Top 14 Predictive Analytics Tools to Know

Turning datasets into roadmaps requires the right tools.

Written by Sunny Betz
A persons hands a round a crystal ball filled with data produced by predictive analytics tools.
Image: Shutterstock / Built In
UPDATED BY
Matthew Urwin | Jul 16, 2024

Running a business means crunching an endless flow of real-time data. Sales percentages, ROI growth, customer retention rates — these numbers can tell you a lot about where your company is at the present moment. But without organization, they won’t be able to tell you where you’re headed next. Predictive analytics tools can address this issue.

Predictive Analytics Tools to Know

  • Alteryx
  • RapidMiner
  • IBM SPSS
  • SAS Viya
  • H2O.ai 
  • Oracle Data Science

 

What Are Predictive Analytics Tools?

Predictive analytics is the process of turning datasets into forecasts and decisions. A subset of advanced analytics, it is a form of data science that uses current data points to forecast the likelihood of certain events and give company leaders a blueprint to follow. Predictive analytics tools can be used to anticipate the success of future products, reduce customer churn and nip fraud in the bud. Every company from clothing retailers to airplane manufacturers needs to be able to turn data into actionable insights in order to maintain longevity and stay competitive with their peers.

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Benefits of Using Predictive Analytics Tools 

But making predictions and pulling meaning from a constant stream of digits and statistics isn’t something any human can do alone. Luckily for everyone, there are tech tools available that can process even the largest data sets and help leaders make informed decisions about the future of their companies. 

 

Predictive Analytics Tools to Know

Bridge Legal

Bridge Legal equips law firms and legal professionals with a platform for analytics and reporting. Its solution features intelligent ROi forecasting, a tool that leverages predictive analytics to estimate a firm’s annual rate of return and optimize its investments.

Pricing: Contact company for pricing.

Key features: intelligent return-on-investment forcasting

Who should use it: Law firms and legal professionals

 

Scorability

Scorability’s SaaS platform connects athletes with college athletic programs, in an effort to make recruiting more efficient and transparent. Founded by parents of Division-1 athletes, the company uses algorithmic technology to optimize the recruitment process by pairing athletes with programs through a straightforward, data-driven approach. This platform aims to save time and money for coaches and athletes alike, by eliminating the guesswork and travel typically involved in collegiate recruiting.

  • Pricing: Contact company for pricing.
  • Key features: Verifies measurables and mentality data, matches athletes to program needs and predicts athlete success.
  • Who should use it: College coaches and athletics program recruiters looking to build their rosters with top-tier talent.

 

Alteryx

Alteryx is an end-to-end predictive analytics platform that incorporates machine learning principles to help clients easily build forecasting data models. Like other platforms on this list, Alteryx offers collaboration capabilities, but is also built so that users without a coding background can still access insights. The company also offers an analytics process automation platform so that users can unify all their data science and analytics operations in one central location, making monitoring and deployment more straightforward.

  • Pricing: Individual plans start at $5,195 per user. Contact company for enterprise pricing.
  • Key features: Automated processes; easy-to-use and low-code; centralizes data science and analytics operations. 
  • Who should use it: Companies looking for a tool that is advanced yet accessible to non-technical team members.

 

RapidMiner

RapidMiner (now part of Altair) is a data analytics and AI platform that supports predictive analytics with a low-code environment. This makes it simple to design, test and deploy machine learning models with predictive and prescriptive capabilities. The RapidMiner platform also automates the tedious process of cleaning and organizing data, saving data science teams and company executives time with automation.

  • Pricing: Contact company for pricing.
  • Key features: Low-code code environment; automated data cleaning; determines trends with real-time data and presents results in understandable data visualizations. 
  • Who should use it: Anyone of any coding skill level who wants to build predictive models and glean insights from them in a short amount of time.

 

IBM SPSS

IBM SPSS is a software suite that complements its advanced abilities with an interface that caters to both coders and non-coders. Users can get started with IBM SPSS Modeler, which leverages machine learning to automate tedious tasks, builds accurate data models and determines the perfect chart for visualizing data insights. Teams can then use IBM SPSS Statistics to glean insights from data and fine-tune their decision-making.

  • Pricing: Subscriptions start at $99 per month when paid annually. 
  • Key features: Machine learning automation; data visualization tools; platform for building data models. 
  • Who should use it: Companies looking to give their entire workforce the ability to build data models, visualize the results and take proactive measures based on their findings.

 

SAS Viya

SAS Viya provides clients with tools to turn large amounts of data into large-scale forecasts automatically with the help of AI technology. In addition to its predictive analytics services, SAS Viya also offers text mining and data visualization tools to help clients take full advantage of their available data, according to its website. Marketed specifically for enterprise usage, it does feature built-in security features to help protect sensitive enterprise data.

  • Pricing: Contact company for pricing.
  • Key features: AI technology that automates analytics tasks; data visualization and data mining tools; intuitive dashboard for building and deploying visual forecasts.  
  • Who should use it: Organizations looking for tools that are easy for technical and non-technical personnel to use and that streamline the process for building various data models.

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H2O.ai

H2O.ai is a cloud-based predictive analytics tool that uses AI and machine learning technology to help customers build scale data models and forecast future data trends. The platform can handle data prediction types like metric learning, time series forecasting, text classification and regression, according to its site. H2O.ai’s advantage is its open source model, which makes it a more flexible and scalable solution than other proprietary models. Its AI capabilities can also predict bias in datasets and give users the ability to control the parameters of their data analysis in case they want to hone in on specific small models.

  • Pricing: Free trial available. Contact company for pricing.
  • Key features: Open source provides flexibility; range of data prediction types; bias detection for datasets. 
  • Who should use it: Technical personnel who want tools that offer great customization and can perform more complex tasks.

 

Oracle Data Science

Oracle Data Science is a comprehensive data tracking tool that can be used to organize existing data and transform it into predictive models so companies can make informed strategic decisions. Since Oracle Data Science is included in Oracle’s product database, users can also access the company’s cloud and artificial intelligence tools as needed. In addition to constructing data models, Oracle Data Science users can also store datasets in the cloud for instant accessibility and synchronization across their organizations, according to the company’s site.

  • Pricing: Contact company for pricing.
  • Key features: Predictive models; datasets stored in cloud for convenience; open-source and works well with other open-source tools and frameworks.  
  • Who should use it: Technical personnel who are comfortable working with complex analytics tools and want to be able to tailor model-building processes to their needs.

 

Qlik 

Qlik offers a comprehensive analytics platform that speeds up data analyses by automating tasks with AI and machine learning. The platform is also equipped with natural language features, so users can build models by asking questions and view insights in real time after the platform centralizes data from a variety of sources. Teams can gather even more intel by integrating embedded analytics with platforms like Salesforce and Workday, enabling even employees with no coding experience to compile insights and convert them into polished reports.

  • Pricing: Standard analytics plan starts at $20 per month per user when billed annually. 
  • Key features: Machine learning- and AI-powered automation; natural language-generated data visuals; embedded analytics; automated and low-code reporting tools. 
  • Who should use it: Technical and non-technical personnel, especially in industries like sales, marketing, finance and HR. 

 

SAP Analytics Cloud

SAP Analytics Cloud is a business intelligence platform that informs business decisions with a range of predictive analytics features. With the platform’s tools, teams can easily build data visualizations, reports and dashboards. Companies can also run simulations and create forecasting models for further insights, adjusting their plans based on observations and any changes in long-term trends.

  • Pricing: $432 per year per user.
  • Key features: Data visualization, report and dashboard tools; simulation and forecasting capabilities; prebuilt packages that cater to companies in different industries. 
  • Who should use it: Businesses that want their entire organizations to be able to build data models, understand the results and make data-driven decisions. 

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TIBCO Statistica

TIBCO’s Spotfire platform is built with collaboration in mind, with workflow options that can be shared across multiple teams for heightened visibility. TIBCO doesn’t offer an open-source option, but can be scaled to take on both small and large datasets to generate different types of models, according to its website. The platform also offers IoT-focused capabilities that other platforms do not. It also is built with open-source functionalities to give clients access to a wider range of analytics functions.

  • Pricing: Plans starting at $25 monthly per user.
  • Key features: Open-source features; interactive visual analytics models; machine learning-powered automation; immediate insights from real-time data.  
  • Who should use it: Any business in search of a predictive analytics tool that all teams can feel comfortable using. 

 

Emcien

Adopted by Cisco, Dell, GM and other major companies, Emcien is a full-spectrum predictive analytics tool that can integrate with platforms like Tableau and Salesforce to build comprehensive data forecasts. Emcien can turn raw data into business predictions to help customers reduce churn and improve their customer retention initiatives, making it more of an ideal tool for marketing and retail clients. The platform delivers predictions based on real-time data and can organize insights into a variety of visualization formats beyond simple graphs, according to its website.

  • Pricing: Contact company for custom pricing.
  • Key features: Powered by machine learning; quickly determines patterns and delivers predictions; produces data visualizations for analysis. 
  • Who should use it: Ideal for marketing and retail teams looking to gain fast business insights and manage customer churn and retention. 

 

FICO Predictive Analytics

Specifically designed for the finance industry, FICO Predictive Analytics offers tools for tracking, modeling and forecasting financial and other relevant data, according to its site. Alongside its predictive analytics dashboard, FICO also offers a decision management platform for companies to manage governance and deal with risks to their data’s security. The platform’s focus may not make it ideal for customers in all industries, but FICO’s services can support clients in healthcare, retail and transportation as well as finance, according to its website.

  • Pricing: Contact company for pricing. 
  • Key features: Decision management capabilities; easy to develop and deploy machine learning models; customizable data visualizations that convey results. 
  • Who should use it: Businesses in industries like finance, healthcare and e-commerce that want to de-silo their data and increase collaboration between different teams. 

 

Q Research

Geared toward market researchersQ Research is a data analytics and forecasting tool that can quickly record and interpret data automatically, according to its site. Datasets can be imported from Q Research to presentation platforms like PowerPoint, and users can view their data forecasts in different formats like predictive trees and cluster tables. Q Research’s existing client base includes household names like Amazon, Meta and Nielsen.

  • Pricing: Standard license starts at $2,235 per user annually.
  • Key features: Can import data to different presentation platforms; statistical testing according to data type; data forecasts can be converted into various formats. 
  • Who should use it: Market researchers looking to quickly compile data and deliver insights in the form of easy-to-understand visualizations and reports.

 

Frequently Asked Questions

Predictive analytics refers to using data to make accurate predictions and forecasts about future events and trends. The process often relies on machine learning and AI to mine historical data and build statistical models that help business leaders visualize patterns and inform their decision-making. 

Predictive analytics tools are software suites and platforms that do the work of compiling, cleaning and organizing data to build accurate models and provide business insights. These tools come with AI and machine learning features, so they can automate complex actions and free up employees to focus more on taking proactive measures based on data-driven insights.

Sara B.T. Thiel and Ashley Bowden contributed reporting to this story.

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