Predictive Analytics Sector Booms: Report Unveils Key Players and Innovations

According to the report, the global predictive analytics industry was estimated at $7.32 billion in 2019, and is expected to hit $35.45 billion by 2027, registering a CAGR of 21.9% from 2020 to 2027.

Predictive analytics is the practice of using statistics and modeling techniques to extract information from current and historical datasets to predict potential future outcomes and trends. Predictive analytics uses various statistical techniques, including automated machine learning algorithms, data mining, deep learning, and AI, to generate predictive models, which extract information from datasets, identify patterns, and offer a predictive score for an array of organizational outcome.

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Factors such as rise in the adoption of Big Data analytics, increase in use of predictive modeling to deliver optimum performance, big data supporting initiatives taken by government across the world, and upsurge in spending on Big Data infrastructure are driving the growth of global predictive analytics market. Furthermore, the need to gain competitive advantage is boosting the growth of this market.

Based on industry vertical, the BFSI segment contributed to more than one-fifth of the global predictive analytics market revenue in 2019 and is projected to retain its dominance during the study period. This is attributed to high deployment of predictive analytics for risk management, fraud detection, customer management, customized solutions, and others. Simultaneously, the healthcare segment would manifest the fastest CAGR of 24.8% from 2020 to 2027. This is due to increase in use of predictive analytics for developing precision medicine, predicting virus spread, and managing the supply chain.

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Based on components, the solution segment accounted for nearly two-thirds of the global predictive analytics market share in 2019 and is expected to rule the roost by 2027. Increase in need to optimize marketing campaigns, improvement in operations to better manage inventory and other resources, and reduce business risks drive the growth of the segment. The services segment, on the other hand, would portray the fastest CAGR of 23.8% throughout the forecast period. This is due to its adoption to ensure effective functioning of software and platforms throughout the predictive analysis process.

Region-wise, the predictive analytics market size was dominated by North America in 2019. Factors such as major the presence of leading market vendors developing predictive analytics in North America and high spending on Big Data technology in this region are the major drivers for the predictive analytics market growth. In addition, the deployment of predictive analytics has increased in each stage of the retail process to predict market demands, understand customer behavior, and optimize pricing, which is anticipated to significantly contribute toward market growth.

The key players operating in the global predictive analytics industry include Alteryx, Inc., Fair Isaac Corporation, Information Builders, International Business Machines Corporation, KNIME, Microsoft Corporation, Oracle Corporation, SAP SE, SAS Institute Inc., and TIBCO Solution Inc. This study includes market trends, predictive analytics market analysis, and future estimations to determine the imminent investment pockets.

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The predictive analytics market has been experiencing substantial growth due to increasing data volumes, technological advancements, and the need for businesses to gain actionable insights from data. Here are some key trends and factors shaping the predictive analytics market:

1. Increasing Adoption Across Industries: Predictive analytics is being adopted across various industries such as retail, healthcare, finance, manufacturing, and others to improve decision-making processes, enhance operational efficiency, and gain competitive advantages.

2. Technological Advancements: Advancements in artificial intelligence (AI), machine learning (ML), and big data technologies are driving innovation in predictive analytics solutions. This includes the development of more sophisticated algorithms, predictive modeling techniques, and automated decision-making systems.

3. Big Data: The proliferation of big data is fueling the demand for predictive analytics solutions, as organizations seek to extract valuable insights from large and complex datasets. Predictive analytics helps businesses analyze historical data, identify patterns, and predict future outcomes.

4. Cloud-Based Solutions: The adoption of cloud-based predictive analytics solutions is increasing, as it offers scalability, flexibility, and cost-effectiveness. Cloud computing enables businesses to access predictive analytics tools and infrastructure without significant upfront investments in hardware and software.

5. Focus on Customer Analytics: Businesses are increasingly leveraging predictive analytics to understand customer behavior, preferences, and trends. By analyzing customer data, organizations can personalize marketing campaigns, improve customer satisfaction, and drive revenue growth.

6. Rise of Prescriptive Analytics: Prescriptive analytics, which goes beyond predicting future outcomes to recommending actions, is gaining traction. Organizations are using prescriptive analytics to optimize decision-making processes, automate decision workflows, and drive business outcomes.

7. Integration with Business Intelligence (BI) Tools: Predictive analytics solutions are being integrated with BI tools to provide comprehensive insights into business operations. This integration enables organizations to combine historical data analysis with real-time data visualization and reporting capabilities.

8. Focus on Risk Management and Fraud Detection: In industries such as banking, insurance, and cybersecurity, predictive analytics is being used for risk management and fraud detection. By analyzing historical data and identifying anomalies, organizations can mitigate risks and prevent fraudulent activities.

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