Returns and exchanges, connected to the full customer journey
SourceMedium syncs Loop Returns data and joins every return to its original order and customer — so you can analyze return rates, exchange vs refund split, return reasons by SKU, and how post-purchase outcomes affect long-term retention.
Loop Returns
Post-purchase support, helpdesk, and returns platforms that power customer-facing operations.
Why Loop Returns?
Loop Returns is the source of truth for return events. Shopify's refund data lags and misses exchange details entirely. SourceMedium connects Loop to your full order history so you can measure true return economics and understand which return outcomes predict loyalty vs churn.
Return outcome analysis
Exchange, refund, upsell, store credit, and mixed outcomes sync with full financial detail per return.
Return reason hierarchy
Two-level return reason data at the SKU level reveals the root cause behind your return rates.
Post-purchase retention
Returns join order history and customer LTV so you can measure whether exchange customers repurchase at higher rates.
Return timing and cost
Days to return, return timing bands, and net return cost (refund minus upsell capture) sync per return.
What you can ask
With the AI Analyst, you can query Loop Returns data using natural language. Here are some examples.
What percentage of returns result in an exchange vs a refund? Which SKUs have the highest return rates this quarter? What are the top return reasons by product category? Do customers who exchange repurchase at higher rates than those who refund? Which acquisition channels produce orders with the lowest return rates? How does return timing differ between exchange and refund outcomes? What is our net return cost as a percentage of gross revenue? How it works
Get started in minutes. Connect your account, configure sync settings, and start querying unified data in BigQuery.
Connect Loop Returns
Share your Loop Returns API key. We pull return records, outcomes, and line-item data.
Return data sync
Returns sync with outcome, financials, reason hierarchy, and exchange variant data.
Post-purchase analysis
Return data joins your order and customer models for full lifecycle analysis.
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