Attribuly Blog
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Alex Li
30 min read

What is multi-touch attribution in Shopify email?

Plain-English guide to multi-touch attribution for email in Shopify: why Shopify and Klaviyo numbers differ, common models, UTMs, identity stitching, and fixes.

What is multi-touch attribution in Shopify email?

If Shopify says an order came from “Direct,” Klaviyo credits a reminder email, and paid social claims an assist, who’s right? Here’s the short answer and the setup you need so email gets fair credit without double‑counting.

Definition — Multi‑touch attribution for email in Shopify: It’s a way to share conversion credit across every meaningful email touch (flows and campaigns) alongside other channels on the path to a Shopify order, so reporting reflects real‑world collaboration instead of a single last click.

Key takeaways

  • Multi‑touch attribution for email in Shopify distributes credit across flows and campaigns, not just the final click.

  • Shopify and Klaviyo disagree because of lookback windows, click vs. open rules, identity/deduping, and revenue timing.

  • A practical mixed journey to test: campaign click → social retargeting → email reminder click → mobile purchase.

  • Keep email touches from being lost by enforcing UTMs, aligning windows, stitching identities, and using Shopify pixels and (optionally) server‑side events.

  • Validate with model comparisons and document your rules to prevent apples‑to‑oranges debates.

What is multi-touch attribution in Shopify email? (the short answer)

In email‑heavy stores, a purchase rarely comes from one message. A welcome email introduces the brand, a campaign drives the first browse, a retargeting ad brings them back, and a cart recovery email closes the deal. Multi‑touch attribution acknowledges this teamwork. Instead of giving 100% credit to the last click, it shares credit across the touches that happened within your chosen windows and rules.

Scope notes:

  • “Email touches” include both automated flows (welcome, browse/cart recovery, win‑back) and one‑time campaigns.

  • Cross‑device journeys are normal; identity stitching connects desktop email clicks to mobile checkouts.

  • Privacy changes (like Apple Mail Privacy Protection) can inflate opens; prefer click‑based email attribution when reconciling to click/session tools.

Why Shopify and Klaviyo numbers don’t match

Most disputes trace back to five mechanics:

  1. Lookback windows

  1. Click vs. view/open

  1. Model rules

  • Klaviyo defaults to last‑touch for message attribution, with an option to switch to Linear (equal split) in settings (Help Center, 2025): https://help.klaviyo.com/hc/en-us/articles/36457929459227

  • Shopify’s marketing reports let you compare multiple models, while many analytics views remain session‑centric (see changelog link above).

  1. Deduplication and identity

  1. Revenue definitions and timing

If you want fewer disagreements later, align windows, prefer click‑based email credit when you compare to session tools, enforce UTMs on every message, and fix identity gaps early.

The mixed journey we’ll use (campaign → retargeting → email reminder → mobile purchase)

Here’s a realistic cross‑device path we’ll reference:

  • Email campaign click on desktop (T0)

  • Social retargeting impression/click on mobile (T1)

  • Email reminder click on mobile (T2)

  • Purchase on mobile via Shopify checkout (T3)

Journey diagram: email campaign click to social retargeting to email reminder to mobile purchase with windows and identifiers

In your diagram or notes, record for each touch: timestamp (T0–T3), device/channel, identifiers present (email hash, Shopify customer ID, cookie/session), UTM parameters, and lookback windows (e.g., 5‑day email click; 7‑day paid social click / 1‑day view if you use view‑through for ads).

How common models split credit on this journey

We’ll assume all three interactions are within their windows and we use click‑only for email. If your stack counts a social view‑through, decide whether that view qualifies as a touch before you apportion credit.

  • First click: 100% to the initial email campaign.

  • Last click: 100% to the email reminder.

  • Linear: Split equally across qualifying touches (e.g., 33/33/33 for campaign email, social retargeting click, reminder email).

  • Position‑based (U‑shaped): Heavier weight to first and last touches (e.g., 40/20/40, where middle gets the remainder).

  • Time decay: Heavier toward recent touches (e.g., 20/25/55 if T2 is close to purchase).

  • Data‑driven (GA4 context): Fractional shares are learned from your data; requires consistent tagging and enough volume. See GA4’s DDA documentation: https://support.google.com/analytics/answer/12958241

Model credit split diagram for a three-touch journey across common attribution models

Tip: When you present these numbers internally, include your rules (click‑only vs. open, whether views count, exact windows) on the same slide. Otherwise, the same order can “move” channels depending on assumptions.

Implementation checklist: keep email touches from getting lost

  1. UTM conventions in Klaviyo

  • Set defaults in Settings → Other → UTM Tracking. Recommended: utm_source=klaviyo, utm_medium=email, utm_campaign={{ message or campaign name }}, optional utm_content and utm_id for variants. Ensure lowercase and human‑readable values. See Klaviyo’s UTM tracking documentation: https://help.klaviyo.com/hc/en-us/articles/115005247808

  1. Identity stitching and cross‑device

  1. Shopify Web Pixels and (optionally) server‑side events

  1. Window alignment and model selection

  • In Klaviyo, consider click‑only email attribution and align the click window (e.g., 5 days) to reduce drift when comparing to Shopify or GA4. In Shopify’s marketing reports, compare models (last, first, linear, position‑based, time decay) so stakeholders see the assist value. For model options within your analytics stack, see a multi‑touch attribution product overview such as https://attribuly.com/product/attribution/

  1. Validation passes in GA4

  • GA4 defaults to data‑driven attribution. Use Model comparison to view Last click vs. Linear/Time decay and gauge whether email assists line up with your expectations. Ensure UTMs pass cleanly into GA4. See GA4 model comparison docs: https://support.google.com/analytics/answer/13644080

  1. Documentation and dashboards

  • Document your chosen windows, whether opens/views qualify, and your dedup rules. Label dashboards accordingly so future comparisons aren’t apples to oranges.

Practical example: aligning windows and identities with a tool

You can operationalize the above with a neutral analytics layer that supports multi‑touch credit, window alignment, and identity stitching across Shopify and Klaviyo. For instance, Attribuly can be used to compare last‑click vs. linear vs. position‑based models and to align attribution windows; see the Settings article on adjustable attribution windows for supported ranges. It also supports Shopify and Klaviyo integrations so UTMs and identifiers can flow into a single path view. For an overview of model and window options, review the multi‑touch attribution product page, plus the Shopify and Klaviyo integration pages for connection details.

Tone note: The above links are provided for configuration context; you can implement equivalent setups with any tool that documents its models, windows, and identity handling.

Troubleshooting quick wins

FAQ

  • What is multi‑touch attribution in Shopify email, in one sentence?

    • It’s a ruleset that shares revenue credit across qualifying email touches (flows and campaigns) and other channels on the path to a Shopify order, instead of assigning 100% to the last click.

  • Should I include email opens in attribution?

    • For reconciliation with click/session tools, it’s safer to stick to click‑based email credit and exclude Apple Privacy opens. If you keep opens, label your charts clearly.

  • How do I compare my view to GA4?

    • Use GA4’s Model comparison to look at Last click vs. Linear or Time decay; your email assist value should rise under multi‑touch models if campaigns are doing their job.

  • Which model should I start with?

    • If you have frequent messaging, start with Linear or Time decay to avoid overly favoring the final cart touch. Reevaluate quarterly as your cadence and device mix change.

Further reading

A last word: pick clear rules, align windows, and label your dashboards. Do that, and the “who gets credit?” debate gets a lot quieter while your email program gets the credit it actually earned.