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Analysis of Web Data

Web Analytics has been a central part of many companies’ online strategies for many years.
Web Analytics describes the evaluation and use of customer data collected online and information to optimize customer relationships, products and services.

In many web analytics projects, data from tracking and shop systems, SEA and SEO are used to make predictions about future customer behavior, e.g. about conversions, buying habits or using certain services. Methods from statistics and machine learning are used for the calculation and analysis.

Recommendation engines

Analysis of shopping baskets to generate product recommendations and activation of upselling potential.


Click-Through Prediction

Creation of machine learning models for forecasting click rates in search engines and paid advertising.


Attribution models

Modeling customer data to optimize spending at channel and publisher level.


Conversion forecasts

Modeling factors influencing conversions and customer-specific conversion predictions.


Next Best Product

Calculate which products and services customers are likely to buy next.


Forecasting models

Use our models to forecast sales, page views and other KPIs in the web analytics area.

Data Science in Web Analysis

The good availability of data generated online creates exciting data science applications for web analytics.

All data you collect can help you better understand your customers, better address them and use statistics and machine learning to make predictions about their future behavior.

Our data scientists support you in the development of use cases and projects in the web analytics environment, consolidate and aggregate internal and external data sources for you and develop models from statistics and machine learning for the optimization of your online shops, services and products.