AMC playbook: Customer journey analytics
In short: The playbook groups campaigns, categories or brands by funnel phase and shows the paths to conversion as a Sankey diagram. It shows which campaigns and ad products influenced a purchase and which conversion subtypes such as add to cart or wish list occurred. The path analyses themselves are hard to visualise.
What it is about
Customer journey analytics identifies a customer's interactions with an ad before an outcome, such as add to cart, purchase or cart abandonment. Path-to-purchase and path-to-conversion analyses give the chronological sequence of touches but are hard to visualise. A Sankey diagram depicts the data flow between campaign paths.
Which questions the playbook answers
- How do you represent the customer journey with an effective diagram?
- Which campaigns influenced the buyer along the way?
- Which conversion subtypes (add to cart, review, wish list) occurred?
- Which ad products, DSP or sponsored ads, influenced the path?
Flow
- Run the queries: path to conversion by campaign and by campaign group.
- Split the data into source and destination and prepare it for the Sankey diagram (Python).
- Visualise in Amazon QuickSight and interpret.
Prerequisites according to Amazon
Our take
Path diagrams show sequences, not causes. Reading a diagram as proof of effect confuses correlation with causation; effect questions need a comparison with non-exposed users.
Amazon documents the playbooks in technical English with SQL and Python. This page summarises what the playbook does; the queries and scripts are in the original.