What Is Last-Click Attribution? How It Works and What It Misses

If someone sees a social ad, later reads a blog post, and finally clicks a branded search result before buying, last-click credits the search result alone. It is simple, easy to explain and the default in many analytics tools, which is why it is so widespread.

Its weakness is that it favours channels near the end of the path, such as branded search, email and retargeting, and undervalues the ones that started the journey, such as video, social and content. If you judge channels only by last-click, you may cut the awareness work that feeds the conversions it reports. It also ignores views that did not involve a click.

It is not useless: it is stable, auditable and a reasonable baseline for short purchase cycles. Compare it against other approaches (see what-is-multi-touch-attribution and what-is-attribution-modeling) and, where you can, test whether channels cause sales (see what-is-incrementality-testing). The right question is not which model is correct, but which is least misleading for the decision at hand.

Last-click is a reporting lens in your analytics and ad platforms, not something Infinall AI measures. Infinall turns a product URL into research, strategy, ad copy and creative that land in an Approval Queue for review before export, and it does not buy media, track conversions or report results. The relevance is how you read results afterwards: top-of-funnel creative from a campaign may look weak under last-click even when it helps start journeys, so consider that before dropping awareness work based on last-click numbers alone.