Attribution & Conversion Counting

First-Click Attribution vs Linear Attribution

In short: Both models look past the final click to give credit to earlier parts of the journey, but they disagree on how much of the journey deserves recognition. First-click hands the entire conversion to the very first touch and nothing else. Linear spreads credit evenly across every touch in the path, first included but not favored. Both were retired as selectable models in Google Ads and GA4 in 2023, so today you would be computing either from an external multi-touch export. Pick first-click when you specifically need to isolate the discovery moment; pick linear when you want to see the whole path without singling any one step out.

By the AdFlint research team · Fact-checked against current Google and Meta platform behavior · Last reviewed July 2026

First-Click Attribution

Assigns the full conversion credit to the first recorded ad interaction in a user's path, treating discovery as the decisive moment.

The earliest touch in the conversion path takes 100 percent of the credit, which highlights channels that create demand rather than harvest it. Teams reach for it when arguing that prospecting is undervalued by default reporting. Google Ads and GA4 retired it as a selectable model in 2023, so it now lives mainly in independent analytics. Its flaw is symmetrical to last click: it ignores everything that closed the sale.

Full definition

Linear Attribution

Splits conversion credit evenly across every touchpoint in the path, so a five-touch journey gives each interaction twenty percent.

Every recorded interaction receives an identical share of the conversion, which makes long paths visible without asserting that any one step mattered more. Analysts use it as a neutral starting point when comparing channel involvement rather than channel impact. Google Ads and GA4 removed it from their reporting in 2023, though it remains standard in other analytics tools. The trap is treating equal credit as evidence of equal influence.

Full definition

Side by side.

The differences that actually change what happens in your account.

	First-Click Attribution	Linear Attribution
What gets credited	Only the first touch, 100 percent.	Every touch, split evenly.
Sensitivity to path length	None - the first click always gets everything regardless of how many touches follow.	High - each individual touch's share shrinks as more touches are added to the path.
What question it answers	What introduced this customer to us?	How many different touches, and roughly which channels, were present along the way?
Availability today	Retired as a selectable model in Google Ads and GA4 in 2023.	Also retired as a selectable model in Google Ads and GA4 in 2023.
Treats mid-path and last-click touches as	Zero credit, no matter how influential they were.	Equal partners with the first touch, each getting the same share.
Best paired with	Last-click, as the two opposite extremes to bracket a channel's real range of value.	A weighted model like time-decay or position-based, once you know linear's flat baseline.
Failure mode	A campaign that happened to be first by chance, not strategy, gets full credit for a sale it barely influenced.	A ten-touch path dilutes the one channel that actually mattered down to a 10 percent share, same as every other touch.

What actually separates them.

First-click is fixed to a single moment in time, whichever click happened earliest, while linear's credit is spread across the entire recorded sequence, so first-click can never see anything that happened after the opening touch.

Linear's per-touch share is inversely proportional to path length; first-click's share is unaffected by path length entirely, since the winner is always the same one touch regardless of how many followed it.

Both models were removed as selectable options in Google Ads and GA4 in 2023, so unlike the last-click comparisons in this family, neither one is a live platform setting anymore - both require an external path export to compute.

First-click structurally cannot represent that a channel showed up three times across the journey, while linear counts every occurrence, which means a channel that repeats itself accumulates more total credit under linear even though each individual touch's share is small.

Running both models side by side on the same conversion data tells you something neither does alone: a channel that is strong on first-click but weak on linear likely only shows up once, right at the start, while a channel that is weak on first-click but present on linear likely recurs throughout the path without ever opening it.

Which one should you use?

Use First-Click Attribution when

You need to isolate specifically which channel introduced a customer, separate from everything that happened afterward.
You are building a case for awareness or prospecting spend that never shows up as the closing touch.
You have the timestamped path data to compute it, since it is no longer live in Google Ads or GA4.
You want the sharpest possible contrast against last-click to bracket a channel's plausible range of influence.

Use Linear Attribution when

You want a neutral view of every touch in the path without deciding in advance that any one moment matters most.
You are checking whether a channel shows up repeatedly throughout journeys, not just once at the start or end.
You have full multi-touch tracking across the path, since partial tracking will understate whatever you did not capture.
You are using it as a baseline before moving to a weighted model like time-decay or position-based.

Common questions.

Is linear attribution better than first-click for understanding my funnel?

Neither is objectively better, they answer different questions. First-click isolates the single discovery moment; linear shows the full spread of touches without deciding any one of them was more important, which is useful precisely because it makes no claim about which step mattered most.

Can I combine first-click and linear into one number?

Not directly as standard models, but many advertisers look at both side by side: a channel that scores high on first-click and low on linear typically only appears once, right at the start of the path, while a channel that scores low on first-click but reasonably on linear tends to recur throughout the journey without ever opening it.

Why did Google Ads remove both of these models?

Google Ads and GA4 retired the full set of rule-based comparison models, including first-click and linear, in 2023 and moved every account to data-driven attribution as the default, on the reasoning that a modeled, data-based split is more useful than a fixed rule picked in advance. Both models still exist conceptually and can be reconstructed from exported path data, just not inside the platforms themselves.

Does linear attribution require the same tracking as first-click?

It requires more. First-click only needs you to correctly identify the earliest touch in a path; linear needs every touch in that same path tracked and timestamped, so any tracking gap, a missed UTM or a blocked pixel, understates linear's credit for that channel more than it would understate first-click, which only cares about one specific touch.

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