You will be able to explain how last click and data-driven attribution give credit and which channels each tends to favour.
One of Farah's customers bought a pair of work trousers on a Thursday night. Looking back through the data, the story went like this. Two weeks earlier she clicked a Meta ad, looked at the trousers and left. A week later she searched Google for the shop's name and browsed for a few minutes. On Thursday she opened Farah's newsletter, clicked the button and bought.
So who made the sale: the ad, the search or the email? Farah's freelancer, who runs the ads, would say the ad found her. Farah, who writes the newsletter, would say the email closed it. Both have a point. Attribution is the set of rules that decides how credit for a sale or enquiry is shared among the touches that came before it, and the rule you pick changes which channel looks best.
For a cheap, quick purchase, there may be one touch: someone searches, clicks, buys. For anything that takes thought, like work clothes, a tuition centre or a sofa, people usually come back several times through different channels before they act. Lesson 2.1 of Digital marketing foundations: strategy before tactics, The journey from noticing a problem to telling a friend, described that journey from the customer's side. Attribution looks at it from the report's side.
Each touch that GA4 can see is a click or visit with a source: a Meta ad, an organic search, a newsletter link. GA4 records the sequence for each user, as far as it can follow them on one browser, and then applies a model to share out the credit when a key event happens.
The simplest model is last click. All the credit goes to the last channel the person came through before the key event. In Farah's example, the newsletter gets the whole sale, and the Meta ad and the Google search get nothing.
Last click is easy to understand and easy to check. Its bias is predictable: it favours channels that tend to come at the end of a journey, when people are ready to act. That usually means branded search, where people type your name, and email, which reaches people who already know you. Channels that tend to start journeys, like social ads, display ads and content that introduces you to strangers, look weak under last click even when they are doing the work of finding new customers.
GA4 offers last click as an option, in a form that ignores direct visits where an earlier source exists. Google Ads has a version that gives credit only to Google paid channels.
GA4's default model is data-driven attribution. Instead of a fixed rule, it uses your property's own data to estimate how much each touch added. Broadly, it compares the paths of people who went on to act with the paths of people who did not, and gives more credit to touches that appear to make a key event more likely.
Under data-driven attribution, Farah's sale might be split between the Meta ad, the branded search and the newsletter, with the exact shares depending on patterns in her data. Google does not publish the formula in detail, so you cannot check the split by hand. It is still a reasonable default, because it does not decide in advance which position in the journey matters most.
Its limit is the data it learns from. A small site with few key events gives it less to work with, and it can only share credit among touches GA4 actually saw. Lesson 5.3 covers what that leaves out.
If you read older guides, you will see models called first click, linear, time decay and position based. They gave credit by fixed rules: all to the first touch, equal shares to every touch, more to recent touches, or more to the first and last. Google removed these rule-based models from GA4 and Google Ads in 2023, leaving data-driven and the last click options. If an agency report or course still shows a linear or first click view from GA4, it is out of date.
The useful exercise is not picking the right model. It is comparing them. GA4's advertising section has a model comparison report that shows key events by channel under two models side by side, and a conversion paths report that shows which channels tend to appear early, in the middle or late in journeys.
When Farah compared data-driven with last click for one month, Paid Social gained credit under data-driven and Email lost some. That told her something real: the Meta ads were starting journeys that the newsletter finished. Cutting the ads because they looked weak under last click would probably have shrunk the newsletter's results a few weeks later.
One caution: the model you choose in GA4's attribution settings changes the numbers in the advertising section and some other places, but the traffic acquisition report from lesson 4.1 still credits each session to its own source. That is one reason numbers in different parts of GA4 do not always match.
Your own property will have its own pattern. Which channels gain credit when you move away from last click, and which lose it, tells you more about what each channel does for you than any single number in the report.
Compare key events by channel under data-driven and last click attribution in GA4 and write down which channels gain or lose credit.
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