Summary  
This chapter covers algorithms for allocating credit across a sequence of user events using fixed-weight rules (first-click, last-click, linear, time-decay) as well as machine-learning–driven dynamic weighting.  

General domain of usage  
Digital marketing analytics

Attribution is the process of assigning credit to the different touchpoints a user interacts with before converting.

Example customer path:
**Instagram Ad → Blog Post → Email → Purchase**

Definition

### Common Attribution Models

1) **First-click attribution**: credit goes to the very first interaction;

2) **Last-click attribution**: credit goes to the final interaction before conversion;

3) **Linear attribution**: equal credit is split across every touchpoint;

4) **Time-decay attribution**: touchpoints closer to the conversion get more credit;

5) **Data-driven attribution (DDA)**: Machine learning assigns credit based on actual user behavior.

Which attribution model assigns equal credit across all interactions?

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Attribution and Conversion Path Analysis

Common Attribution Models

1. Which attribution model assigns equal credit across all interactions?

2. Match the attribution model to its core logic:

Attribution and Conversion Path Analysis

Common Attribution Models