In a collaborative project with niceshops, we designed various recommendation algorithms to enhance revenue through diverse recommendation scenarios. We aimed to boost sales by suggesting a wide range of products to customers, increasing the chances of purchase by catering to different preferences and needs. Our approach included collaborative filtering, content-based filtering, and hybrid methods, ensuring a balance between personalized suggestions and product variety. By diversifying the recommended items, we successfully captured a broader customer base, significantly improving overall revenue.

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