Statistical analysis is an important part of market research, but most studies are limited to the presentation of descriptive results. With the use of advanced statistical methods, significantly more knowledge can be extracted from the same data. Common methods are regressions for driver analyzes, cluster analyzes to form segments or attribution modeling to explain changes over time. With C Square you have the experts on board who are familiar with the latest analytics and data science methods from science.
Descriptive Analysis
The most common form is a graphic representation of the most important results, e.g. as a bar or line diagram. If you have a large amount of data, you can use tables and heat maps.
Driver Analysis
Regressions and correlations show the relationship between several variables. For example, they provide information on which areas have the greatest impact on overall satisfaction.
Machine Learning
Machine learning models can also be used to analyze non-linear relationships and changes over time. This makes it possible to determine what the specific influencing factors were on the change in overall satisfaction over time.
For more information on analytics and advanced data analysis, please contact us at info@c-square.ch or use our contact form
Linking different data sources
