Os 10 Melhores Softwares de Análise Preditiva Avaliados para 2026

Avaliações do melhor software de análise preditiva

1. 

   1

   Customerscore.io

   Best for automating customer health scoring

   • 7-day free trial + free demo available
   • From $199/month (billed annually)

   Visit Website

   Customer Rating:4.8/5This rating combines scores from multiple user review sites to reflect overall customer sentiment about the product.

   

   CustomerScore.io helps SaaS teams spot churn risks and expansion opportunities before they impact revenue. Its AI health scoring, customer segmentation, CRM integrations, and automated playbooks make it useful for customer success, growth, and RevOps teams that need actionable insights from customer data.

   Who Is Customerscore.io Best For?

   Customerscore.io is a strong fit for customer success and RevOps teams at B2B SaaS companies that need to monitor customer health and act on churn risk signals.

   Why I Picked Customerscore.io

   I picked CustomerScore.io because it automates customer health scoring across your entire customer base, helping you identify churn risks without manually reviewing each account. It scores customers based on signals from product usage, billing, CRM, and support data, then explains the key factors behind each score. I also like that your team can use those scores to segment at-risk customers and trigger targeted playbooks for follow-up. This makes it a strong option for SaaS teams that want to act on predictive insights before customer health declines further.

   Customerscore.io Key Features

   Some other features in CustomerScore.io support SaaS teams with retention analysis and revenue forecasting:

   • AI retention assistant: Lets you ask natural language questions about your customer base, such as why a segment is churning, and receive data-backed answers.
   • Upsell signal detection: Identifies expansion-ready accounts and can trigger targeted upsell sequences for customers most likely to upgrade.
   • Customer journey drop-off analysis: Shows where customers stall or disengage, helping your team identify where retention issues begin.
   • Unified customer data view: Pulls data from tools like Stripe, Mixpanel, and Intercom into a single customer profile.

   Customerscore.io Integrations

   Integrations include Stripe, Chargebee, Mixpanel, PostHog, HubSpot, Salesforce, Pipedrive, Raynet, Intercom, and Freshdesk.

   Pros and Cons

   Pros:

   • Triggers playbooks from customer risk segments
   • Explains churn risk with clear score drivers
   • Automates health scoring across every customer account

   Cons:

   • Product usage data is aggregated once daily
   • Tracker events require metric mapping before becoming usable
   Learn more about Customerscore.io:

   • Check out Customerscore.io on their website
2. 

   2

   Tableau

   Best for data visualization across any industry

   • 14-day free trial
   • Pricing upon request

   Visit Website

   Customer Rating:4.5/5This rating combines scores from multiple user review sites to reflect overall customer sentiment about the product.

   

   Tableau offers a web and cloud-based platform with a variety of data tools that are designed to provide a data-driven experience to fit into your current strategy and workflow.

   One of Tableau’s signature tools is their embedded analytics, which provide interactive analytical capabilities to help users increase product engagement and enhance customer satisfaction. This feature delivers rich content, data, and analytics that provide predictive data, forecasting analysis, and readable visuals to interpret what you’re seeing.

   Tableau has solutions for businesses of all sizes, including freelancers as well as enterprise-grade organizations. They offer tools by industry, technology, and department so business leaders can pinpoint the features that best fit their needs.

   Tableau Standout Features and Integrations

   Features include data preparation and visualization, reports interface and dashboard, on-premise servers, cloud tools, desktop tools, auto modeling, data discovery, big data services, and collaboration tools.

   Integrations include Amazon Athena, Amazon Redshift, Google Analytics, Google BigQuery, Hive, PostgreSQL, Salesforce, Snowflake, Splunk, and Vertica.

   Pros and Cons

   Pros:

   • Simplified user interface
   • Data is very visually appealing
   • Accessible through all devices

   Cons:

   • Large data sets are slow to collate
   • Limited phone app capabilities
   Learn more about Tableau:

   • Check out Tableau on their website
3. 

   3

   RapidMiner

   Best for scalable, governed, and safe business analytics

   • Free plan available
   • From $15/user/month (billed annually)

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   Customer Rating:4.6/5This rating combines scores from multiple user review sites to reflect overall customer sentiment about the product.

   

   This analytics software is designed for the simplification and optimization of data mining processes through a suite of products that include RapidMiner Studio, Radoop, Server, and Streams. Features include batch processing, template library, and automated charts, as well.

   One focus of RapidMiner is predictive maintenance that determines the lifetime of factory machines and components to help users predict repair and maintenance schedules. They paired cloud-based computing systems with intuitive machine learning tools to analyze data from the shop floor and keep a closer eye on equipment health.

   RapidMiner provides solutions for small, medium, and large businesses across a number of industries, including utilities, automotive, communications, energy, manufacturing, logistics, and life sciences.

   RapidMiner Standout Features and Integrations

   Features include automated data science, real-time scoring, hybrid cloud deployment, visual analytics workflow, code-based data science, data engineering, model building, AI app building, and ML ops.

   Integrations include Braincube, Clarkson Consulting, Google Cloud Platform, Hivecell, Hexware Technologies, Tableau Software, Qlik, and UI Path.

   Pros and Cons

   Pros:

   • Many support videos
   • Easy to install
   • Simplifies the user experience

   Cons:

   • Slow to update new algorithms
   • Has a bit of a learning curve
   Learn more about RapidMiner:

   • Check out RapidMiner on their website
4. 

   4

   Databricks

   Best for collaborative lakehouse analytics

   • Free edition available + 14-day free trial
   • From $0.15/DBU

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   Customer Rating:4.5/5This rating combines scores from multiple user review sites to reflect overall customer sentiment about the product.

   

   Databricks is a data intelligence platform that unifies data engineering, ML model training, AutoML, MLflow-based experiment tracking, and model serving on an open lakehouse architecture.

   Who Is Databricks Best For?

   Databricks is a strong fit for data engineering and data science teams at mid-to-large enterprises that need a unified platform for large-scale ML development and analytics.

   Why I Picked Databricks

   I've included Databricks in my top picks because its lakehouse architecture keeps raw data, feature engineering, and trained models in one place, which removes the usual handoff friction between data and ML teams. I like that collaborative notebooks let engineers and data scientists iterate on the same predictive model in real time. Delta Lake also ensures the data feeding those models is versioned and consistent, so predictions don't drift because of upstream changes.

   Databricks Key Features

   • AutoML: Automatically generates baseline predictive models by scanning your data, testing multiple algorithms, and surfacing the best-performing candidates with explainability notebooks.
   • MLflow experiment tracking: Logs parameters, metrics, and model artifacts across every training run so you can compare model versions and reproduce results.
   • Model serving: Deploys trained predictive models as low-latency REST API endpoints directly from the Databricks workspace.
   • Feature Store: Centralizes reusable ML features so teams can discover, share, and serve the same feature definitions across multiple predictive models.

   Databricks Integrations

   Databricks offers validated integrations with various third-party solutions through its Partner Connect portal, spanning data ingestion, transformation, BI, and machine learning. Key integrations include Fivetran, dbt Cloud, Prophecy, Tableau, Power BI, Dataiku, Hightouch, Qlik Sense, and Sigma Computing. Databricks is also available on Zapier, and it provides a REST API for custom integrations.

   Pros and Cons

   Pros:

   • Built-in MLflow tracks full model lifecycle
   • Supports Python, R, SQL, and Scala
   • Scales distributed model training across petabytes

   Cons:

   • Requires Spark expertise for advanced configurations
   • Compute costs spike without active monitoring
   Learn more about Databricks:

   • Check out Databricks on their website
5. 

   5

   Oracle Crystal Ball

   Best for working with spreadsheet models

   • Student and faculty pricing is $410

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   Customer Rating:4.4/5This rating combines scores from multiple user review sites to reflect overall customer sentiment about the product.

   

   Oracle Crystal Ball was designed to be the leading spreadsheet-based app for forecasting, predictive modeling, optimization, and simulation. Crystal Ball offers a complete suite of tools for uncertainty management to help businesses determine the best results while minimizing risk.

   One of the unique features of Crystal Ball is that it offers a classroom edition for the academic community through a fully functional version designed for students and teachers. This product includes Crystal Ball Decision Optimizer to add optimization power for any classroom simulation. They offer both student and faculty editions.

   Crystal Ball provides solutions for education, financial analysts, engineers, strategic planners, scientists, marketing managers, venture capitalists, and Six Sigma professionals. With tiered pricing for on-premise and cloud applications, Crystal Ball can be the right tool for businesses of all sizes.

   Crystal Ball Standout Features and Integrations

   Features include algorithms, data interactions, analysis, modeling, data unification, report generation, data visualizations, designed for Monte Carlo simulations, spreadsheet-based, time series forecasting, and optimization.

   Integrations include Excel.

   Pros and Cons

   Pros:

   • Data visualization is easy to read
   • Low barrier for entry
   • User friendly interface

   Cons:

   • Excel add-on occasionally crashes
   • Limited uncertainty data displays
   Learn more about Oracle Crystal Ball:

   • Check out Oracle Crystal Ball on their website
6. 

   6

   Anaconda

   Best for developing and deploying secure Python solutions

   • Free plan available
   • From $9/month

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   Customer Rating:4.6/5This rating combines scores from multiple user review sites to reflect overall customer sentiment about the product.

   

   This open-source data science platform provides tools to help engineers and data scientists develop performant machine learning applications with Python. This platform also allows users to perform predictive modeling, visualize, publish, and share data, analyze financial time series, and handle Jupyter Notebooks.

   Anaconda delivers the ability to code with what they claim is the world’s most trusted distribution for lightweight queries and AI solutions. They currently offer over 6,000 Python libraries, 2,000 interoperable R packages, and source-built, tamper-free solutions.

   Because it’s an open-source data science platform, Anaconda provides solutions for academic institutions, government agencies, enterprises, and individuals. This platform offers tiered pricing that can provide solutions for businesses of all sizes, as well as students and teachers.

   Anaconda Standout Features and Integrations

   Features include basic repository, cloud-hosted notebooks and workspace storage, on-demand training courses, predictive analytics, and online payment functionality. Panel app deployments and data catalogs are coming soon.

   Integrations include Azure Data Science Virtual Machines, Celebrus Customer, Celebrus Fraud, Datapell WMS, Domino Data Lab, Jovian, Kixie PowerCall, OpenSCAP, QuantRocket, and statsmodels.

   Pros and Cons

   Pros:

   • Flexible and robust platform
   • Comprehensive onboarding and training
   • Great community support

   Cons:

   • Slows down with large data sets
   • A bit of a learning curve
   Learn more about Anaconda:

   • Check out Anaconda on their website
7. 

   7

   Board

   Best for unifying strategy, finance, and operations

   • Free demo available
   • Pricing upon request

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   Customer Rating:4.4/5This rating combines scores from multiple user review sites to reflect overall customer sentiment about the product.

   

   This predictive analytics software provides the tools businesses need to explore crucial insights into what drives their operations. Used by over 2,000 companies globally, some of Board’s top customers use their end-to-end planning applications for comprehensive business performance.

   One of the tools Board offers for better data analysis is the simulation feature, which allows users to run multiple scenarios at speed. With a simulation, data scientists may create models to reflect the results of decision making based on your business challenges to ensure you have more information about the effects of every choice.

   Board offers solutions by department and by industry. They have targeted plans for finance, supply chain, sales performance management, and workforce planning departments, as well as opportunities to support retail, CPG, and professional services industries.

   Board Standout Features and Integrations

   Features include reporting interface, report generation, data visualization, big data services, dashboards, graphs and charts, score cards, self-service, data column filtering, collaboration tools, auto modeling, and simulation tools.

   Integrations include Google Analytics 360, HubSpot CRM, Marketo Engage, Microsoft Office, Oracle On Demand, Salesforce Sales Cloud, SAP HANA Cloud, Service Max, SugarCRM, and Veeva CRM.

   Pros and Cons

   Pros:

   • Can handle large amounts of data
   • All-in-one platform
   • Easy to implement

   Cons:

   • No dynamic system maintenance
   • Reporting alignment is tricky
   Learn more about Board:

   • Check out Board on their website
8. 

   8

   SAS Advanced Analytics

   Best for robust data visualization capabilities

   • 14-day free trial available
   • From $0.55 units/hour

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   Customer Rating:4.3/5This rating combines scores from multiple user review sites to reflect overall customer sentiment about the product.

   

   With navigation, visualization, and analysis capabilities, SAS Advanced Analytics is designed to provide actionable insights with no coding, as well as versatile programming options with fourth-generation language abilities that support SQL, data visualization, and data mining. In addition to providing solutions for organizations like Honda, SAS has also been used to tackle human trafficking and public health needs.

   SAS Advanced Analytics offers a number of statistical analysis features, including SAS Visual Forecasting Software that allows users to generate a massive variety of accurate forecasts very quickly. SAS claims this is a future-proof forecasting tool that helps you plan better by generating, visualizing, and deploying reliable forecasts at scale – with no human involvement.

   This web-based predictive analysis tool offers solutions for businesses of all sizes. Some of their most popular use cases include marketing, risk management, fraud, and IoT in industries like banking, insurance, the public sector, retail, consumer goods, and life sciences.

   SAS Advanced Analytics Standout Features and Integrations

   Features include scripting statistical tools, data mining, algorithms, data analysis, data interactions, modeling, data visualizations, report generation, and knowledge base.

   Integrations include SAS Integration Technologies for API integration.

   Pros and Cons

   Pros:

   • Similar to SQL
   • Ease of use
   • Free training

   Cons:

   • Limited pre-built module functionality
   • Error messages aren’t always clear
   Learn more about SAS Advanced Analytics:

   • Check out SAS Advanced Analytics on their website
9. 

   9

   IBM Watson Studio

   Best for AI optimization of predictive analytics

   • Free plan available
   • Pricing upon request

   Visit Website

   

   This cloud-based data management tool is designed for analysts, data scientists, and developers with features that include AI lifecycle automation, automated data preparation, visual model development, automated feature engineering, hyperparameter optimization, predictive analytics, and decision optimization.

   In addition to predictive analytics, IBM Watson Studio also offers prescriptive analytics that are designed to provide businesses with recommendations for optimal actions for specific business objectives. Once a user specifies their business needs, like customer satisfaction or cost savings, the prescriptive analytics help solve the most complex decisions with these constraints in mind.

   IBM Watson Studio is designed to be as versatile as possible with free plans, as well as pay-as-you-go solutions. They also offer subscription services for optimal savings. Some of the industries in which this company specializes include sustainability, security, and infrastructure.

   IBM Watson Studio Standout Features and Integrations

   Features include data integrations suite for ETL, automation for financial and operational planning, IDE to build and run AI models, complex optimization model building, analytics engine that adapts to custom domains, and data warehouses.

   Integrations include App Connect, Coveo, Facebook Messenger, Google Custom Search, HubSpot, Salesforce, Slack, Twilio Flex, WhatsApp, and Zendesk

   Pros and Cons

   Pros:

   • All-in-one analytics platform
   • Integrates with open-source platforms, like Python
   • Accurate and reliable models

   Cons:

   • Premium price point
   • Slows down with large data sets
   Learn more about IBM Watson Studio:

   • Check out IBM Watson Studio on their website
10. 

    10

    Qlik Sense

    Best for easily building customizable dashboards

    • 30-day free trial
    • Pricing upon request

    Visit Website

    

    Qlik is a data science tool that’s useful for predictive analytics, as its software can quickly generate machine learning models and analyze a variety of what-if scenarios through a code-free user interface.

    The main predictive analytics tool you’ll be using for data mining is a cloud-based solution called the Qlik AutoML, which provides a code-free way to conduct experiments and identify key drivers in your training models and data. Publish the data or integrate it into other dashboards for a more fully interactive analysis.

    Qlik offers data integration and predictive analytics solutions for SMBs and enterprise-grade organizations through two tiered plan options. Enterprise solutions are completely customized for the needs of business users. Some industries they specialize in supporting include healthcare, retail, communications, life sciences, and energy and utilities.

    Qlik Sense Standout Features and Integrations

    Features include smart visualization and dashboard, phone app for Android and Apple, augmented analytics with advanced AI, flexible APIs and custom extensions, self-service analysis creation, and data change alerts.

    Integrations include Amazon Web Services, Databricks, Google, Microsoft, Mongo DB, Rowshare, Smartsheet, Snowflake, SysAid, and TOPdesk.

    Pros and Cons

    Pros:

    • Tons of customization
    • Quick to implement
    • Easy to use

    Cons:

    • Limited navigation features
    • Limited data modeling
    Learn more about Qlik Sense:

    • Check out Qlik Sense on their website