Features

This chapter covers the core features and capabilities of Funnel Analyzer.

Features

• Step-by-step analysis — Conversion rate between each funnel step
• Drop-off detection — Exact numbers and percentages of users lost at each step
• Overall conversion — End-to-end funnel conversion rate
• Time-to-convert — Average time from funnel entry to each step
• Cohort comparison — Compare funnel performance across user segments
• Visual bar report — ASCII bar chart showing funnel shape
• JSON/CSV input — Works with any event data format
• JSON output — Machine-readable results for dashboards

Requirements

• Python 3.10+
• No external dependencies (stdlib only)

Quick Start

Follow this guide to get Funnel Analyzer up and running in your environment.

Quick Start

# Analyze a funnel
python src/funnel_analyzer.py --events examples/sample_funnel.json \
    --steps "page_view,signup,activate,purchase"

# Compare cohorts
python src/funnel_analyzer.py --events examples/sample_funnel.json \
    --steps "page_view,signup,purchase" --cohort source

# Export results
python src/funnel_analyzer.py --events data.json \
    --steps "visit,signup,activate" --output results.json

Event Data Format

Events should be a JSON array of objects:

[
    {"event_name": "page_view", "user_id": "u1", "timestamp": "2026-01-01T10:00:00Z"},
    {"event_name": "signup",    "user_id": "u1", "timestamp": "2026-01-01T10:05:00Z"},
    {"event_name": "activate",  "user_id": "u1", "timestamp": "2026-01-01T10:30:00Z"}
]