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IBM SPSS Modeler - Predictive Analytics Software

IBM SPSS Modeler Reviews in July 2026: User Ratings, Pros & Cons

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4.2

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IBM SPSS Modeler Reviews & Ratings

4.2

Very Good

Based on 300 ratings & 143 reviews

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Rating Distribution

Excellent

(74)

Very Good

(47)

Good

(12)

Poor

(4)

Terrible

(6)

Spotsaas Editor’s POV

IBM SPSS Modeler consistently delivers for teams needing comprehensive, visual-driven predictive analytics. I appreciate how quickly I can build data preparation and modeling pipelines through its intuitive drag-and-drop interface, even without writing code. The broad algorithm support—from regression to text mining—is robust and well-suited for business and ...Read more

IBM SPSS Modeler pros and cons

  • Offers extensive analytics, clustering, and predictive modeling tools.

  • The drag-and-drop UI simplifies data preparation and model building.

  • IBM provides extensive documentation, training, and community support

  • Includes regression, decision trees, neural nets, time-series, and text analytics

  • High cost may not be justified for small organizations or occasional users

  • Graphs and charting tools are seen as old-fashioned and hard to customize

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Showing 61-70 out of 143

AU

Anonymous User

02/11/19

5 out of 5

"Wasy and simple"

What do you like best about IBM SPSS Modeler? That its very simple to use and veru user friendly What do you dislike about IBM SPSS Modeler?

AU

Anonymous User

02/11/19

5 out of 5

"Predictive for the masses"

What do you like best about IBM SPSS Modeler? Thank you IBM for your continued investment in SPSS. You have made it easier for me and my customers to leverage exiwting SPSS models and take advantage of development in "R".

JC

Juan Carlos O

02/11/19

5 out of 5

"Business Analytics for all"

What do you like best about IBM SPSS Modeler? If you are business user, you keep thinking on the business problem you want to resolve, building an analysis at speed of thinking. Once finished you can deploy the result easily. If you are coder, you can also use Python or R, in the same environment, so is pretty handy for both approaches.

AC

Andrea C

02/11/19

5 out of 5

"Friendly"

What do you like best about IBM SPSS Modeler? This software is very friendly and easy to use for business users. What do you dislike about IBM SPSS Modeler?

MM

Mauricio M

02/11/19

5 out of 5

"excelent for datamining and analytics"

What do you like best about IBM SPSS Modeler? algorithms menu, easy to use, visualization tools, audits and data preparation nodes What do you dislike about IBM SPSS Modeler?

AU

Anonymous User

02/11/19

4.5 out of 5

"My experience with IBM SPSS Modeler"

What do you like best about IBM SPSS Modeler? The new interface is really fantastic. The new features about graphic analytics allows to user to explote really his data organization,, it's interactive and analytically powerfull.

AU

Anonymous User

02/05/19

4 out of 5

"Good at modelling data for text mining"

What do you like best about IBM SPSS Modeler? text mining algorithms and modelling based on text analysis What do you dislike about IBM SPSS Modeler?

AU

Anonymous User

02/04/19

5 out of 5

"Chief Enterprise Architect"

What do you like best about IBM SPSS Modeler? Ability to perform par our expectations and meet our business needs What do you dislike about IBM SPSS Modeler?

AU

Anonymous User

02/01/19

5 out of 5

"Great software for analyzing large amounts of data"

What do you like best about IBM SPSS Modeler? This is a very easy, intuitive software to use to connect multiple databases and sources together and transform data as well as apply different statistical forecasting methods to it. It is point and click so you don't need to write code.

AU

Anonymous User

01/06/19

4.5 out of 5

"Best Analytics Tool"

What do you like best about IBM SPSS Modeler? Modeler itself is very powerful and relatively easy to use. Creating powerful streams requires almost no programming. What do you dislike about IBM SPSS Modeler?

Disclaimer: This research has been collated from a variety of authoritative sources. We welcome your feedback at [email protected].