Returned Orders

This topic demonstrates how to set up a dashboard that provides a detailed analysis of your store’s returns.

Before getting started, you must be an Adobe Commerce customer and should make sure that your company is using the enterprise\_rma table for returns.

This analysis contains advanced calculated columns.

Getting Started

Columns to track

  • enterprise_rma or rma table

  • entity_id

  • status

  • order_id

  • customer_id

  • date_requested

  • enterprise_rma_item_entity or rma_item_entity table

  • entity_id

  • rma_entity_id

  • qty_returned

  • status

  • order_item_id

  • product_name

  • product_sku

Filter sets to create

  • enterprise_rma table

  • Filter set name: Returns we count

  • Filter set logic:

    • Placeholder - enter your custom logic here
  • enterprise_rma_item_entity table

  • Filter set name: Returns items we count

  • Filter set logic:

    • Placeholder - enter your custom logic here

Calculated Columns

Columns to create

  • enterprise_rma table

  • Order's created at

  • Select a definition: Joined Column

  • Create Path:

  • Many: enterprise_rma.order_id

  • One: sales_flat_order.entity_id

  • Select a table: sales_flat_order

  • Select a column: created_at

    • enterprise_rma.order_id = sales_flat_order.entity_id
  • Customer's order number

  • Select a definition: Joined Column

  • Select a table: sales_flat_order

  • Select a column: Customer's order number

    • enterprise_rma.order_id = sales_flat_order.entity_id
  • Time between order's created_at and date_requested is created by an analyst as part of your [RETURNS ANALYSIS] ticket

  • enterprise_rma_item_entity table

  • return_date_requested

  • Select a definition: Joined Column

  • Create Path:

    • Many: enterprise_rma_item_entity.rma_entity_id
    • One: enterprise_rma.entity_id
  • Select a table: enterprise_rma

  • Select a column: date_requested

    • enterprise_rma_item_entity.rma_entity_id = enterprise_rma.entity_id
  • Return item total value (qty_returned * price) is created by an analyst as part of your [RETURNS ANALYSIS] ticket

  • sales_flat_order table

  • Order contains a return? (1=yes/0=No)

  • Select a definition: Exists

  • Select a table: enterprise_rma

    • enterprise_rma.order_id = sales_flat_order.entity_id
  • Customer's previous order number is created by an analyst as part of your [RETURNS ANALYSIS] ticket

  • Customer's previous order contains return? (1=yes/0=no) is created by an analyst as part of your [RETURNS ANALYSIS] ticket

NOTE
If you are interested in analyzing only business hours for Seconds to resolution or Seconds to first response, let the analyst know when requesting the ticket.

Metrics

  • Returns

  • In the enterprise_rma table

  • This metric performs a Count

  • On the entity_id column

  • Ordered by the date_requested

  • Filter: Returns we count

  • Returned items

  • In the enterprise_rma_item_entity table

  • This metric performs a Sum

  • On the qty_approved column

  • Ordered by the return date_requested

  • Filter: Returns we count

  • Returned item total value

  • In the enterprise_rma_item_entity table

  • This metric performs a Sum

  • On the Returned item total value (qty_returned * price) column

  • Ordered by the return date_requested

  • Filter: Returns we count

  • Average time between order and return

  • In the enterprise_rma table

  • This metric performs an Average

  • On the Time between order's created_at and date_requested column

  • Ordered by the date_requested

  • Filter: Returns we count

NOTE
Make sure to add all new columns as dimensions to metrics before building new reports.

Reports

  • Repeat order probability after making a return

  • Metric A: Number of orders with returns

  • Metric: Number of orders

  • Filter:

    • Order contains a return? (1=yes/0=No) = 1
    • Is in current month? = No
  • Metric B: Non-last orders with returns

  • Metric: Number of orders

  • Filter:

    • Is customer's last order? (1=yes/0=no) = 0
    • Order contains a return? (1=yes/0=No) = 1
  • Formula: Repeat order probability

  • Formula: B / A

  • Format: Percentage

  • Time period: All time

  • Interval: None

  • Group by: Customer's order number

  • Chart Type: Bar

  • Avg time to return (all time)

  • Metric A: Avg time between order and return

  • Metric: Avg time between order and return

  • Time period: All time

  • Interval: None

  • Chart Type: Number

  • Percent of orders with a return

  • Metric A: Number of orders

  • Metric: Number of orders

  • Metric B: Orders w/ return

  • Metric: Number of orders

  • Filter:

    • Order contains a return? (1=yes/0=No) = 1
  • Formula: % of orders with return

  • Formula: B / A

  • Format: Percentage

  • Time period: All time

  • Interval: None

  • Chart Type: Number - % of orders with return

  • Revenue returned by month

  • Metric A: Returned item total value

  • Metric: Returned item total value

  • Time period: All time

  • Interval: By month

  • Chart Type: Line

  • Customers who have made a return and not purchased again

  • Metric A: Number of orders with returns

  • Metric: Number of orders

  • Filter:

    • Order contains a return? (1=yes/0=No) = 1
    • Is customer's last order? (1=yes/0=no) = 1
  • Time period: All time

  • Interval: None

  • Group by: Customer_email

  • Chart Type: Table

  • Return rate by item

  • Metric A: Returned items (Hide)

  • Metric: Returned items

  • Metric B: Items sold (Hide)

  • Metric: Number of orders

  • Filter:

  • Formula: Return %

  • Formula: B / A

  • Format: Percentage

  • Time period: All time

  • Interval: None

  • Group by: product_sku AND/OR product_name

  • Chart Type: Table

After compiling all the reports, you can organize them on the dashboard as you desire. The result may look like the above sample dashboard.

If you run into any questions while building this analysis or want to engage the Professional Services team, contact support.

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