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Conversion lag

Conversion lag is the time between an ad click and the purchase that follows it, which leaves the latest days of a report short of orders still to come.

How it works

Shoppers often buy days after the click. Google Ads dates a conversion to the click, not the purchase. So each day keeps collecting orders for up to 30 days by default, while its spend is already counted in full.

The latest days of any report therefore show less revenue and a lower ROAS than they will later. That is why the last week always looks worse. The lag differs from store to store.

Formula

Date of the conversion − date of the ad interaction, in days

Where you see it

  • Google Ads: the “Conversions” column dates a conversion to the click, and “Conversions (by conv. time)” to the day it happened. Among the attribution reports, the time lag report shows how the delays are spread.
  • Google Ads API: the segments.conversion_lag_bucket segment.

Example

Example store, not client data.

The tableware shop spends 1,000 on one day, and that day’s clicks eventually bring 4,500 in revenue: a ROAS of 4.5. Say 60% of those orders come on the day of the click, 30% in the following week and 10% later. The report shows 2,700 and a ROAS of 2.7 the next morning, and 4,050 and 4.05 a week later.

How GetProfit reads it

The portal’s change log marks a change less than 7 days old as “Too early” and gives a confident conclusion at 14 days. By then, each day of the first week after the change has had at least 7 days to collect late orders.

Not to be confused with

  • Conversion window — the longest lag Google Ads still counts. Google Ads ignores orders after the window.
  • Learning period — the time a bidding strategy needs after a change. Its first days are unreliable because the bidding is still settling, not because orders are on their way.

Right and wrong readings

  • Wrong: “ROAS for the last three days fell, so Monday’s change did harm.” Right: those days are still collecting orders, while their spend is final. Compare periods whose clicks are equally old. In a sales peak, this guides what not to touch in Black Friday week.

Sources