In order to identify which marketing channels/placements/tactics are driving users who more frequently return orders, you can conduct this analysis and reconciliation by leveraging Rockerbox's raw log level reports (down to the user and order level).
By exporting this report, you can match it on the order level to the orders that were returned, and then see all of the marketing touchpoints that drove to that order.
You can also use this analysis to establish avg return rates per marketing channel and then apply those moving forward.
Rockerbox currently does not support ingesting and processing returns directly.
This is due to the reconciliation process, as returns can be completed on an ongoing basis, resulting in data consistency issues as the historical data would be consistently changing.
If you use Shopify, this is why we do not factor in returns, and the revenue we show is subtotal_price.
In Shopify, this is the subtotal of the line items and their discounts (does not contain shipping costs and shipping discounts) in shop and presentment currencies. (Documentation here)
Updated about 1 year ago