Recommendation Search Engine Market Research Report Type (Collaborative Filtering, Content-Based Filtering, Hybrid Recommendation), Technology (Context-Aware, Geospatial Aware), Application, Deployment, End-User (BFSI, Healthcare, IT & Telecom, Retail) - Forecast till 2030

Recommendation Search Engine Market Overview

In 2022, the global recommendation engine market value is registered as USD 1.77 billion and the recommendation search engine market size is projected to grow at the highest CAGR OF 34.2% along with the market value of USD 13.3 Billion during the forecast period 2022-2030.

At the starting of the website era, there will be an information overload over the internet to get the relevant information which is resolved by the search engines like Google, Yahoo, and more. They fail to provide the personal data which is provided by the recommended search engine by additionally filtering the data. The recommendation engine is a type of software and technique that analyzes and scrutinizes the available data which may interest the website user.

Moreover, this does not use an explicit query but evaluates the user context and user profiles which is the recently or last purchased or read. Now, one or more specifications of the object of your interest are provided by the recommendation search engine. This is considered an essential chunk of applications and software products in the ICT domain. These search engines are highly preferred in e-commerce, social media, and content-based websites. To achieve long-term business objectives, this system retrieves the right information from the user in an automated way. Privacy is an essential issue for these systems.

COVID-19 Analysis:

The COVID-19 pandemic has spread all over the world and impacted various industries in numerous ways. To curb the spread of the virus, most of the governments implemented lockdowns and several stringent rules like social distancing, traveling restrictions, manufacturing industries shut down, and public places closed. Most of the companies offers work from home for their employees to control the spread of the virus.

Due to these restrictions and increasing fear of getting infected, people shifted their physical shopping to online shopping. Hence the demand for online shopping platforms increases. In the first quarter of 2017, the e-commerce giant Amazon.com, Inc got USD 33 million an hour in sales. This shift among the consumers towards online shopping is boosting the demand for the recommendation search engine market. Thus, this pandemic is positively impacted the recommendation search engine market sales.

Market Dynamics

Drivers:

The rising need to enhance customer experience and increasing adoption of digital technologies among organizations are the major factors driving the recommendation search engine market growth. Rising demand to analyze large volumes of data is propelling market growth.

Restraint:

For providing the recommendation to the user, the system needs the deep information of the user including demographic data like age, sex, hobbies, etc, and also the data about the location of a particular user. Growing concerns regarding the safety of customer information are limiting the growth of the market.

Opportunities:

The rising volume of quantitative and qualitative data and the emergence of deep learning technology are creating opportunities for the growth of the market in the assessment period. 

Challenges:

Concerns regarding infrastructure compatibility cloud are hampering the market growth.

Recommendation Search Engine Market Segment Insights

The global recommendation search engine market has been divided into six segments based on type, application, end-user, technology, deployment, and region.

Recommendation Search Engine Type Insights

The recommendation search engine types are trifurcated into collaborative filtering, content-based filtering, and hybrid recommendation. Among them, the collaborative filtering segment is dominating the largest market share due to the increasing demand for reliable recommendation engines from e-commerce platforms by enhancing the customer’s shopping experience and suggesting products related to their preferences.

Recommendation Search Engine Application Insights

The Recommendation Search Engine Market by application is classified into four types such as personalized campaigns & customer discovery, product planning, strategy & operations planning, and proactive asset management. Out of these segments, the personalized campaigns & customer discovery segment is dominating the largest market share due to the rise in need to provide better service to the customers and customer experience.

Recommendation Search Engine Technology Insights

The recommendation search engine market segments by technology are context-aware and geospatial aware. Further, the context-aware is sub-segmented into machine learning & deep learning, and natural language processing. Among them, the context-aware segment holds the largest market share due to the need to understand users’ preferences based on past location records.

Recommendation Search Engine Deployment Insights

The recommendation search engine market deploys into on-cloud and on-premise. The on-cloud segment is holding a significant share due to the growing demand for cloud technologies adoption among the players to integrate the recommendation engines into their web-based applications like media, retail industries.

Recommendation Search Engine End-user Insights

The recommendation search engine industry is categorized into various types such as retail, banking, media & entertainment, financial services, insurance, transportation, healthcare, and others. Among them, the retail segment is accounting for the highest share for the rising adoption of recommendation systems by e-commerce and retail organizations for providing better and quick services to their customers.

Recommendation Search Engine Regional Insights

Region-wise, the global recommendation search engine market is divided into four main geographies like North America, Asia-Pacific, Europe, and the Rest of the World. Among them, North America is accounting for the largest market share due to most of the organizations shifting towards new and upgraded technologies.  

Regional Analysis 

Geographically, the recommendation search engine (RSE) market is segmented into four major regions such as Asia-Pacific, North America, Europe, and the Rest of the World. Out of these regions, North America is holding the highest recommendation search engine market share due to most of the organizations shifting towards new and upgraded technologies coupled with the rising adoption of digital business strategies.

Moreover, increasing focus to enhance the customer experience by the vendors is propelling the growth of the market in this region. Owing to rapid digitalization, an upsurge in online shopping transactions, the rising presence of over-the-top players (OTT), Asia-Pacific is predicted to grow at a significant rate.

Competitive Landscape

The recommendation search engine market top leaders are the following:

• IBM (US)


• Google (US)


• SAP (Germany)


• Microsoft (US)


• Salesforce (US)


• Intel (US)


• HPE (US)


• Oracle (US)


• Sentient Technologies (US)


• AWS (US).

Recent Developments

• A well-known and popular enterpriser, Google acquired an innovative app maker named Jetpac which recommends destinations based on an analysis of publicly shared Instagram photos. Automatically, this technology extracts the information from large numbers of publicly available photos instead of relying on curation or other human processes.


• In June 2019, the most popular enterprise Amazon.com, Inc. introduced their machine learning service named Amazon Personalize that helps users to make personalized and non-personalized recommendations for their applications. Without the requirement of any machine learning experience, this service allows them to curate recommendations.


• In January 2021, a famous vendor, Google Cloud introduced an innovative solution named AI recommendation engine for online retailers with extraordinary solutions for strengthening personalized online shopping.