Reading Funnels Like an Analyst

# Reading Funnels Like an Analyst A funnel is a sequence of steps users move through, with drop-off at each step. ## Funnel drop-off calculation in Python ```python import pandas as pd # User journey log across funnel steps funnel_data = [ {"step_order": 1, "step_name": "Landed Homepage", "users": 100000}, {"step_order": 2, "step_name": "Started Signup", "users": 30000}, {"step_order": 3, "step_name": "Completed Signup", "users": 18000}, {"step_order": 4, "step_name": "Verified Email", "users": 15000}, {"step_order": 5, "step_name": "Activated (First Action)", "users": 8000}, {"step_order": 6, "step_name": "Day-7 Retained", "users": 5000}, ] df_funnel = pd.DataFrame(funnel_data) # Calculate step-to-step conversion, total conversion, and drop-off df_funnel["step_conv_pct"] = df_funnel["users"] / df_funnel["users"].shift(1) df_funnel["step_conv_pct"] = df_funnel["step_conv_pct"].fillna(1.0) df_funnel["dropoff_users"] = df_funnel["users"].shift(1) - df_funnel["users"] df_funnel["dropoff_pct"] = 1.0 - df_funnel["step_conv_pct"] df_funnel["overall_conv_pct"] = df_funnel["users"] / df_funnel["users"].iloc[0] print(df_funnel[["step_name", "users", "step_conv_pct", "dropoff_pct", "overall_conv_pct"]].to_string( index=False, formatters={ "users": "{:,}".format, "step_conv_pct": "{:.1%}".format, "dropoff_pct": "{:.1%}".format, "overall_conv_pct": "{:.1%}".format, } )) ``` ## Takeaway Focus on steps with the highest conversion opportunity, not just the top-of-funnel drop.