New Product Launches, and Product Enhancements and Partnerships are the Key Growth Strategies Adopted in the Recommendation Engine Market
The recommendation software and solutions with AI capabilities deployed in the cloud or on-premises offer organizations with various benefits, such as ease of deployment, reduced operational cost, and higher scalability. MarketsandMarkets expects the recommendation engine market size based on AI, 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. The need to deliver enhanced customer experience in areas, such as product and content searching, retain old customers and attract new customers, and analyze a large volume of data to design recommendations are expected to provide growth opportunities for the market.
The major vendors in the global recommendation engine market based on AI, are IBM (US), SAP (Germany), Salesforce (US), HPE (US), Oracle (US), Google (US), Microsoft (US), Intel (US), AWS (US), and Sentient Technologies (US). New product launches, and product enhancements and partnerships are the key growth strategies adopted by these market players to offer feature-rich products and services to their customers and penetrate deeper into the unserved regions.
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. For instance, in May 2017, Salesforce announced innovations in its AI recommendation solution - Commerce Cloud Einstein - to help the retailers deliver personalized experience to their customers while connecting on the web, social, or in-store. Moreover, the solution would help various organizations provide personalization through product recommendation, tailored product sorting, and meaningful search result at every touch point.
Related Reports:
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
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