Causal Email Journey
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Let’s say that you work for an E-commerce store. A new marketing manager joins the company and redesigns the existing new-user email journey to try and boost customer conversion rates. A few weeks after launching the new email journey, the new-user to customer conversion rate goes up from 40% to 43%.
Before you can celebrate, the company’s CMO points out a troubling fact. Just a few months prior to the new manager starting the conversion rate already stood at 45%, before slowly dropping down to the “starting” 40%.
How would you investigate if the redesigned email campaign actually led to the increase in the conversion rate, and that the increase wasn’t instead the result of other factors?
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Topic
Analytics
Tags
A/B Testing
Data Normalization
Causal Inference
Directed Acyclic Graph (DAG)
Design of Experiments
Interrupted Time Series Analysis
Seasonality Analysis
Bayesian Structural Time Series Modeling
Synthetic Control Method
Category
Case Study
Position
Data Analyst
Data Scientist
Marketing Analyst
Product Manager
Growth Marketer
Difficulty
Medium
Success
N/A
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