How to manage UTM Tracking in external platforms with Instant AI

Instant AI automatically appends UTM parameters to every link in your flows and campaigns. These UTMs allow external analytics tools (Shopify, GA4, Triple Whale, etc.) to classify traffic correctly.

Each platform uses a different attribution model, it’s important to understand how UTMs behave in Shopify and what conditions must be met for accurate tracking.

Below is a quick reference of the UTMs we include, followed by the key checks you should make before using external platforms to analyse Instant AI performance.

Example URL:
https://yourstore.com/products/example-product?_ix=abc123&utm_source=instantai&utm_medium=email&utm_campaign=ABANDONED_CART&utm_id=marketingFlow_123abc456def

Technical Requirements for Accurate UTM Tracking and Attribution

The following conditions directly determine how UTMs appear in Shopify, GA4, and other external reporting tools. These are not recommendations — they are the technical factors that govern how attribution works.

1. How URL Type Affects UTM Preservation

Shopify treats storefront URLs and checkout URLs differently. When a shopper is dropped directly into checkout, Shopify may remove UTM parameters during the redirect process, meaning external reporting tools never receive the tracking information identifying the click as email traffic.

This can cause the purchase to be classified under Direct, Organic, or Paid. Storefront URLs, despite coming from your email provider. If your Abandoned Cart or Abandoned Checkout flows link directly to checkout, contact your CSM or help@instant.one to confirm these flows are configured to use storefront URLs where required. Preserving UTMs at the link level is the first dependency for consistent attribution in Shopify and GA4.

You can read more about this behaviour here:
Why Might Instant Be Underperforming in Reporting Tools That Rely on UTMs?

2. How External Analytics Tools Attribute Traffic

Most external analytics platforms, including Shopify, GA4, use session-based attribution. This model assigns revenue to the channel associated with the final tracked interaction within the purchase session. Because attribution is tied to sessions rather than individuals, several predictable behaviours occur:

1. The latest interaction is prioritised over the email click
   If a shopper clicks an email but later engages with a paid ad, organic search result, or social link, the final click replaces the earlier email touchpoint.
2. A new session resets attribution.
   If the shopper returns after a session timeout, reopens the site in a new tab, or resumes activity the next day, the original email click is no longer linked to the conversion. The tool often reclassifies the visit as Direct by default.
3. Device switching breaks continuity.
   If the shopper opens the email on mobile but completes the purchase on desktop or tablet, the analytics platform sees these as different users. Email influence is lost unless the shopper is logged in (which is rare for most stores).

Does the platform that you're using matter?
Shopify is the strictest example of this behaviour. Shopify attribution depends entirely on the continuity of a single browser session and a single last click. It performs no multi-touch modelling, no assisted conversion logic, and no meaningful identity stitching across sessions or devices. When a session restarts, Shopify drops all previous context and reassigns attribution based solely on the new visit. GA4 has a more flexible attribution engine and can use alternative attribution frameworks beyond strict last-click. These mechanisms allow GA4 to preserve some influence that Shopify cannot, though GA4 still loses attribution frequently in cross-device or multi-session journeys.

As a result, you may find that Shopify, GA4, and similar platforms routinely attribute less revenue to email. It's important to understand this isn't necessarily because the email underperformed, but can be due to a number of factors where the model cannot see the full picture through identity-based attribution.

3. Why ESPs Capture Influence External Tools Cannot See

Email platforms use identity-based attribution, meaning every open, click, and purchase is tied back to a known subscriber’s email address. Because this attribution is built on a persistent identity, the ESP can recognise the same shopper across different devices, sessions, and touchpoints. This enables the ESP to continue attributing influence even when the shopper takes a longer or more complex path to purchase.

External analytics tools (Shopify, GA4, Triple Whale) do not track identity using email addresses. They rely on browser sessions, cookies, device IDs, or Google Signals, which means they treat each session, and in many cases each device, as a separate user. If the shopper changes devices, returns in a new session, or interacts with other channels before converting, these tools have no mechanism to link that behaviour back to the original email.

Because ESPs track identity, not just sessions, they can attribute a purchase even if the shopper only opened the email and didn’t click it. They can also attribute based on influence over a longer window (e.g., 5-day open/click influence) instead of requiring the conversion to happen in the same browser session. This is common in emails where a customer journey needs to be nurtured over a multi-day flow. 

4. Why Conversions Don’t Always Come From a Clicked Link

UTM-based reporting only tracks conversions that begin with a recorded click, but many purchases influenced by email do not start this way. A shopper may read an email, absorb the content, and return later through Direct, Organic Search, or another channel without ever clicking a link in the email. In these cases, the email still shaped the purchase decision, but because no tracked click occurred, external analytics tools cannot attribute the visit to email.

Email design plays a significant role in whether UTMs are captured. Emails focused on storytelling, education, social proof, product highlights, or general brand reinforcement often drive intent rather than clicks. These emails influence the shopper’s decision-making, but do not always prompt a direct click to the site. In contrast, emails engineered around click-heavy CTAs (e.g., “redeem your offer” or “shop now”) naturally generate more UTM-tagged sessions simply because they require a click to proceed. 

Because UTMs only measure click-driven activity, they capture just one portion of email influence. A low UTM count does not indicate weak performance, it reflects how the shopper interacted with the email, how the email was designed, and whether the conversion journey required a click at all. Many high-performing emails drive revenue through influence rather than direct click-through behaviour, especially in multi-touch or multi-day customer journeys.

Understanding these differences in link behaviour, session attribution, identity tracking, and click dynamics explains why external reporting tools often show lower email-attributed revenue than ESP dashboards.

These discrepancies reflect how each platform measures attribution, not the performance of the emails themselves. If accurate UTM tracking is important for your reporting setup, contact your CSM or help@instant.one to ensure your flows are configured to preserve UTMs across all entry points.