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. /Tracking a company's pricing power with eCommerce data
Use case

How can investors measure whether a consumer brand has pricing power before it reports?

Pricing power shows up online as price increases that stick without extra discounting. The clearest read combines matched-SKU price changes (are identical products getting more expensive?) with markdown breadth and depth (is the brand giving the increase back through promotions?), tracked weekly across the brand's own site and its wholesale partners.

For:Public market investorsPrivate equity

Last reviewed 24 September 2026

What pricing power looks like in the data

  • Matched-SKU prices rising faster than the category, so the brand is raising prices on the same products.
  • Markdown breadth flat or falling versus the same weeks last year, so the increase is not being discounted away.
  • Full-price availability holding up, so products still sell out at the new price.
  • Consistency across channels, so wholesale partners are not discounting what the brand's own site holds.

A practical workflow

  1. 1Resolve the company to all of its brands and select the brands that matter for revenue.
  2. 2Pull weekly matched-SKU price changes by brand and category, normalized per unit where pack sizes vary.
  3. 3Overlay markdown breadth and discount depth for the same weeks last year to remove seasonality.
  4. 4Split the brand's own site from wholesale retailers to see who is carrying the discounting.
  5. 5Compare against peers in the same categories to separate brand strength from category-wide inflation.

Where it fits in an investment process

Fundamental analysts use it to test management commentary on pricing and promotions between reporting dates. Quantitative teams use the same series as inputs to gross-margin and revenue-per-unit models.

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.
  • Discount depth: The average percentage reduction from full price across products that are on sale.
  • 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.
  • 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.