Top 10 Predictive Analytics Companies in 2024

Companies	Employees	HQ location	Revenue	Website	Industry
Iqvia	View 68,529 employees	🇺🇸 United States, North Carolina, Durham	$ 500-1000M	iqvia.com	Health Care, Data and Analytics, Artificial Intelligence, Software, Science and Engineering, Biotechnology
SAS	View 22,888 employees	🇺🇸 United States, North Carolina, Cary	$ 500-1000M	sas.com	Artificial Intelligence, Data and Analytics, Software, Science and Engineering, Information Technology
Exl	View 29,120 employees	🇺🇸 United States, New Jersey, West New York	$ 500-1000M	exlservice.com	Data and Analytics, Information Technology, Software, Artificial Intelligence, Professional Services, Apps
Datamatics	View 5,863 employees	🇺🇸 United States, New Jersey, Edison	$ 500-1000M	datamatics.com	Data and Analytics, Information Technology, Software, Artificial Intelligence, Science and Engineering, Hardware, Professional Services
[24]7.ai	View 6,510 employees	🇺🇸 United States, California, San Jose	$ 500-1000M	247.ai	Artificial Intelligence, Data and Analytics, Information Technology, Science and Engineering, Software, Professional Services
American Cybersystems	View 1,282 employees	🇺🇸 United States, Georgia, Duluth	$ 500-1000M	acsicorp.com	Data and Analytics, Information Technology, Software, Artificial Intelligence, Science and Engineering, Professional Services, Apps
RxDataScience	View 12 employees	🇺🇸 United States, North Carolina, Durham	$ 500-1000M	rxdatascience.com	Data and Analytics, Software, Artificial Intelligence, Information Technology, Science and Engineering, Professional Services, Health Care, Design, Biotechnology
Dynata	View 4,373 employees	🇺🇸 United States, Connecticut, Shelton	$ 500-1000M	dynata.com	Data and Analytics, Information Technology, Software, Design, Artificial Intelligence
Freshworks	View 6,423 employees	🇺🇸 United States, California, San Mateo	$ 500-1000M	freshworks.com	Artificial Intelligence, Data and Analytics, Information Technology, Science and Engineering, Software, Hardware
SenseTime	View 1,316 employees	, Science Park	$ 500-1000M	sensetime.com	Artificial Intelligence, Data and Analytics, Science and Engineering, Software, Hardware, Information Technology, Design

1. Iqvia

Iqvia is a prominent player in the field of predictive analytics, specializing in the healthcare and life sciences industries. By leveraging big data and advanced analytics, Iqvia provides insights that help pharmaceutical companies, healthcare providers, and researchers predict market trends, improve patient outcomes, and enhance operational efficiency. Their cutting-edge solutions support the entire healthcare ecosystem in making data-driven decisions, thus accelerating the pace of innovation and optimizing the delivery of healthcare services globally.

Location 🇺🇸 United States, North Carolina, Durham	Size View 68,529 employees
Revenue $ 500-1000M	Industries Health Care, Data and Analytics, Artificial Intelligence, Software, Science and Engineering, Biotechnology
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2. SAS

SAS Institute Inc. is a leader in the predictive analytics space, renowned for its advanced analytics software and solutions that enable businesses to make data-driven decisions. With a stronghold in mining, refining, and deploying data, SAS helps companies anticipate customer needs, streamline operations, and mitigate risks. Their comprehensive suite of software offers tools for statistical analysis, predictive modeling, and data visualization, aiding industries ranging from healthcare to finance in optimizing their operations and enhancing their strategic initiatives. SAS’s commitment to innovation and customer success positions it as an indispensable ally in the analytics realm.

Location 🇺🇸 United States, North Carolina, Cary	Size View 22,888 employees
Revenue $ 500-1000M	Industries Artificial Intelligence, Data and Analytics, Software, Science and Engineering, Information Technology
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3. Exl

EXL is a leading operations management and analytics company that specializes in predictive analytics, helping businesses harness the power of data to forecast trends and make informed decisions. By integrating advanced analytics, AI, and data-driven insights, EXL enables companies across industries such as insurance, healthcare, banking, and travel to optimize processes, mitigate risks, and enhance operational efficiency. Their deep expertise in analytics and committed approach to solving complex business challenges position EXL as a pivotal partner for companies aiming to transform data into a strategic asset.

Location 🇺🇸 United States, New Jersey, West New York	Size View 29,120 employees
Revenue $ 500-1000M	Industries Data and Analytics, Information Technology, Software, Artificial Intelligence, Professional Services, Apps
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4. Datamatics

Datamatics is a prominent player in the field of predictive analytics, specializing in leveraging data to forecast trends and behaviors across various industries. By harnessing advanced algorithms and machine learning techniques, Datamatics transforms vast amounts of data into actionable insights, empowering businesses to make data-driven decisions. This capability enables organizations to optimize operations, enhance customer engagement, and mitigate risks, giving them a competitive edge in rapidly changing markets. Datamatics’ integration of technology and expertise makes it an essential partner for enterprises aiming to thrive in an increasingly data-centric world.

Location 🇺🇸 United States, New Jersey, Edison	Size View 5,863 employees
Revenue $ 500-1000M	Industries Data and Analytics, Information Technology, Software, Artificial Intelligence, Science and Engineering, Hardware, Professional Services
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5. [24]7.ai

[24]7.ai stands out as a trailblazer in leveraging predictive analytics to enhance customer engagement across various sectors. This innovative firm harnesses sophisticated artificial intelligence to analyze customer behavior patterns, enabling businesses to deliver personalized, contextually relevant interactions at just the right moment. Through their cutting-edge technology, [24]7.ai helps companies increase customer satisfaction, boost conversion rates, and streamline operations, making it an invaluable partner for businesses aiming to thrive in a data-driven market.

Location 🇺🇸 United States, California, San Jose	Size View 6,510 employees
Revenue $ 500-1000M	Industries Artificial Intelligence, Data and Analytics, Information Technology, Science and Engineering, Software, Professional Services
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6. American Cybersystems

American Cybersystems (ACS) is a prominent player in the predictive analytics sector, offering advanced solutions that empower businesses to anticipate market trends and customer behaviors. By harnessing complex algorithms and data analysis techniques, ACS aids companies across various industries in making data-driven decisions that enhance operational efficiency and drive growth. Their robust analytics tools not only identify future opportunities but also mitigate risks, positioning ACS as an essential partner for organizations aiming to thrive in dynamic market conditions.

Location 🇺🇸 United States, Georgia, Duluth	Size View 1,282 employees
Revenue $ 500-1000M	Industries Data and Analytics, Information Technology, Software, Artificial Intelligence, Science and Engineering, Professional Services, Apps
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7. RxDataScience

RxDataScience is a pioneering firm in the realm of predictive analytics, focusing on delivering advanced data science solutions to the healthcare industry. By leveraging big data and machine learning, RxDataScience helps healthcare organizations optimize patient outcomes, enhance operational efficiency, and drive innovation. Their comprehensive suite of analytics tools and platforms empowers healthcare providers, pharmaceutical companies, and biotech firms to make informed, data-driven decisions, effectively transforming the landscape of healthcare through predictive insights and actionable intelligence.

Location 🇺🇸 United States, North Carolina, Durham	Size View 12 employees
Revenue $ 500-1000M	Industries Data and Analytics, Software, Artificial Intelligence, Information Technology, Science and Engineering, Professional Services, Health Care, Design, Biotechnology
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8. Dynata

Dynata is a global leader in first-party data and analytics, specializing in predictive analytics that empower businesses to make informed decisions. By harnessing a vast dataset collected from millions of consumers worldwide, Dynata provides unparalleled insights that help companies anticipate market trends, consumer behavior, and industry shifts. Their expertise in data collection, coupled with advanced analytical tools, allows clients to optimize marketing strategies, enhance customer engagement, and drive sustainable growth. Dynata’s robust approach to predictive analytics makes them a vital partner for businesses looking to thrive in a data-driven economy.

Location 🇺🇸 United States, Connecticut, Shelton	Size View 4,373 employees
Revenue $ 500-1000M	Industries Data and Analytics, Information Technology, Software, Design, Artificial Intelligence
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9. Freshworks

Freshworks, a dynamic player in the customer engagement software sector, excels in leveraging predictive analytics to drive sophisticated solutions. By integrating AI and machine learning, Freshworks enhances customer support, sales automation, and marketing processes. Their predictive analytics tools empower businesses to anticipate customer needs, personalize interactions, and streamline operations, leading to improved customer satisfaction and business efficiency. Freshworks’ commitment to innovation positions them as a pivotal resource for companies aiming to excel in customer relationship management and operational intelligence.

Location 🇺🇸 United States, California, San Mateo	Size View 6,423 employees
Revenue $ 500-1000M	Industries Artificial Intelligence, Data and Analytics, Information Technology, Science and Engineering, Software, Hardware
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10. SenseTime

SenseTime is a global leader in artificial intelligence and predictive analytics, specializing in advanced AI algorithms that power facial recognition, autonomous driving, and smart city technologies. Their cutting-edge solutions in predictive analytics particularly enhance decision-making processes by analyzing data patterns to forecast future outcomes, benefiting industries ranging from retail to healthcare. With a strong commitment to innovation, SenseTime is instrumental in driving digital transformation efforts for businesses seeking to harness the potential of AI for improved efficiency and strategic growth.

Location , Science Park	Size View 1,316 employees
Revenue $ 500-1000M	Industries Artificial Intelligence, Data and Analytics, Science and Engineering, Software, Hardware, Information Technology, Design
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Things to Consider When Prospecting into Predictive Analytics Companies

Common Pain Points and Challenges for Companies in Predictive Analytics

Integration Complexity

Integrating predictive analytics into existing systems can be daunting due to differences in technologies and the complexity of data structures.

Compatibility issues between new analytic tools and legacy systems.
High initial tech infrastructure costs.
Requirement for skilled personnel to manage integration.

Sales Insight: As you approach potential clients, emphasize your understanding of these integration challenges. Offer clear examples of how your solutions minimize disruption and align with existing technologies. Sharing stories of successful integrations can instill confidence and demonstrate your expertise.

Data Quality and Collection

Effective predictive analytics requires high-quality, relevant data, which can be a significant hurdle for many organizations.

Difficulty in collecting large volumes of data.
Challenges in ensuring data accuracy and cleanliness.
The need for continuous data updating and management.

Sales Insight: Highlight your solution’s capability to work with less-than-perfect data sets or enhance data quality. Demonstrating how your tool simplifies data collection or integrates data cleaning features can set you apart from competitors.

Skill Gaps

There is often a gap between the technical skills available and those required to effectively implement and utilize predictive analytics.

Scarcity of professionals skilled in advanced analytics.
The need for ongoing training and education.
Resistance to change from traditional decision-making to data-driven practices.

Sales Insight: Offer solutions that include user-friendly interfaces and are complemented by training services. Position your product as not just a tool, but a part of an ecosystem that enhances skill sets and eases the transition to analytics-driven processes.

Cost Concerns

The perceived high cost of predictive analytics tools can deter companies from adopting this technology.

High upfront investment in software and infrastructure.
Ongoing costs associated with software maintenance and upgrades.
Potential hidden costs in data collection and processing.

Sales Insight: In your discussions with prospective clients, focus on the long-term ROI of implementing predictive analytics. Explain how better forecasting can reduce costs and increase efficiency, providing examples and case studies where relevant.

Scaling Challenges

Businesses often struggle to scale their predictive analytics capabilities to keep up with growth, making it a critical area to address.

Difficulties in managing increasingly large datasets.
Challenges in maintaining performance levels as demand increases.
Need for modular solutions that grow with the company.

Sales Insight: Stress the scalability of your solutions, explaining how they can easily expand in functionality and capacity. Offering scalable solutions will reassure prospects that they can invest confidently, knowing the tool will grow with their business needs.

Privacy and Security Concerns

Handling sensitive data raises significant privacy and security concerns, crucial in industries like healthcare and finance.

Managing compliance with global data protection regulations.
Risk of data breaches and cyber-attacks.
Public sensitivity to data misuse.

Sales Insight: Clearly communicate how your solutions address these concerns. Providing details about compliance certifications, security features, and data handling policies will help build trust and address the anxiety surrounding data privacy issues.

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Key Decision-Makers and Influencers in Predictive Analytics

Key Departments

Data Science

Insight: This team drives the core function of predictive analytics firms. Data scientists seek solutions that offer advanced algorithms, high-speed data processing, and integrative features with existing data platforms. Their buying criteria heavily weigh on computational power and accuracy of insights.

IT & Systems Management

Insight: Responsible for the infrastructure that supports data analysis. IT leaders look for robust, scalable solutions that can handle complex data workloads without compromising security. Their focus is on interoperability, reliability, and security features.

Marketing

Insight: Uses predictive analytics to better understand customer behavior and optimize marketing strategies. Marketing professionals value tools that provide detailed consumer insights and enhance personalization and targeting capabilities.

Sales

Insight: Sales departments utilize predictive analytics to forecast sales trends and customer purchasing patterns. They prioritize tools that integrate seamlessly with CRM systems and provide actionable insights to drive sales strategies and performance.

Executive Management

Insight: Senior executives make strategic decisions based on predictive insights to steer the company direction. They consider tools that provide a clear competitive edge, are cost-effective, and have a proven ROI.

Risk Management

Insight: Focuses on identifying, analyzing, and mitigating risks using predictive analytics. These professionals need highly accurate and reliable tools that can forecast various risk scenarios and their potential impacts on the organization.

Seniority Level

Vice Presidents of Data Analytics or Business Intelligence

Insight: These executives are critical in shaping the company’s data strategy. They look for predictive analytics solutions that integrate seamlessly with existing IT infrastructure and provide scalable, actionable insights to drive decision-making processes.

Directors of Data Science

Insight: Directors are hands-on leaders who focus on the technological and practical applicability of predictive analytics solutions. They value tools that enhance data accuracy, speed, and analytical depth, facilitating better business decisions based on predictive models.

IT Managers

Insight: Tasked with the operational management of IT resources, IT Managers need predictive analytics tools that are reliable, secure, and easy to integrate with current systems. They prioritize solutions that require minimal downtime and offer substantial support and training.

Business Development Managers

Insight: Look for predictive analytics tools that can identify new business opportunities and optimize current operations. Their focus is on how these tools can directly influence revenue growth and market expansion.

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Buying Processes and Behaviors in Predictive Analytics

Long Decision-Making Cycles

Predictive Analytics solutions often involve considerable investments and impact multiple departments, leading to longer decision-making cycles.

Complexity of integrating new systems with existing IT infrastructure.
The need for extensive stakeholder buy-in across different departments.
Evaluation of long-term ROI versus initial costs.

How to leverage: Focus on nurturing relationships throughout the sales cycle. Provide detailed, clear information and case studies to help stakeholders understand the benefits and long-term gains from implementing predictive analytics solutions in their operations.

Focus on Customization

Companies in the Predictive Analytics space highly value customized solutions that can seamlessly integrate into their existing processes.

Each industry and company has unique data and specific analytic needs.
Customization ensures maximized effectiveness and efficiency in analytics.
Integrative solutions often require less training and adaptation period.

How to leverage: Highlight your product’s adaptability and how it can be tailored to meet specific business needs. Demonstrate your capability in understanding their industry’s unique challenges and provide examples of personalized implementations.

Security Concerns

Security is a paramount concern when purchasing predictive analytics tools, given the sensitivity of data involved.

Companies risk exposure of confidential data while integrating new analytics tools.
Regulatory compliance and data protection laws necessitate secure solutions.
Breaches or data theft can lead to significant financial and reputational damage.

How to leverage: Ensure your communication emphasizes strong security features of your solution. Provide clear, substantial evidence of compliance with industry standards and how your product protects their data above all else.

Demand for Scalability

The ability to scale solutions as the company grows is essential for firms investing in predictive analytics.

Businesses anticipate growth and require solutions that can expand accordingly.
Scalability ensures that investments are future-proof and adaptable.
Flexibility in handling increasing data volumes and complexity is crucial.

How to leverage: Discuss the scalability of your solutions, providing examples of how you have successfully scaled products for other clients. Focus on the ease of upgrading or expanding functionalities as their business needs grow.

Demonstrable ROI

Companies need to see a clear and measurable return on investment when adopting predictive analytics technologies.

Tangible benefits help justify the high costs associated with these technologies.
Executives and decision makers need solid evidence to push for adoption.
Demonstrable ROI assists in quicker stakeholder buy-in and approval.

How to leverage: Prepare case studies and gather data that explicitly demonstrates the ROI of your solutions. Tailor this information to reflect the potential benefits specifically for the prospect’s sector to make the case more compelling.

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Prospecting Tips for Selling to Predictive Analytics Companies

Showcase Technological Compatibility

Companies in predictive analytics prioritize technological advancement. Show how your solution seamlessly integrates with existing systems and enhances their current processes without causing disruptions.

Tip: Mention the technologies your product is compatible with and how easy it is to integrate with their current setups.

Stress on Data Security

Data is at the heart of predictive analytics. Stress the security measures of your product to assure potential clients that their data will be handled with the utmost care and protection.

Tip: Provide details about security certifications or compliance standards that your solution meets.

Display Scalability

Predictive analytics projects often start small and scale significantly. Emphasize the scalability of your solution, showing its potential to grow as their data needs expand.

Tip: Share case studies where your product has successfully scaled with client needs, maintaining performance and reliability.

Highlight Customization Capabilities

Each predictive analytics project has unique needs and challenges. Point out how your product or service can be customized to meet specific requirements.

Tip: Share examples of how you have tailored your solution for different use cases or industries to meet specialized needs.

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18,245

Want to see more Predictive Analytics companies?

Things to Consider When Prospecting into Predictive Analytics Companies

Common Pain Points and Challenges for Companies in Predictive Analytics

Cost Concerns

Scaling Challenges

Privacy and Security Concerns

Start finding new prospects that match your ICP

Key Decision-Makers and Influencers in Predictive Analytics

Key Departments

Seniority Level

Not joined surfe yet? Sign up to Surfe today

Buying Processes and Behaviors in Predictive Analytics

Demand for Scalability

Demonstrable ROI

Not joined Surfe yet? Get 20 free credits

Prospecting Tips for Selling to Predictive Analytics Companies

Need prospects?

Top 10 Predictive Analytics Companies — a guide for sales

Want to see more Predictive Analytics companies?

Things to Consider When Prospecting into Predictive Analytics Companies

Common Pain Points and Challenges for Companies in Predictive Analytics

Privacy and Security Concerns

Start finding new prospects that match your ICP

Key Decision-Makers and Influencers in Predictive Analytics

Key Departments

Seniority Level

Not joined surfe yet? Sign up to Surfe today

Buying Processes and Behaviors in Predictive Analytics

Not joined Surfe yet? Get 20 free credits

Prospecting Tips for Selling to Predictive Analytics Companies