The CJA Market has been proliferating. The market growth attributes to the rising adoption of journey analytics across the end-user industries to enhance customer experience & support. Enterprises across industries worldwide strive to gain actionable insights from large data sets, using AI to perform to solve business problems more effectively complex tasks.
Resultantly, implementations of cloud-based AI-enabled data platforms to help and support customers throughout the entire customer journey are rising continually. Besides, the accelerating digital transformation in businesses boosts the demand for the open, cloud-based platform. Moreover, the increasing adoption of customer journey analytics software in various organizations to advance their digital adoption and far-reaching business impact escalate market growth.
According to Market Research Future (MRFR), the global customer journey analytics (CJA) market is projected to reach USD 14.92 BN by 2023, growing at 20% CAGR throughout the forecast period (2018 – 2023). Rising business needs to build rich data sets, optimize machine learning at scale, and streamline workflows across teams substantiate market growth. Also, the pressure to reduce infrastructure complexity and deliver superior customer experiences positively impacts market growth.
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Additionally, the increasing numbers of enterprises worldwide and developments in analytics software led by advances in AI and machine learning technology accelerate market growth. The integration of smart data discovery capabilities, machine learning, and automation in the entire analytics workflow have led to increasing the market size. Furthermore, increasing investments to develop data analytics tools that can support business needs fosters the market’s growth.
Conversely, the complexity of data synchronization, lack of awareness about journey analytics, and reluctance in its adoption are major factors projected to impede the market growth. Nevertheless, the increase in adoption of analytics platform for cloud deployment would support the growth of the market throughout the forecast period.
Global Customer Journey Analytics Market –Segments
The report is segmented into six dynamics;
By Interaction Type: Web, Social Media, Mobile, Email, Branch/Store, Call Center, and others (surveys, promotional events, and sales representatives).
By Deployment Model: On-Premises and Cloud.
By Organization Size: Small & Medium-Sized Enterprises (SMEs) and Large Enterprises.
By Application: Customer Journey Mapping & Visualization, Customer Behavioral Analysis, Customer Attrition Analysis, Campaign Management, Brand Management, Product Management, and others (customer process management).
By End-User: Banking, Financial Services, and Insurance (BFSI), Retail & eCommerce, Government & Defense, Healthcare, Telecommunications & IT, Media & Entertainment, Travel & Hospitality, Automotive & Transportation, and others (Education, Real Estate, others).
By Regions: Asia Pacific, Americas, Europe, and the Rest-of-the-World.
Global Customer Journey Analytics Market – Geographical Analysis
North America dominates the global customer journey analytics market. The largest market share attributes to the increasing demand for customer journey analytics led by the growing awareness for cloud-based deployment benefits like cost-effectiveness and easy availability. Besides, high technology adoption in the IT industry and other industries like healthcare, retail, and entertainment in the region substantiate the growth of the market.
The increasing digitization of customer journey processes and the presence of several key players, mainly in the US, are the major market growth drivers in the region. The US accounts for the largest share in the regional market due to the vast technological advances.
Europe stands second in the global customer journey analytics market. Market growth is driven by the rapid and constant technological advancements and enormous investments in customer churn analysis development. Additionally, the evolving digital technology and increasing demand for analytics software from the retail & consumer goods industry to enhance customer experience influence the market growth.
The Asia Pacific customer journey analytics market is growing promisingly. Factors such as the increasing industrialization and new data centers in emerging countries like India and Japan accelerate the regional market growth. Increasing numbers of enterprises and massive advances in related technologies such as natural language processing and machine learning drive the regional market’s growth.
The growing adoption of smartphones and data-driven customer journey analytics software foster market demand. Developing countries such as Japan, China, and India lead the regional market. Furthermore, increasing analytics software expertise, artificial intelligence technology propels the journey analytics market in the region.
Global Customer Journey Analytics Market – Competitive Analysis
Fiercely competitive, the customer journey analytics market appears fragmented with the presence of many key players. To gain a larger competitive share, these players incorporate strategic initiatives such as mergers & acquisitions, collaboration, expansion, and technology launch. Major players in the market are committed to delivering reliable, leading-edge solutions and services. They make substantial R&D investments in developing unique solutions entirely on a different level compared to their competition.
Players leading in the global customer journey analytics market include Adobe Systems, Acxiom, Salesforce, Nice Systems, IBM, Verint Systems, Pointillist, SAP, Clickfox, and Quadient.
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December 01, 2020 —- Mindtree Limited (India), a leading digital transformation and technology services company, announced its partnership with a US-based data and AI company Databricks, to help customers implement cloud-based data platforms for advanced analytics. This service would support the use of the Databricks platform from implementation throughout the entire customer journey. Collaboration enables the seamless implementation of self-service analytics to improve data-driven decision-making.
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