Content recommendation engine is an analytic tool to generate meaningful recommendations to specific users about products or items they might be interested in. Content recommendation engine works on the search keywords used by the user, which help in describing the items the user is looking for, as well as on the user profile, which later helps in indicating the type of items or products the user prefers. In order to create a user profile, the recommendation engine focuses on the history of the user’s interactions with the engine. For instance, recommending news articles on the basis of browsing of news is useful; however, what is desirable is when music, videos, and products from different services are also recommended to the user based on his browsing history.

Increase in emphasis on enhancing customer experience is a key factor expected to drive the content recommendation engine market during the forecast period. Rapid digitization is anticipated to boost the deployment of content recommendation engine platforms. Furthermore, increasing need for analyzing large volume of customer data is expected to propel the content recommendation engine market. In addition, rise in use of artificial intelligence in recommendation engine to offer personalized customer experience is expected to create lucrative opportunities for the content recommendation engine market. However, protecting sensitive information of customers, lack of technical expertise, and issues related to infrastructural and technological compatibilities are estimated to hamper the content recommendation engine market during the forecast period.

The global content recommendation engine market can be segmented based on component, deployment, type, enterprise size, end-user industry, and geography. In terms of component, the market can be classified into solutions and services. The services segment of the content recommendation engine market is expected to grow significantly due to the increasing need of the recommendation engine in the field of consulting services, development services, training services, support services, implementation services, and many more. Based on deployment, the market can be classified into cloud and on-premise. The cloud segment is expected to grow at a higher growth rate during the forecast period as cloud-based content recommendation engine offers better and wider solutions to the end-user. On the basis of type, the content recommendation engine market can be segmented into collaborative filtering, hybrid recommendation, and content-based filtering. The collaborative filtering segment is anticipated to hold the dominant share of the market as this technique uses a large volume of information such as users’ preferences, behavior, and activities to segment users based on similarity of likings. Based on enterprise size, the content recommendation engine market can be divided into small and medium enterprises and large enterprises. The large enterprise size segment is expected to hold the leading share of the market during the forecast period. In terms of end-user industry, the content recommendation engine market can be classified into retail, consumer goods, media and entertainment, gaming, e-commerce, hospitality, and others.

By geography, the global content recommendation engine market can be segmented into North America, South America, Asia Pacific, Europe, and Middle East & Africa. The content recommendation engine market in North America is anticipated to expand at a substantial growth rate during the forecast period. This is due to technological advancement and high emphasis on technology innovation in the region. Asia Pacific is expected to be a lucrative market for content recommendation engine during the forecast period due to the rapid digitization activities in the region.

The global content recommendation engine market is characterized by the presence of several key players. Major players of the content recommendation engine market compete with other players based on features, such as, price and quality. Key players operating in the global content recommendation engine market include Boomtrain, Amazon Web Services, Curata, Cxense, Kibo Commerce, Revcontent, ThinkAnalytics, Outbrain, Uberflip, IBM, and Dynamic Yield.

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