/attribution-analysis-modeling

name: attribution-analysis-modeling
description: Perform multi-touch attribution analysis using Markov chains, Shapley values, and custom attribution models. Use when you need to analyze marketing channel effectiveness, calculate conversion attribution, optimize marketing budgets, or understand customer journey paths. Supports channel transition analysis, ROI calculation, and marketing optimization insights with Chinese language support.
allowed-tools: Read, Write, Bash, Glob

Marketing Attribution Analysis & Modeling

A comprehensive attribution analysis skill that evaluates marketing channel effectiveness using advanced statistical models, helping optimize marketing spend and understand customer journey patterns.

Instructions

1. Data Loading and Preparation

When users provide marketing touchpoint data:

• Load and validate channel interaction data
• Parse customer journey paths and touchpoint sequences
• Handle different data formats (CSV, JSON, Excel)
• Support both user-level and session-level attribution analysis
• Process timestamp data for chronological path analysis

2. Customer Journey Analysis

• Reconstruct customer journey paths from touchpoint data
• Calculate path lengths and conversion patterns
• Identify common conversion paths and bottlenecks
• Analyze channel sequencing and order effects
• Support both online and offline channel attribution

3. Attribution Model Implementation

• **Markov Chain Attribution**: Build transition probability matrices and calculate removal effects
• **Shapley Value Attribution**: Calculate fair channel contributions using game theory
• **First-Touch Attribution**: Assign full credit to the first channel in the path
• **Last-Touch Attribution**: Assign full credit to the last channel before conversion
• **Linear Attribution**: Distribute credit equally across all channels
• **Time-Decay Attribution**: Weight channels based on recency
• **Position-Based Attribution**: Weight first and last touches more heavily

4. Channel Performance Analysis

• Calculate conversion rates by channel and channel combinations
• Compute ROI and cost-per-acquisition (CPA) for each channel
• Analyze channel synergy and interaction effects
• Identify underperforming and overperforming channels
• Generate channel contribution percentages

5. Visualization and Reporting

• Create attribution weight distribution charts
• Generate customer journey path visualizations
• Build channel transition heatmaps and network graphs
• Produce ROI analysis and budget allocation recommendations
• Generate comprehensive attribution reports

Usage Examples

Marketing Channel Attribution

Analyze the effectiveness of our marketing channels:
[CSV with columns: user_id, timestamp, channel, conversion_status, conversion_value]

Digital Campaign Attribution

Calculate attribution for our digital marketing campaigns:
[Marketing touchpoint data with campaign, channel, timestamp, and conversion data]

E-commerce Conversion Attribution

Perform attribution analysis for e-commerce customer journeys:
[Customer path data showing touchpoints before purchase]

Budget Optimization

Help optimize our marketing budget based on attribution results:
[Channel performance data with spend and conversion metrics]

Key Features

Advanced Attribution Models

• **Markov Chain Analysis**: Probabilistic model for channel transition analysis
• **Shapley Values**: Game theory-based fair attribution calculation
• **Custom Models**: Flexible framework for custom attribution logic
• **Model Comparison**: Compare different attribution models side-by-side

Customer Journey Analysis

• **Path Reconstruction**: Automatically build conversion paths from raw data
• **Touchpoint Sequencing**: Analyze order and timing effects
• **Conversion Funnels**: Identify drop-off points in customer journeys
• **Multi-path Analysis**: Handle customers with multiple conversion paths

Channel Performance Metrics

• **Attribution Weights**: Calculate each channel's contribution to conversions
• **ROI Analysis**: Compute return on investment for each channel
• **Synergy Effects**: Measure how channels work together
• **Incremental Impact**: Estimate additional value from channel combinations

Business Intelligence

• **Budget Optimization**: Recommend optimal budget allocation
• **Channel Recommendations**: Suggest best channel combinations
• **Performance Benchmarks**: Compare channel performance against baselines
• **Trend Analysis**: Track attribution changes over time

File Requirements

Standard Touchpoint Data Format

user_id,timestamp,channel,conversion_status,conversion_value,cost
USER001,2024-01-15T10:30:00Z,paid_search,0,0,50
USER001,2024-01-16T14:20:00Z,social_media,0,0,30
USER001,2024-01-18T09:15:00Z,email,1,1000,10

Required Fields:

• **user_id**: Unique customer identifier
• **timestamp**: Touchpoint timestamp (ISO format preferred)
• **channel**: Marketing channel or touchpoint
• **conversion_status**: Binary indicator of conversion (0/1)
• **conversion_value**: Monetary value of conversion (optional)
• **cost**: Marketing cost for touchpoint (optional, for ROI analysis)

Supported Channel Types:

• Digital: paid_search, organic_search, social_media, email, display, video
• Traditional: tv, radio, print, outdoor, direct_mail
• E-commerce: marketplace, affiliate, referral
• Custom: Any channel name can be used

Output Files Generated

• **attribution_results.csv**: Complete attribution analysis with channel weights
• **channel_performance.csv**: Channel metrics including ROI and CPA
• **customer_paths.csv**: Reconstructed customer journey paths
• **transition_matrix.csv**: Markov chain transition probability matrix
• **attribution_dashboard.png**: Comprehensive visualization dashboard
• **attribution_report.md**: Detailed analysis report and recommendations

Dependencies

• **Core Analytics**: pandas, numpy,