Global Popularity is a pre-defined, product recommendation logic based on the recent browsing activity and the purchase history. You can select the predict recommendation types listed here:
Content > Personalization Rules > Create Personalization Rule >Global Popularity
Prerequisites
The prior conditions and the requirements are the same that applies to the Personalization rules. See, Personalization rules' prerequisites.
How does it benefit me?
Global Popularity is a powerful recommendation tool in Personalization Rules, which helps you create a general list of the most popular products. It includes the most-viewed and most-purchased items in the past 90 days from the customers’ Product catalog.
Use cases
Recommending popular items that in sale
You can create a campaign for your top-selling products. Let's say your campaign will contain personalized recommendations based on the list of the most popular product items.
Recommending popular items from a particular category
You can create a campaign for your customers, where the campaign contains personalized recommendations. Let's say you want to recommend items based on your customers' interest and behavior, but recommending the specific category only.
Recommending popular items from a particular brand
You can create a campaign for your customers, where the campaign contains personalized recommendations. The list is based on your customers' interest and behavior, recommending a specific brand only.
Recommending popular items based on a certain price point
You can create a campaign for your customers where you recommend popular products that are above/below a certain price point.
How does it work?
In order to create personalized recommendations we need to combine the following information:
- Your contact's browser history
- An item-to-item similarity based on the co-occurrence of products in the historical user sessions.
Interpreting the main logic
Globally popular products are the most popular products in a brand's product catalog. The ranking is based on the most-purchased and most-viewed products in the last 90 days from the brands product catalog.
- All products are considered that have at least 1 view or purchase event in the past 180 days.
- It is counted how many contacts have viewed or purchased each product and create a score.
- Filtering rules are applied (e.g., keep items above a certain price or items that belong to a certain category)
- The number of products that are returned to each contact is limited to 20.
Known limitations
Currently we do not have support for the following:
- Missing Parent-child level matching: One of the elements of our calculation is item-to-item similarity. This means that we might show the same item multiple times in one recommendation, just in different sizes, or color.
- Localized Fields: Not available yet.
- Like other Personalization rules, Personal Logic can only be used in batch type email campaigns. It cannot serve Transactional use cases (for e.g. abandoned cart).
- You can only send product personalized email campaigns to those customers who received any email from you in the last 180 days.
- Product Availability needs to be selected and filtered manually.