Shopify

Stop the revenue leakage between store and reporting.

Connect Shopify to Attributed Intelligence for reconciled orders, refunds, discounts and repeat-purchase evidence. The commercial source of record for ecommerce — reconciled against analytics and paid media.

The commercial proposition

Shopify is the commercial source of record for the order — not the whole revenue story.

Attributed Intelligence connects to Shopify and reads orders, refunds, discounts, customers and repeat-purchase behaviour where permissions allow. We treat Shopify as authoritative for what the store actually sold, refunded and repeated — and reconcile it against GA4, Google Ads and any CRM in play. Shopify is not framed as universal truth for anything outside commerce.

1Ring 1
First order

Acquired customer, first revenue, source-attributed at point of sale.

2Ring 2
Post-purchase

Delivery, review, subscription setup, cross-sell offers.

3Ring 3
Second order

Repeat window, LTV signal, cohort placement.

4Ring 4
Third order onwards

Compounding value, retention economics, dunning & reactivation.

Shopify is the source of record for orders and customers. The commercial value comes from watching the rings — not the last click that got the first order.

Evidence contributed

What Shopify contributes to the reconciled view.

Orders & line items

Order state, currency, tax, shipping and product-level detail.

Refunds & adjustments

Post-purchase reality — cancellations, refunds and store credits reflected in reported revenue.

Discounts & promotions

Automatic and code-based discounts — used vs unused, revenue impact by promotion.

Customers & repeat behaviour

Customer records and repeat-order cadence used to build cohorts and LTV signals.

Typical Findings

Where the commerce story breaks

  • — GA4 reporting materially over- or under-stating Shopify revenue.
  • — Discount codes cannibalising full-price demand without protection rules.
  • — High-refund SKUs distorting new-customer economics and paid ROAS.
  • — Retention cohorts flattening because second-order timing is missed.
  • — Checkout drop-off unexplained by any tracked event.
Example Recommendations

How senior operators respond

  • — Reset GA4 purchase reporting to match Shopify ex-tax revenue.
  • — Introduce discount-eligibility rules and monitor incremental revenue effect.
  • — Move margin-negative SKUs off paid acquisition and merchandising priority.
  • — Design lifecycle programmes around the observed second-order window.
  • — Deploy a checkout-audit Pack with instrumentation and diagnostic tests.
Implementation Packs

Commerce evidence, made ownable.

Shopify evidence flows into Implementation Packs alongside analytics and paid media. Each Pack contains the finding, the commercial impact, the owner in-store, the change specification and the QA checks.

Owner

Ecommerce manager, merchandising lead or engineering — depending on the change.

QA & validation

Order-count and revenue reconciliation pre/post; refund-rate and cohort re-check on a rolling window.

Outcomes supported

Revenue integrity, EBITDA protection, retention economics, reduced value leakage.

Where this fits

Reconcile your Shopify revenue and stop the leakage.

45 minutes with a senior operator to review orders, refunds, cohorts and reporting integrity.