The G2M Platform (formerly Analyzr) is a software-as-a-service offering by G2M Insights focused on making machine learning analytics simple and secure for midmarket and enterprise customers that may not have a full-fledged data science team. For B2B sales and marketing predictive analytics, the G2M Platform provides a streamlined solution connecting data sources, predictive models, and production systems of record with real-time predictive analytics. With it, users…
$0
for a single user with 10 models and 10 datasets
IBM SPSS Modeler
Score 7.1 out of 10
N/A
IBM 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.
$4,670
per year
Pricing
G2M Platform
IBM SPSS Modeler
Editions & Modules
Starter
$0
for a single user with 10 models and 10 datasets
Premium
$499
per month per installation
Enterprise
Let's talk
per year per installation
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
Offerings
Pricing Offerings
G2M Platform
IBM SPSS Modeler
Free Trial
Yes
Yes
Free/Freemium Version
Yes
No
Premium Consulting/Integration Services
No
No
Entry-level Setup Fee
No setup fee
Optional
Additional Details
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IBM 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.
More Pricing Information
Community Pulse
G2M Platform
IBM SPSS Modeler
Considered Both Products
G2M Platform
Verified User
Anonymous
Chose G2M Platform
Analyzr gives more transparency than the others tools we have used, allowing us to see the actual model and data insights instead of a black box approach. The tool is also more intuitive then others, allowing members with limited Python, R coding to create models.
IBM SPSS Modeler is considerably easier to use. It allows for very rapid development and the ability to get to a goal quickly. There is no need to learn a new programming language so the analyst has the ability to focus on the problem rather than the pedantics of managing …
We additionally use SAS Data Miner as a toolkit. Compared to SAS Data Miner, the SPSS Modeler is a good competitor. SAS probably is more integrated in the market for a visual-based code for data science activities. However, I don't think it offers anything better than SPSS, and …
SPSS has a great set of analytical models, but SPSS is especially strong (compared to other tools) in complex statistical modeling and predictive analytics/statistics. However, the data connectivity features of SPSS are not the best, as the data sources SPSS can work with are …
The field of data analytics has important value for each organization. IBM SPSS Modeler is one of the leaders in this highly competitive vertical. IBM SPSS is very intuitive compared with others, and has reduced the complexity. This software has various good functionalities …
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.
Modeler is well suited for understanding consumer data. The ability to create a prediction and then to understand what is driving that prediction is strong in Modeler. Modeler is closely aligned with the CRISP-DM data mining approach meaning it is not just the 'doing' but also the theoretical background behind the development of data mining models.
The ability to do predictive modeling, text analytics for both structured & unstructured data, decision management, optimization, and support for various data sources
Analyzr gives more transparency than the others tools we have used, allowing us to see the actual model and data insights instead of a black box approach. The tool is also more intuitive then others, allowing members with limited Python, R coding to create models.
We additionally use SAS Data Miner as a toolkit. Compared to SAS Data Miner, the SPSS Modeler is a good competitor. SAS probably is more integrated in the market for a visual-based code for data science activities. However, I don't think it offers anything better than SPSS, and I really like several of the helpful components for usability for SPSS like peaks into nodes.