-- Using predictive analytics, organizations can gain insights through the data collected from social media platforms. Organizations use this data to study consumer behavior and collect the views of consumers on new product launches.
The Complete Report Global Predictive Analytics Market: Research Report 2015-2019 spreads across 65 pages and provides 22 Exhibits to support the research is available at http://www.sandlerresearch.org/global-predictive-analytics-market-research-report-2015-2019.html
The following companies are the key players in the Global Predictive Analytics Market: IBM, Oracle, SAP, and SAS.
Other Prominent Vendors in the market are: Accretive Technologies, Angoss Software, HP, Information Builders, Megaputer Intelligence, Microsoft, Microstrategy, Pegasystems, Pitney Bowes, Revolution Analytics, StatSoft, Tableau Software, Teradata, and TIBCO Software.
According to the report, increasing customer demand and pricing pressure has led to intense competition in the global business environment, thus prompting enterprises to gain visibility of business operations, such as supply chain and human resources, from the perspectives of enterprises and consumers.
Further, the report states that validating business data to support corporate decision-making is a key market challenge due to cost and time constraints.
Order a Single User License Copy of Global Predictive Analytics Market: Research Report 2015-2019 Report at http://www.sandlerresearch.org/purchase?rname=45589 for US $2500.
Predictive analytics helps to extract information from the existing data. It helps in understanding the pattern and predict the trend or future for the organization. It uses what-if scenarios to predict possible risks involved in the future. Predictive analytics also helps in the optimization of the marketing campaigns and understanding of the customer behaviour for increasing the end-user response and to reduce the churn.
Predictive analytics is segmented into:
• Risk management: Includes processes such as fraud detection, mortgage underwriting, credit scoring, clinical DSS and the development of new pharmaceuticals
• Marketing: Includes applications such as direct marketing, predictive modeling, customer retention, and predictive advertisement targeting
• Personalized services: Includes customized services
Global Predictive Analytics Market 2015-2019, has been prepared based on an in-depth market analysis with inputs from industry experts. The report covers the landscape of the market and its growth prospects in the coming years. The report also includes a discussion of the key vendors operating in this market. Browse complete table of content of the report at http://www.sandlerresearch.org/toc/global-predictive-analytics-market-research-report-2015-2019.html.
The report also describes the predictive analytics market into four types of application:
• Sales and marketing
• Fraud management
• Risk management
• Operations management
The report also describes the market segmentation by end-users:
• BFSI
• Manufacturing
• Communication
• Healthcare
• Retail
• Transportation
List of Exhibits
Exhibit 01: Product offerings
Exhibit 02: Predictive analytics workflow
Exhibit 03: Predictive analytics as part of business analytics model
Exhibit 04: Difference between BI and predictive analytics
Exhibit 05: Analytics overview
Exhibit 06: Global predictive analytics market 2014-2019 ($ billions)
Exhibit 07: Five forces analysis
Exhibit 08: Global predictive analytics market segmentation by application 2014
Exhibit 09: Global predictive analytics market segmentation by end-user 2014
Exhibit 10: Global predictive analytics market segmentation by region 2014
Exhibit 11: Global predictive analytics market segmentation by region 2014-2019 ($ millions)
Exhibit 12: Key leading countries
Exhibit 13: Impact of drivers
Exhibit 14: Impact of drivers and challenges
Exhibit 15: IBM: Business segmentation by revenue 2014
Exhibit 16: IBM: Business segmentation by revenue 2013 and 2014 ($ billions)
Exhibit 17: Oracle: Business segmentation by revenue 2014
Exhibit 18: Oracle: Business segmentation by revenue 2013 and 2014 ($ millions)
Exhibit 19: Oracle: Geographical segmentation by revenue 2014
Exhibit 20: SAP: Business segmentation by revenue 2014
Exhibit 21: SAP: Business segmentation by revenue 2013 and 2014 ($ billions)
Exhibit 22: SAP: Geographical segmentation by revenue 2014
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