# Recommendation Engine

Canonical URL: https://babadook.tech/modules/recommendation-engine
Entity: modules
Content hash: 8e0bf328b381b2dba68af92849c49faa3706c6b516e26bfa5f5f18dd913d8158

AI-powered content, product, and next-best-action recommendations using collaborative filtering, content-based, hybrid, and deep learning approaches.

AI-powered content, product, and next-best-action recommendations using collaborative filtering, content-based, hybrid, and deep learning approaches.

## the-right-content-for-every-user

The Right Content for Every User The Recommendation Engine serves personalized content, product, and action recommendations based on user behavior, preferences, and predictive models. Collaborative filtering identifies patterns from similar users. Content-based filtering matches based on item attributes. Hybrid models combine both approaches. Recommendations are served in real-time via API and can be embedded anywhere — product pages, email campaigns, in-app messages, or custom widgets. A/B testing integration measures the lift from recommendations against non-personalized baselines.

### data Viz

## Recommendation Engine Specifications

- **Algorithms:** Collaborative filtering, content-based, hybrid, deep learning (neural collaborative filtering)
- **Latency:** <20ms for recommendation retrieval
- **Contexts:** Product pages, email, in-app, search results, custom
- **A/B Testing:** Built-in recommendation experiment framework
- **Cold Start:** Popularity-based fallback for new users/items

## features

hybrid: true

collaborative: true

true

deep learning: true

## Relationships

### products

- DXP — https://babadook.tech/products/dxp

### capabilities

- AI-Powered Content — https://babadook.tech/capabilities/ai-powered-content
- Customer Intelligence — https://babadook.tech/capabilities/customer-intelligence

### sub modules

- Customer Data — https://babadook.tech/sub-modules/customer-data

### use cases

- Content Management
- Customer Data Unification