What is the main goal of collaborative filtering?

The main goal of collaborative filtering is to identify similar customers and recommend products based on their preferences and behaviors. This technique relies on the idea that if two users have similar tastes or interests, the recommendations made for one user can also be suitable for the other. By evaluating patterns in user behavior, such as items that are frequently liked or purchased together, collaborative filtering creates a personalized experience, enhancing user satisfaction and engagement.

This approach hinges on the strength of user interactions, allowing systems to generate recommendations without needing to understand the content of the items themselves. As a result, collaborative filtering is widely used in various applications, including e-commerce sites, streaming services, and social media platforms, to improve customer experience and drive sales through targeted suggestions.

Other options, while related to marketing and product recommendations, do not capture the essence of collaborative filtering, which specifically focuses on leveraging user similarities to enhance recommendation systems.