Data Purl
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  • 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
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  1. Home
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  3. /Using eCommerce data in a consumer earnings preview
Use case

What eCommerce data should an analyst check before a consumer company reports earnings?

Before a consumer company reports, weekly online data can test the main debates: whether price increases held, whether promotions rose (a gross-margin risk), whether inventory looks clean, and whether the assortment is growing or shrinking. Checking these against the same fiscal weeks last year gives an independent read ahead of management commentary.

For:Public market investors

Last reviewed 24 September 2026

The pre-earnings checklist

  1. 1Pricing: matched-SKU price change versus last year, by key brand and category.
  2. 2Promotions: markdown breadth and depth versus the same fiscal weeks last year.
  3. 3Inventory: full-price availability and in-stock rates as a read on clean or heavy inventory.
  4. 4Assortment: product count and newness, and any cuts at key wholesale partners.
  5. 5Channel: DTC versus wholesale pricing and discounting.

Aligning to the fiscal calendar

Retailers and brands report on fiscal calendars that rarely match calendar months. Aligning weekly data to the company's own quarter boundaries, and to the prior-year equivalent weeks, avoids reading a calendar shift as a change in trend.

Metrics used

  • Matched-SKU inflation (same-SKU price change): The price change of identical products observed in both periods, which isolates true price moves from changes in product mix.
  • 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.
  • Full-price availability: The share of a brand's products that are both in stock and selling at full price, a proxy for clean, healthy demand.
  • Assortment count: The number of distinct products a brand or retailer has live for sale at a point in time.
  • DTC vs wholesale mix: How a brand's online assortment and pricing split between its own direct-to-consumer site and its wholesale retail partners.

How each measure is built: methodology.

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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)

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400+
retailers
1,900+
public companies mapped
4,000
product categories
2013
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© 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.