In this article, you can find a list of the most common use cases connected to the personalization of customer experience. The list below should help you find the one that best suits your needs and a guide on how to set it up.
# Personalized Product Recommendations
**E-commerce Goal:** Activation, Repeated purchases, Cross-sell **Example Usage:** Personalized product recommendations show the most relevant products for each customer based on their product views and purchases. This Use Case enhances the customer shopping experience by increasing personalization. It could be used to activate a customer and cross-selling additional products to existing customers and increase their loyalty. **Ideal Placements:** Homepage, Campaigns **Requirements:**
Product catalog
Event tracking for the following events: view product, add to cart, purchase product
**Setup:** This guide will help you to understand how to set up personalized product recommendations to show the most relevant products for each customer.
**What are the personalized product recommendations use cases?**
There are two options for setting up this use case:
Show products with which the customer has recently interacted such as the last viewed products. This option should be preferred if recent interactions are more important than longer customer interactions history. For this option, you should use the [Customer recent interactions template](🔗).
Show products that are the most relevant for a customer by analyzing customer interactions and finding similar customers that viewed or purchased similar products as a target customer. This option could be set to capture customer preferences on long interaction history and therefore it works well for loyal customers (customers with a lot of interaction history). For this option, we will use [Personalized Recommendations for You Template](🔗).
In this example, we will work with the events shown in the following picture
Event view_item which is tracked when a customer visit a detail page of a product. It is defined in the Data & Assets -> Data manager -> Events.
Event purchase_item which is tracked when a customer purchase a product. It is defined in the Data & Assets -> Data manager -> Events.
Event add_to_cart which is tracked when a customer adds a product in the cart. It is defined in the Data & Assets -> Data manager -> Events.
# Retention Campaign
**E-commerce Goal:** Repeated purchases **Example Usage:** Reactivate customers with personalized campaigns containing relevant products. **Ideal Placements:** Email campaigns **Requirements:** Product catalog, Event tracking for the following events: purchase product, view product, add a product to cart, at least several months of these data **Setup:** We suggest using the [Personalized Recommendations for You Template](🔗) since it provides the best recommendations based on the preference of other similar customers.
# Top Products from Category
**E-commerce Goal:** Activation and Repeated Purchases **Example Usage:** We would like to show customers the top products from the category that they are currently viewing. **Ideal Placements:** Category page **Requirements:** Data mapping for events that denote customer interactions with items that represent similarities such as view_item and purchase_item **Setup:** In this use-case, we suggest using the [Metric based category” template](🔗).
# Personalized Products from Category
**E-commerce Goal:** Repeated purchases, Cross-sell **Example Usage:** Personalized product recommendations show the ranked products from the category for each customer based on their product views and purchases. This use case enhances the customer shopping experience while interacting with the category page. **Ideal Placements:** Category page, Homepage **Requirements:** Event tracking for the following events: purchase product, view product, add product to cart, at least several months of these data. Product catalog with columns:
Category column (required): column called e.g. “category_id” that contains string values. It can be single category (e.g. "t-shirt") or list of categories (e.g. "t-shirt;blue"). In the case of a category list, individual categories have to be separated by a delimiter (e.g. "t-shirt;blue;man", where "t-shirt", "blue" and "man" are categories and ";" is a delimiter).
Datetime column (optional): column called “date_added” of values like “2019-01-01” indicating when a product was added to the catalog. You have to mark it as `
date_added` (label in catalog mapping import) when the catalog is imported.
Catalog import
Category column should be always imported as a string e.g. "t-shirt" or "t-shirt;blue". Please, do NOT use list type for import.
Event tracking
You do NOT need to track categories in the events. On the contrary, it has to be presented in the product catalog.