LAMEA Recommendation Engine Market

LAMEA Recommendation Engine Market Size, Share & Industry Trends Analysis Report By Type, By Application, By Deployment Type, By Organization Size, By End Use, By Country, Historical Data and Growth Forecast, 2021 - 2027

Report Id: KBV-7680 Publication Date: February-2022 Number of Pages: 142
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Market Report Description

The Latin America, Middle East and Africa Recommendation Engine Market would witness market growth of 37.5% CAGR during the forecast period (2021-2027).

Since consumers are increasingly spending their time on surfing internet for various activities, companies are capitalizing on this trend. For example, the movie and show suggestions appeared on the Netflix are made through recommendation engine.

Amazon, on the other hand, uses a recommendation engine to provide product recommendations to its users. While each utilizes this technology for slightly different reasons, the end aim is the same: to increase sales, increase engagement and retention, and provide more personalized customer experiences.

In the Middle East region, government initiatives are attracting numerous companies to enter the region and expand their market. Supportive government policies and standards are making it easier for companies to implement numerous advanced technologies for business benefits. The Emirati government refers IT as ICT, and it is one of the key areas, in which the UAE government is highly focusing on the improvements. The government is making huge strides in the public sector to achieve its goals of being at the forefront.

The Brazil market dominated the LAMEA Recommendation Engine Market by Country 2020, and would continue to be a dominant market till 2027; thereby, achieving a market value of $227.4 million by 2027. The Argentina market is expected to witness a CAGR of 38.2% during (2021 - 2027). Additionally, The UAE market is expected to witness a CAGR of 37.1% during (2021 - 2027).

Based on Type, the market is segmented into Collaborative Filtering, Content-based Filtering and Hybrid Recommendation. Based on Application, the market is segmented into Personalized Campaigns & Customer Delivery, Product Planning & Proactive Asset Management and Strategy Operations & Planning. Based on Deployment Type, the market is segmented into Cloud and On-premise. Based on Organization Size, the market is segmented into Large Enterprises and Small & Medium Enterprises. Based on End Use, the market is segmented into Retail, BFSI, Healthcare, Media & Entertainment, Information Technology and Others. Based on countries, the market is segmented into Brazil, Argentina, UAE, Saudi Arabia, South Africa, Nigeria, and Rest of LAMEA.

Free Valuable Insights: The Global Recommendation Engine Market is Predict to reach $11.4 Billion by 2027, at a CAGR of 32.5%

The market research report covers the analysis of key stake holders of the market. Key companies profiled in the report include IBM Corporation, Oracle Corporation, Microsoft Corporation, SAP SE, Salesforce.com, Inc., Adobe, Inc., Google LLC, Intel Corporation, Hewlett-Packard Enterprise Company, and 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 Country

  • Brazil
  • Argentina
  • UAE
  • Saudi Arabia
  • South Africa
  • Nigeria
  • Rest of LAMEA

Key Market Players

List of Companies Profiled in the Report:

  • IBM Corporation
  • Oracle Corporation
  • Microsoft Corporation
  • SAP SE
  • Salesforce.com, Inc.
  • Adobe, Inc.
  • Google LLC
  • Intel Corporation
  • Hewlett-Packard Enterprise Company
  • Amazon.com, Inc.
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