Content Recommendation Engine Market Research Report – Forecast to 2027

Content Recommendation Engine Market Research Report, by Component (Solution), Filtering Approach (Collaborative Filtering, Content-Based Filtering), Organization Size (Small & Medium Enterprises, Large Enterprises), Vertical — Forecast till 2027

ID: MRFR/ICT/4831-HCR | February 2021 | Region: Global | 100 pages

Content Recommendation Engine Market Overview:


The Content Recommendation Engine market growth is expected to surpass over USD 6 Billion by the year 2023 while registering a CAGR of 30%. The Content Recommendation Engine is a software solution that generates recommendations for specific users about the products or services they search online. The Content recommendations work with the help of the keywords given by the user which potentially describe the item or the service, further the recommendations help in identifying the types of data or the items that the user prefers. The software solution is highly beneficial in obtaining essential news based on news recommendations. However, the recommendations are provided to the user based on the browsing history of the user.


The item can be a book, a video, music, a service, news, or any content available on the internet. The recommendation engine analyses the structured data and presents the most relatable data to the user. The Content Recommendation software is prevalently utilized by the E-commerce industry and social media. The increasing growth of social media content and the E-commerce industry has aided the growth of the Content Recommendation Engine in recent years.


COVID 19 Analysis:


The Pandemic has affected several industries across the world and they have struggled to get out of the reduced production rates in recent times. The Content Recommendation Engine industry has also suffered significantly due to the large volume of data being generated and filtering them and getting more audience have been a challenge in recent times. However, on the other hand, the restrictions in the movement have increased the demand for the e-commerce industry, which has stimulated the growth of the Content Recommendation Engine industry in recent times.


The lockdown has increased the usage of internet access as most of the people are staying at home. The increasing data generation in social media and surging small sectors have propelled the demand for the Content Recommendation Engine market growth in this pandemic. The changing trends in supply chain stress have encouraged retailers to deploy smart devices and analytics to gain resilience.


Market dynamics:


Market drivers:


The increased number of applications for the Content Recommendation Engine has increased the overall market value in recent years. The verticals like E-commerce, IT and telecommunications, BFSI, educational sectors, and so on are highly influenced by the Content Recommendation Engine. The emerging companies that are focusing on digital marketing are highly utilizing the Content Recommendation Engine Market to promote their business.


The potential Content Recommendation Engine would possess characteristics like higher coverage of various items while maintaining lower latency, higher diversity so that the customer would get to know about diverse items also. Higher adaptability of the content, since the data generation has increased tremendously in recent years, the software solution must be able to adapt to the data being added newly. Organizations are opting for these potential Content Recommendation Engines which have increased the growth of their businesses. These attractive characteristics have drawn several industries to adopt the Content Recommendation Engine into their business processes.


Market opportunities:


The growing digitalization in developing countries has provided major opportunities for the growth of the Content Recommendation Engine Market. These countries are emphasizing their e-commerce strategies to build their businesses. Primarily, the E-commerce industry has been growing in Asia-pacific countries. This has stimulated the growth of the Content Recommendation Engine Market demand in these countries


The two potential filtration systems are highly utilized by industries across the globe, which are content-based filtration systems and collaborative filtration systems. However, the advent of hybrid filtering systems has leveraged the major benefits of both of these filtration systems. Such advancements have enabled the users to create a set of recommendations for themselves. This has increased the user experience significantly. Hence the increasing adaptation of hybrid recommendation filtering systems has increased the overall growth of the Content Recommendation Engine Market.


Market restraints:


The feature representation is crucial for the sales of these items. The feature representation is carried out by hand-engineering. This requires skilled professional and domain knowledge to represent the item in a better way. The lack of skilled professionals has restricted the growth of the Content Recommendation Engine Market in recent years. Additionally, the recommendations are based on the interests of the current users, the trends and the interests would change very often and the Content Recommendation Engine can’t derive a precise recommendation list.


The lack of proper security measures is the major restraining factor of the Content Recommendation Engine industry. The usage of sensitive information of the customers without the security protocols has paved the way for professional hackers and enabled them to access the source code.


Market challenges:


The recommendations might be repetitive and the users will not be exposed to the new items. The expansion of business is hindered due to this factor. The calculation of the user matrix and the similarity matrix has to be done precisely for the supreme recommendation. These factors have hindered the growth of the Content Recommendation engine industry.


The recommendations that are based on geography are unstable. The current trends of the local region highly influence the Geo-dependent users. The frequent updating of the current trends is a must, lacking which will affect the growth of the Content Recommendation Engine market.


Cumulative growth analysis:


The global Content Recommendation Engine market growth is expected to surpass over USD 6 Billion by the year 2023 while registering a CAGR of 30%. The growing demand for personalized content in social media and increasing competition have bolstered the Content Recommendation Engine market demand in recent years. The leading streaming platforms like Netflix and Amazon are utilizing hybrid filtering systems which increases the overall growth of the businesses.


The automation search processes of the Content Recommendation Engine have enhanced the user experiences in the leading streaming services. The recommender engine is deployed in such leading streaming platforms enables them to collect the data points from several instances in the network and align them properly for the user search. Additionally, the increasing data generation and video content in social media platforms like youtube have propelled the growth of the Content Recommendation Engine market in recent years. Additionally, the multi-cloud facility and cloud-based intelligence are driving the growth of the Content Recommendation Engine market in recent years. Over 98% of organizations have adopted multi-cloud architectures.


Value chain analysis:


The E-commerce sector is intensively utilizing the Content Recommendation Engine in recent times. The growth of the E-commerce sector has been tracked in recent years. The recent report says that in the year 2018, the e-commerce sector has generated over USD 524 billion and in the year 2019, the value has raised to USD 602 billion. Moreover, the pandemic has propelled the growth of e-commerce owing to the restrictions in movement. Therefore the growth of e-commerce has impacted the growth of the Content Recommendation Engine in recent years.


The recommender engine utilized by Amazon enables the organization to blend the data obtained from observing the real-time user activity with the profile and product information to identify the optimal product and content recommendations. Such practices have provided amazon user's a higher quality of user experience. The report states that over 35% of the revenue relies on the recommendation engine and over USD 45.9 billion are generated via content recommendation platform. Such examples have propelled other emerging e-commerce industries to utilize the Content Recommendation Engine.


Segment overview:


Based on the component:



  • Solution


Based on organization size:



  • Small & medium enterprises

  • large enterprises


Based on filtering approach:



  • Content-based filtering

  • Collaborative filtering

  • Hybrid filtering


Based on vertical:



  • Media entertainment & gaming

  • IT & telecommunication

  • Retailer and consumer goods

  • Education & training

  • BFSI

  • Healthcare & pharmaceuticals.


Regional analysis:


The Content Recommendation Engine market is currently dominated by North America, as the region is comprised of major players of the industry and the advent of advanced technologies has hugely affected the Content Recommendation market growth. The leading players are intensively focusing on enhancing the user experience of their websites. The rapid digitalization in the region and the increased internet and smartphone usage in the region have also highly influenced the growth of the Content Recommendation industry in North America.


A large amount of data is being generated in the European countries owing to increasing industrialization. The necessity of proper management of the data has propelled the overall growth of the Content Recommendation Engine industry in the region. The changing trends and lifestyles of the residents and increasing usage of E-commerce have augmented the overall growth of the industry.


Competitive landscape:



  • Amazon Web Services (US)

  • Boomtrain (US)

  • Certona (US)

  • Curata (US)

  • Cxense (Norway)

  • Dynamic Yield (US)

  • IBM (US)

  • Kibo Commerce (US)

  • Outbrain (US)

  • Revcontent (US)

  • Taboola (US)

  • ThinkAnalytics (UK)


Recent developments:


The CNN have recently developed an all-purpose content personalization structure, that involves various attributes like human curation, and on-device machine learning, which enables the user to discover their favorite books almost instantly while protecting their private data.


The 'Text Travel content recommendation management system' that has been recently introduced enables the user to identify the scenic spots and relevant tourism places and regional comparison information and other similar market insights effortlessly.


Report overview:


This report has covered:



  • Market overview

  • COVID 19 Analysis

  • Market dynamics

  • Cumulative growth analysis

  • Value chain analysis

  • Segment overview

  • Regional analysis

  • Competitive landscape

  • Recent developments



Frequently Asked Questions (FAQ) :


The content recommendation engine market is expected to reach a signficant market value of USD 6 billion by 2023.

The global content recommendation engine market is maturing at a whopping 30% CAGR over the review period of 2017 to 2023.

A few significant players of the glob al content recommendation engine market are Certona (US), Boomtrain (US), Curata (US), Cxense (Norway), IBM (US), Dynamic Yield (US), among others.

The service segment is expected to drive market growth over the review period.

The SME segment is slated to witness higher growth over the assessment period.