With the beginning of web era, there has been an information overload over the internet which often makes it exhaustive for the user to get the relevant information. This issue is resolved by search engines like Google, Yahoo and many more,however, even they fail to provide personalized data. So, to additionally filter the data we need a recommendation search engine. Recommendation systems are software and techniques, designed with an objective to provide a useful and sensible recommendation to users for items or products that might interest them. Recommendation system typically does not use an explicit query, instead analyzes the user context and user profile, i.e., what the user has recently purchased or read. Then the recommendation mechanism provides the user with one or more specification of objects that may be of interest.
Recommendation search engine system predicts consumer needs based on previous purchase history, online behavior, ratings, reviews, and other personalized attributes. Nowadays companies are investing in real-time technologies to understand consumer behavior at a more granular level across channels and devices. The objective of recommendation search engine is to get more personalized recommendations, customer satisfaction, and increase the sales. Recommendation search engine solves common problems that general search engine face such as inability to scale, generate relevant recommendations, provide flexible processing plans, etc. The recommendation search engine market is gaining momentum to enhance the consumer experience and increase sales.
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Some of the key players of Recommendation Search Engine market include Google (US), IBM (US), Microsoft (US), SAP (Germany), Salesforce (US), HPE (US), Oracle (US), Intel (US), AWS (US), and Sentient Technologies (US).
The prominent players keep innovating and investing in research and development to present cost-effective offerings. Merger and acquisitions among various players are changing the market structure. For instance, Google has acquired Jetpac, makers of an app that recommends destinations based on an analysis of publicly shared Instagram photos. The technology works automatically, extracting information from large numbers of publicly available photos instead of relying on curation or other manual processes.
According to MRFR, The global Recommendation Search Engine market is expected to reach approximately USD 5,900 Million by 2023 growing at a ~40% CAGR over the forecast period 2018-2023.
The geographical analysis of Recommendation Search Engine market is studied for North America, Europe Asia Pacific and the rest of the world.
North America is expected to dominate the Recommendation Search Engine market during the forecast period as many organizations are shifting towards new and upgraded technologies with the increasing adoption of digital business strategies. Also due to the rise in the focus of the companies to enhance consumer experience is major driving for the growth of Recommendation Search Engine Market. Asia Pacific is expected to grow at a faster rate due to rapid digitalization and the increasing presence of over the top players (OTT).
By Type, the market is segmented into Collaborative Filtering, Content-Based Filtering, Hybrid Recommendation.
By Technology, the market is segmented into Context-Aware and Geospatial Aware. Context-Aware is further segmented into Machine Learning and Deep Learning, and Natural Language Processing.
By Application, the market is segmented into Personalized Campaigns and Customer Discovery, Product Planning, Strategy and Operations Planning, Proactive Asset Management.
By Deployment, the market is segmented into on Cloud and On-Premise.
By End Users, the market is segmented into Media and Entertainment, Retail, Banking, Financial Services, and Insurance, Transportation, Healthcare, and others.
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- AI recommendation engine software and platform providers
- Training and consulting service providers
- AI System integrators
- Recommendation Search Engine vendors
- Government Agencies
- Managed service providers
- Research organizations
- Value-added Resellers (VARs)