Top 25 Companies in the Predictive Analytics Market & Report (2025–2035): Key Insights & Innovations
RELEASE DATE: Aug 2025 Author: Spherical InsightsRequest Free Sample Speak to Analyst
Description
According to a research report published by Spherical Insights & Consulting, The Global Predictive Analytics Market Size is projected to Grow from USD 18.75 Billion in 2024 to USD 285.50 Billion by 2035, at a CAGR of 28.09% during the forecast period 2025–2035. The market for predictive analytics is driven by the exponential growth of data generated through various channels, such as IoT and digital platforms. The emergence of advanced analytical tools for deriving actionable insights enables an organization to make informed decisions.
Introduction
Predictive analytics is the branch of advanced analytics that includes the use of statistics and modeling techniques to forecast future outcomes by using historical data with statistical modeling. The model exploits patterns found in historical and transactional data to identify risks and opportunities, capturing relationships among many factors to allow assessment of risk or potential associated with a particular set of conditions, guiding decision-making for candidate transactions. Internet retailers use predictive analytics to fine-tune purchase recommendations to their users and increase sales. Predictive analytics is a crucial tool for organizations aiming to make predictive models for efficient data-driven decisions. With cloud computing providing scalable resources, businesses can harness predictive analytics to gain a competitive edge and navigate the evolving digital landscape. Furthermore, the adoption of AI and machine learning technologies is increasing as companies drive the need for improving their analytical capabilities.
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Predictive Analytics Market Size & Statistics
The Market Size for Predictive Analytics Was Estimated to be worth USD 18.75 Billion in 2024.
The Market Size is Going to Expand at a CAGR of 28.09% between 2025 and 2035.
The Global Predictive Analytics Market Size is anticipated to reach USD 285.50 Billion by 2035.
North America is expected to generate the highest demand during the forecast period in the predictive analytics Market
Asia Pacific is expected to grow the fastest during the forecast period in the predictive analytics Market.
Regional growth and demand
Asia Pacific is expected to grow the fastest during the forecast period in the predictive analytics market. The market for predictive analytics is growing in Asia Pacific due to an increase in data generation with the proliferation of digital technologies and the adoption of smartphones and IoT devices. In the Asia Pacific region, SMEs are recognizing the benefits of using predictive analytics solutions for enhancing product offerings for clients, which is bolstering the market growth.
North America is expected to generate the highest demand during the forecast period in the Predictive Analytics market. The predictive analytics market with the quickest rate of growth throughout the study period is anticipated to be in Asia Pacific. The regions’ advanced technological infrastructure and a growing focus on data-driven decision-making across various sectors, including healthcare, finance, and retail companies, are propelling the market growth of predictive analytics. Consequently, the market is anticipated to increase steadily in the region throughout the course of the forecast period.
Top 5 trends in the Predictive Analytics Market
- Quantum computing
- Real-time Predictive Analytics
- AI-driven Predictive Models
- Customer Experience Precognition
- Automation of forecasting capabilities
1. Quantum computing
Predictive analytics powered by quantum computing provides more insightful consumer behavior predictions. Researchers can analyze vast datasets, uncovering patterns and trends that were previously difficult to identify. Quantum-inspired algorithms have shown significant promise in analytics, offering a new approach to solving complex problems by leveraging the principles of quantum mechanics, like superposition and entanglement, to explore an exponentially large solution space more efficiently.
2. Real-time Predictive Analytics
Real-time analytics is often used in applications where the timeliness of the data is critical, like personalized advertisements or offers, smart pricing, or predictive maintenance. It is built on the foundational capability of data streaming. With the use of the right tools and technologies, organizations can harness the power of real-time analytics to gain a competitive edge and drive business success.
3. AI-driven Predictive Models
AI in predictive analytics is proving to be a lifeline, transforming mountains of past data into actionable predictions. The technology harnesses AI in predictive analytics to predict trends, customer behavior, and risks with unmatched precision. AI-driven predictive models can forecast things such as customer churn, demand spikes, or equipment failures with impressive accuracy. AI-driven predictive analytics enables businesses to run smarter, serve customers more effectively, minimize risk, and make more informed decisions with real use cases, measurable impact, and implementation strategies.
4. Customer Experience Precognition
Predictive analysis is a powerful tool that uses data and delivers personalized results to users. A business can create personalized marketing campaigns, addressing potential issues, and offering customized product recommendations. Businesses can gain valuable insights into customer behavior, preferences, and potential issues, allowing them to predict and proactively address customer needs through predictive customer analytics.
5. Automation of forecasting capabilities
Automation has emerged as a transformative combination of solutions, offering potential for revolutionizing the forecasting process. With AI-driven automation, the forecasting process transcends traditional boundaries, introducing a level of precision, speed, and adaptability that was considered beyond reach.
Empower your strategic planning:
Stay informed with the latest industry insights and market trends to identify new opportunities and drive growth in the predictive analytics market. To explore more in-depth trends, insights, and forecasts, please refer to our detailed report.
Top 25 Companies Leading the Predictive Analytics Market
- SAS Institute Inc.
- IBM Corporation
- SAP SE
- Oracle
- Microsoft
- Salesforce, Inc.
- Alteryx
- Altair Engineering Inc.
- Cloud Software Group, Inc.
- QlikTech International AB
- TIBCO Software Inc.
- Amazon Web Services, Inc.
- Cloudera, Inc.
- FICO
- Accenture
- AVEVA Group Plc.
- Teradata Japan, Ltd.
- ONTROX Co., Ltd.
- Emotion Intelligence
- Tibidabo.tech
- Gigalogy
- Data Viz Lab
- edison.ai
- General Electric Company
- Siemens AG
1. SAS Institute Inc.
Headquarters: Cary, North Carolina, United States
SAS Institute Inc. is the provider of analytics, business intelligence, and data management services intended to help access, manage, analyze, and report on data to aid in decision-making. The company’s offerings include advanced analytics solutions, artificial intelligence, machine learning, cloud, data management, decisioning, fraud, and security intelligence.
2. IBM Corporation
Headquarters: Armonk, New York, United States
IBM Corporation is one of the oldest technology companies in the world, providing software, IT consulting services, and hardware to help business customers modernize their technology workflows. IBM operates in 175 countries and employs approximately 300,000 people. The company has a robust roster of business partners to service its clients, which includes 95% of all Fortune 500 companies.
3. SAP SE
Headquarters: Walldorf, Germany
SAP SE is a multinational software company, developing business software, such as e-business and enterprise management software, consulting on organizational usage of its applications software, and providing training services. SAP predictive analytics solutions enable building predictive models to discover hidden insights and relationships in the data, from which predictions are made about future events.
4. Oracle
Headquarters: Austin, Texas, USA
Oracle is a cloud technology company that provides organizations around the world with computing infrastructure and software to help them innovate. Oracle Analytics predictive models use several embedded Oracle Machine Learning algorithms to mine datasets, predict a target value, or identify classes of records. Use the data flow editor to create, train, and apply predictive models to data. Oracle Analytics predictive model applies a specific algorithm to a dataset to predict values, predict classes, or identify groups in the data.
5. Microsoft
Headquarters: Redmond, Washington, United States
Microsoft Corp is a developer and provider of software products, services, and devices. Microsoft Fabric can play an essential role here by serving as a consolidated data and analytics platform. The tool streamlines data integration, management, and analysis for businesses. Essentially, it combines different tools and services from Microsoft Azure into one cohesive platform, offering an all-in-one solution.
Are you ready to discover more about the predictive analytics market?
The report provides an in-depth analysis of the leading companies operating in the global predictive analytics market. It includes a comparative assessment based on their product portfolios, business overviews, geographical footprint, strategic initiatives, market segment share, and SWOT analysis. Each company is profiled using a standardized format that includes:
Company Profiles
- SAS Institute Inc.
- Business Overview
- Company Snapshot
- Products Overview
- Company Market Share Analysis
- Company Coverage Portfolio
- Financial Analysis
- Recent Developments
- Merger and Acquisitions
- SWOT Analysis
- IBM Corporation
- SAP SE
- Oracle
- Microsoft
- Salesforce, Inc.
- Alteryx
- Altair Engineering Inc.
- Cloud Software Group, Inc.
- Others.
Conclusion
The predictive analytics market is driven by the widespread use of big data and other related technologies, along with the increasing use of predictive modeling tools. Companies are likely to increase their reliance on predictive analytics solutions through the integration of AI and machine learning into predictive models for more accurate forecasts and insights. With the growing prioritization of data-driven strategies, there is an increasing demand for real-time analysis and decision-making, encouraging businesses to invest in predictive analytics tools for providing timely insights.
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