The Recommendation Engine market was valued at USD 2.12 billion in 2020, and it is expected to reach USD 15.13 billion by 2026, registering a CAGR of 37.46% during the period of 2021-2026

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New York, June 16, 2021 (GLOBE NEWSWIRE) — Reportlinker.com announces the release of the report “Recommendation Engine Market – Growth, Trends, COVID-19 Impact, and Forecasts (2021 – 2026)” – https://www.reportlinker.com/p06095506/?utm_source=GNW

– With the growing number of enterprises and the rising competition among them, many companies are trying to integrate technologies, like artificial intelligence (AI), with their applications, businesses, analytics, and services. Majority of the organizations globally are pursuing digital transformation, focusing on improving the experience of customers and employees, which are being leveraged by automation solutions.
– With governments worldwide enforcing lockdown to home quarantines to curb transmission of COVID-19, people are staying back at home, which has led to increased online shopping and bulk buying of goods. This resulted in massive supply chain stress. Thus, such supply chain players amongst retailers are looking to deploy AI and smart analytics to ensure resilience.
– Digital transformation provides opportunities for retailers to acquire new customers, engage with existing customers better, reduce the cost of operations, and improve employee motivation. These benefits, among others, create a positive impact on the revenue and margins. This positive impact is expected to create significant opportunities for adopting recommendation engines over the forecast period.
– The growing digital commerce market and the tighter operational budgets enable e-commerce players to make smart choices regarding the technologies to invest in and the ones they should forego. To understand customers and their need for convenient and consistent shopping experiences, retailers must transform the store and move the business forward digitally.
– The rising trend of multi-cloud functioning and the growing need for cloud-based intelligence services are also driving the demand for AI as a service. IBM stated that by 2021, 98% of the organization would adopt multi-cloud architectures, with 41% having a multi-cloud management strategy and 38% having procedures and tools to operate a multi-cloud environment.

Key Market Trends
IT and Telecommunication industry is showing a promising growth for recommendation engine market. h rate.

In the fiercely competitive mobile and broadband services market, leading providers recognize the importance of understanding the preferences, demographics, and purchasing habits of the subscribers. The ability to use all the distributed information available to serve the customer better and cross-sell and up-sell effectively can be a significant advantage.

– Advances in technology enable providers to collect massive amounts of information on geolocation. The challenge is effectively processing this data and combining it with existing customer intelligence, to improve the success of marketing campaigns in near-real-time and offer convenient and relevant services and incentives for increased ROI.
– The recommender system for the telecom domain is proposed and implemented to combine collaborative filtering algorithms on a data set made of user preferences on different services in the telecom domain. In addition, the bundled services provided by telecom providers, such as subscriptions to Netflix and Amazon Prime, are also greatly influenced by recommendation engines.
– The IT industry is also witnessing the gradual adoption of recommendation engines to build product recommendation chatbots with the help of ML and AI algorithms. For example, gnani.ai offers a personalized recommendation chatbot based on user preferences and chat history. This drives more customers to the final stage of the sales funnel.
– Furthermore, vendors are rolling out new solutions in the recommendation engine market for the telecom industry to have a strong foothold. For instance, in January 2021, Envestnet Inc. announced the launch of a new version of its recommendation engine for enterprise organizations.
– The IT and telecommunication industry is expected to witness growth during the forecast period. The increasing focus of businesses in this end-user industry to make investments and initiatives to enhance customer experience and increase customer retention, coupled with the high level of social media penetration, may propel market growth.

Europe region is registering second highest growth rate in the market.

– Germany, France, the United Kingdom, Italy are the prominent countries that have a maximum number of internet users in the European region. According to International Telecommunications Union, Germany had 79.13 million internet users in June 2020, followed by France having 60.4 million users, Italy at 54.8 million, and Spain at 42.96 million.
– The recent pandemic has accelerated the adoption of digital services and e-commerce. Companies have seen a surge in market share from new customers in digital channels. As the region is navigating through Covid-19 and economic recovery, companies that can engage their customers in a relevant, meaningful way are expected to realize stronger growth rates. As a result, to best utilize online channels to generate revenue, various end-user industries are utilizing Recommendation engines.
– The region also has a growing retail market which is highly driven by recommendations through various online platforms. As a result, the region is witnessing a surge in customized recommendation engines that are specific to the industry.
– The demand for AI and machine learning is growing. Other industries are witnessing a growth in terms of adoption, as recommendation engines provide details about customers’ preferred meals based on their ordering history, spending capacities, preference to “near me” stores, etc.
– As a result, Takeaway.com, Just Eat, and other local services have become more readily available. The region is also witnessing the entry of more food ordering platforms, such as Uber Eats, which may provide further opportunities to recommendation engine vendors during the forecast period.

Competitive Landscape
The recommendation engine market is moderately competitive and consists of a few major players. In terms of market share, some of the players are currently dominate the market. However, with the advancement in the analytics across AI-based platforms, new players are increasing their market presence thereby expanding their business footprint across the emerging economies. Hence the market concentration is low.

– May 2021 – IBM announced the expansion of IBM Watson Advertising Accelerator for OTT and video, designed to help marketers move beyond contextual relevance alone. Accelerator aims to leverage artificial intelligence to dynamically optimize OTT ad creative for improved campaign outcomes at scale, not dependent on traditional advertising identifiers. While compatible with most streaming platforms, IBM is partnering closely with Xandr, an industry leader in programmatic and converged video solutions, to help scale the adoption of Accelerator.
– January 2021 – Google Cloud launched an AI recommendation engine for online retailers with a new suite of solutions to strengthen personalized online shopping. Product Discovery Solutions for Retail includes Recommendations AI that can deliver highly personalized product recommendations at scale and across all channels.
– November 2020 – The company introduced version 7.0.0 of the Recolize tool, with a new method of displaying data. The new version offers an organized display of the revenue and share using bar charts, pie graphs and line graphs. The tool also displays the number of clients, behavior pattern, growth cure, conversions among various other information which is vital for the users.
– July 2020 – Adobe Target increased Adobe Analytics-enhanced reporting with the artificial intelligence-powered testing and personalization capabilities of the new Auto-Allocate, Auto-Target, and Recommendations through Adobe Sensei, Adobe’s AI technology.

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