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Configure Recommenders

Learning Objectives

After completing this unit, you’ll be able to:

  • List three recommender types.
  • Explain how to use each recommender type.
  • List three strategies you can use on a product details page.
  • List the rule actions.

Introduction

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.

Recommender Types

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.

Product to Product

For this type, Einstein generates recommendations either by analyzing a product's similarity to other products or by analyzing the view or purchase behavior of other customers. It renders recommendations on these pages.

  • Product details
  • Cart
  • Mini-cart
  • Wishlist
  • Checkout

On the product details page, for example, Brandon wants to recommend footwear that’s similar to the footwear that the shopper is already viewing.

Products in a Category

For this type, Einstein generates recommendations for products that are in the same category. This recommender is typically on a category page. For example, Cloud Kicks has the categories Luxury, Athletic, Outdoor, and Fashion. If a shopper frequently views luxury footwear, Einstein can recommend products in the same category (Luxury) from different areas of the site such as clothing or accessories.

Products in All Categories

To generate recommendations across all categories, Brandon places this recommender type on these pages.

  • Home
  • My Account
  • My Recommendations

Recently Viewed

For this type, Einstein generates recommendations simply by including products that the shopper recently viewed. Brandon can place this recommender type on any page. For example, he can place it on the search results page, where it can help him lower the abandonment rate.

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.

Note

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

Strategies

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.

Strategy

Einstein Analyzes...

Customer recently viewed items

The items the shopper recently viewed.

Customers who bought also bought

The purchasing behavior of other shoppers who bought the same product.

Customers who viewed also viewed

The viewing behavior of other shoppers who viewed the same product.

Customers who viewed ultimately bought

The purchasing behavior of other shoppers who viewed the same product.

Product Affinity Algorithm

The product's similarity to other products.

Real-Time Personalized Recommendations

The shopper’s current and past viewing and purchasing behavior.

Recent Most-Viewed Products

The products recently viewed by other shoppers.

Recent Top-Selling Products

The products recently purchased by other shoppers that are top sellers.

Complete the Set

The shopper’s past and current product choices, combined with other products that are most often purchased with those products.

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

For this page...

Use this recommender type

With these strategies

  • Product details
  • Product to Product
  • Complete the Set
  • Product Affinity Algorithm
  • Customers who viewed also viewed
  • Customers who viewed ultimately bought
  • Customers who bought also bought
  • Real-Time Personalized Recommendations
  • Complete the Set
  • Category
  • Products in a Category
  • Recent Top-Selling Products
  • Recent Most-Viewed Products
  • Real-Time Personalized Recommendations
  • Home
  • My Account
  • My Recommendations
  • Cart
  • Mini-cart
  • Wishlist
  • Checkout

The footer is also a great placement, though it’s not really a page.

  • Products in All Categories
  • Complete the Set
  • Recent Top-Selling Products
  • Recent Most-Viewed Products
  • Real-Time Personalized Recommendations
  • Complete the Set
  • Any page
  • Recently Viewed
  • Customer recently viewed items

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.

For this recommender type...

Use this primary strategy

Use this secondary strategy

Product to Product

Customers who viewed also viewed

Product Affinity Algorithm

Products in a Category

Real-Time Personalized Recommendations

Recent Top-Selling Products

Products in All Categories

Real-Time Personalized Recommendations

Recent Top-Selling Products

Recently Viewed

Customer recently viewed Items

Complete the Set

Complete the Set

Note

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

Rules

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.

Rule Actions

Here are the rule actions that Brandon can use.

Rule Action

B2C Commerce...

Show

Shows items that match the specified field values and hides items that don’t.

Hide

Hides items that match the specified field values.

Promote

Moves matching items to the beginning of the product ID list.

Demote

Moves matching items to the end of the product ID list (or removes the item from the list if there are too many product IDs).

When Brandon configures rules, he makes sure they don’t conflict. For example, he doesn’t configure a recommender to simultaneously show and hide the same product, or promote and demote the same product. If there are conflicts, he simply reviews his rules and adjusts them.

Rule Fields and Values

Einstein compares the rule field and its values to each recommended product returned by the recommender's strategies. If the recommended product's field matches the selected field values, Einstein executes the associated action.

For example, Brandon can create a rule that tells Einstein to put products of the same brand as the shopper’s viewed product at the top of the recommended list. If there are no other products of that brand in the list, it displays products of other brands.

Configure a Recommender

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. Configurator, Site Recommendations tab
  3. Click the Site Recommendations tab.
  4. Click New Recommender.
  5. Select your site.
  6. Select a recommender type: Product to ProductCreate a new recommender
  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). Create a recommender page
  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.
  1. Click the Strategies tab (1). Configurator Strategies tab 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.
  1. Click the Rules tab. Configurator 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.
  1. Click Add Rule.
  2. Select the If the Shopper sees this anchor field (Brand) and anchor value (Brand-X).
  3. Select the action: Show.
  4. 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.

Preview a Recommender

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. Preview a recommender showing gloves in Configurator.
    • 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.
  1. Click Go. You see a list of products returned by the recommender.

Next Steps

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.

Resources

Salesforce 도움말에서 Trailhead 피드백을 공유하세요.

Trailhead에 관한 여러분의 의견에 귀 기울이겠습니다. 이제 Salesforce 도움말 사이트에서 언제든지 새로운 피드백 양식을 작성할 수 있습니다.

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