The global recommendation engine market is driven by factors such as rise in adoption of digital technologies, increase in focus to enhance customer experience, and increase in use of the deep learning technology in AI recommendation engine solution.
PORTLAND, Ore., April 26, 2023 /PRNewswire/ -- Allied Market Research published a report, titled, "Recommendation Engine Market by Type (Collaborative Filtering, Content-based Filtering and Hybrid Recommendation), by Deployment Model (On-Premises and Cloud), by Enterprise Size (Large Enterprises and Small & Medium Enterprises), by Application (Product Planning, Strategy & Operations Planning, Proactive Asset Management and Others) by Industry Vertical (BFSI, Media & Entertainment, Transportation, Healthcare, Retail and Others): Global Opportunity Analysis and Industry Forecast, 2021-2031". According to the report, the global recommendation engine industry generated $2.7 billion in 2021, and is anticipated to generate $43.8 billion by 2031, witnessing a CAGR of 32.1% from 2022 to 2031.
Drivers, restraints, and opportunities-
The global recommendation engine market is driven by factors such as rise in adoption of digital technologies, increase in focus enhance customer experience, and increase in use of the deep learning technology in AI recommendation engine solution. However, lack of skills & expertise and concerns over accessing customers' personal data hamper the recommendation engine market growth. On the contrary, increase in demand to analyze large volume of data is expected to offer remunerative opportunities for expansion of the recommendation engine market during the forecast period.
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Report coverage & details:
Report Coverage | Details |
Forecast Period | 2022-2031 |
Base Year | 2021 |
Market Size in 2021 | $2.7 billion |
Market Size in 2031 | $43.8 billion |
CAGR | 32.1 % |
No. of Pages in Report | 339 |
Segments covered | type, deployment model, application, enterprise size, industry vertical, and region. |
Drivers | Rise in adoption of digital technologies Increase in focus enhance customer experience Increase in use of the deep learning technology in AI recommendation engine solution |
Opportunities | Increase in demand to analyze large volume of data |
Restraints | Lack of skills & expertise and concerns over accessing customers' personal data |
COVID-19 scenario-
- The COVID-19 pandemic had positively impacted the growth of the recommendation engine market, owing to increase in demand for digitization and the appearance of new e-commerce platforms.
- Moreover, with the increase in fear of getting infected, people were compelled to make the shift from physical stores to online shopping. This shift resulted in the growing demand for recommendation engine market.
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The collaborative filtering segment to retain its dominance by 2031-
By type, the collaborative filtering segment accounted for the highest share in 2021, garnering more than two-fifths of the global recommendation engine market revenue and is expected to maintain its lead in terms of revenue during the forecast period, owing to increase in demand for reliable recommendation engines from e-commerce platforms to enhance their customers' shopping experience by suggesting products based on their tastes and preferences. However, the hybrid recommendation segment would cite the fastest CAGR of 33.8 from 2022 to 2031, owing to surge in usage of hybrid systems to improve the effectiveness of end-user solutions.
The retail and consumer goods segment to rule the roost-
By industry vertical, the retail and consumer goods segment held the major share in 2021, generating more than one-fourth of the global recommendation engine market revenue and is expected to maintain its lead in terms of revenue during the forecast period, as it is used to identify customer behavior patterns in order to improve customer service and marketing strategies. The BFSI segment, on the other hand, would portray the fastest CAGR of 35.3% from 2022 to 2031, owing to increase in technological innovations and the need to secure online consumer data and activities.
The personalized campaigns and customer delivery segment to dominate by 2031-
By application, the personalized campaigns and customer delivery segment accounted for more than two-fifths of the global recommendation engine market revenue in 2021 and is expected to maintain its lead in terms of revenue during the forecast period. The product planning and proactive asset management segment would also portray the fastest CAGR of 34.6% from 2022 to 2031, as it provides more accurate recommendations to users, which has led to an increase in their adoption this can help a business to identify areas of improvement, develop better strategies and operational plans, and better target customers.
North America garnered the major share in 2021 -
By region, North America generated nearly two-fifths of the global recommendation engine market revenue in 2021, and is expected to dominate by 2031. The growth of the market across North America is driven by various factors such as the increase in adoption of advanced technologies and increase in government support for emerging technologies in the region. However, Asia-Pacific would showcase the fastest CAGR of 34.6% from 2022 to 2031. The marker growth across Asia-Pacific is driven by increase in penetration of e-commerce, an upsurge in online shopping transactions, and an upsurge in the number of Over the Top (OTT) service providers.
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Key players in the industry-
- Adobe
- Amazon Web Services
- Google LLC
- Hewlett Packard Enterprise Development LP
- IBM Corporation
- Intel Corporation
- Microsoft Corporation
- Oracle Corporation
- Salesforce Inc
- SAP SE
The report analyzes these key players in the global recommendation engine market. These players have adopted various strategies such as expansion, new product launches, partnerships, and others to increase their market penetration and strengthen their position in the industry. The report is helpful in determining the business performance, operating segments, developments, and product portfolios of every market player.
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