First vs. last click attribution models

What first-click and last-click attribution are

Most customers interact with a brand multiple times before converting. They might see a social ad, later click a search result, then return through email a week after, and finally buy. Attribution models decide which of those touchpoints gets credit for the resulting conversion. First-click attribution gives all the credit to the very first touchpoint in that path. Last-click attribution gives all the credit to the touchpoint immediately before the conversion.

Both are single-touch models, meaning they assign 100% of the credit to one interaction and ignore everything else in the path, even if several channels clearly contributed.

How each model works

First-click attribution answers “what got this person interested in the first place.” If someone discovered a brand through a Meta ad, then converted three weeks later after a direct visit, first-click credits the original Meta ad, since it was the entry point into the relationship.

Last-click attribution answers “what pushed this person over the line.” Using the same example, last-click would credit the direct visit, since it was the touchpoint immediately preceding the purchase, even though the Meta ad was what introduced the customer in the first place.

Neither model looks at the touchpoints in between. A model like linear attribution splits credit evenly across every touchpoint in the path, and time-decay attribution weights later touchpoints more heavily than earlier ones, but first-click and last-click remain the two simplest and most common reference points.

Why it matters

The choice of model changes which channels look valuable, sometimes dramatically. Channels that excel at introducing new customers, like broad prospecting campaigns, tend to look strong under first-click and weak under last-click, since they rarely happen to be the final touchpoint. Channels that excel at closing an already-interested customer, like retargeting or branded search, look strong under last-click and weak under first-click.

Neither view is wrong on its own, but relying on only one gives an incomplete and sometimes misleading picture of what is actually driving results. A business that only looks at last-click data risks underfunding the prospecting activity that generates its customer pipeline in the first place, since prospecting rarely gets credit under that model.

How to act on it

Look at more than one attribution model side by side rather than picking a single default and treating it as the definitive answer. Comparing first-click and last-click views for the same conversion path highlights which channels are doing introduction work versus closing work, which is useful information even without a perfect combined model.

Where possible, favor multi-touch models like linear or data-driven attribution for overall budget planning, and reserve first-click or last-click views for specific questions, like understanding where new customer relationships originate versus what closes them. Incrementality testing remains the best check on any attribution model’s conclusions, since attribution describes correlation along a path, not causation.

Common mistakes

Picking last-click as the sole measure of channel value systematically undervalues prospecting and awareness-stage activity. Assuming first-click captures the “real” source of a conversion ignores that later touchpoints may have done meaningful work to convert genuine interest into a sale. Comparing campaigns evaluated under different attribution settings, without noting the model used, produces numbers that are not actually comparable. Treating any single-touch model as a substitute for true incrementality testing conflates correlation along a click path with causation.