Predictive Analytics Market Report

Predictive Analytics Market Analysis, Market Size, Application Analysis, Regional Outlook, Competitive Strategies, And Segment Forecasts, 2015 To 2022

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  • Report ID: GVR1607
  • Format: Electronic (PDF)
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Massive data dependence and improved technological implementations are expected to drive the predictive analytics market over the forecast period. The importance for data and its analysis for estimating future scenario may offer sustainable competitive edge to end-users. The key drivers for the predictive analytics market growth are enhanced product usability, adoption of new technologies, massive data deluge, and newer levers of differentiator. In addition, database management, forecasting, data warehouses, data mining, CRM analytics, smart, logistics, decision-making process, data visualization in dashboards, and increasing demand of business having analytic capabilities are expected to drive predictive analytics market growth over the forecast period. However, time-consuming process of analysis and lack of awareness coupled with lack of qualified professionals may restrain market growth. The adoption of cloud technology and the application of predictive analytics in small and medium-sized businesses may offer significant growth opportunity for the market.

Techniques for implementing predictive analytics include regression techniques, machine learning techniques, mathematical techniques, regression modeling, neural nets, machine learning, genetic algorithms, text mining, decision trees, clustering, and data exploration techniques to extract insights from historical and present data. End-use of predictive analytics include analytical Customer Relationship Management (CRM), collection analytics, clinical decision support systems, direct marketing, customer retention, cross-sell, risk management, fraud detection, portfolio, product or economy-level prediction, underwriting, and credit scoring.

Predictive analytics finds application in verticals such as actuarial science, Banking and Financial Services, Insurance (BFSI), healthcare, government, retail, manufacturing, transportation & travel, it, entertainment, sports, and energy & utilities. Predictive analytics helps to manage the diversified applications across the above all verticals. In the manufacturing industry, predictive analytics may be used for equipment maintenance management, cross-selling and up-selling, and workforce management. In sports, predictive analytics may be used for betting analysis and equipment maintenance management. Healthcare industry may apply predictive analytics in governance, risk, and compliance management, chronic disease management, and billing & payment management. Energy & Utilities and Oil & Gas may implement predictive analytics in asset surveillance solution and demand planning and forecasting. Media and entertainment may use predictive analytics in financial and workforce management and pricing analytics. Telecom and IT industry may use predictive analytics in marketing, sales, and CRM by implementing churn, cross-sell and up-sell, and pricing optimization. Government segment may use predictive analytics for weather forecasts, natural calamities forecasts, and flight safety among others.

The North American region dominates the global predictive data analysis market due to technological advancements and a myriad of players especially in the U.S. Financial funding to new entrants from venture capitalists is expected to alleviate competition in market. Furthermore, innovations in predictive analytics techniques and methods are anticipated as key opportunity for the established players. The key players in the predictive analytics market include GraphLab Create, Statsoft, Oracle, FICO, Salford Systems, TIBCO, Oracle Advanced Analytics, IBM, RapidMiner, Angoss Predictive Analytics, TIMi Suite, Pervasive, Portrait, Revolution Analytics, SAS Predictive Analytics, Predixion, and SAP InfiniteInsight.

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