We asked business professionals to review the solutions they use. Here are some excerpts of what they said:
"Automation is great and this product is very organized."
"It is a great product for running statistical analysis."
"Very good data aggregation."
"You take two quarters and compare them and this tool is ideal because it gives you a lot of visibility on the before and after."
"The supervised models are valuable. It is also very organized and easy to use."
"Capability analysis is one of the main and valuable functions. We also do some hypothesis testing in Minitab and summary stats. These are the functions that we find very useful."
"Since we are using the software as a statistical tool, I would say the best aspects of it are the regression and segmentation capabilities. That said, I've used it for all sorts of things."
"The most valuable feature is the user interface because you don't need to write code."
"In terms of the features I've found most valuable, I'd say the duration, the correlation, and of course the nonparametric statistics. I use it for reliability and survival analysis, time series, regression models in different solutions, and different types of solutions."
"You can quickly build models because it does the work for you."
"It is a modeling tool with helpful automation."
"SPSS is quite robust and quicker in terms of providing you the output."
"The solution is very comprehensive, especially compared to Minitabs, which is considered more for manufacturing. However, whatever data you want to analyze can be handled with SPSS."
"When you are not using the product, such as during the pandemic where we had worldwide lockdowns, you still have to pay for the licensing."
"Dimension reduction should be classified separately."
"It would be good if IBM added help resources to the interface."
"Time Series or forecasting needs to be easier. It is a very important feature, and it should be made easier and more automated to use. For instance, for logistic regression, binary or multinomial is used automatically based on the type of the target variable. I wish they can make Time Series easier to use in a similar way."
"Requires more development."
"The solution could improve by providing a visual network for predictions and a self-organizing map for clustering."
"The solution needs more planning tools and capabilities."
"The design of the experience can be improved."
"If there is any self-generation data collection plan (DCP), it would be helpful in gathering data. It would also be useful if there is a function to scale it up to, let's say, UiPath and have it consolidate and integrate into a UiPath solution."
"SPSS slows down the computer or the laptop if the data is huge; then you need a faster computer."
"I'd like to see them use more artificial intelligence. It should be smart enough to do predictions and everything based on what you input."
"Each algorithm could be more adaptable to some industry-specific areas, or, in some cases, adapted for maintenance."
"It would be helpful if there was better documentation on how to properly use the solution. A beginner's guide on how to use the various programming functions within the product would be so useful to a lot of people. I found that everything was very confusing at first. Having clear documentation would help alleviate that."
"Its price is okay for a company, but for personal use, it is considered somewhat expensive."
"This tool, being an IBM product, is pretty expensive."
"The price of this solution is a little bit high, which was a problem for my company."
"The pricing of the modeler is high and can reduce the utility of the product for those who can not afford to adopt it."
IBM SPSS Modeler is an extensive predictive analytics platform that is designed to bring predictive intelligence to decisions made by individuals, groups, systems and the enterprise. By providing a range of advanced algorithms and techniques that include text analytics, entity analytics, decision management and optimization, SPSS Modeler can help you consistently make the right decisions from the desktop or within operational systems.
IBM SPSS Modeler is ranked 3rd in Data Mining with 5 reviews while IBM SPSS Statistics is ranked 2nd in Data Mining with 15 reviews. IBM SPSS Modeler is rated 8.4, while IBM SPSS Statistics is rated 8.0. The top reviewer of IBM SPSS Modeler writes "User-friendly, and it gives you a lot of visibility through features like comparing fiscal quarters". On the other hand, the top reviewer of IBM SPSS Statistics writes "Offers good Bayesian and descriptive statistics". IBM SPSS Modeler is most compared with IBM Watson Studio, KNIME, Alteryx, Microsoft BI and Microsoft Azure Machine Learning Studio, whereas IBM SPSS Statistics is most compared with TIBCO Statistica, Weka, Alteryx, Microsoft Azure Machine Learning Studio and MathWorks Matlab. See our IBM SPSS Modeler vs. IBM SPSS Statistics report.
We monitor all Data Mining reviews to prevent fraudulent reviews and keep review quality high. We do not post reviews by company employees or direct competitors. We validate each review for authenticity via cross-reference with LinkedIn, and personal follow-up with the reviewer when necessary.