Recommendation Engine Market Expected to Reach $43.8 Billion by 2031—Allied Market Research

According to a new report published by Allied Market Research, titled, “Recommendation Engine Market," The recommendation engine market was valued at $2.7 billion in 2021, and is estimated to reach $43.8 billion by 2031, growing at a CAGR of 32.1% from 2022 to 2031.

Recommendation engines are also called as recommenders are win to win features for both customers and the businesses that deploy them. Customers enjoy the level of personalization and assistance a well-tuned recommendation engine provides. Moreover, businesses build them because they fuel engagement and encourage sales. Furthermore, recommendation engines are advanced data filtering systems that use behavioral data, computer learning, and statistical modeling to predict the content, product, or services customers will like 

Furthermore, growing adoption of digital technologies and increase in focus enhance customer experience is boosting the growth of the global recommendation engine market. In addition, increase in use of the deep learning technology in AI recommendation engine solution is positively impacting growth of the recommendation engine market. However, lack of skills and expertise and concerns over accessing customers personal data is hampering 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 during the recommendation engine market forecast.  

Depending on enterprise size, the large enterprise segment holds the largest recommendation engine market share as large enterprises are adopting recommendation engine to make better decisions, efficiently manage their business portfolio, and gain a competitive edge in the global market. However, the SMEs segment is expected to grow at the highest rate during the forecast period, owing to increase need to find alternative solutions for saving marketing and advertising costs due to limited budgets is also boosting the demand for recommendation engines among small and medium organizations. 

Region-wise, the recommendation engine market size was dominated by North America in 2021, and is expected to retain its position during the forecast period, owing to, increase in use of cutting-edge technologies and rising government funding for new ones. However, Asia-Pacific is expected to witness significant growth during the forecast period, owing to growing technological adoption and economies such as India and China and cloud native countries like Japan. 

The recommendation engine market has witnessed stable growth during the COVID-19 pandemic, owing to adoption of digital technologies and various others solutions among organizations during the pandemic situation. In addition, the COVID-19 pandemic has resulted in changes in model performance, as more continuous monitoring and validation is required to mitigate various types of risks, compared to static validation and testing methods, which, in turn, drive the development of advanced machine learning models. In addition, with rapid digital transformation, various governments have introduced stringent regulations to protect end users' data such as General Data Protection Regulation (GDPR) and the California Consumer Privacy Act (CCPA). Thus, governments in various countries have taken strict actions toward the defaulters of COVID-19 regulations, and natural language processing technology is helps suppliers by using digital transformation to gain new consumers, communicate with existing customers, lower the cost of corporate operations, and boost employee enthusiasm. However, COVID-19 pandemic is making it even harder to keep pace, and even more difficult for mid-size and smaller companies to adopt AI/ML technologies, owing to long development timelines and high investment requirements. 

The integration of advanced technologies to build product recommendation chatbots with the help of machine learning (ML) and artificial intelligence (AI) algorithms helps the industries to improve various aspects of a company such as perception, reasoning, learning, and problem solving of the human mind for detecting and predicting risks, which, in turn, drives the growth of the market. For instance, 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, 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 launched AI recommendation engine for online retailers worldwide, including Asia. The cloud computing service's product discovery solutions for retail allowed retailers to implement search and recommendation capabilities that enhance customer engagement and improve conversions across their digital properties, which, in turn, is expected to provide lucrative opportunity for the growth of the recommendation engine industry. 

KEY FINDINGS OF THE STUDY 

• By type, the collaborative filtering segment accounted for the largest recommendation engine market share in 2021. 

• Region wise, North America generated highest revenue in 2021. 

• Depending on end user, the retail and consumer goods segment generated the highest revenue in 2021. 

The key players profiled in the recommendation engine market analysis are Adobe, Amazon Web Services, Google LLC, Hewlett Packard Enterprise Development LP, IBM Corporation, Intel Corporation, Microsoft Corporation, Oracle Corporation, Salesforce, Inc., and SAP SE. These players have adopted various strategies to increase their market penetration and strengthen their position in the recommendation engine industry.