Dashboard
Marketing Attribution Models
Analyze the effectiveness of marketing channels across different attribution models
Feature in Development
Advanced attribution modeling functionality is currently being implemented. The visualizations below contain placeholder data.
Coming soon: First-touch, last-touch, linear, time-decay, Markov Chain, and Shapley Value attribution models.
Attribution Model Selection
Customer Journey Flow (Sankey Diagram)
Visualization of customer touchpoints across the conversion journey
Channel Attribution Summary
| Channel | Attributed Conversions | Attributed Revenue | % of Total |
|---|---|---|---|
| Facebook Ads | 127 | $12503.45 | 32.5% |
| Google Ads | 98 | $9876.50 | 25.7% |
| Organic Search | 76 | $7125.33 | 18.5% |
| 54 | $4987.22 | 13.0% | |
| Direct | 39 | $3982.45 | 10.3% |
Model Comparison
| Attribution Model | Organic | Direct | |||
|---|---|---|---|---|---|
| Last Touch | 24.5% | 28.7% | 18.5% | 10.0% | 18.3% |
| First Touch | 42.7% | 32.1% | 15.3% | 4.1% | 5.8% |
| Linear | 33.6% | 30.4% | 16.9% | 7.2% | 11.9% |
| Markov Chain | 32.5% | 25.7% | 18.5% | 13.0% | 10.3% |
* Percentages represent the attribution of total conversions to each channel according to different models
Methodology
Last Touch attribution assigns 100% of the conversion credit to the final touchpoint before conversion. This model is simple but tends to overvalue bottom-of-funnel activities.
First Touch attribution assigns 100% of the conversion credit to the first touchpoint in a customer journey. This model emphasizes discovery channels and top-of-funnel activities.
Markov Chain attribution uses a probabilistic approach to model the customer journey as a series of states and transitions. It calculates the removal effect of each channel to determine its importance in driving conversions.
The credit assigned to each channel is based on how much conversion probability would decrease if that channel were removed from the path entirely, representing the true incremental value of each touchpoint.
Shapley Value attribution is based on cooperative game theory. It calculates the marginal contribution of each channel by considering all possible combinations of channels and their respective conversion outcomes.
This model provides a fair distribution of credit by considering the value added by each channel in all possible sequences, making it highly accurate but computationally intensive.