CAUSAL EFFECT ANALYTICS
ENHANCE YOUR DATA INSIGHTS
TAKE ADVANTAGE OF THE MOST REWARDING DATA ANALYSIS APPROACHES
Causal Effect Analytics is a data analysis approach that uses causal designs to analyse causal relationships, carry out experiments, impact evaluations and support evidence-based decision-making.
The tools and techniques we use are part of statistical-methodological field of Causal Inference – one of the most complex, but also the most rewarding data analysis approaches.
REVEAL SUBTLE DIFFERENCES AND ENHANCE DECISION-MAKING
Causal Effect Analytics is based on an experimental data framework and enables you to extract the most informative and valid insights from data.
METHODS BEHIND CAUSAL EFFECT ANALYTICS
We use a holistic approach and combine knowledge of causal designs, subject matter theory and science behind causal thinking.
We understand that data quality determines success of data-based solutions — we overcome “garbage-in, garbage-out” problem with a well-thought-out data collection strategy.
We eliminate different types of biases by utilising modern statistical thinking and advanced modern statistical-methodological approaches.
WHAT CAN CAUSAL
EFFECT ANALYTICS DO FOR YOU?
- Do you deal with experiments, impact evaluations, personalizations, or target marketing?
- Do you want to enhance ML algorithms and improve accuracy of predictive analytics?
- Would you like to handle biases most effectively?
- Would you like to learn how to analyse causal relationships?
- Would you like to learn what it takes to analyse data in a scientifically objective way
If the answer to at least one of the above questions is YES, Causal Effect Analytics will not only be of great help but the method of choice. Learn about the workflow of this service below.
WORKFLOW OF CAUSAL EFFECT ANALYTICS SERVICES
UNDERSTANDING DATA
We e-meet to discuss desired and possible data solutions by exploring available data sets.
DEVELOPING STRATEGY
We bring in the science of causal inference to prepare a strategy for a causal design and data selection.
PRESENTING DATA DESIGN
We e-meet again to discuss a suitable data design and a choice of data analyses that can be implemented.
IMPLEMENTING ANALYSIS
We assist your data analysis team with implementation of design and analysis, or we do it for you.
Non-disclosure agreements are part of our culture.
P R I V A C Y F I R S T.
OTHER BENEFITS OF CAUSAL EFFECT ANALYTICS SERVICES
Working with us on your project enables your team to learn about the methods and techniques that we use in Causal Effect Analytics.
Your team learns about foundations to analyse causal-and-effect relationships, perform experiments and impact evaluations.
This service is designed to transfer the know-how of Causal Effect Analytics to our customers.
Schedule your first meeting using the form below
Interested in learning about Causal Effect Analytics tools and techniques?
TAKE ADVANTAGE OF THE MOST REWARDING DATA ANALYSIS APPROACHES
LEARN ABOUT CAUSAL EFFECT ANALYTICS ONLINE
Join our online course on Causal Inference for Data Analytics to learn how to analyse cause-and effect relationships in a scientifically objective way. Some prior knowledge of statistics is recommended. For those with little or no prior knowledge we recommend to start with our online course on Modern Statistical Thinking which equips you with key understandings on how to analyse data in a scientifically objective way.
Join a learning adventure that uplifts understandings about the world of data.
The importance of analysing causal relationships was recognised by Nobel Prize in Economics in 2021, awarded to Guido Imbens and Joshua Angrist for their research in the field of Causal Inference.