In this chapter, we are going to dive deeper into building product recommendation systems with which we can target customers better, using product recommendations that are custom-tailored toward individual customers. Studies have shown that personalized product recommendations improve conversion rates and customer retention rates. As we have more data available for utilizing data science and machine learning for target marketing, the importance and effectiveness of customized product recommendations in marketing messages have grown significantly. In this chapter, we are going to discuss the commonly-used machine learning algorithms for developing recommendation systems, collaborative filtering, and the two approaches to implementing collaborative filtering algorithms for product recommendations.
In this chapter, we will cover the following topics...