IBM and Salesforce are Renowned Player in the Recommendation Engine Market - Report by MarketsandMarkets™

According to recent research "Recommendation Engine Market by Type (Collaborative Filtering, Content-Based Filtering, and Hybrid Recommendation), Deployment Mode (Cloud and On-Premises), Technology, Application, End-User, and Region - Global Forecast to 2022", The recommendation engine market size based on AI, is expected to grow from USD 801.1 Million in 2017 to USD 4414.8 Million by 2022, at a Compound Annual Growth Rate (CAGR) of 40.7% during the forecast period. Increase in focus toward enhancing consumer experience and growth in trend of digitalization are some of the major driving factors for the recommendation engine market. Furthermore, surge in demand to analyze large volumes of data and increase in use of deep learning technology in recommendation solution, are expected to provide growth opportunities for the market.

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The collaborative filtering type segment is expected to be the largest contributor in the recommendation engine market during the forecast period

A large volume of customer data generated through smartphones, web, and various touch points requires filtering to create personalized recommendations. Collaborative filtering type used in recommendation engines filter data based on the similarity of user interests. Hence, various end-users have deployed recommendation engine solution based on AI, with collaborative filtering type to categorize the customers with similar interests to deliver personalized recommendations.

The media and entertainment end-user segment is expected to grow at a significant growth rate during the forecast period

The demand for recommendation engine based on AI, is expected to grow across various end-users with the increase in need to understand customer behavior and formulate various customer retention strategies. Specifically, the media and entertainment segment is expected to record the highest growth rate during the forecast period. The market for media and entertainment is expected to grow at a faster rate, owing to the increase in need for deployment of recommendation engine solution either on cloud or on-premises.

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North America is expected to account for the largest market share during the forecast period

North America is the most competitive and rapidly changing region in the recommendation engine market across the globe. North America, among all the regions, has witnessed maximum adoption of recommendation engine, due to the rise in focus of the companies to enhance consumer experience, growth in technological advancement, and surge in government support. The US and Canada are projected to extensively implement recommendation engine solutions. Hence, North America is expected to account for the largest market share in the global recommendation engine market during the forecast period.

The major vendors in the global recommendation engine market based on AI, include IBM (US), SAP (Germany), Salesforce (US), HPE (US), Oracle (US), Google (US), Microsoft (US), Intel (US), AWS (US), and Sentient Technologies (US).

IBM is one of the leading vendors of the recommendation engine solutions powered by AI. The company has followed inorganic growth strategy, such as partnership, to deliver its recommendation product and solution to different industries. For instance, in August 2017, IBM formed a partnership with Metro Shoes to help deliver a personalized shopping experience to its customers. As a part of this partnership, Metro Shoes would incorporate Watson Customer Engagement solution into its digital commerce platform to enhance the overall shopping experience.

Another market-leading company, Salesforce adopted the inorganic growth strategy, such as partnerships, to deliver AI powered recommendation engine solutions to different industries. For instance, in June 2017, Salesforce partnered with Airbus to offer AI-powered recommendation engine solution. To detail, Airbus would leverage the CRM platform, offered by Salesforce, into its operations to analyze customer behavior from purchase history and interactions to offer recommendations. In addition, product launch could be a significant strategy followed by Salesforce.

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