- Do you deal with experiments, personalization, or target marketing?
- Do you want to enhance ML algorithms and improve accuracy of predictive analytics?
- Would you like to handle biases effectively?
If the answer to at least one of the above questions is YES, Causal Effect Analytics will not only be of a great help but, in many cases, the method of choice.
Causal Effect Analytics is a highly rewarding approach for obtaining enhance data insights. It can reveal subtle differences about which things work better and thereby lead to making better choices for what to implement. In some situations, the increases relative to using naive methods for estimation can be substantial.
How do we help
Understanding your data
We meet to discuss beneficial data solution outcomes
Developing a strategy
We prepare strategies for data selection and data analysis design by bringing in the science of causal inference
Presenting analysis design
We meet again to present the strategies and to discuss implementation
Implementing causal effect analysis
We help and assist your data science team with the implementation of the chosen analysis design, or we do it for you.
How do you benefit
Enhancing your business
Supporting your business endeavours with beneficial data solution outcomes
Empowering your team
Working with us enables your data team to learn about causal effect evaluations, and improve causal and statistical thinking skills
For more information, please get in touch via email@example.com or by visiting the ‘Get in touch’ area. We look forward to helping you.