founders
400+
retailers
1,900+
public companies mapped
4,000
product categories
2013
history back to

© 2026 Data Purl. All rights reserved. Data Purl is a trading name of Cleveland Alternative Data Limited, a company registered in the United Kingdom with company number 16234509. Registered office: Basement, 52 Cleveland Square, London W2 6DB. Contact: support@data-purl.com.