How can we trace user sessions from product view -> add to cart -> checkout -> payment to calculate step conversion rates?
Aggregating step occurrence flags per session and computing ratios evaluates conversion friction across stages.
Product analytics dashboards optimizing checkout flows and identifying user drop-off points.
df_funnel = df_events.groupBy("session_id").agg(max(when(col("event") == "view_item", 1).otherwise(0)).alias("viewed"), max(when(col("event") == "add_to_cart", 1).otherwise(0)).alias("carted"), max(when(col("event") == "purchase", 1).otherwise(0)).alias("purchased"))Practice typing production-grade PySpark code for Scenario: E-Commerce Funnel Conversion Analytics.