Content Recommendation Engine Global Market Report 2024

The content recommendation engine is a platform that uses data collection, data storage, data analysis, and data filtering to provide personalized content and suggestions to website visitors to optimize their experience, which leads to increased viewership and purchases. The content recommendation engine is used for predicting user behavior based on user visits to a website or user profile and then recommending content, products, or services a customer is likely to consume or engage with.

The main components of a content recommendation engine include solution and service. Content recommendation engine solutions include website development services, application development services for devices, software developments, and others. The different content recommendation engine filtration approaches include collaborative filtering, content-based filtering and hybrid filtering. The organization size for content recommendation engines is small and medium enterprises and large enterprises. The content recommendation engine verticals include e-commerce, media, entertainment, gaming, retail and consumer goods, hospitality, IT and telecommunication, BFSI, education and training, healthcare and pharmaceutical and other verticals.

The content recommendation engine market research report is one of a series of new reports that provides content recommendation engine market statistics, including content recommendation engine industry global market size, regional shares, competitors with an content recommendation engine market share, detailed content recommendation engine market segments, market trends and opportunities, and any further data you may need to thrive in the content recommendation engine industry. This content recommendation engine market research report delivers a complete perspective of everything you need, with an in-depth analysis of the current and future scenarios of the industry.

The content recommendation engine market size has grown exponentially in recent years. It will grow from $5.95 billion in 2023 to $8.08 billion in 2024 at a compound annual growth rate (CAGR) of 35.7%. The growth in the historic period can be attributed to increasing volume of digital content, user engagement and retention, personalization trends, competition in streaming services.

The content recommendation engine market size is expected to see exponential growth in the next few years. It will grow to $28.19 billion in 2028 at a compound annual growth rate (CAGR) of 36.7%. The growth in the forecast period can be attributed to cross-platform integration, integration with voice and conversational interfaces, ai explainability and transparency, contextual recommendations, enhanced privacy measures, dynamic user profiles. Major trends in the forecast period include rise of personalization, data analytics and machine learning advances, integration with streaming platforms, cross-platform recommendations, context-aware recommendations.

The rapid digitalization is expected to propel the growth of the content recommendation engine market. Digitalization is the use of various digital technologies and the increase in digital access to change a business model and value-producing opportunities to generate high revenue. For instance, in March 2023, according to the International Energy Agency (IEA), a France-based intergovernmental organization, in advanced economies, the level of digitalization, on average, increased by 6%. Notably, in sectors with greater digitalization, there was a substantial reduction of 20% in labor productivity losses when comparing the 75th percentile to the 25th percentile of digitalization levels. Content recommendation engines are widely used in many firms to optimize business operations and attract maximum customers, improve customer engagement and drive higher revenues. According to the article published by Barilliance Ltd., an Israel-based company that provides personalized solutions for e-commerce platforms and email marketing, in September 2021, approximately 31% of e-commerce revenue is generated from product recommendations. Therefore, rapid digitalization in businesses is driving the content recommendation engine market growth.

The growing internet user is expected to boost the growth of the content recommendation engine market going forward. An internet user refers to an individual who accesses and utilizes the internet for various purposes, such as browsing websites, sending and receiving emails, using online applications, engaging in social media, conducting research, and accessing digital content. The growing number of internet users provides content recommendation engines with more data, better opportunities for personalization, and a broader user base, which collectively leads to increased demand for these systems in a variety of sectors. For instance, in November 2022, according to a report published by the International Telecommunication Union, a Switzerland-based specialized agency, an estimated 5.3 billion people, accounting for 66 percent of the global population, use the Internet in 2022. This reflects a 6.1% growth rate from 2021. Therefore, the growing internet user is driving the growth of the content recommendation engine market.

New product innovation is the key trend gaining popularity in the content recommendation engine market. Major companies operating in the content recommendation engine market are focused on product innovations that could give better recommendation solutions used online business platforms and strengthen their position in the market. For instance, in June 2022, Algolia, a US-based company providing personalized solutions for e-commerce platforms, introduced its advanced recommendation platform based on hybrid filtering combined with artificial intelligence known as Algolia recommend spring. Hybrid filtering technology uses both filtering methods to fill gaps in prediction processes, such as content-based filtering for users’ current interests and collaborative filtering for preferences and behaviours of users this combination can provide an accurate prediction. The platform is an artificial intelligence-based recommendations engine integrated with a search and discovery platform to connect with users to provide relevant, actionable recommendations to enhance customer engagement.

Major companies operating in the content recommendation engine market are developing innovative products such as personalized content recommendation products to meet larger customer bases, more sales, and increase revenue. A personalized content recommendation product refers to a technology or software solution that uses algorithms and user data to suggest specific content, products, or services to individuals based on their preferences, behaviours, and past interactions. For instance, in February 2023, Amplitude Inc., a US-based software company, launched Amplitude Audiences. A distinctive aspect of this product is its ability to seamlessly integrate AI-powered recommendations with robust audience management features, all within a user-friendly, self-service solution. Amplitude Audiences offers a range of distinctive features, including behavioral segmentation through cohort analysis and computations, predictive modeling and segmentation based on predictions, activation through syncs and profile API, seamless integrations with over 30 destinations such as Braze, HubSpot, Intercom, Iterable, and Marketo, as well as powerful recommendations for achieving personalized 1:1 content experiences.

In April 2022, Taboola, a US-based company operating in content recommendation engine, acquired Gravity R&D for an undisclosed amount. Through this acquisition, Taboola aims to strengthen its product in the portfolio in content recommendations by providing personalized offers to customers to drive sales, increase average order sizes, and build customer loyalty to increase its market presence. Gravity R&D is a Hungry-based company operating in a content recommendation engine market.

Major companies operating in the in the content recommendation engine market report are International Business Machines Corporation (IBM), Amazon Web Services Inc, RevContent, Taboola, Outbrain Inc, Cxense ASA, Dynamic Yield Ltd, Curata Inc., Adobe Systems Inc., Salesforce. com Inc., Kibo Commerce, BloomReach Inc., Certona Corporation, RichRelevance Inc., Reflektion Inc., Barilliance Inc., Strands Labs Inc., Qubit Digital Ltd., ThinkAnalytics Ltd., Episerver Inc., Uberflip, Acquia Inc., Sailthru Inc., Zeta Global, Monetate Inc., Emarsys eMarketing Systems AG, IgnitionOne Inc., Boxever Ltd., BlueConic Inc., Sitecore Corporation A/S

North America was the largest region in the content recommendation engine market in 2023. Asia-Pacific is expected to be the fastest-growing region in the forecast period. The regions covered in the content recommendation engine market report are Asia-Pacific, Western Europe, Eastern Europe, North America, South America, Middle East, Africa

The countries covered in the content recommendation engine market report are Australia, Brazil, China, France, Germany, India, Indonesia, Japan, Russia, South Korea, UK, USA, Italy, Canada, Spain.

The content recommendation engine market consists of revenues earned by entities by providing content recommendation engine that are used for data collection and analysis based on user behavior. Values in this market are ‘factory gate’ values, that is the value of goods sold by the manufacturers or creators of the goods, whether to other entities (including downstream manufacturers, wholesalers, distributors, and retailers) or directly to end customers. The value of goods in this market includes related services sold by the creators of the goods.

The market value is defined as the revenues that enterprises gain from the sale of goods and/or services within the specified market and geography through sales, grants, or donations in terms of the currency (in USD, unless otherwise specified)).

The revenues for a specified geography are consumption values that are revenues generated by organizations in the specified geography within the market, irrespective of where they are produced. It does not include revenues from resales along the supply chain, either further along the supply chain or as part of other products.


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