Create recommendation configurations
Create recommendation configurations
This is for:
DeveloperYou need to create a recommendation slot configuration before you can fetch Product Recommendations (PR) from the Commerce API.
Recommendation slot configurations define the recommendation strategies and the locations within your storefront where the recommendation slots will be used.
You can create or modify your recommendation configurations in two ways:
-
Using the configuration endpoints directly (which the CMH uses under the hood)
Note
The CMH lets you modify recommendation strategies and view performance metrics for your recommendation slots. However, it doesn’t currently support creating new recommendation slots or setting specific rules to filter and rank products. This functionality is coming soon. For now, to create new recommendation slots or set rules to filter and rank your products, you’ll have to call the configuration endpoints directly. |
Recommendation slots
A recommendation slot is a specific area within a storefront where product recommendations are displayed. It can be configured to determine where and how recommendations will appear to users.
When creating a recommendation slot, you need to define the location of the slot within your storefront, the type of products used to generate recommendations, and the recommendation strategy to use.
This can be done by setting the slotType
, seedType
, and strategy
parameters in the recommendation slot configuration.
Configuring the recommendation slot
The recommendation strategy used by a slot depends on several parameters that you need to configure:
-
The
slotType
for your recommendation slot. This determines the location of the recommendation slot in your storefront. It also determines whichseedType
can be used. -
The
seedType
specifies the type of products used to generate recommendations. Seed types include:-
unseeded
: Recommendations are based on the user’s overall behavior, not on any particular product. -
Seeded: In addition to the user’s behavior, recommendations are based on a specific product or set of products. There are three types of seeded recommendations:
-
product
: Recommendations are based on a single particular product. -
cart
: Recommendations are based on items in the user’s cart. -
purchased
: Recommendations are based on the user’s purchase history.
-
The
seedType
also determines whichstrategy
can be used.To understand which slot types support which seed types, see Supported seed types by slot type.
-
-
The
strategy
parameter specifies which recommendation algorithm to use, based on theseedType
. Several strategies are available:-
popular_bought
- recommends the most purchased products. -
popular_viewed
- recommends the most viewed products. -
cart
- recommends other products that were frequently purchased together in previous similar carts. -
viewed_together
- recommends products that are frequently viewed together with one or more products provided as seeds. -
bought_together
- recommends products that are frequently bought together with one or more products provided as seeds.
To understand which seed types support which strategies, see Supported strategies by seed type.
-
Supported seed types by slot type
The following table shows the supported seed types for each slot type.
Slot type | Supported seed types |
---|---|
home |
unseeded |
cart |
|
listing |
unseeded |
cart |
|
search |
unseeded |
cart |
|
productDetail |
unseeded |
product |
|
cart |
|
cart |
unseeded |
cart |
|
confirmation |
unseeded |
cart |
|
purchased |
|
global |
unseeded |
product |
|
cart |
|
purchased |
Supported strategies by seed type
The following table shows the supported strategies for each seed type.
Seed type | Strategies |
---|---|
unseeded |
popular_viewed |
popular_bought |
|
product |
all unseeded strategies |
viewed_together |
|
bought_together |
|
cart |
all unseeded strategies |
cart |
|
viewed_together |
|
bought_together |
|
purchased |
all unseeded strategies |
viewed_together |
|
bought_together |
Manage recommendations using the Coveo Merchandising Hub
The Coveo Merchandising Hub (CMH) allows merchandisers to manually curate the products displayed in recommendation slots.
While Coveo ML models provide intelligent and personalized recommendations, the CMH allows you to manually adjust them to meet your business needs.
For example, merchandisers can use the CMH to:
-
Promote specific products when certain products are viewed.
-
Boost or bury products on recommendations based on specific criteria.
To learn more about the CMH and how to use it, see Coveo Merchandising Hub (CMH).
Manage recommendations using the configuration endpoints
A recommendation slot configuration is a JSON object that follows a specific format. You can modify it by calling the configuration endpoints and providing a configuration JSON.
Here is a sample configuration for a recommendation slot that lives on the cart page:
{
"name": "Cart Recs",
"trackingId": "sports",
"slotType": "cart",
"seedType": "cart",
"strategy": "bought_together",
"headlines": [
{
"headline": "Customers also bought",
"language": "en"
}
],
"minRecs": 5,
"queryConfiguration": {
"additionalFields": [
"color",
"shirtsize"
],
"perPage": 10
}
}
The name of the recommendation slot configuration. This is what appears in the CMH. | |
The trackingId allows you to segregate your configurations. |
|
The slotType helps merchandisers determine where the recommendation slot lives on the storefront. |
|
The seedType determines which type of data will be used to generate recommendations and which strategies can be used.
For example, if you set the seed type to |
|
The strategy parameter specifies which recommendation algorithm to use within the context defined by the seedType .
strategy can be changed over time depending on the merchandiser’s needs, without altering the seedType . |
|
The headline to display in the recommendation slot. | |
The query configuration to use for the recommendation slot.
In this example, additional fields are specified to be returned by the query, and the number of recommendations per page is set to 10. |