Recommendation Engine Industry Overview

Study Period: | 2018 - 2028 |
Fastest Growing Market: | Asia-Pacific |
Largest Market: | Asia-Pacific |
CAGR: | 37.46 % |
Major Players![]() *Disclaimer: Major Players sorted in no particular order |
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Recommendation Engine Market Analysis
The Recommendation Engine market is expected to register a CAGR of 37.46% during the period. With the growing amount of information over the internet and a significant rise in the number of users, it is becoming essential for companies to search, map, and provide the relevant chunk of information according to their preferences and tastes.
- 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. Most organizations globally are pursuing digital transformation, focusing on improving customer and employee experience, leveraged by automation solutions.
- 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, positively impact the revenue and margins. This positive impact is expected to create significant opportunities for adopting recommendation engines over the forecast period.
- The advancement of digitalization across emerging economies, coupled with the growth of the e-commerce market, has driven the demand for recommendation engines. Integrating the machine learning model across AI-based cloud platforms drives automation across multiple end-user industries.
- The increasing need to consider all the user information to personalize and customize the best possible output is expected to impact the adoption of recommendation systems across industries. One of the significant attributes adding to consumer information is the content that the customer sees, i.e., the visual of the product.
- The COVID-19 pandemic has led businesses to take precautionary measures leading to the closures of several outlets. Owing to this, companies across the globe are facing short-term challenges across sustained revenues, health and safety, supply chain management, labor shortages, and pricing, to name a few. Multiple studies have identified that, amidst this outbreak, the use of advanced technologies, such as AI, ML, Analytics, and many more solutions, have assisted businesses in attaining positive outcomes.
Recommendation Engine Industry Segments
Recommendation engines are data filtering tools that use various algorithms and data to recommend the most relevant items to a particular customer. It first captures the past behavior of a customer and, based on that, recommends products that the users might be likely to buy. The integrated software context analyzes available data to make suggestions for something (product/services) that a website user might be interested among other possibilities. Recommendation engine systems are common among e-commerce, social media, and content-based websites.
The Recommendation Engine Market report is segmented by Deployment Mode (Cloud, On-Premise), Type (Collaborative Filtering, Content-Based Filtering, Hybrid Recommendation Systems), End-user Industry (Retail, Media and Entertainment, IT and Communication, BFSI, and Healthcare), and Geography.
Deployment Mode | |
On-Premise | |
Cloud |
Types | |
Collaborative Filtering | |
Content-Based Filtering | |
Hybrid Recommendation Systems | |
Other Types |
End-user Industry | |
IT and Telecommunication | |
BFSI | |
Retail | |
Media and Entertainment | |
Healthcare | |
Other End-user Industries |
Geography | |
North America | |
Europe | |
Asia Pacific | |
Latin America | |
Middle East and Africa |
Recommendation Engine Market Trends
This section covers the major market trends shaping the Recommendation Engine Market according to our research experts:
IT and Telecom industry is showing a promising growth for recommendation engine market.
- Advances in technology allow providers to collect massive amounts of geolocation information. 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 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 to have a strong foothold in the telecom industry. In January 2021, Envestnet Inc. announced the launch of a new version of its recommendation engine for enterprise organizations.
- The penetration of social media among people is also driving market growth. Companies use these recommendation platforms to gauge the users' sentiments and feed their social media pages with their respective product choices through advertisements. These advertisements are chosen based on clicks, watch time, likes/dislikes, comments, freshness, and upload frequency, among other factors. For instance, Youtube uses an unsupervised machine learning algorithm to recommend similar content creators for any channel.
- The IT and telecommunication industry is expected to grow 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 social media penetration, may propel market growth.

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Asia Pacific is Expected to Hold Significant Market Share
- They were led by countries such as Australia, India, China, and South Korea; the Asia-Pacific region is expected to witness the fastest growth in the recommendation engine market. China is one of the major countries in Asia-Pacific with growing technological adoption. The country is home to one of the fastest Internet bands and strong e-commerce players, like Alibaba.
- China is the second-largest OTT market in the world, after the United States. According to Instituto Federal de Telecomunicaciones (Mexico), as of January 2020, there were 68 subscriptions per 100 homes in China, and the rate of online video users is increasing effectively. However, the country is stringent regarding the industry's regulations, the data they use, and the content that is allowed to be circulated.
- Moreover, one of the e-commerce giants, Alibaba, uses AI and machine learning to drive its recommendations. For instance, AI OS is an online service platform developed by the Alibaba search engineering team that integrates personalized search, guidance, and advertising. The AI OS engine system supports various business scenarios, including all Taobao Mobile search pages, Taobao Mobile information flow venues for major promotion activities, product recommendations on the Taobao homepage, personalized recommendations, and product selection by category and industry.
- Additionally, the changing consumer behavior after the spread of COVID-19 across the region is expected to boost the adoption of recommendation engines by end-users, such as retail, hospitality, and BFSI. Furthermore, in January 2021, Google Cloud announced its plans to launch an AI recommendation engine for online retailers worldwide, including in Asia. The cloud computing service's Product Discovery Solutions for Retail may allow retailers to implement search and recommendation capabilities that enhance customer engagement and improve conversions across their digital properties.

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Recommendation Engine Market Competitor Analysis
The recommendation engine market is competitive and consists of several major players. In terms of market share, some of the players are currently dominating the market. However, with the advancement in 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. The Accelerator aims to leverage artificial intelligence to optimize OTT ad creative dynamically 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.
- March 2021 - SAP SE Acquired Signavio, a significant provider in the enterprise business process intelligence and process management space. Signavio’s products become part of SAP’s business process intelligence portfolio and complement SAP’s holistic process transformation portfolio.
- February 2021 - UNBXD Inc. collaborated with Google Cloud to offer AI-powered commerce search on Google Cloud for retail stores. As part of the collaboration, Unbxd planned to leverage Google Cloud’s advanced search, recommendations, and AI technologies to better enable product discovery for retail customers. The company also planned to deliver its commerce search service, hosted on Google Cloud, to retail customers.
Recommendation Engine Market Top Players
IBM Corp.
Salesforce.com inc.
Amazon Web Services Inc.
Microsoft Corp.
Google LLC (Alphabet Inc.)
*Disclaimer: Major Players sorted in no particular order

Recommendation Engine Market Recent Developments
- January 2022 - Adobe launched the same page enhanced personalization with Adobe Target and a real-time customer data platform. This new integration with Adobe Real-time Customer Data Platform (CDP) provides Adobe Target with a unified profile sourced from all online and offline interactions.
Recommendation Engine Market Report - Table of Contents
1. INTRODUCTION
1.1 Study Assumptions and Market Definition
1.2 Scope of the Study
2. RESEARCH METHODOLOGY
3. EXECUTIVE SUMMARY
4. MARKET INSIGHTS
4.1 Market Overview
4.2 Industry Attractiveness - Porter's Five Forces Analysis
4.2.1 Bargaining Power of Suppliers
4.2.2 Bargaining Power of Buyers
4.2.3 Threat of New Entrants
4.2.4 Threat of Substitute Products
4.2.5 Intensity of Competitive Rivalry
4.3 Assessment of the Impact of COVID-19 on the Market
4.4 Technology Snapshot
4.4.1 Geospatial Aware
4.4.2 Context Aware (Machine Learning and Deep Learning, Natural Language Processing)
4.5 Emerging Use-cases (Key use-cases pertaining to the utilization of Recommendation Engine across multiple end users)
5. MARKET DYNAMICS
5.1 Market Drivers
5.1.1 Increasing Demand for Customization of Digital Commerce Experience Across Mobile and Web
5.1.2 Growing Adoption by Retailers for Controlling Merchandising and Inventory Rules
5.2 Market Challenges
5.2.1 Complexity Regarding Incorrect Labeling Due to Changing User Preferences
6. MARKET SEGMENTATION
6.1 Deployment Mode
6.1.1 On-Premise
6.1.2 Cloud
6.2 Types
6.2.1 Collaborative Filtering
6.2.2 Content-Based Filtering
6.2.3 Hybrid Recommendation Systems
6.2.4 Other Types
6.3 End-user Industry
6.3.1 IT and Telecommunication
6.3.2 BFSI
6.3.3 Retail
6.3.4 Media and Entertainment
6.3.5 Healthcare
6.3.6 Other End-user Industries
6.4 Geography
6.4.1 North America
6.4.2 Europe
6.4.3 Asia Pacific
6.4.4 Latin America
6.4.5 Middle East and Africa
7. COMPETITIVE LANDSCAPE
7.1 Company Profiles
7.1.1 IBM Corporation
7.1.2 Google LLC (Alphabet Inc.)
7.1.3 Amazon Web Services Inc.
7.1.4 Microsoft Corporation
7.1.5 Salesforce.com Inc.
7.1.6 Unbxd Inc.
7.1.7 Oracle Corporation
7.1.8 Intel Corporation
7.1.9 SAP SE
7.1.10 Hewlett Packard Enterprise Co.
7.1.11 Qubit Digital Ltd.
7.1.12 Algonomy Software Pvt Ltd
7.1.13 Recolize GmbH
7.1.14 Adobe Inc.
7.1.15 Dynamic Yield Inc.
7.1.16 Kibo Commerce
7.1.17 Netflix Inc.
*List Not Exhaustive8. INVESTMENT ANALYSIS
9. MARKET OPPORTUNITIES AND FUTURE TRENDS
Recommendation Engine Market Research FAQs
What is the study period of this market?
The Recommendation Engine Market is studied from 2018 - 2028.
What is the growth rate of Recommendation Engine Market?
The Recommendation Engine Market is growing at a CAGR of 37.46% over the next 5 years.
Which region has highest growth rate in Recommendation Engine Market?
Asia-Pacific is growing at the highest CAGR over 2018 - 2028.
Which region has largest share in Recommendation Engine Market?
Asia-Pacific holds highest share in 2021.
Who are the key players in Recommendation Engine Market?
IBM Corp., Salesforce.com inc., Amazon Web Services Inc., Microsoft Corp., Google LLC (Alphabet Inc.) are the major companies operating in Recommendation Engine Market.
Recommendation Engine Industry Reports
In-depth industry statistics and market share insights of the Recommendation Engine sector for 2020, 2021, and 2022. The Recommendation Engine research report provides a comprehensive outlook of the market size and an industry growth forecast for 2023 to 2028. Available to download is a free sample file of the Recommendation Engine report PDF.