An attribution model is a rule for distributing credit for a conversion across the marketing touchpoints in a customer’s journey. A customer who saw a Facebook ad, clicked a Google ad, and purchased after an email gets tracked differently depending on which model you use. Each model tells a different story about which channel deserves credit — and choosing the wrong model can lead to budget decisions that hurt your results.
The Six Main Attribution Models
1. Last Click Attribution
All credit goes to the last touchpoint before the conversion. Most common default in GA4 and many ad platforms.
Best for: understanding which channels close sales. Good for evaluating lower-funnel campaigns (branded search, retargeting).
Problem: undervalues awareness channels (Meta prospecting, YouTube, display) that influence purchase intent without getting the last click.
2. First Click Attribution
All credit goes to the first touchpoint that brought the customer in. Flips the last-click problem — now discovery channels get all the credit.
Best for: understanding which channels are best at bringing in new customers. Useful for evaluating top-of-funnel prospecting campaigns.
Problem: ignores everything that happened between discovery and conversion, which can be significant for considered purchases.
3. Linear Attribution
Credit is divided equally across all touchpoints in the conversion path. If there were 5 touchpoints, each gets 20% of the credit.
Best for: giving every touchpoint some recognition without overclaiming for any single channel. Useful when you want to see relative engagement across channels.
Problem: treats all touchpoints as equally important, which is rarely true. The email that converted the customer deserves more credit than the display impression from three weeks ago.
4. Time Decay Attribution
Credit is distributed across all touchpoints, but touchpoints closer to the conversion in time get more credit. The touchpoint right before the purchase might get 30%, three days earlier might get 20%, and the Instagram ad from two weeks ago gets 5%.
Best for: longer sales cycles where multiple touches over a period of time contribute to the purchase decision. The more recent the touchpoint, the more it mattered.
Problem: still undervalues early-stage awareness if the consideration period is long.
5. Position-Based (U-Shaped) Attribution
First touch and last touch each get 40% of the credit. The remaining 20% is distributed across all middle touchpoints. Designed to value both the initial discovery and the final conversion touchpoint.
Best for: stores where first contact (discovery) and final conversion trigger are both strategically important to understand.
Problem: the 40/40/20 split is arbitrary. It is better than last-click but not based on actual data about what influences your specific customers.
6. Data-Driven Attribution (DDA)
Uses machine learning to assign credit based on the actual contribution each touchpoint makes to conversions in your specific account. Google Ads and GA4 offer DDA for accounts with sufficient conversion volume.
Best for: accounts with enough data (hundreds of conversions per month) where the model can identify genuine patterns in how touchpoints influence purchase decisions.
Problem: requires significant conversion volume to be statistically meaningful. For small accounts, DDA may not have enough data and reverts to a simpler model.
Which Attribution Model Should You Use in GA4?
GA4 uses Data-Driven Attribution by default for conversion reporting if your property has enough data. If not, it falls back to Last Click.
For most Shopify stores with moderate ad spend:
- Use Last Click in GA4 as your baseline for cross-channel comparison (consistent, comparable)
- Use Data-Driven in Google Ads Manager if your account qualifies (best for campaign optimisation within Google)
- Use platform-native attribution within each ad platform for within-platform decisions
Attribution Models in Ad Platforms vs GA4
Each ad platform has its own attribution model applied within its own ecosystem. When you change the attribution model in Google Ads, it only affects how Google attributes conversions within Google Ads — not how GA4 reports channel performance.
GA4’s model (accessible in Reports → Attribution → Attribution Settings) applies to how GA4 distributes credit across all channels in its reports. These are two separate systems that can coexist.
The Practical Takeaway
No attribution model is perfectly accurate. Every model is a simplification. The goal is not to find the one true attribution model but to use consistent models that help you make better decisions:
- Consistent last-click for cross-channel comparison
- Native platform attribution for within-platform optimisation
- Incrementality testing when you need to know true causal impact
Book your free Shopify tracking audit here and we will review your current attribution settings across GA4 and your ad platforms to make sure you are measuring performance consistently.