Everything you need to know about the ECDB methodology

Our data process at each stage is characterized by one thing above all: The analytical effort of our data analysts. Together with the latest tools and artificial intelligence, they are the basis for an unique and consistent data cube. Find out everything you need to know about our methodology on this page.

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Data Research & Analysis

High-quality research & analysis ensure a perfect data basis

Our experienced team of data analysts conducts extensive research across multiple sources to ensure comprehensive market insight. Using the latest tools and our industry knowledge, they ensure data accuracy and relevance. In addition, continuous quality control ensures high quality and up-to-date data.

Quality control measures ensure reliability by eliminating erroneous sources. In keeping with its commitment to data integrity, ECDB remains dynamic, adapting to any changes in the eCommerce landscape, such as new forecasts or annual reports.

Data Research Helix

Our data sources

Company data

Company publications such as annual reports, quarterly reports or company statements.

Market data

Macroeconomic data such as market forecasts, historical market developments and market drivers.

Own data

Our own data collection, for example in the form of surveys of thousands of online shops.

Partners

High quality data from our selected data partners.

Stefanie Eden - Chief Data Officer
Stefanie Eden - Chief Data Officer
Stefanie Eden Chief Data Officer

Our industry and methodological expertise in combination with tools and AI provide the perfect data foundation.

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Data Cleaning & Standardization

Conscientious data cleaning optimizes further processing

Data Cleaning Graph

For us, the focus is always on high data quality. In order to be able to guarantee that, we require a data pool that is consistent in itself and which serves as the perfect foundation for modeling markets or companies.

Our data analysts therefore spend a lot of time standardizing and cleaning the data they have obtained. In the course of our data cleaning and standardization, different definitions are eliminated, and incorrect sources are sorted out.

Why data cleaning and standardization is relevant

Standardized data basis

For our extensive modelling, we need an excellent data basis, which can only be guaranteed by extensive preparatory work in the course of data cleansing and standardization.

Deviations in definitions

The large number of sources on the eCommerce market is associated with a large number of different definitions. In order to be able to process them further, these definitions and the associated data must be harmonized.

Removing incorrect data

As in many other areas, the eCommerce sector also contains a large amount of inaccurate or incorrect data. These can only be found and subsequently eliminated through a comprehensive analysis.

Reducing complexity

With our far-reaching processes for data cleaning and standardization, we are actively working on defining market standards and making the eCommerce market easier to access for our customers.

Lukas Peters - Data Analyst
Lukas Peters - Data Analyst
Lukas Peters Data Analyst

Data cleaning and standardization is the essential step in order to create an optimal data basis for our modelings.

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Data Modeling

As the heart of our data process, modeling is the key to unique data

Data modeling by our analysts is the heart of data generation. Based on researched, collected, harmonized and cleaned data from the previous steps, the different datasets are compiled into a consistent data model.

Our experienced data analysts dive deep into individual markets, countries and players and merge all data strings. With the help of a variety of tools created in-house, this results in data modelings with unique data as its output.

Data Modeling Graph

What makes us unique in data modeling

Regular updates throughout the year

We do not generate data and leave it unadjusted in the market. Instead, we regularly adjust our modelings and include new data points.

Modeling by true experts

Each of our data analysts is a true expert in their market. Accordingly, collected data can be optimally processed and contextualized.

Human intelligence

A large part of our modeling is carried out by our experienced data analysts. We use tools but put the analyst at the center of the data modeling.

Combination of different data sources

We always access all plausible data on the market and use it in our modeling. This is the only way to develop a complete data pool.

Kimberley Vesting - Data Analyst
Kimberley Vesting - Data Analyst
Kimberley Vesting Data Analyst

With data modeling as the heart of our data generation, we generate unique and always up-to-date data.

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Data Forecasting

Based on multifaceted analysis, our forecasts lead the way into the future

Data Forecast Graph

As ECDB, we not only provide detailed data on current and past years, but also take a look at developments in the coming years with our data forecasts. In order to do this, our analysts combine various data sources and use them to develop a forecast for markets and individual players.

Our analysts examine key performance indicators, general market forecasts, historical developments and statements by individual players, among other things, and develop a forward-looking picture of the eCommerce landscape.

Input data for our forecasts

Historical developments of markets and players

Based on the developments of recent years or even decades, conclusions are drawn for the future and thus serve as a good basis for our forecast.

Macroeconomic changes

Any changes in macroeconomic parameters imply changes in the market environment and are incorporated into our forecasts accordingly.

Forecasts of individual players

The statements and information of individual companies provide valuable information on the future development of companies and markets.

Development of eCommerce KPIs

The development of important key figures such as average order value, conversion rate or cart abandonment rate provide an indication of future developments in eCommerce.

Nikolai Surminski - Data Analyst
Nikolai Surminski - Data Analyst
Nikolai Surminski Data Analyst

Our forecasts are based on many different data points and therefore show a multi-faceted picture of the future eCommerce landscape.

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Data Enrichment

A variety of eCommerce indicators further enrich the modeled data

The data modeled by our data analysts is supplemented by a wide range of indicators. These are obtained through expert research in combination with the latest tools and include a wide range of parameters on payment and shipping providers, store software, marketing performance and much more.

Together with the modeled data, the indicators offer a perfect symbiosis and enable a complete picture of individual retailers, countries or categories.

Globe with data illustration

Indicators we are covering

Shipping service providers
Payment providers
Marketplace analytics
Consumer behavior (AOV/CVR)
Shop software
Marketing performance
Key financial metrics
Company & contact information
And many more
ECDB Sales Team

Learn more about our eCommerce Analytics Data Hub from our team of experts

Introduction to our platform
Explanation of our methodology
Presentation of use cases
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