Our Data

We understand that data reliability and accuracy are crucial when it comes to making decisions in e-commerce. Continue reading to discover our data methodology.
Product categories

How do we project sales?

To create our dataset, we use state-of-the-art machine-learning models which combine consumer panel data with the world's largest truth set of online sales data.

Consumer panels help us identify traffic patterns on retail domains across the home, category, and product pages. We apply conversion rate models based on product-level sales data from more than 200K retailers to predict sales for each product. These bottom-up (from SKU-level) sales prediction models back into predictions of total retailer sales.
Data Collection

Step 1

We have developed several productivity tools, such as Retailer Benchmarking, which collectively create the world’s largest set of online sales data. Additionally, we use public data captured from hundreds of millions of products and product category URLs as well as licensed data from the leading data providers.
Data Classification & Cleaning

Step 2

To prepare for our modeling phase, we classify page types (home, category and product), categorize hundreds of millions of products and then clean and homogenize the data.
Data Modelling

Step 3

We predict sales from the SKU-level upwards by estimating traffic to product and category pages for each URL and applying conversion rates as well as the retailers' price points. These models are continuously calibrated against our set of live retailer data.

How accurate is our data?

US Census vs Grips Intelligence

US Census Data
e-commerce Sales vs. Grips Estimations of top 30k retailers

Grips covers >80% of all of U.S. eCommerce transactions across tens of thousands of retailers.
Reported Data vs Grips

ETSY– Reported Revenue vs. Grips Estimated GMV

Grips data correlates strongly with a company’s reported financial data.
Track Key Performance Indicators

Reported AOV vs.
Grips Estimated AOV

Grips reports on leading KPIs such as Average Order Value or Conversion Rate to provide you additional context of e-commerce performance for retailers and product categories.

Grips Research

Discover how Grips data has fueled transformative research projects, propelling industries forward with insightful discoveries.

Frequently asked questions

What metrics do you include?
  • Revenue: Revenue for the domain from online sales (in USD) for the selected period 
  • Transactions: Number of transactions for the domain for the selected period
  • Sessions: Number of visits for the domain for the selected period
  • Conversion rate: Number of sessions divided by transactions
  • AOV: Average order value 
  • Ad spend: Total ad spend for the domain for Google Ads search network
  • CPC: Cost per click for the domain for Google Ads search network


and many others!

What's included in your retailer estimates?

Subdomains are included as part of the domain. For example, uk.louisvuitton.com is covered by www.louisvuitton.com.

We do not include top-level domain variations. For example, adidas.com doesn’t include adidas.de revenue.

What does your data include?

We include one-time sales running through the checkout of a retailer’s website. We also include Click and Collect as online revenue (E.g. Over $100B in US 2022).

What does your data not include?

We do not include subscriptions, returns or sales generated in an app.