IBM SPSS Modeler Reviews & Product Details

New York, USA
$50BN to $100BN
Discussions (4)
Demos (1)


SPSS Modeler reduces the complexities involved in the transformation of data by providing easy-to-use models. SPSS Modeler is extensively used across various languages to analyze data from multiple databases. It majorly helps in analyzing data to predict customer churn rates and data sets. The application can be used across various industry verticles. Request IBM SPSS MODELER Pricing to get more information.


IBM SPSS Predictive Analytics Enterprise provides both predictive and descriptive analytics for data obtained from varied sources. The solution can be utilized in data mining, real-time scoring, statistical & supply chain analysis, and decision management. It also includes a framework of deployment to integrate predictive intelligence with business rules and to optimize business decisions.


  • Data Management: It helps extract physical data and combine it with current as well as historical data to improve the accuracy of predictions and identifies trends and patterns
  • Extensive Analytics Capabilities: It provides numerous machine learning techniques that help in the association, segmentation, and classification of data
  • Integrated Sources: It can read data from varied sources and expand its capabilities to choose the most suitable model to be used

Top Usecases

  1. Data Visualisation
  2. Financial Management
  3. Customer Response Modelling
  4. Data Preparation
  5. Location Intelligence
  6. Customer Data Platform
  7. Risk Management
  8. Operations Management
  9. Sales and Marketing Management
  10. Network Management

360 Quadrants

Strengths and Weaknesses
  • +10 Most Advanced Predictive Analytics Tools
  • +9 Deploy Statistical Models
  • +8 Enhances The Transactional Decision
  • +7 Useful Capabilities
  • +6 Export Data From All Types Of Files
  • +5 Scalable And Most Flexible Software
  • +14 Detect Anomalies Quickly
  • +13 Converts Regular Tansactional
  • +12 Leverages Both Structured And Unstructured Data
  • +11 Best Visual Analytics Software
  • +10 Strong Capabilities In Information Management
  • +10 Static Visualisation
  • +13 Report Generation
  • +6 Transaction Data
  • +5 Database Administrators
  • +8 Data Preparation (Data Management)
  • +12 Real Time Dashboarding
  • +5 Customer Data
  • +9 Data Blending
  • +12 Demographic
  • -14 Weak NLP Capabilities
  • -13 Dated Visualization Tool
  • -5 Code free to configurable addresses
  • -14 Lacks important statistical tests
  • -6 Real Time Dashboarding and Custom Predictive Algorithms
  • -14 Event Detection (Use case)
  • -13 Root Cause Analysis (Use case)
  • -14 Location [Pincodes]
  • -10 Enterprise Features
  • -6 Licensing - Data Volume
  • -11 Licensing - Hybrid
  • -7 Licensing - No of Records
  • -9 Licensing - Per data connection
  • -8 Licensing - Per Processor
  • -5 Licensing - Per seat
  • -10 Licensing - Per use / Per query
  • -12 Cost - $ per GB
  • -13 Cost - $ per license
  • -14 Hybrid (Please specify)
  • -9 Consultants
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IBM SPSS MODELER presence in Predictive Analytics Software

IBM is one of the prominent players, providing IT products and services worldwide. It has direct as well as an indirect presence in over 170 countries, with R&D centers in over 10 countries employing around 3,000 researchers bringing about innovations. The company has been following the policy of integrating IT framework and cloud, to attain higher profitability from market transitions. IBM Corporation assists in creating values for its clients by enabling new capabilities that transform their businesses and help them to engage with their customers efficiently. IBM intends to derive greater values from global integration and process efficiency. Furthermore, along with its wide diversity in the areas it caters, the company has built a portfolio of products and services. Additionally, IBM’s R&D expenditure is continuously increasing, leading to re-inventions and also focuses on high-value growth opportunities. For instance, since 2010, IBM Corporation has invested around USD 40 billion in building and developing the IBM Cloud on a global scale and has prolonged cognitive systems to abundant enterprises and industries. Moreover, the acquisition of Star Analytics and strategic collaboration with CVS Health and Juniper Network indicates that IBM will be further investing in the inorganic growth strategy to strengthen its market position in analytics offerings and target all potential and emerging economies to bring about an analytics transformation.



Buyer, Construction, Enterprise

Apr 03, 2019

“Decision making made easier with this data analysis program.”

The software’s ability to organize and use variable for tool application is what works best for me. Evaluation of the behavior of dependent and independent variables for linear regression analysis makes it easy to compile reports, further enabling easier decision making. It is also extremely user-friendly, with each icon distinctly visible. If I had to pick an area of improvement, I would say it is the quality of its graphics. They do not seem very professional and perhaps they can be updated to seem so.

I believe that this is an ideal software for organizations lookimg to systemize its data and work using dependent as well as independent variables. It works excellently to present inferential statistics to help organizations grow. However, if you’re looking for exceptional graphics, then this might not be the one for you.

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Buyer, Media & Entertainment, SME

Apr 03, 2019

“A great way to professionally build and manage databases”

One of the most revolutionary software, especially in my field, where I need to use multiple statistical variables to analyze databases of chemical elements. It is flexible as well, so I can convert databases of other software into the IBM SPSS format and they work better! For me, the best feature is its ability to filter and modify variables as per what I need. It is extremely versatile and perfect for my daily work requirements. Since it is quite a complicated software, it can get a bit tedious to understand all its functionalities, which may require a certain level of computer science knowledge. I had to take up an intensive course to understand it completely. This is possibly the best software for management and analysis of databases. It is extremely effective in creating variables and I dare say any company that uses it is bound to see a noticeable enhancement in employee performance.
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James Smith

Feb 20, 2019

“Complicated and old school”

IBM offers SPSS Predictive Analytics Enterprise solution for data (both structured and unstructured) derived from any source. This software is a bit complicated with not so extraordinary visualization tools. Proper training and expertise are needed to use this solution. The R Integration Package provides the ability to use programming features of R within IBM SPSS Statistics. The solution can be used across various applications such as real-time scoring, statistical analysis, data mining, and decision evidence-based medicine, supply chain analysis, and crime prediction and prevention.
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James Smith

Feb 12, 2019

“IBM Modeler is perfect for mining and analysing complex data.”

Even someone without in-depth knowledge of programming can use this software. That’s how user friendly its interface is. It not only creates predictive models but also performs other analytical tasks. The only drawback I could identify is that I might not be able to take advantage of all the features. It will take me some time to fully learn and harness all its benefits. I would recommend it to anyone who is looking to work with complex sets of data to obtain statistical models. It has simplified the process to a great extent.

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Buyer, Chemicals and Materials, SME

Feb 12, 2019

“Great software! Very easy to use!”

The best part about Modeler is that it can be automated and integrated with R project and with Python. This enables more functions, especially when you have multiple problems that need to be solved using analytics. It helps you modify data using a large number of techniques. What we found to be a drawback is that Modeler does not carry out normality or randomness tests. This makes it difficult, especially while making regressions since the assumptions about the errors need to be tested. Another drawback is that the lack of techniques for the testing of images and videos. Consider adding alternatives for users of entity analytics and social network analytics.
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Top Features

  1. Product Features and Functionality / Enterprise Features
  2. Product Features and Functionality / Core Features
  3. Enterprise Features / Analytics Workflow
  4. Data Management / Report Generation
  5. Product Features and Functionality / Integration with Big Data Frameworks / Data Stores
  6. Data Collections / Transaction Data
  7. Core Features / Data Investigation
  8. Services Offered / Implementation
  9. Data Management / Static Visualisation
  10. Data Management / Interactive Visualisation
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