How can you isolate performance per trigger type?

You've got a welcome series, an abandoned cart flow, and a post-purchase sequence all running at once. Your dashboard shows blended revenue and a single open rate. That number means almost nothing. A welcome email that converts 8% and a cart abandonment that converts 1% look identical when you average them together.

Here's how to pull them apart so you can actually see what's working.

Step 1: Tag every trigger type in your UTM parameters

If you're not adding UTM parameters to your automation links, you're flying blind in Google Analytics. The utm_medium field should always be email. The utm_source should identify the trigger type. Something like welcome, cart-abandonment, post-purchase, or winback. Use utm_campaign for the specific flow name and utm_content for the individual email inside that flow.

A finished UTM string for a welcome flow might look like this:

?utm_source=welcome&utm_medium=email&utm_campaign=welcome-series&utm_content=email-2-day3

Once you're consistent with this structure, you can filter your GA4 or Shopify analytics by source and see exactly how much revenue each trigger type generates, not just in aggregate.

Step 2: Use custom fields or tags inside your ESP

Now most platforms (Klaviyo, ActiveCampaign, Brevo) let you tag a contact or an event with a custom property at the point the trigger fires. In Klaviyo, you can add a flow tag like trigger_type: cart_abandonment when a checkout-started event fires. This means your email-level reporting inside the platform can be filtered by trigger type too, not just by flow name.

In ActiveCampaign, you'd use a custom deal or contact tag added by an automation action. In Brevo, campaign labels do the same job. The exact setup varies by platform, but the principle is the same: stamp the trigger source at the moment it fires, not after the fact.

Step 3: Compare each trigger type against the right benchmark

This is where people go wrong. A welcome email will almost always have higher open rates than a winback email. That's not because your welcome flow is brilliant. It's because the audience is warmer. Comparing them head-to-head misses the point.

Instead, set a KPI that fits each trigger type. Transactional and behavioural triggers (cart abandonment, post-purchase) should be judged on revenue per recipient or conversion rate. Welcome and onboarding flows are better measured on engagement rate and list health over the first 30 days. Winback flows should be measured on re-engagement rate and unsubscribe rate (because clearing out disengaged contacts is actually a win there).

Step 4: Run a holdout group per trigger type

If you want to know the true lift your automation is generating, you need to hold back a small percentage of people from each trigger type. Around 5-10% works for most senders. The people who get nothing become your control group. Compare their conversion rate to the group that received the automation, and you'll know whether the trigger is genuinely driving behaviour or just capturing people who would have converted anyway.

But this matters most for cart abandonment, where correlation is high but true incrementality is often lower than it looks. A shopper might have come back to buy regardless. The holdout tells you how much of that revenue is really yours to claim.

If you're not sure how conversion attribution works differently across trigger types, that's worth reading before you start interpreting these numbers.

Once you have clean data by trigger type, you'll know exactly where to put your optimisation energy. Usually one or two triggers drive most of the value. The rest either need fixing or aren't worth the maintenance. (That's a more useful conclusion than a blended revenue number will ever give you.)

If you want a second pair of eyes on your automation setup or you're not sure which metrics to trust in your specific ESP, our SOS hotline is free and we're happy to take a look.