Personal logic 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 > Behavior based logics for email recommendations: Personal
Prerequisites
The prior conditions and the requirements are the same that applies to the Personalization rules. See, Personalization rules' prerequisites.
Packages: Advanced or MAX AI/accelerator package. Regarding the pricing, Personalization rules are part of the E-Commerce & Retail accelerator SKU.
How does it benefit me?
Personal logic is a powerful recommendation tool in Personalization Rules, which helps you create true, one-to-one personalization.
Use cases
Recommending items per price
You can create a campaign for your top-spending customers. Let's say your campaign will contain personalized recommendations based on these customers' interest and behavior, but recommending the more expensive items only.
Recommending items per interest
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 brands only.
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
When contacts browse the webshop they presumably search for those products that match their interests. Items that are often visited together are deemed to be similar.
When identifying similar products, the algorithm aggregates all the browsing information available for the customers' contact base.
For determining the recommended set of items to the contacts the algorithm uses the contacts' browsing history as it is representative of their interest.
The items to be promoted are compared with the contact's interests. The algorithm finds the similar products by the previously determined item similarity relations.
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.