Predictive Analytics Market Size, Industry Analysis Report, Regional Outlook, Application Development Potential, Price Trends, Competitive Market Share & Forecast, 2020 - 2026
Report ID: GMI1731
Predictive Analytics Market size is anticipated to witness growth over the forecast timeline owing to the emergence of e-commerce and the growing data traffic. Increasing demand for mobility and accessibility of cloud-based solutions coupled with the transformation from traditional business intelligence (BI) methods to help achieve high and advanced analytical techniques is offering several growth opportunities to the predictive analytics market.
The predictive analytics technology is being utilized by several businesses as a useful tool for reducing risks associated with fraudulent claims and for surging marketing efficiency. It is mainly used by organizations to increase their bottom line and competitive advantage. The presence of interactive and easy-to-use software, availability of faster & cheaper computers, and rising adoption of innovative technologies are contributing to the growth of the predictive analytics market. In addition, increasing volumes, data types, and the extraction of valuable insights by analyzing current data to help make predictions of future opportunities and trends is expected to fuel the industry growth.
Increasing adoption of cloud-based technologies in various sectors such as BFSI and IT and telecom due to the presence of high volume data is providing high growth opportunities for the predictive analytics market. In addition, in the BFSI sector, predictive analytics provides insight to approach each client by analyzing buying patterns, consumer behavior, and social media interaction and offers insights into channels to help connect with those customers. Wide applications of predictive analytics market in SMEs and SMBs is offering outstanding growth opportunities. Rise in fraudulent activities along with the need of improvising operational efficiency is expected to escalate the demand for predictive analytics market. Factors such as high time consumption, the requirement of continuous trail, and testing of the complex algorithm might hinder the industry growth.
The predictive analytics market can be segmented based on software solution, deployment model, application, and end use. On the basis of the software solution, the market can be classified into data mining & management, customer intelligence, performance management, financial intelligence, fraud and security intelligence, and decision support systems. In data mining & management, predictive analytics market helps by offering a record of the past data which can be analyzed to determine what customers are most likely to renew or purchase. Precise data mining and predictive modeling can shorten the target customers and allow the organization to tailor its advertisements to each online customer, which ensures the marketing team to form multiple advertisements based on the previous search history of the visitors. These factors are expected to boost the data mining & management segment growth in the predictive analytics market over the forecast timeline.
The financial intelligence segment is anticipated to show a steady growth in the predictive analytics market over the future. It is helpful for understanding the patterns of individuals in committing crimes. Pattern discovery is necessary to look for intricacies of fraudulent activities. Automatic elimination of the noise surrounding the actionable insight associated with the credit card transaction data and pattern detection enables the analysts to avoid certain activity and help monitor the suspicious data patterns.
Based on application segment, the predictive analytics market can be classified into risk management, networking management, sales and marketing management, human resource management, operations management, and supply chain management. In the risk management, the software can obtain potential areas of risk from the substantial number of data points collected by the organizations and going through them to detect risk and trends in the data which can influence the businesses. On implementation of these analytics solutions, organizations can quantify risk-related issues, evaluate, and formulate a course of action to reduce the risk factors.
End users in the predictive analytics market are in the BFSI, IT & telecom, energy, manufacturing, government & public, transportation & logistics, healthcare, travel, and hospitality sectors. In the BFSI sector, predictive analytics has several growth potentials owing to the enormous repositories of customer profiles and transactional data. In the IT and telecom sector, the predictive analytics market is anticipated to be the must-have technology owing to the complexity inherent in modern day cloud architectures along with the interrelations among architecture components.
The U.S. is anticipated to dominate the predictive analytics market owing to the high adoption rate of cloud computing and several latest technologies. Technological advancements and massive data surge often faced by the organizations along with the growing demand for structured data are expected to drive the predictive analytics market in the region. Rising demand for prediction of consumer behavior and trends offer significant growth opportunities for the industry.
In the Asia Pacific region, predictive analytics market is expected to grow fast owing to the rapid developments in the economies such as China, India, and Japan. The need to provide real-time data analysis is contributing to the growth of the industry in the region. In addition, predictive analytics market has a huge growth potential due to the high adoption and implementation of the technology in various sectors such as BFSI, IT and telecommunications, and SMBs.
The key players in the predictive analytics market include IBM Corporation, SAP, Microsoft Corporation, SAS Institute, Oracle, Dell, FICO, Tibco Software, Alteryx, and RapidMiner. Considering the latest developments in the industry, organizations are eyeing on easier ways to bridge the data gap and inclining more toward more streamlined cloud platforms to boost the time to insights along with shrinking the barrier between internal and external data. IBM is offering several products under its predictive analytics portfolio –SPSS Modeler, SPSS Analytical Server, Analytical Decision Management, SPSS Data Collection, SPSS Statistics, SPSS Predictive Analytics Enterprise, and Social Media Analytics.
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