What eCommerce data helps private equity, M&A bankers and consultants with commercial due diligence on a consumer brand?
For commercial due diligence, eCommerce data gives an outside-in view of a brand that management materials cannot: how widely it is distributed, how its prices compare with competitors, how often it discounts, and how its range has changed, with multi-year history. Data Purl provides this at SKU level across 400+ retailers, with the brand resolved to its owner so the whole footprint is visible in one place.
Last reviewed
Questions it answers in a diligence
- Distribution: which retailers carry the brand, and has that footprint grown or shrunk?
- Positioning: where do its prices sit versus direct competitors, category by category?
- Promotional reliance: how much of the range is regularly discounted, and how deeply?
- Range health: how fast is the assortment refreshed, and which categories are growing?
- Channel mix: how does the brand's own site compare with its wholesale partners?
Why history matters
Diligence usually needs a multi-year view to separate trend from noise. Data Purl's history reaches back to 2013, so pre-pandemic baselines are available. Scraped data bought for the first time starts on the day collection starts.
A practical workflow
- 1Define the target and a competitor set at brand level.
- 2Pull distribution, price architecture and discounting by retailer and category for the last three to five years.
- 3Benchmark the target against competitors on the same retailers and categories.
- 4Carry the same metrics into the value-creation plan and track them after close.
Metrics used
- Share of shelf (online): A brand's share of the products a retailer lists in a category, measured on the retailer's website.
- Price architecture: How a brand's or category's products are distributed across price tiers, such as value, mid-market, premium and luxury.
- 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.
- 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.
- Assortment count: The number of distinct products a brand or retailer has live for sale at a point in time.
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.