How long does it take customers to buy, according to GA4?
GA4 shows it as Days to key event in its attribution paths report. If most buyers arrive once and buy, the figure looks tiny. GA4 only times the touches it can tie to one browser or signed-in user, so the full wait is usually longer.
By Joris van Huët, Founder & CEOUpdated 6 min read
GA4 answers it in the Days to key event column of its attribution paths report: the days from an ad interaction to the purchase. If most of your buyers arrive once and buy, the figure looks like hours. The full wait is usually longer, because GA4 can only join touches it ties to one browser or signed-in user.
The usual answer quotes one number from that report and moves on. One number hides two very different kinds of buyer, and it only times the part of the trip GA4 saw. Google defines Days to key event as the number of days from when the ad interaction happened until the key event. Its partner column, Touchpoints to key event, counts the ad interactions it took.
What one store's data shows
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 to 3 touches (12.5 days to buy) | 12.2% | Journeys sheet, 2-3 touches row |
| Journeys with 4 to 9 touches (16.9 days to buy) | 5.4% | Journeys sheet, 4-9 touches row |
| Journeys with 10 or more touches (16.0 days to buy) | 3.0% | Journeys sheet, 10+ touches row |
Ask how long this one store's customers took, and the Journeys sheet gives two honest answers.
Follow the money, and most of it says about half a day. Journeys with 1 touch hold 79.5% of revenue in this one store, and they took 0.5 days (Journeys sheet).
Count distinct paths instead, and the answer is closer to two weeks. Multi-touch journeys are 3,656 of the 3,670 distinct path sequences on the Journeys sheet, and they took between 12.5 and 16.9 days. Those are distinct routes, not purchases. Together they hold about a fifth of revenue.
More touches did not mean more days. On the Journeys sheet, journeys with 10 or more touches took 16.0 days. Journeys with 4 to 9 touches took a little longer, at 16.9 days (Journeys sheet). Past a few visits, extra touches seem to bunch into the same couple of weeks rather than stretch the wait.
Then look at how buyers arrived. Direct holds 57.7% of revenue in this one store, in last click, first click and touched views alike (Channels sheet). A Direct visit can be where a trip GA4 lost track of comes back into view.
What the sheet cannot show is the spread inside each row, or anything GA4 never recorded. A shopper who heard about you on a podcast, then typed your address, shows up as a single Direct touch. A shopper who browsed on a phone and bought on a laptop can look just as quick.
Why does GA4's answer run short?
The count starts at a touch GA4 recorded. Google lists touchpoints such as site visits, impressions, engaged views and emails. A tip from a friend or a shop window never starts the clock.
A new device looks like a new customer. Google's own example is a shopper on three screens. They browse on a tablet at breakfast, research on a work computer at lunch and buy on a phone after dinner. GA4 joins those visits through a user ID you send, or through one browser's client ID. Without a sign-in, the phone purchase can look like a quick, one-touch trip.
Declined cookies leave gaps. Google says that when users decline Analytics identifiers like cookies, behavioral data for those users is unavailable. So their earlier visits usually cannot join the path that ends in a purchase.
The lookback window sets a ceiling. For purchases it is 90 days by default, with 30 or 60 days as the other choices. A touch older than that drops out of the path, so the count of days stops there too.
What can the number not tell you?
It cannot tell you whether the ads were needed. A fast path may be a loyal customer using an ad as a shortcut to checkout. A slow one may be someone who was always going to buy, just not yet.
It also gives you one cell, not a spread. The report's top row puts Days to key event for every selected path into a single figure. A slow minority can hide behind many quick buyers, so split the paths by length before you quote anything.
What to do this week
- Read the purchase-only figure. In GA4, click Advertising, then Attribution paths, and untick every key event except purchase. Note Days to key event in the top row. Pass: you have a figure for purchases alone. Fail: it blends sign-ups or carts, because GA4 selects every key event by default.
- Split quick buyers from slow ones. Under Customize report, set Path length to equal to 1 and note the days and revenue. Then switch to greater than 1. Pass: you can say what share of purchase revenue takes several touches, and how long those paths take. Fail: you still quote one blended number.
- Check how GA4 recognises your buyers. In Admin, under Data display, open Reporting identity. Pass: it reads Blended or Observed, and your store sends a user ID for signed-in customers. Fail: it reads Device based, or no user ID is sent, so each new device starts a new, shorter path.
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: Key events attribution paths report (Google Analytics Help); Analytics dimensions and metrics (Google Analytics Help); Get started with attribution (Google Analytics Help); Select attribution settings (Google Analytics Help); Reporting identity (Google Analytics Help); About attribution reports (Google Ads Help).
Related answers
Frequently asked questions
Why does GA4 say most customers buy on their first visit?
Usually because GA4 counts from the first touch it recorded. A shopper who switched devices, cleared cookies or declined them arrives as a new user, so their purchase shows as a short path. The habit may be real, but check your reporting identity before you believe it.Does Google Ads measure time to purchase the same way as GA4?
No. Google Ads' Path metrics report counts only Google ad interactions, and you choose whether to measure from the first or the last one. GA4's attribution paths hold every channel GA4 recorded. Quote each figure with its source and its starting point.Do one-visit purchases mean my ads are not needed?
No. A one-touch path only means GA4 recorded one touch before the purchase. The buyer may have seen your ads on another device, or before a cookie reset. To learn whether the ads were needed, keep some people or regions away from them and compare sales.
Go deeper: Causal attribution, explained.
Sixty-second versions of these ideas: Causality Engine on YouTube Shorts.
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Terms in this article
- AnalyticsAnalytics is the systematic computational analysis of data. It reveals customer behavior and measures campaign performance.
- AttributionAttribution identifies user actions that contribute to a desired outcome and assigns value to each. It reveals which marketing touchpoints drive conversions.
- Attribution ReportAttribution Report shows which touchpoints or channels receive credit for a conversion. It identifies which campaigns drive desired actions.
- ConversionConversion is a specific, desired action a user takes in response to a marketing message, such as a purchase or a sign-up.
- Google AdsGoogle Ads is an online advertising platform where advertisers bid to display ads, service offerings, and product listings.
- Google AnalyticsGoogle Analytics is a web analytics service that tracks and reports website traffic.
- ImpressionAn Impression counts each time an ad or content displays on a user's screen. It measures exposure, not engagement.
- TouchpointTouchpoint is any interaction a customer has with a brand throughout their journey. In marketing attribution, each touchpoint is a data signal to understand marketing impact.