MarketsandMarkets expects the recommendation engine market to grow from USD 588.9 Million in 2016 to USD 4414.8 Million by 2022, at a Compound Annual Growth Rate (CAGR) of 40.7% during the forecast period. The base year considered for this study is 2016, and the forecast period considered is from 2017 to 2022. The market based on AI, is projected to grow at a significant rate over the next 5 years, due to the need to retain old customers and attract new customers, achieve higher sales and Return on Investment (RoI), and analyze large volumes of customer data to create recommendations. Increase in focus to enhance the customer experience and growth in the digitalization trend are some of the major driving factors for the market.
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The objective of the study is to define, describe, and forecast the recommendation engine market powered by AI, on the basis of types (collaborative filtering, content-based filtering, and hybrid recommendations) deployment modes (cloud and on-premises), technologies (context aware and geospatial aware), applications (personalized campaigns and customer discovery, product planning, strategy and operations planning, and proactive asset management), end-users (Banking, Financial Services, and Insurance (BFSI); media and entertainement; healthcare; retail; and transportation), and regions. Moreover, the report aims at providing detailed information about the major factors influencing the growth of market, such as drivers, restraints, opportunities, and challenges.
Top Key Players
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).
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.
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