Modeling approach

The revenues of the provided online stores are collected or modeled and approximated in various ways.

In the first step, our team of eCommerce experts conducts a survey among thousands of online stores and investigates the key performance indicators in the eCommerce sector, including web sales revenue, category split, country split, and average shopping cart size.

Additionally, the team of eCommerce experts reviews and evaluates all available quantitative and financial data from various public sources such as annual reports, financial statements, media reports, and interviews related to eCommerce company revenues. Based on this data, the revenue of an online store is individually modeled in combination with other store-specific data, such as traffic data and market-specific data.

For stores that do not have any available key performance indicators or additional information, revenue is then entered into an advanced statistical model. The model takes into account store-specific indicators (i.e., product range, peer group affiliation, traffic) as well as country-specific macroeconomic developments (i.e., purchasing parity power, price level index) and market research insights (i.e., regional acceptance of online shopping, brand awareness).

All collected and estimated information is then reevaluated by a team of industry specialists to offer the highest level of data quality.


Revenue forecasts are based on a combination of individual factors (i.e., historical revenue developments as well as online store traffic trends), market trends (i.e., regional developments of their respective products), and store categories (using industry-standard statistical algorithms). These figures are then reevaluated by our expert panel and enriched with their informed opinions and insights.

ecommerceDB revenue analytics and KPI information

Our approach

We combine extensive data research and Statista modeling:

  • Data research & monitoring
  • Data cleaning & standardization
  • Bottom-up modeling of revenue at domain level
  • KPI analysis & forecasting

Our data sources

Our modeling & forecasts are based on:

  • Data from surveys covering thousands of online stores
  • Data from annual reports & media reports
  • Store-specific data such as traffic, category share, and country share
  • Macroeconomic data like market development

Modeling and forecasts

We provide informative statistics and forecasts about different aspects of an online store’s status quo and future development based on secondary data from annual reports, media reports, and store-specific data from international institutions and partnerships. Additionally, we provide forecasts based on data-focused trend analyses and advanced statistical modeling.

Key performance indicators

Intensive research, continuous market monitoring, and advanced analyses allow us to detect relevant KPIs and keep them up to date, such as:

  • SEO and SEA budget
  • Shipping provider and payment options
  • Shop software
  • Contact information


General questions about ecommerceDB

Store profile and net sales

Key performance indicators (KPIs)

Data tool & categories

Specialist groups


Technical questions & support