Data Purl
  • Platform
  • Solutions
  • Coverage
  • Custom data
  • Research
  • Methodology
Client loginTalk to the foundersStart free
  • Platform
  • Solutions
  • Coverage
  • Custom data
  • Research
  • Methodology
  • Start free
  • Talk to the founders
  • Client login
  1. Home
  2. /Use cases
  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: 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 a brand's or retailer's live products that are selling below their full price at a point in time.
  • 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.

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 turns public retailer websites into investment-grade data: SKU-level price, discount, availability and assortment history across 400+ retailers back to 2013, 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

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

Resources

  • Research
  • Use cases
  • Glossary
  • FAQ
  • About
  • 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.