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Klaviyo Attribution Setup: Measure True Email Impact

Is your email marketing actually creating new sales, or just capturing them? Tag your Klaviyo links so GA4 sees them as Email, and a causal read shows what Email caused next to what last-click gave it.

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By , Founder & CEOUpdated 3 min read

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Your Email List is an Asset. Are You Measuring Its True Value?

Klaviyo credits an order to the last email a customer opened or clicked within five days, by default (Klaviyo's attribution rules), whether or not the email made the difference. That's self-reported attribution: it can't tell you how many of those customers would have bought anyway, so it flatters the flows that reach people already on their way to checkout. Tag your Klaviyo links so GA4 files them under Email, and you get a second number to hold it against.

GA4 counts differently. It only sees email when someone clicks a tagged link, so an email that was opened but never clicked gets no credit there, and in its Traffic acquisition report a buyer who clicked an email and came back through another channel counts for that channel. Neither number is what Email caused. If much of your email revenue would have happened anyway, for example abandoned-cart discounts going to customers who were about to buy regardless, what Email caused is smaller than Klaviyo reports, and only causal inference or a test can say by how much.

See Beyond the Click: The Causal Impact of Email

Setup takes minutes, in Klaviyo and GA4. In Klaviyo's UTM tracking settings, turn on automatic UTM parameters for campaigns and flows and check that utm_medium reads email: accounts that saved their settings before June 2, 2025 can still send campaign or flow (Klaviyo's UTM guide), and GA4 usually files those visits under Unassigned instead of Email. Give it a few weeks of tagged sends, then look at your email marketing next to Paid Social, Paid Search and Organic Search in GA4's Traffic acquisition report.

Three checks before you cut or scale email:

  • Put Klaviyo's number in proportion. Divide the revenue Klaviyo attributes to email by your store's total revenue for the same days. Anyone who opened a message in the five days before buying counts, so a big share partly measures how often your list opens, not only what email sold.
  • Hold it against GA4. Compare it with the revenue GA4 gives the Email channel for the same days. The gap is roughly the orders Klaviyo credits on an open, or where the buyer came back through another door, sometimes a retargeting ad.
  • Test it. Run a simple incrementality test: hold out a random slice of a flow's recipients for a few weeks and compare how many of them converted with the rest. The difference is what the flow added.

The Math of Incremental Email Revenue

Klaviyo's reported revenue answers "which orders followed an email?" The number you want answers a different question:

Incremental Email Revenue = (Revenue from Email Group) - (Predicted Revenue if Group Received No Email)

Every platform grades its own homework, and Klaviyo's attributed revenue is no exception: it counts the orders that followed an email within its window. The second term is the hard part; the holdout in the checks above measures it directly, and why email attribution breaks goes into the rest.

Klaviyo attribution: what email caused, as a channel

Frequently asked questions

  • Does this replace Klaviyo's reporting?
    No. Keep Klaviyo for open rates, click rates and flow performance. The checks here answer a different question, what Email caused as a channel, by holding Klaviyo's number against GA4 and a holdout.
  • How quickly can I see results for my Klaviyo integration?
    There is no Klaviyo connection to set up; the read runs on your GA4 export. Results arrive 1 to 2 minutes after the upload, and there is no pixel and no SDK to install.
  • Can you differentiate between flows and campaigns?
    No. The read works on GA4's channel groups, so it shows what Email caused as a whole, not flows and campaigns separately. To compare a flow with a campaign, use Klaviyo's own reports for the operational view, or run a holdout test on the flow.

Go deeper: Causal attribution, explained.

Sixty-second versions of these ideas: Causality Engine on YouTube Shorts.

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