What is position-based attribution?
Position-based attribution, or U-shaped, gives 40% of a sale's credit to the first touch and 40% to the last, and shares 20% across the middle. GA4 and Google Ads dropped it in 2023 and Shopify does not offer it, so you rebuild it from a paths export.
By Joris van Huët, Founder & CEOUpdated 7 min read
Position-based attribution usually gives the first and last touch before a sale 40% of the credit each. The touches in between share the other 20%. Plotted, the credit forms a U, so it is also called U-shaped. GA4 and Google Ads no longer offer it, so today you rebuild it from your own paths export.
What one store's data shows
The formula is the easy part. The harder part is how much of your revenue has a first, a middle and a last touch at all. One store's export puts a size on that.
One store's anonymised GA4 export, 1 January 2024 to 21 August 2026. It holds shares of revenue only: no ad spend, no order counts.
| What the export shows | Share of revenue | Source cell |
|---|---|---|
| Journeys with 1 touch (0.5 days to buy) | 79.5% | Journeys sheet, 1 touch row |
| Journeys with 2 or more touches, added up | 20.6% | Journeys sheet, 2 to 3, 4 to 9 and 10+ rows added |
| Journeys with 2 to 3 touches (12.5 days to buy) | 12.2% | Journeys sheet, 2 to 3 touches row |
| Direct, in last click, first click and touched views | 57.7% | Channels sheet, Direct row |
On the Journeys sheet, journeys with 1 touch hold 79.5% of revenue, with 0.5 days to buy. A path of one touch has no positions. Its first touch is its last touch, so position-based hands it the whole sale, exactly as last click would.
Only journeys with 2 or more touches give the model anything to weigh. On the Journeys sheet they hold 20.6% of revenue: 12.2%, 5.4% and 3.0% added together. Swap last click for position-based, and on the Journeys sheet's numbers only that 20.6% can change hands.
The middle is smaller still. It needs at least 3 touches, and a two-touch path simply splits between its two ends. The 2 to 3 touches row, with 12.2% of revenue on the Journeys sheet, mixes both kinds. So in this one store, the middle can never collect more than a fifth of the 20.6% on the Journeys sheet.
On the Channels sheet, Direct holds 57.7% of revenue in last click, first click and touched views alike. Position-based is mostly a blend of first and last. On longer paths the two ends take four fifths of the credit, and on short ones all of it. When both views agree on a channel to the decimal, the blend has little room to move it.
So for this one store, choosing between position-based and last click is a small question. The bigger one is what the export cannot see: whether the first recorded touch introduced anybody, and whether any touch changed a mind.
Why does the fixed split mislead?
Because it is a setting, not a finding. Google's legacy help called it one common scenario to give the first and last interaction 40% each and the middle 20%. The same page says to use the model if you most value the touchpoints that introduced customers and the ones that closed the sale.
That is a statement of belief. Google's old Model Comparison Tool even let users build custom models from a Position Based baseline, tailored to the assumptions they wished to test. Feed the rule your weights and it hands your weights back, neatly formatted.
Then there is the word first. It means the first touch a tool recorded inside its lookback window, not the day the buyer first heard of you. For key events such as purchases, GA4's lookback window defaults to 90 days. Shopify resets a visitor's first interaction referrer if they buy nothing within 30 days of a session. A buyer who hears about you at a dinner party and then searches your name opens the path with that search. The search collects the introducer's prize.
Direct is the next trap. Take Google's legacy example: Paid Search, then Social Network, then Email, then a direct visit. Position-based gave Paid Search and Direct 40% each, and Social Network and Email 10% each. A typed visit at the end earned as much as the ad that opened the journey. GA4's current models go the other way: direct visits get no credit unless the whole path was direct. Rebuild the model yourself and you have to pick a side.
And the middle is where reminders and second looks sit, such as a review email or a retargeting ad. Position-based pays all of them a fifth between them, whatever they did.
What can position-based not tell you?
It cannot tell you which touch changed the buyer's mind. It pays places in a queue, not influence. A branded search in last place earns the same share as the ad that started the journey.
It cannot see touches that left no record, such as a recommendation from a friend or a video watched on someone else's phone. Those come before the first recorded touch, so the U starts in the wrong place.
Google gave its own verdict when it dropped the model. Its April 2023 notice says rules-based models don't provide the flexibility needed to adapt to evolving consumer journeys. GA4 lost position-based in November 2023, and Google Ads moved conversion actions that still used it to data-driven attribution. Shopify's marketing reports offer Last non-direct click, Last click, First click, Any click and Linear, but no position-based model.
Even the old help told users to test their assumptions by experimenting: move investment as the model suggests, then watch the results. That is the honest use of position-based today. It frames a question cheaply, and a holdout test answers it.
What to do this week
- Measure how much revenue has a middle. In GA4, click Advertising, then Attribution paths under Attribution, pick purchase and note the total purchase revenue. Then set Path length to greater than or equal to 3 touchpoints and note it again. Pass: most purchase revenue sits on paths of 1 or 2 touches, so position-based and last click will mostly agree. Fail: most of it sits on longer paths, so the weights move real money.
- Put first click next to last click. In your Shopify admin, open Analytics > Reports, set the Category filter to Marketing and choose Performance by referring channel. In the Attribution menu, include First click and Last click. Pass: both rank your channels the same way, so a blend of the two usually will too. Fail: they disagree, so the weighting would be making your decision for you.
- Check the middle against GA4's own model. In the same Attribution paths report, set the chart's attribution model drop-down to data-driven and read the Early, Mid and Late touchpoints bars. Pass: your main channels earn most of their credit early or late, where the U pays most. Fail: a channel you pay for earns most of it in Mid, so position-based would underpay it.
Check the homework. Your GA4 Attribution paths export already holds the evidence. Causality Engine reads that one file and shows what each channel caused next to what last-click gave it, in 1 to 2 minutes, for €99 once (excluding VAT), refundable within 30 days. Check the homework
Sources, 1 October 2026: Overview of Attribution modeling in MCF (legacy) (Google); About the default MCF attribution models (legacy) (Google); About the MCF Model Comparison Tool (legacy) (Google); Get started with attribution (Google); Key events attribution paths report (Google); Select attribution settings (Google); First click, linear, time decay, and position-based attribution models are going away (Google); About attribution models (Google); Marketing reports (Shopify)
Related answers
Frequently asked questions
Is position-based attribution the same as U-shaped attribution?
Yes, they are two names for one rule. It usually gives 40% of the credit to the first touch, 40% to the last and 20% to the touches between. Plotted along the path, the credit forms a U. Google's legacy help called it the Position Based model.Can I still use position-based attribution in GA4 or Google Ads?
No. GA4 dropped first click, linear, time decay and position-based models in November 2023. Google Ads upgraded conversion actions on those models to data-driven attribution, and last click is still supported. To see position-based today, rebuild it from GA4's Attribution paths export.Which touch counts as first in position-based attribution?
The first one the tool recorded inside its lookback window, not the moment the buyer first heard of you. For key events such as purchases, GA4's window defaults to 90 days. Shopify's first interaction referrer resets if a visitor buys nothing within 30 days of a session.
Go deeper: Incrementality testing, explained.
Sixty-second versions of these ideas: Causality Engine on YouTube Shorts.
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Terms in this article
- AttributionAttribution identifies user actions that contribute to a desired outcome and assigns value to each. It reveals which marketing touchpoints drive conversions.
- Attribution ModelAn Attribution Model defines how credit for conversions is assigned to marketing touchpoints. It dictates how marketing channels receive credit for sales.
- Attribution ModelingAttribution Modeling is a framework for assigning credit for conversions to various touchpoints in the customer journey. It helps marketers understand and improve campaign effectiveness.
- ConversionConversion is a specific, desired action a user takes in response to a marketing message, such as a purchase or a sign-up.
- Holdout TestA holdout test is an experiment where a portion of the audience does not see a campaign. This measures the campaign's true incremental impact.
- IncrementalityIncrementality measures the true causal impact of a marketing campaign. It quantifies the additional conversions or revenue directly from that activity.
- Incrementality TestingIncrementality Testing measures the additional impact of a marketing campaign. It compares exposed and control groups to determine causal effect.
- RetargetingRetargeting is online advertising that targets users who have previously interacted with your website or content. Attribution analysis shows the causal role of retargeting in driving conversions and improving ad spend.