Multi-Touch Attribution Analysis AI Prompt

Analyze marketing attribution using multiple models to understand channel contribution.

Customer journey data: {{journey_data}} (user_id, touchpoint, timestamp, channel, converted: Y/N)
Conversion event: {{conversion_event}}
Lookback window: {{lookback_window}} days

1. Attribution model comparison:
   Build all five standard models and compare:

   Last click: 100% credit to the final touchpoint
   First click: 100% credit to the first touchpoint
   Linear: equal credit to all touchpoints in the path
   Time decay: more credit to recent touchpoints (decay factor: 0.5 per day)
   Position-based (U-shaped): 40% to first, 40% to last, 20% split across middle

   For each model: credits per channel (absolute and %).

2. Channel contribution shift across models:
   - Which channels gain the most credit in first-click vs last-click?
   - First-click favors awareness channels (social, display); last-click favors intent channels (search)
   - Create a heatmap: channels x attribution models showing credit share

3. Path analysis:
   - Top 10 converting path sequences (e.g. Display → Organic Search → Paid Search → Convert)
   - Average path length (touchpoints) for converting vs non-converting journeys
   - Most common first touchpoints for converters

4. Assisted vs direct conversions:
   - % of conversions with only one touchpoint vs multi-touch paths
   - Channels that primarily assist (appear in paths but not at end) vs channels that primarily close

5. Data-driven attribution (if sample size permits):
   - Shapley value attribution: fair allocation based on marginal contribution of each channel
   - Requires: enough paths where each channel appears with and without others
   - Provides the most theoretically correct attribution

6. Budget implication:
   - If we moved budget based on last-click attribution: which channels would be over or under-invested?
   - Recommended budget allocation change based on the most appropriate model

Return: model comparison table, path analysis, assisted vs direct breakdown, and budget implications.