Best-selling products by market
How to use the Metrics API to get the Top 5 best-selling products for each of your organization's market
You want to get the total number of orders over a selected date and time range, grouped by the different markets of your organization. For each market, you also want to know what the best-selling SKUs are.
You need to perform a breakdown query setting the required query keys as follows and adding the optional ones based on your needs:
Key | Value |
|---|---|
by | market.name |
field | order.id |
operator | value_count |
Key | Value |
|---|---|
by | line_items.name |
field | order.id |
operator | value_count |
limit | 5 |
Set the desired date and time range using the
date_from and date_to keys and add an additional filter on the line items field to restrict the related computation on SKUs only:Attribute | Operator |
|---|---|
types | "in": [ "skus" ] |
As shown in the example below, use
placed_at as the date_field in the date filter if you want the results to count all the orders that were placed in the selected date and time range (read more about this).Request
Response
The following request uses the Metrics API to get the total number of orders, grouped by market name and, for each market, the Top 5 best-selling SKUs:
curl -g -X POST \
'https://{{your_domain}}.commercelayer.io/metrics/orders/breakdown' \
-H 'Accept: application/vnd.api.v1+json' \
-H 'Content-Type: application/vnd.api+json' \
-H 'Authorization: Bearer {{your_access_token}}' \
--data-raw '{
"breakdown": {
"by": "market.name",
"field": "order.id",
"operator": "value_count",
"sort": "desc",
"limit": 100,
"breakdown": {
"by": "line_items.name",
"field": "order.id",
"operator": "value_count",
"sort": "desc",
"limit": 5
}
},
"filter": {
"order": {
"date_from": "2021-01-01T00:00:00Z",
"date_to": "2021-12-31T23:59:00Z",
"date_field": "placed_at"
},
"line_items": {
"types": {
"in": ["skus"]
}
}
}
}'
On success, the API responds with a
200 OK status code, returning the aggregated, nested values in the data object and extra information in the meta object:{
"data": {
"market.name": [
{
"label": "UK",
"value": 545904,
"line_items.name": [
{
"label": "Blue T-shirt",
"value": 25281
},
{
"label": "Red T-shirt",
"value": 23923
},
{
"label": "Green T-shirt",
"value": 13413
},
{
"label": "Black T-shirt",
"value": 13206
},
{
"label": "White T-shirt",
"value": 11814
}
]
},
{
"label": "Italy",
"value": 164862,
"line_items.name": [
{
"label": "Black T-shirt",
"value": 98244
},
{
"label": "White T-shirt",
"value": 28799
},
{
"label": "Yellow T-shirt",
"value": 19833
},
{
"label": "Blue T-shirt",
"value": 13942
},
{
"label": "Red T-shirt",
"value": 524
}
]
},
{ ... }
]
},
"meta": {
"type": "breakdown",
"trace_id": "fe571ea2-8a4f-4a5e-bd26-ac54651bb2e4",
"mode": "test",
"organization_id": "xYZkjABcde",
"market_ids": [ "yzXKjYzaCx", "..." ]
}
}
Just changing a couple of query keys and/or filter parameters you can address lots of very similar use cases, such as: