Setup guide
Setup guide
To properly leverage Coveo for Commerce capabilities, it’s essential that your Coveo organization is optimally configured to integrate with the Commerce API. This setup also enables you to manage Coveo-powered search, product listing pages (PLPs), and recommendation slots through the Coveo Merchandising Hub (CMH).
This guide provides an overview of the Coveo for Commerce implementation process. It contains collapsible sections that you can expand to learn more about each aspect of the implementation. It also includes links to additional articles with detailed instructions on how to complete specific tasks.
This guide covers the following topics:
Map your storefront architecture to Coveo
To effectively index your product inventory, track commerce events, use the Commerce API, and manage product discovery through the Coveo Merchandising Hub (CMH), you need to map your storefronts in a way that’s compatible with Coveo.
In Coveo for Commerce, storefronts are organized into properties, and each property can support multiple locales. For example, if you have two storefronts—one in Canada and one in the United States—your organization would include two properties, one for each storefront.
Each property can have multiple locales. For example, if your Canadian storefront supports both English and French, you would have two locales under the Canadian property. Each storefront/locale combination would have its own Catalog source and catalog entity representing the products available for that specific combination.
The following diagram shows how the Barca brand’s storefront architecture could be set up in Coveo for Commerce, considering the following variations:
-
Two storefronts: Canada storefront and USA storefront
-
Two supported currencies:
CAD
andUSD
-
Supported languages for each storefront:
-
Canada storefront: English and French
-
USA storefront: English and Spanish
-
Expand the following sections to learn more about the different concepts that you must consider when mapping your storefront architecture to Coveo. Note that you won’t implement these concepts right away, but you should be aware of them to ensure that your storefronts are set up correctly in Coveo.
Tracking ID
Tracking ID
tracking IDs are unique identifiers that identify specific storefronts in usage analytics events. All of your storefronts must have their own tracking ID.
While tracking ID values are specified when sending usage analytics events, each value that’s sent must be registered using a Property in your organization. See Properties for more information.
In the context of the CMH, the management of the product discovery solutions is segmented by tracking ID. This means that merchandising actions, such as boosting products or creating rules, are specific to each tracking ID.
See What’s a tracking ID? for more information about tracking IDs.
Properties
Properties
Properties allow the management of tracking IDs within a Coveo organization. A property consists of a user-readable display name that simplifies the management and analysis of data across different sites or applications.
Each of your storefronts must have its own property so you can manage the tracking ID associated with it.
Although tracking ID values are specified when sending usage analytics events, properties are managed through the Properties (platform-ca | platform-eu | platform-au) page of the Coveo Administration Console.
Each tracking ID used in your usage analytics events must be registered as a property in your Coveo organization to allow for proper data tracking and interpretation.
Your Coveo organization powers two brands that each have their own storefronts: Barca sports and Barca parts.
Usage analytics events logged from these storefronts are sent with the following tracking IDs:
-
barca_sports_us
-
barca_sports_ca
To allow for accurate data tracking and analysis, you create two properties to register these tracking IDs:
-
Barca Sports US
-
Barca Sports CA
For more information on how to manage properties, see Properties.
Locale
Locale
A given storefront can support many languages, countries, and/or currencies, resulting in variations in product attributes like names, descriptions, and prices.
The Coveo Platform addresses this complexity by utilizing locales to distinguish unique combinations of language, country, and currency.
Locales are defined by a combination of the values of the language
, country
, and currency
parameters sent in Commerce API requests.
Locales allow for reporting according to the language, country, and currency of the user’s experience, as well as managing product discovery solutions for each language, country, and currency permutation within the CMH.
Notes
|
Locales are defined for every potential combination of supported language, country, and currency that your storefronts support.
Your organization powers two brands: Barca sports and Barca parts.
You operate in two different countries: United States and Canada. In the United States, you only support English, and in Canada, you support both English and French.
Therefore, you have three different locales:
-
en-US-USD
-
en-CA-CAD
-
fr-CA-CAD
Index your catalog data
To make your product inventory available in the Coveo ecosystem, you need to add your product content to the Coveo index. Typically, this content is stored in repositories such as product information management systems (PIMs) and digital asset management systems (DAMs) in your own ecosystem.
To ensure a successful Coveo for Commerce implementation, it’s necessary to aggregate and format this content in a way that can be read and understood by Coveo. Bringing your product inventory to the Coveo ecosystem and maintaining it involves the following steps:
-
Creation of index sources.
-
Configuration and mapping of commerce fields.
-
Streaming your content to the sources using the Stream API.
-
Creation of a catalog entity.
-
Updating the content using the different update operations offered by the Push API.
The articles of the Index and manage catalog data collection cover each steps in details, but this section provides an high-level overview of everything that’s required to have your product inventory in Coveo and maintaining it.
Expand the following sections to learn more about the different steps required to index and maintain your product inventory in Coveo for Commerce:
Index sources
Index sources
To index your product inventory to the Coveo ecosystem, you’ll typically use a Catalog source.
It’s recommended to create separate product sources for each locale you’re supporting (variations in country, languages, and currency)[1].
This allows the Coveo ML models to learn independently from each experience. Such a setup will result in recommendations that are optimally personalized to users' preferences and search behavior on each website in your multi-catalog structure.
The company Barca sells products in Canada and the US. In Canada, they support French and English. In the US, they support English and Spanish.
They have the following storefronts:
-
Barca Canada (
www.barca.com/ca/
). This storefront supports French (www.barca.com/ca/fr/
) and English (www.barca.com/ca/en/
). -
Barca US (
www.barca.com/us/
). This storefront supports English (www.barca.com/us/en/
) and Spanish (www.barca.com/us/es/
).
This setup requires the creation of four product sources:
-
One for the English variation of the Canadian storefront.
-
One for the French variation of the Canadian storefront.
-
One for the English variation of the US storefront.
-
One for the Spanish variation of the US storefront.
Note
Some setups require an additional source to index items of the availability catalog object. See Source configuration approaches for availability channel for details. |
1. Having a separate source for each locale you’re supporting will likely lead to content duplication. This could affect your product entitlements.
For instructions on how to create Catalog sources, see Add a Catalog source.
Configure and map commerce fields
Configure and map commerce fields
It’s essential to configure and map your commerce fields to ensure that your product inventory is properly indexed and that the Coveo Machine Learning models can learn from your data. These fields contain metadata, such as the product name or price.
To learn how to configure and map commerce fields, see Commerce fields.
Streaming content
Streaming content
To add content to your Catalog sources, you’ll have to use the Stream API.
You’ll likely use the Stream API in two different stages of your Coveo for Commerce implementation:
-
To push a sample of your catalog data to your source for the first time.
-
To push your entire catalog data to your source.
For instructions on how to use the Stream API, see Stream your catalog data to your source.
Catalog entities
Catalog entities
The catalog entity is at the core of a Coveo for Commerce implementation. It establishes relationships between the catalog objects. A catalog entity also lets you standardize your commerce fields to ensure data reliability for Coveo Machine Learning (Coveo ML) models.
There’s a 1-to-1 relationship between product sources and catalog entities.
For each source you create that contains products, you must also create a catalog entity.
However, sources that only contain items of the availability
object type can be shared across multiple catalog entities.
For instructions on how to manage catalog entities, see Commerce catalog entity.
Update content
Update content
Catalog source updates are required when you need to add, remove, or update items (products, variants, or availabilities) in your source after an initial stream.
Coveo offers three update operations to maintain your sources up-to-date with your own product ecosystem:
-
Full item updates: Update all fields in a given item, or add and delete items.
-
Partial item updates: Update one or more fields in an existing source.
-
Shallow merge operation: Update one or more fields in an item. If the item doesn’t exist, it will be created, and if the field is missing, it will be added.
Configure query pipelines
To ensure that your Coveo for Commerce implementation works seamlessly with the Commerce API, you must configure your query pipelines in the Coveo Administration Console. This allows queries to send the right information to the Commerce API, as well as managing the product discovery solutions that you want to use with the Coveo Merchandising Hub (CMH).
Expand the following sections to learn more about the different aspects of query pipeline configurations:
General query pipeline configuration
Query pipeline configuration
Query pipelines must be created in accordance with the number of properties that your implementation supports. This means that for each registered property, you must create a query pipeline for each product discovery solutions that you’re using.
Query pipelines must follow a strict naming convention, as well as a specific description, which are as follows:
-
Query pipeline name:
cmh-<solution>-<tracking-id>
-
Query pipeline description:
<solution>-<tracking-id>
Where:
-
<solution>
is the product discovery solution that the query pipeline supports. Allowed values are:-
search
-
product-listing
-
recommendations
-
-
<tracking-id>
is the tracking ID (registered by a property) that the query pipeline supports.
Your organization powers the Barca sports Coveo-powered commerce implementation.
You operate in two different countries: United States and Canada.
Therefore, you have two properties:
-
Barca Sports US, which registers the tracking ID
barca_sports_us
-
Barca Sports Canada, which registers the tracking ID
barca_sports_ca
This means that you would have to create the following query pipelines:
Property | Product discovery solution | Query pipeline name | Query pipeline description |
---|---|---|---|
Barca Sports US ( |
Search |
|
|
Product listing |
|
|
|
Recommendations |
|
|
|
Barca Sports Canada ( |
Search |
|
|
Product listing |
|
|
|
Recommendations |
|
|
Query pipeline conditions
Query pipeline conditions
You must configure query pipeline conditions to route queries originating from the different product discovery solution interfaces to the correct query pipeline.
Query pipeline conditions are elements that determine which query pipeline to use based on the product discovery solution the end user is interacting with. For example, if a user is interacting with the search interface, the query pipeline condition will route the query to the query pipeline dedicated to search.
In Coveo for Commerce, query pipeline conditions are built with values of parameters sent to the Commerce API when requesting products using the different endpoints.
Query pipeline conditions must follow a strict naming convention. The naming convention differs based on the product discovery solution that the query pipeline condition supports. The following table provides the naming convention for each product discovery solution:
Product discovery solution | Naming convention |
---|---|
Search |
|
Product listing |
|
Recommendations |
|
Where <my_trackingId>
is the value of the tracking ID parameter as used in the request to the Commerce API.
For example, when requesting products for your kayaks
listing page, the value sent in the trackingId
parameter is barca_sports_ca
.
Therefore, the value of the <my_trackingId>
will be barca_sports_ca
.
See Tracking ID for more information about how to define tracking IDs.
For the barca_sports_ca
, you created the following query pipelines:
-
Search query pipeline:
cmh-search-barca_sports_ca
-
Listing query pipeline:
cmh-product-listing-barca_sports_ca
-
Recommendations query pipeline:
cmh-recommendations-barca_sports_ca
The following table provides the query pipeline conditions that you would have to create for each query pipeline:
Product discovery solution | Query pipeline | Query pipeline condition |
---|---|---|
Search |
|
|
Product listing |
|
|
Recommendations |
|
|
Leading practice
If your organization contains query pipelines that route queries that shouldn’t target the Commerce API (that is, query pipelines that target the Search API), we strongly recommend that you add the following condition to the query pipeline:
This condition ensures that queries going through the Commerce API don’t target these query pipelines. |
For instructions on how to create query pipeline conditions, see Manage query pipeline conditions.
Query pipeline for product listings
Product listings specific configuration
When configuring the query pipeline for routing product listing queries, you must configure a ranking weight query pipeline rule to optimize the ranking of products on product listing pages.
You must configure the ranking rule to set all ranking factors to 0
.
Machine learning models for Coveo for Commerce
Coveo recommends that you configure Coveo Machine Learning (Coveo ML) models to power and enhance product discovery experiences. To increase personalization and relevancy, configure the recommended Coveo ML models for each of the product discovery solutions:
Product discovery solution | Recommended model |
---|---|
Search |
Automatic Relevance Tuning (ART) (optimized for search) |
Intent-Aware Product Ranking (IAPR) (optional) |
|
Predictive Query Suggestions (PQS) or Query Suggestions (QS) |
|
Product listing |
ART (optimized for listing pages) |
Recommendations |
|
Session-Based Product Recommendations (SBPR) (required to power the Intent-aware product recommendation strategy) |
Configuring Coveo ML models
Configuring Coveo ML models
To configure the Coveo ML models for product discovery solutions:
-
Configure the appropriate models for each product discovery solution.
For optimal results, we recommend that you configure one model of each type for each of your property.
-
Session-Based Product Recommendations (SBPR)
Contact your Coveo representative to enable SBPR in your Coveo organization.
-
Associate the models with the query pipelines that you’ve created.
NoteWhen associating a PR model with the query pipeline for recommendations, you must configure an association for each of the strategy available in the association flow.
-
For ART, QS, DNE, and PR models, configure learning filters to ensure that the model only uses the data that’s relevant to the website on which it’s deployed.
You’ve defined the following properties for your two Coveo-powered ecommerce sites or applications:
-
Barca Sports US, which registers the tracking ID
barca_sports_us
-
Barca Sports Canada, which registers the tracking ID
barca_sports_ca
Therefore, you create the following Coveo Machine Learning models:
Property | Product discovery solution | Model name |
---|---|---|
Barca Sports US ( |
Search |
Barca Sports US Search IAPR model |
Barca Sports US Search PQS model |
||
Barca Sports US Search DNE model |
||
Listing |
Barca Sports US Listing ART model |
|
Recommendations |
Barca Sports US Product Recommendations PR model |
|
Barca Sports Canada ( |
Search |
Barca Sports CA Search IAPR model |
Barca Sports CA Search PQS model |
||
Barca Sports CA Search DNE model |
||
Listing |
Barca Sports CA Listing ART model |
|
Recommendations |
Barca Sports CA Product Recommendations PR model |
Note
To effectively power commerce-optimized Coveo ML models, substantial usage analytics data is needed. Properly logging commerce events is crucial for feeding models the required data and enhancing relevance over time as more data is collected. |
To configure learning filters:
When using an ART, QS, DNE, or PR model for a Coveo for Commerce organization that has multiple properties, you must configure learning filters to ensure that the model only uses the data that’s relevant to the website on which it’s deployed.
For example, if your Coveo for Commerce organization powers multiple websites, the model should only learn from the data of the website on which it’s deployed.
Note
For IAPR and PQS models, instead of defining learning filters, you’ll need to configure the model to use the appropriate tracking IDs (registered as properties in your Coveo organization). |
To configure learning filters:
-
Once you’ve created your model, access the Models (platform-ca | platform-eu | platform-au) page.
-
Click the desired model, and then click More > Edit JSON in the Action bar.
-
In Edit a Model JSON Configuration, add the following
commonFilter
object:"commonFilter": "(c_context_website=@'<TRACKING-ID>')"
Where you replace
<TRACKING-ID>
with the tracking ID (registered by a property) defined for the website on which you want to use the model. -
Click Save.
If you have a model that you want to use on a website for which the registered tracking ID is barca_sports_us
, your JSON configuration should look like this:
{
"modelDisplayName": "My Commerce ML Model",
"exportPeriod": "P3M",
"intervalTime": 1,
"intervalUnit": "WEEK",
"commonFilter": "(c_context_website=@'barca_sports_us')",
"exportOffset": "PT0S"
}
Define storefront associations
There’s a 1:1 relationship between Catalog sources and catalog entities. This means that you should have one Catalog source and a matching catalog entity for each language, country, currency, and brand you’re selling your products in.
A single tracking ID can apply to multiple locale combinations.
For example, if you have a tracking ID identifying a storefront for a brand that sells products in both English and French in Canada, you would have a single tracking ID associated with two locales: en-CA-CAD
and fr-CA-CAD
.
Storefront associations let you manage the relationship between properties, locales, and catalog entities.
This allows the Coveo Platform to automatically infer the catalog ID targeted by a property and locale combination. So, there’s no need to specify the catalog ID when authenticating commerce requests.
For more information on storefront associations, see Storefront associations.
Build commerce interfaces
Your storefront visitors use commerce interfaces to search, browse, and purchase products. Each of these interfaces is powered by a product discovery solution.
Coveo for Commerce provides three distinct product discovery solutions: Search, Product listings, and Recommendations. It also offers a set of tools to simplify the implementation of your commerce interfaces.
The articles of the Build commerce interfaces collection cover each aspect of building commerce interfaces in details, but this section provides an high-level overview of the different approaches you can take to build commerce interfaces in Coveo for Commerce.
Headless
Headless
The Coveo Headless library is a Redux-based toolset for developing your own UI component libraries. It provides the underlying functionality of the Atomic library without tying that functionality to a specific UI implementation.
We strongly recommend that you use the Headless library rather than work directly with the REST APIs, as Headless abstracts their complexity and provides a more developer-friendly interface.
For more information, see Headless for commerce.
Atomic
Atomic
The Atomic library commerce components are in open beta and therefore under active development. Reach out to your Coveo team for support in adopting them. |
The Coveo Atomic library is a collection of pre-built UI components meant to quickly create product discovery interfaces. You can theme and customize the Atomic components to suit your needs. Under the hood, Atomic relies on the Coveo Headless library to interface with Coveo and handle the application state.
Rest APIs
Rest APIs
The Coveo Commerce REST APIs are a set of APIs that allow you to interact with the Coveo Platform.
These APIs offer the most flexibility for interacting with the Coveo Platform, though they require more development effort and can be more challenging to use than Headless or Atomic.
To implement your product discovery solution using the REST APIs, you need to send requests to the following APIs:
-
Commerce API: This API allows you to query the Coveo Platform for products.
-
Event API: This API allows you to log commerce events using the Event Protocol.
After you’ve chosen the right approach, you can start building your search, listing, and recommendation interfaces:
Log commerce events
It’s crucial that you track touchpoints to analyze storefront performance, create reports, and power Coveo Machine Learning (Coveo ML) models. You can do this by sending events to the Coveo Usage Analytics (Coveo UA) service.
Building commerce interfaces with Coveo UI libraries, such as Coveo Atomic and Coveo Headless, considerably simplifies the implementation of usage analytics tracking. |
In Coveo for Commerce, you’ll typically have to track the following user actions:
-
Product views
-
Product clicks
-
Cart events
-
Purchases
It’s through usage analytics tracking that tracking IDs are defined to identify the different storefronts user actions are coming from. Once you’re ready to track these actions, you must register the tracking IDs as properties using the Properties (platform-ca | platform-eu | platform-au) page of the Coveo Administration Console.
For instructions on how to implement usage analytics tracking in Coveo for Commerce, see Log commerce events.