Configure Recommenders

Brandon Wilson, Cloud Kicks’s merchandiser, is almost ready to create product recommendations. First he wants to learn more about recommender types, strategies, and rules.

Remember, recommenders are configurations that you create in the Configurator tool. They let you:

• Relate what the shopper is looking at to what you recommend.
• Specify the algorithm you use to determine what you recommend.
• Specify if and when you display the recommendation.

Here are the recommender types you can use.

• Product to Product: Recommend similar or related affinity products.
• Products in All categories: Recommend products from all categories.
• Products in a Category: Recommend products in the same category.
• Recently Viewed: Recommend recently viewed products.
• Complete the Set: Recommend complementary products for apparel sets.

Brandon takes a look at how each recommender type works and the types of pages they’re best suited for.

Complete the Set

For this type, Einstein reviews shopper storefront activities to understand the types of products most often purchased together, and then applies intelligence around product categories to create a set or a look. Brandon can preview the recommendations and choose to enable or disable them by category. Einstein automatically creates sets of products without extra feeds or integrations.

This recommender supports apparel, accessories, beauty products, and home furnishings.

Strategies represent different approaches, or algorithms, for generating recommendation lists. For each recommender, Brandon can configure up to three strategies. This table shows what Einstein does for each strategy.

This table shows how Brandon can match the type of storefront page to a recommender type when considering available strategies.

Strategy order is important. Einstein uses the strategy at the top of the list first, and then the second strategy, and so on. A best practice is to configure a primary and a secondary strategy. Einstein uses the secondary strategy as a backup in case the primary strategy returns insufficient results.

For your primary and secondary strategies, we recommend that you use one that applies to all shoppers and another that’s based on an individual's history. This provides personalized experiences for both existing and new shoppers.

Here are some great choices.

The Recently Viewed and Complete the Set recommender types use only one strategy.

A recommender rule specifies an action, field, and one or more field values. When Einstein applies a rule, it checks each product in the list of IDs returned by the strategies and compares the product's field value to the values specified in the rule. If the product's field value matches the field value in the rule, Einstein applies the action. When there are no rules, Einstein sends all product IDs in the list to the storefront in the order in which the strategies returned them.

Brandon is ready to configure a recommender. He already has the credentials to access the Configurator site.

In this module, we assume you are a B2C Commerce merchandiser with the proper permissions to perform these tasks. If you’re not a B2C Commerce merchandiser, that’s OK. Read along to learn how your merchandiser would take these steps. Don't try to follow the steps in your Trailhead Playground. This functionality isn't available in the Trailhead Playground.

Here’s how Brandon configures a recommender that recommends more products of the same brand.

1. In a web browser, go to https://configurator.cquotient.com.
2. Log in to the Configurator tool using the credentials provided to you by your administrator. 
3. Click the Site Recommendations tab.
4. Click New Recommender.
5. Select your site.
6. Select a recommender type: Product to Product. 
7. Enter the recommender name: related-product-brand-x, and click OK. The name must be unique for the site and contain less than 100 characters. It can contain letters, hyphens, and underscores (no spaces). 
8. Click the Generaltab in the left pane, and enter these enter values.
   1. Enter a description: Related products with the same brand.
   2. Maximum number of Recommendations: 4. (This field isn’t always available.)
   3. Choose two products to appear at the top of the list.
9. Click the Strategies tab (1).  Each row of the table is one strategy, and is in priority order. (This tab isn’t always available.)
   1. Click Add Strategy (2). A new row is created at the bottom of the table.
   2. Select the strategy: Product Affinity Algorithm, and click Save.
10. Click the Rules tab.  An empty table with up to two columns appears.
    • If the shopper sees this: This column appears when you create rules for the Product to Product type. Specify an anchor field and anchor field value. Anchors let you narrow in on a specific product or catalog. We get into more detail about anchors in the next unit.
    • Recommend products according to the following criteria: This column appears for all recommender types. Specify an action, field, and field value.
11. Click Add Rule.
12. Select the If the Shopper sees this anchor field (Brand) and anchor value (Brand-X).
13. Select the action: Show.
14. For the recommended product criteria, select the field (Brand) and value (Brand-Y).

You can’t change a recommender’s name, but you can create one with a different name and delete the old one.

As Brandon adds, deletes, or changes the order of his strategies or rules, he previews them to see how his changes affect recommendations.

Here’s how he does it.

1. Open Configurator.
2. Select a recommender.
3. Click the Preview tab. 
   • For a Product in a Category recommender, specify a category anchor (category-id).
   • For a Product to Product recommender, specify a product anchor (product-id).
   • Other recommender types don’t require an anchor when previewed.
4. Click Go. You see a list of products returned by the recommender.

Brandon’s made great progress. He just learned how to set up recommenders in Configurator. Next, he works with the developer on an ISML template so shoppers see the personalized product recommendations.

• Salesforce Help: Product Recommendations
• Salesforce Help: Configure Recommenders