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Inferring Causal Impact with Google's Causal Impact Package
What you'll learn
- Inferring the Causal Impact of a event (Promotion, Marketing Campaign, etc) over sales, website visits, download apps or any other variable you want to analyse
- How to use the pythons implementation of Google Causal Impact package
- How to calculate the ROI of a marketing campaign or a sales promotion
Requirements
- Basic knowledge of python programming
- Basic knowledge of python library pandas
Description
Welcome to our Google Causal Impact Course.
This course I'll teach you how to use the google's package Causal Impact in your on job or personal projects.
The Causal Impact model developed by Google works by fitting a bayesian structural time series model to observed data which is later used for predicting what the results would be had no intervention happened in a given time period. The idea is to used the predictions of the fitted model (depicted in blue) as a reference to what probably would had been observed with no intervention taking place.
After this course you will have a powerful tool, to measure (with statistical significance):
* The extra number of sales / app downloads / clicks / web site visits caused by a marketing campaign
* The ROI of a Marketing Campaign
* The effect of a promotion over demand
* Any change of behavior in a series, caused by a known event
Who this course is for:
- Data Analysts and Data Science Students
- Anyone interested in causal inference techniques and data analysis with python
You should keep in mind that the Coupons last a maximum of 4 days or until 1000 registrations are exhausted, but it can expire anytime. Get the course with coupon by clicking on the following button:
