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    Overview
    ProductRatingMost Used ByProduct SummaryStarting Price

    IBM SPSS Modeler

    Score9.5 out of 10
    N/AIBM SPSS Modeler is a visual data science and machine learning (ML) solution designed to help enterprises accelerate time to value by speeding up operational tasks for data scientists. Organizations can use it for data preparation and discovery, predictive analytics, model management and deployment, and ML to monetize data assets.

    $499

    per month

    IBM watsonx.ai

    Score8.8 out of 10
    N/AWatsonx.ai is part of the IBM watsonx platform that brings together new generative AI capabilities, powered by foundation models, and traditional machine learning into a studio spanning the AI lifecycle. Watsonx.ai can be used to train, validate, tune, and deploy generative AI, foundation models, and machine learning capabilities, and build AI applications with less time and data.

    $0

    Pricing
    IBM SPSS ModelerIBM watsonx.ai
    Editions & Modules
    IBM SPSS Modeler Personal
    4,670
    per year
    IBM SPSS Modeler Professional
    7,000
    per year
    IBM SPSS Modeler Premium
    11,600
    per year
    IBM SPSS Modeler Gold
    contact IBM
    per year
    Free Trial
    $0
    ML functionality (20 CUH limit /month); Inferencing (50,000 tokens / month)
    Standard
    $1,050
    Monthly tier fee; additional usage based fees
    Essentials
    Contact Sales
    Usage based fees
    Offerings
    Pricing Offerings
    IBM SPSS ModelerIBM watsonx.ai
    Free Trial
    YesYes
    Free/Freemium Version
    NoYes
    Premium Consulting/Integration Services
    YesYes
    Entry-level Setup FeeOptionalNo setup fee
    Additional DetailsIBM SPSS Modeler Personal enables users to design and build predictive models right from the desktop. IBM SPSS Modeler Professional extends SPSS Modeler Personal with enterprise-scale in-database mining, SQL pushback, collaboration and deployment, champion/challenger, A/B testing, and more. IBM SPSS Modeler Premium extends SPSS Modeler Professional by including unstructured data analysis with integrated, natural language text and entity and social network analytics. IBM SPSS Modeler Gold extends SPSS Modeler Premium with the ability to build and deploy predictive models directly into the business process to aid in decision making. This is achieved with Decision Management which combines predictive analytics with rules, scoring, and optimization to deliver recommended actions at the point of impact.Pricing for watsonx.ai includes: model inference per 1000 tokens and ML tools and ML runtimes based on capacity unit hours.
    More Pricing Information
    Community Pulse
    IBM SPSS ModelerIBM watsonx.ai
    Considered Both Products
    IBM
    No answer on this topic
    IBM
    No answer on this topic
    Key User Insights
    Would buy again
    100%
    Would buy again
    5 Answers
    98%
    Would buy again
    45 Answers
    Delivers good value for the price
    No answers on this topic
    100%
    Delivers good value for the price
    36 Answers
    Happy with the feature set
    100%
    Happy with the feature set
    5 Answers
    100%
    Happy with the feature set
    46 Answers
    Lived up to sales and marketing promises
    No answers on this topic
    97%
    Lived up to sales and marketing promises
    30 Answers
    Implementation went as expected
    No answers on this topic
    89%
    Implementation went as expected
    33 Answers
    Features
    IBM SPSS ModelerIBM watsonx.ai
    Platform Connectivity
    Comparison of Platform Connectivity features of IBM SPSS Modeler and IBM watsonx.ai
    Feature
    IBM SPSS Modeler
    8.9
    2 Ratings
    6% above category average
    IBM watsonx.ai
    -
    Ratings
    Connect to Multiple Data Sources8.82 Ratings00 Ratings
    Extend Existing Data Sources8.82 Ratings00 Ratings
    Automatic Data Format Detection9.01 Ratings00 Ratings
    MDM Integration9.01 Ratings00 Ratings
    Data Exploration
    Comparison of Data Exploration features of IBM SPSS Modeler and IBM watsonx.ai
    Feature
    IBM SPSS Modeler
    9.0
    1 Ratings
    7% above category average
    IBM watsonx.ai
    -
    Ratings
    Visualization9.01 Ratings00 Ratings
    Interactive Data Analysis9.01 Ratings00 Ratings
    Data Preparation
    Comparison of Data Preparation features of IBM SPSS Modeler and IBM watsonx.ai
    Feature
    IBM SPSS Modeler
    9.0
    1 Ratings
    10% above category average
    IBM watsonx.ai
    -
    Ratings
    Interactive Data Cleaning and Enrichment9.01 Ratings00 Ratings
    Data Transformations9.01 Ratings00 Ratings
    Data Encryption9.01 Ratings00 Ratings
    Built-in Processors9.01 Ratings00 Ratings
    Platform Data Modeling
    Comparison of Platform Data Modeling features of IBM SPSS Modeler and IBM watsonx.ai
    Feature
    IBM SPSS Modeler
    9.0
    1 Ratings
    6% above category average
    IBM watsonx.ai
    -
    Ratings
    Multiple Model Development Languages and Tools9.01 Ratings00 Ratings
    Automated Machine Learning9.01 Ratings00 Ratings
    Single platform for multiple model development9.01 Ratings00 Ratings
    Self-Service Model Delivery9.01 Ratings00 Ratings
    Model Deployment
    Comparison of Model Deployment features of IBM SPSS Modeler and IBM watsonx.ai
    Feature
    IBM SPSS Modeler
    9.0
    1 Ratings
    6% above category average
    IBM watsonx.ai
    -
    Ratings
    Flexible Model Publishing Options9.01 Ratings00 Ratings
    Security, Governance, and Cost Controls9.01 Ratings00 Ratings
    AI Development
    Comparison of AI Development features of IBM SPSS Modeler and IBM watsonx.ai
    Feature
    IBM SPSS Modeler
    -
    Ratings
    IBM watsonx.ai
    6.6
    2 Ratings
    13% below category average
    Machine learning frameworks00 Ratings6.73 Ratings
    Data management00 Ratings6.43 Ratings
    Data monitoring and version control00 Ratings5.83 Ratings
    Automated model training00 Ratings6.43 Ratings
    Managed scaling00 Ratings7.03 Ratings
    Model deployment00 Ratings6.43 Ratings
    Security and compliance00 Ratings7.63 Ratings
    Best Alternatives
    IBM SPSS ModelerIBM watsonx.ai
    Small Businesses
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    Score8.9 out of 10
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    Score7.8 out of 10
    Medium-sized Companies
    Anaconda
    Score8.8 out of 10
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    Score8.2 out of 10
    Enterprises
    IBM Watson Studio
    Score10 out of 10
    DataRobot
    Score8.2 out of 10
    All AlternativesView all alternativesView all alternatives
    User Ratings
    IBM SPSS ModelerIBM watsonx.ai
    Likelihood to Recommend
    9.7
    (8 ratings)
    9.2
    (36 ratings)
    Likelihood to Renew
    -
    (0 ratings)
    6.4
    (1 ratings)
    Usability
    8.9
    (2 ratings)
    7.7
    (6 ratings)
    Support Rating
    10.0
    (1 ratings)
    -
    (0 ratings)
    Ease of integration
    -
    (0 ratings)
    6.4
    (2 ratings)
    Product Scalability
    -
    (0 ratings)
    9.1
    (1 ratings)
    User Testimonials
    IBM SPSS ModelerIBM watsonx.ai
    Likelihood to Recommend
    IBM
    Fast NLP analytics are very easy in SPSS Modeler because there is a built-in interface for classifying concepts and themes and several pre-built models to match the incoming text source. The visualizations all match and help present NLP information without substantial coding, typically required for word clouds and such. SPSS Modeler is good at attaining results faster in general, and the visual nature of the code makes a good tool to have in the data science team's repository. For younger data scientists, and those just interested, it is a good tool to allow for exploring data science techniques.
    Incentivized
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    IBM
    I have built a code accelerator tool for one of the IBM product implementation. Although there was a heavy lifting at the start to train the model on specifics of the packaged solution library and ways of working; the efficacy of the model is astounding. Having said that, watsonx.ai is very well suited for customer service automation, healthcare data analytics, financial fraud detection, and sentiment analysis kind of projects. The Watsonx.ai look and feel is little confusing but I understand over a period of time , it will improve dramatically as well. I do feel that Watsonx.ai has certain limitations from cross-platform deployment flexibility. If an organization is deeply invested in a multi-cloud environment, Watson's integration on other cloud platforms may not be seamless comported to other AI platforms.
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    Pros
    IBM
    • Combine text and data
    • Provide facilities for all phases of the data mining process.
    • Use a node and stream paradigm to easily and quickly create models.
    Incentivized
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    IBM
    • It allows specialists to apply several base models for specific subtasks in the field of NLP.
    • Gives the availability of many models developed for AI enhancement for different solutions.
    • Has incorporated functionality for data governance and security to support access to AI tools by multiple users.
    Incentivized
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    Cons
    IBM
    • Has very old style graphs, with lots of limitations.
    • Some advanced statistical functions cannot be done through the menu.
    • The data connectivity is not that extensive.
    • It's an expensive tool.
    Incentivized
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    IBM
    • IBM watsonx.ai is expensive than other platforms.
    • Limited integraions though it has many but still some tools integrations not there for medical usecase
    • Its little difficult to learn as right now not many open reseouces
    • Community is not that strong to get any answer
    Incentivized
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    Likelihood to Renew
    IBM
    No answers on this topic
    IBM
    I still don't have enough experience, but i have seen a lot of demos and i have made some real world scenarios and so far so long every thing looks fine. I was at IBM Think 2025 and IBM TechXchange 2025 and the labs were really usefull and simple to understand.
    Incentivized
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    Usability
    IBM
    The ability to do predictive modeling, text analytics for both structured & unstructured data, decision management, optimization, and support for various data sources
    Incentivized
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    IBM
    I needed some time to understand the different parts of the web UI. It was slightly overwhelming in the beginning. However, after some time, it made sense, and I like the UI now. In terms of functionality, there are many useful features that make your life easy, like jumping to a section and giving me a deployment space to deploy my models easily.
    Incentivized
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    Support Rating
    IBM
    The online support board is helpful and the free add ons are incredibly appreciated.
    Incentivized
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    IBM
    I still don't have enough experience, but i have seen a lot of demos and i have made some real world scenarios and so far so long every thing looks fine. I was at IBM Think 2025 and IBM TechXchange 2025 and the labs were really usefull and simple to understand.
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    Alternatives Considered
    IBM
    When it comes to investigation and descriptive we have found SPSS Statistics to be the tool of choice, but when it comes to projects with large and several datasets SPSS Modeler has been picked from our customers.
    Incentivized
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    IBM
    IBM watsonx.ai has been far superior to that of Chat GPT AI. the UI elements prompt responses and overall execution of the AI was much better and more accurate compared to the competition. I can not recommend using this platform enough. Great job IBM. I hope the team behind this project continues to grow and prosper.
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    Scalability
    IBM
    No answers on this topic
    IBM
    I still don't have enough experience, but i have seen a lot of demos and i have made some real world scenarios and so far so long every thing looks fine. I was at IBM Think 2025 and IBM TechXchange 2025 and the labs were really usefull and simple to understand.
    Incentivized
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    Return on Investment
    IBM
    • Positive - Ease of decision making and reduction in product life cycle time.
    • Positive - Gives entirely new perspective with the help of right team. Helps expanding the portfolio.
    • Negative - Needs to have good understanding about mathematical modelling, of which talent is rare and expensive. Hence, increase the costs for R&D and manpower.
    Incentivized
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    IBM
    • Time saving to set up the infrastructure - without watsonx.ai we would have had to set up everything individually
    • The first point translates directly into cost savings
    • The compliance aspect was a game changer for us and provided us with the confidence to focus all our efforts only on IBM watsonx.ai
    Incentivized
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    ScreenShots

    IBM SPSS Modeler Screenshots

    Screenshot of Use a single run to test multiple modeling methods, compare results and select which model to deploy. Quickly choose the best performing algorithm based on model performance.Screenshot of Explore geographic data, such as latitude and longitude, postal codes and addresses. Combine it with current and historical data for better insights and predictive accuracy.Screenshot of Capture key concepts, themes, sentiments and trends by analyzing unstructured text data. Uncover insights in web activity, blog content, customer feedback, emails and social media comments.Screenshot of Use R, Python, Spark, Hadoop and other open source technologies to amplify the power of your analytics. Extend and complement these technologies for more advanced analytics while you keep control.

    IBM watsonx.ai Screenshots

    Screenshot of the foundation models available in watsonx.ai. Clients have access to IBM selected open source models from Hugging Face, as well as other third-party models, and a family of IBM-developed foundation models of different sizes and architectures.Screenshot of the Prompt Lab in watsonx.ai, where AI builders can work with foundation models and build prompts using prompt engineering techniques in watsonx.ai to support a range of Natural Language Processing (NLP) type tasks.Screenshot of the Tuning Studio in watsonx.ai, where AI builders can tune foundation models with labeled data for better performance and accuracy.Screenshot of the data science toolkit in watsonx.ai where AI builders can build machine learning models automatically with model training, development, visual modeling, and synthetic data generation.