Understanding the coupon performance of your business is an interesting way to segment your orders and better understand customer habits.
This topic documents the steps required to create this analysis to understand how coupon-acquired customers perform, see trends, and track individual coupon code usage.
First, a note about how coupon codes are tracked. If a customer applied a coupon to an order, three things happen:
base_grand_total
amount (your Revenue
metric in Commerce Intelligence)coupon_code
field. If this field is NULL (empty), the order does not have a coupon associated with it.base_discount_amount
. Depending on your configuration, this value may appear negative or positive.The first step is to construct a new metric with the following steps:
Navigate to Manage Data > Metrics > Create New Metric.
Select the sales_order
.
This metric performs a Sum on the base_discount_amount column, ordered by created_at.
Orders we count
(Saved Filter Set)coupon_code
IS NOT[NULL]
Coupon discount amount
.Once the metric has been created:
_Coupon Analysis_
.This is where you create and add all the reports.
The Time Period** for each report is listed as All-time
. Feel free to alter this to suit your analysis needs. Adobe recommends all reports on this dashboard cover the same time period, such as All time
, Year-to-date
, or Last 365 days
.
Orders with coupons
Metric:Orders
A
] coupon_code
IS NOT [NULL]
Time period: All time
Interval: None
Chart type:Number (scalar)
Orders without coupons
Metric: Orders
A
] coupon_code
IS [NULL]
Time period: All time
Interval:None
Chart type:Number (scalar)
Net revenue from orders with coupons
Metric: Revenue
A
] coupon_code
IS NOT [NULL]
Time period: All time
Interval: None
Chart type: Number (scalar)
Discounts from coupons
Coupon discount amount
All time
None
Number (scalar)
Average lifetime revenue: Coupon acquired customers
Metric: Avg lifetime revenue
A
] Customer's first order's coupon_code
IS NOT [NULL]
Time period: All time
Interval: None
Chart type: Number (scalar)
Average lifetime revenue: Non-coupon acquired customers
Metric: Avg lifetime revenue
Customer's first order's coupon_code
IS[NULL]
Time period: All time
Interval: None
Chart type: Number (scalar)
Coupon usage details (first time orders)
Metric 1
: Orders
A
] coupon_code
IS NOT[NULL]
B
] Customer's order number
Equal to 1
Metric 2
: Revenue
Add filter:
A
] coupon_code
IS NOT[NULL]
B
] Customer's order number
Equal to 1
Rename: Net revenue
Metric 3
: Coupon discount amount
A
] coupon_code
IS NOT[NULL]
B
] Customer's order number
Equal to 1
Create formula: Gross revenue
(B – C)
Currency
Create formula:% discounted
(C / (B - C))
Percentage
Create formula: Average order discount
(C / A)
Percentage
Time period: All time
Interval: None
Chart type: Table
Average lifetime revenue by first order coupon
Metric:Avg lifetime revenue
A
] coupon_code
IS[NULL]
Time period: All time
Interval: None
Chart type: Number (scalar)
Coupon usage details (first time orders)
Metric: Avg lifetime revenue
A
] Customer's first order's coupon_code
IS NOT [NULL]
Time period: All time
Interval: None
Group by: Customer's first order's coupon_code
Chart type:Column
New customers by coupon / non-coupon acquisition
Metric 1
: New customers
Add filter:
A
] Customer's first order's coupon_code
IS NOT [NULL]
Rename: Coupon acquisition customer
Metric 2
: New customers
Add filter:
A
] coupon_code
IS[NULL]
Rename: Non-coupon acquisition customer
Time period: All time
Interval: By Month
Chart type: Stacked Column
After building the reports, refer to the image at the top of this topic for how you can organize the reports on your dashboard.