A product recommendation system is the commonly employed information filtering system designed to predict and provide suggestions for the products based on the user-s preference to purchase them. The product recommendation system achieves high accuracy by suggesting relevant products to user-s preferences. As a consequence, it tends to overspecialization problem. Overspecialization problem occurs while suggesting the products with little sense of similarity from the initial stage of service usage and lead to low user satisfaction. Serendipity-aware product recommendation helps in resolving the overspecialization problem and improves user satisfaction. The Serendipity of the recommendation system describes as a very subjective and rare coincidence in real-world scenarios. Serendipity-aware product recommendation possesses the significant ability to suggest a novel, interesting and unexpected product to a particular user. It is necessary to develop the product recommendation system with serendipity-aware to produce a better and useful recommendation.