This documentation covers an introduction to how Yusp recommendations operate, a detailed description of Yusp Dashboard usage and a guide to developers about how to connect your system with Yusp API.
Yusp is a personalization engine that turns data into powerful user journeys that convert, powered by machine learning.
The Yusp personalization engine, developed by the Gravity R&D team, provides a scalable solution for enterprises coming from various industries, such as Retail, Marketplaces and eCommerce, Telecommunication, News and Media, Classified advertising, dating sites and more. The engine can predict individual behavior and preferences using data and provide personalized recommendations to create a better shopping experience and help product discovery, at scale.
The recommendation engine includes all the personalization features as defined by Gartner, and it consists of a core engine and four, independent modules:
The core Yusp algorithms consider various data sources, including user data, product data, and contextual information, to get a 360-degree view of the personalization opportunities of our client's business.
The Yusp team can then implement four different modules for the clients based on their business needs, and personalize physical and online experiences.
Yusp's machine learning algorithms help our clients personalize the experience by adding dynamically changing content to their sites.
Our clients can leverage machine learning to make product and content discovery easier for their visitors by placing the right recommendations at every step of the user journey.
Yusp clients can provide best-in-class search experiences to their customers by personalizing search results based on prior online behavior and preferences.
Yusp's centralized engine extends the customer journey from our client's site to its marketing channels by delivering personalized interactions to the users in real-time, such as emails, push notifications and more.
With the help of Yusp, brands can deliver relevant content and recommendations to the customers throughout the complete buying journey. As a result, Yusp clients can increase revenues and customer satisfaction.
- Data synchronization:
- Behavior tracking (events)
- Use cases
- Web personalization
- Personalized e-mail recommendations
- Deep dive into the API:
- Backend technologies: REST API, PHP, Java
- Mobile recommendation technologies: Android / Java, iOS
- E-mail recommendation technologies: Batch recommendations
Updated about 3 years ago