Lesson 6 AI
The foundation of the Synerise platform is very much based on Artificial Intelligence algorithms. They allow you to provide personalized recommendations based on what customers like and how they behave at every step of their journey. In this chapter you will learn more about the integration process, how to start using AI and how we can build our own recommendations engines based on customer data updated in real time.
Types of AI recommendations
In general, recommendation types are divided into 3 groups, depending on their context, which determines where and how each campaign may be implemented.
Recommendation with the context of the product
- Similar – shows related offers and recommends similar products to the ones the customer is looking for, based on product feed attributes and which products are frequently viewed together by your customers on your website.
- Visual - shows results of visually similar products because the model analyzes images of the products from the product feed.
- Complementary - shows products which are commonly bought with searched or viewed product.
Typically, these 3 types of campaigns are implemented on the product page, but it’s possible to prepare, for example, cross-selling campaigns on the home page, with recommendations matching recently purchased products.
Recommendations with basket context
- Cart recommendations - products commonly bought with all products added to the basket.
This can be implemented on the cart page.
Recommendation in the context of a particular user
- Personalized recommendations - shows products which are best suited for each customer. The model is trained on the basis of the behavior of all customers, so each customer will get a unique set of recommended products.
This type of campaign may be implemented in any page on your website, from home page to 404 and in emails as well.
Check our Webinar!
Learn more about AI integration from our SYNERISE EXPERTS HUB Webinar.
This is the first introductory part, connected with business overview.
- Learn more about types of recommendations
Thanks to them you will discover many possibilities of our AI module!