UK Markets open in 4 hrs 48 mins
  • NIKKEI 225

    26,907.50
    +691.71 (+2.64%)
     
  • HANG SENG

    17,079.51
    -143.29 (-0.83%)
     
  • CRUDE OIL

    83.75
    +0.12 (+0.14%)
     
  • GOLD FUTURES

    1,704.40
    +2.40 (+0.14%)
     
  • DOW

    29,490.89
    +765.38 (+2.66%)
     
  • BTC-GBP

    17,294.97
    +221.48 (+1.30%)
     
  • CMC Crypto 200

    444.22
    +8.86 (+2.04%)
     
  • Nasdaq

    10,815.43
    +239.83 (+2.27%)
     
  • ^FTAS

    3,773.80
    +10.32 (+0.27%)
     

Global $11.4 Billion Recommendation Engine Markets to 2027: Market to Rise at a Staggering CAGR of 32.5% - Rising Focus on Enhancing Customer Satisfaction

·5-min read
Company Logo
Company Logo

Dublin, Sept. 12, 2022 (GLOBE NEWSWIRE) -- The "Global Recommendation Engine Market By Type, By Application, By Deployment Type, By Organization Size, By End Use, By Regional Outlook, Industry Analysis Report and Forecast, 2021-2027" report has been added to ResearchAndMarkets.com's offering.

The Global Recommendation Engine Market size is expected to reach $11.4 billion by 2027, rising at a market growth of 32.5% CAGR during the forecast period.

Recommendation engines are data filtering technologies that use a variety of algorithms and data to suggest the most relevant results to a certain client. It begins by capturing a customer's prior behavior and then offers products that the customers are likely to purchase based on that information.

The integrated software system evaluates the available data to provide recommendations for things (products/services) that a website user might be interested in, among other things. E-commerce, social media, and content-based websites all use recommendation engines systems.

Many firms are attempting to integrate technology such as artificial intelligence (AI) with their apps, businesses, analytics, and services due to the growing competition in their respective markets. The majority of companies across the world are pursuing digital transformation, concentrating on improving customer and employee experiences through automation technologies.

Retailers may use digital transformation to connect with new customers, better engage with existing customers, save operating costs, and increase employee motivation. Along with that, the rising digitalization and high adoption of smart devices by the consumers is expected to fuel the demand and growth of the recommendation engine market over the forecast period.

COVID-19 Impact Analysis

The outbreak of the COVID-19 pandemic has significantly impacted various companies across the business domain. Several businesses have taken precautionary in response to the COVID-19 pandemic, which has resulted in the closure of some establishments. As a result, businesses all over the world are experiencing short-term difficulties in areas such as sustained revenues, health and safety, supply chain management, labour shortages, and pricing, to mention a few.

Additionally, suppliers can use digital transformation to gain new consumers, communicate with existing customers, lower the cost of corporate operations, and boost employee enthusiasm. These benefits have a favourable effect on earnings and surpluses. This is expected to positively impact the demand for recommendation engines among the enterprises in the coming years.

Market Growth Factors:

Rising focus on enhancing customer satisfaction

The increased focus on improving customer experience in the digital space is a primary factor driving the demand for recommendation engines by the companies. Furthermore, it is critical to improve customer experience in order to increase customer engagement and retention, as well as to boost revenue and return on investment (RoI). Upselling and cross-selling opportunities arise naturally as a result of smart product suggestions made by using recommendation engine.

Rapid pace of digitalization

Online buying has increased as a result of the rise in digitization across the world and the emergence of new e-commerce platforms. These recommendation engines enable easy browsing and display products or information based on the customer's past search. Furthermore, mobile phone ownership is highly contributing to e-commerce growth and encouraging e-commerce companies to use recommendation engines.

Marketing Restraining Factor:

Security and privacy concerns

Consumers can obtain more credible feedback if a recommendation engine generates more personal data. The recommender may acquire information such as the user's identification, demographic profile, behavioural data and purchase history, ranking history, and more. These details could be particularly sensitive in terms of privacy. Providing this information to the companies can increase the risks of privacy and security breaches. The data could be sold to a third party without the client's authorization, or it could be hacked by the attackers.

The recommendation engine market is classified into Collaborative Filtering, Content-based Filtering and Hybrid Recommendation. The collaborative filtering segment dominated the recommendation engine market with the maximum revenue share in 2020 and is estimated to maintain its dominance over the forecast period. This is due to increasing demand for dependable recommendation engines by the e-commerce companies to improve their consumers' shopping experiences by proposing products based on their tastes and preferences. For example, Spotify employs collaborative filtering to suggest "Discover Weekly" and other playlists to listeners based on their previous listening habits.

Application Outlook
By application, the recommendation engine market is classified into Personalized Campaigns and Customer Delivery, Strategy Operations & Planning and Product Planning and Proactive Asset Management. The personalized campaigns and customer delivery segment acquired the largest revenue share in the recommendation engine market and is estimated to maintain its dominance during the forecast period. It is owing to the increase in the requirement to provide better customer experience and services by various companies across different industrial verticals.

KBV Cardinal Matrix - Recommendation Engine Market Competition Analysis

The major strategies followed by the market participants are Product Launches. Based on the Analysis presented in the Cardinal matrix; Microsoft Corporation and Google LLC are the forerunners in the Recommendation Engine Market. Companies such as Amazon.com, Inc., SAP SE and Intel Corporation are some of the key innovators in the Market.

The market research report covers the analysis of key stake holders of the market.

Key Market Players

  • IBM Corporation

  • Oracle Corporation

  • Microsoft Corporation

  • SAP SE

  • Salesforce.com, Inc.

  • Adobe, Inc.

  • Google LLC

  • Intel Corporation

  • Hewlett-Packard Enterprise Company

  • Amazon.com, Inc.

Scope of the Study

Market Segments Covered in the Report:

By Type

  • Collaborative Filtering

  • Content-based Filtering and

  • Hybrid Recommendation

By Application

  • Personalized Campaigns & Customer Delivery

  • Product Planning & Proactive Asset Management and

  • Strategy Operations & Planning

By Deployment Type

  • Cloud and

  • On-premise

By Organization Size

  • Large Enterprises and

  • Small & Medium Enterprises

By End Use

  • Retail

  • BFSI

  • Healthcare

  • Media & Entertainment

  • Information Technology and

  • Others

By Geography

  • North America

  • US

  • Canada

  • Mexico

  • Rest of North America

  • Europe

  • Germany

  • UK

  • France

  • Russia

  • Spain

  • Italy

  • Rest of Europe

  • Asia Pacific

  • China

  • Japan

  • India

  • South Korea

  • Singapore

  • Malaysia

  • Rest of Asia Pacific

  • LAMEA

  • Brazil

  • Argentina

  • UAE

  • Saudi Arabia

  • South Africa

  • Nigeria

  • Rest of LAMEA

For more information about this report visit https://www.researchandmarkets.com/r/pblus2

CONTACT: CONTACT: ResearchAndMarkets.com Laura Wood,Senior Press Manager press@researchandmarkets.com For E.S.T Office Hours Call 1-917-300-0470 For U.S./ CAN Toll Free Call 1-800-526-8630 For GMT Office Hours Call +353-1-416-8900