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IBM Predictive Analytics vs SAS Predictive Analytics comparison

 

Comparison Buyer's Guide

Executive Summary

Review summaries and opinions

We asked business professionals to review the solutions they use. Here are some excerpts of what they said:
 

Categories and Ranking

IBM Predictive Analytics
Ranking in Predictive Analytics
12th
Average Rating
7.0
Reviews Sentiment
5.7
Number of Reviews
1
Ranking in other categories
No ranking in other categories
SAS Predictive Analytics
Ranking in Predictive Analytics
9th
Average Rating
7.0
Reviews Sentiment
7.6
Number of Reviews
2
Ranking in other categories
No ranking in other categories
 

Mindshare comparison

As of October 2025, in the Predictive Analytics category, the mindshare of IBM Predictive Analytics is 2.2%, up from 0.8% compared to the previous year. The mindshare of SAS Predictive Analytics is 3.7%, up from 2.9% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Predictive Analytics Market Share Distribution
ProductMarket Share (%)
SAS Predictive Analytics3.7%
IBM Predictive Analytics2.2%
Other94.1%
Predictive Analytics
 

Featured Reviews

LE
Good prediction capability for marketing purposes, although it needs to be more flexible
I found it very hard to change the algorithm that is used for prediction and I think that this solution can be more flexible. It looks like more of a black box in some cases and there are few ways to intervene and specify actions. Using IBM Predictive Analytics requires more skill, resources, and training than some other solutions. In the next release of this solution, I would like to see better integration with business solutions so that the data can be more easily accessed.
it_user1139529 - PeerSpot reviewer
Drag-and-drop functionality makes the interface easy to use, but the technical support needs to be improved
There are not many people deploying models using this solution, which is a problem. I have done some cross-development and have found that when I am building models with the open-source software, the accuracy is better. For categorical data, the models built by SAS Emailer are very complex compared to those built by the open-source version. Technical support could be improved because they take too long to answer our queries. Models that are created are a block box, and you can't see the details.

Quotes from Members

We asked business professionals to review the solutions they use. Here are some excerpts of what they said:
 

Pros

"The most valuable feature is the predictive capability in marketing use cases."
"The most valuable feature is its flexibility and the ability to integrate with SAS."
"The most valuable features are forecasting and reporting."
 

Cons

"Using IBM Predictive Analytics requires more skill, resources, and training than some other solutions."
"Technical support could be improved because they take too long to answer our queries."
"I think that this solution should be more compatible with other software, including open-source solutions."
 

Pricing and Cost Advice

Information not available
"If SAS were more flexible in terms of licensing then that would be good, because it costs more than other solutions."
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Sample Customers

Getin Noble Bank S.A., North Pacific Bank Ltd., RightShip, California Franchise Tax Board, Consolidated Communications, Coherent Path Inc., Rossmann Supermarkety Drogeryjne Polska Sp. z o.o., Tennessee Highway Patrol, Banco de Prevision Social, Comptel Corp.
MetLife
Find out what your peers are saying about Alteryx, SAP, Altair and others in Predictive Analytics. Updated: October 2025.
870,701 professionals have used our research since 2012.