IBM SPSS Modeler vs. Looker Studio

Overview
ProductRatingMost Used ByProduct SummaryStarting Price
IBM SPSS Modeler
Score 8.9 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.
$499
per month
Looker Studio
Score 8.2 out of 10
N/A
Looker Studio is a data visualization platform that transforms data into meaningful presentations and dashboards with customized reporting tools.
$9
per month per user per project
Pricing
IBM SPSS ModelerLooker Studio
Editions & Modules
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
Looker Studio Pro
$9
per month per user per project
Looker Studio
No charge
Offerings
Pricing Offerings
IBM SPSS ModelerLooker Studio
Free Trial
YesNo
Free/Freemium Version
NoYes
Premium Consulting/Integration Services
YesNo
Entry-level Setup FeeOptionalNo setup fee
Additional DetailsIBM 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
IBM SPSS ModelerLooker Studio
Features
IBM SPSS ModelerLooker Studio
Platform Connectivity
Comparison of Platform Connectivity features of Product A and Product B
IBM SPSS Modeler
8.6
2 Ratings
3% above category average
Looker Studio
-
Ratings
Connect to Multiple Data Sources8.22 Ratings00 Ratings
Extend Existing Data Sources8.22 Ratings00 Ratings
Automatic Data Format Detection9.01 Ratings00 Ratings
MDM Integration9.01 Ratings00 Ratings
Data Exploration
Comparison of Data Exploration features of Product A and Product B
IBM SPSS Modeler
9.0
1 Ratings
7% above category average
Looker Studio
-
Ratings
Visualization9.01 Ratings00 Ratings
Interactive Data Analysis9.01 Ratings00 Ratings
Data Preparation
Comparison of Data Preparation features of Product A and Product B
IBM SPSS Modeler
9.0
1 Ratings
10% above category average
Looker Studio
-
Ratings
Interactive Data Cleaning and Enrichment9.01 Ratings00 Ratings
Data Transformations9.01 Ratings00 Ratings
Data Encryption9.01 Ratings00 Ratings
Built-in Processors9.01 Ratings00 Ratings
Platform Data Modeling
Comparison of Platform Data Modeling features of Product A and Product B
IBM SPSS Modeler
9.0
1 Ratings
7% above category average
Looker Studio
-
Ratings
Multiple Model Development Languages and Tools9.01 Ratings00 Ratings
Automated Machine Learning9.01 Ratings00 Ratings
Single platform for multiple model development9.01 Ratings00 Ratings
Self-Service Model Delivery9.01 Ratings00 Ratings
Model Deployment
Comparison of Model Deployment features of Product A and Product B
IBM SPSS Modeler
9.0
1 Ratings
6% above category average
Looker Studio
-
Ratings
Flexible Model Publishing Options9.01 Ratings00 Ratings
Security, Governance, and Cost Controls9.01 Ratings00 Ratings
BI Standard Reporting
Comparison of BI Standard Reporting features of Product A and Product B
IBM SPSS Modeler
-
Ratings
Looker Studio
7.6
55 Ratings
6% below category average
Pixel Perfect reports00 Ratings7.339 Ratings
Customizable dashboards00 Ratings8.254 Ratings
Report Formatting Templates00 Ratings7.353 Ratings
Ad-hoc Reporting
Comparison of Ad-hoc Reporting features of Product A and Product B
IBM SPSS Modeler
-
Ratings
Looker Studio
8.1
54 Ratings
4% above category average
Drill-down analysis00 Ratings8.946 Ratings
Formatting capabilities00 Ratings8.350 Ratings
Integration with R or other statistical packages00 Ratings5.625 Ratings
Report sharing and collaboration00 Ratings9.753 Ratings
Report Output and Scheduling
Comparison of Report Output and Scheduling features of Product A and Product B
IBM SPSS Modeler
-
Ratings
Looker Studio
8.7
54 Ratings
6% above category average
Publish to Web00 Ratings8.148 Ratings
Publish to PDF00 Ratings9.747 Ratings
Report Versioning00 Ratings8.335 Ratings
Report Delivery Scheduling00 Ratings8.437 Ratings
Delivery to Remote Servers00 Ratings9.020 Ratings
Data Discovery and Visualization
Comparison of Data Discovery and Visualization features of Product A and Product B
IBM SPSS Modeler
-
Ratings
Looker Studio
6.5
53 Ratings
17% below category average
Pre-built visualization formats (heatmaps, scatter plots etc.)00 Ratings8.453 Ratings
Location Analytics / Geographic Visualization00 Ratings8.150 Ratings
Predictive Analytics00 Ratings5.027 Ratings
Pattern Recognition and Data Mining00 Ratings4.63 Ratings
Best Alternatives
IBM SPSS ModelerLooker Studio
Small Businesses
Jupyter Notebook
Jupyter Notebook
Score 8.6 out of 10
Supermetrics
Supermetrics
Score 9.9 out of 10
Medium-sized Companies
Posit
Posit
Score 10.0 out of 10
Supermetrics
Supermetrics
Score 9.9 out of 10
Enterprises
Posit
Posit
Score 10.0 out of 10
IBM Analytics Engine
IBM Analytics Engine
Score 7.3 out of 10
All AlternativesView all alternativesView all alternatives
User Ratings
IBM SPSS ModelerLooker Studio
Likelihood to Recommend
8.8
(8 ratings)
8.7
(56 ratings)
Likelihood to Renew
-
(0 ratings)
9.0
(1 ratings)
Usability
8.6
(2 ratings)
8.5
(7 ratings)
Support Rating
10.0
(1 ratings)
6.7
(10 ratings)
User Testimonials
IBM SPSS ModelerLooker Studio
Likelihood to Recommend
IBM
Fast NLP analytics are very easy in SPSS Modeler because there is a built-in interface for classifying concepts and themes and several pre-built models to match the incoming text source. The visualizations all match and help present NLP information without substantial coding, typically required for word clouds and such. SPSS Modeler is good at attaining results faster in general, and the visual nature of the code makes a good tool to have in the data science team's repository. For younger data scientists, and those just interested, it is a good tool to allow for exploring data science techniques.
Read full review
Google
Looker Studio is well-suited for those wanting to analyze web/site data and performance quickly. It is simple enough to learn/use for quick report-building or drilling into data. Looker Studio is easier to use/understand than the GA4 console and thus has a better UI/UX. It is an efficient tool for fast, simple data needs—especially for team members with limited analytical capabilities and knowledge.
Read full review
Pros
IBM
  • Combine text and data
  • Provide facilities for all phases of the data mining process.
  • Use a node and stream paradigm to easily and quickly create models.
Read full review
Google
  • Self-service
  • Easy to use, point and click
  • Little to no training required
  • Easy to share internally and externally
  • Rich visualizations
  • Canned reports
  • Easy to copy/paste/dupe existing reports
  • Ability to join data sets
  • Easy integration with various data sources
  • Flexible data integrations, including lowest common denominator (CSV, XLS, G-Sheets)
  • Wide range of APIs
  • Secure / authentication via Google SSO
  • Easy to share / re-assign ownership of reports and data sources
Read full review
Cons
IBM
  • Has very old style graphs, with lots of limitations.
  • Some advanced statistical functions cannot be done through the menu.
  • The data connectivity is not that extensive.
  • It's an expensive tool.
Read full review
Google
  • Few functionalities are very exclusive only for data studio.
  • It's time taking to load data and at the same time only single Data source can be connected.
  • When editing the reports you have to switch between Edit and View mode to see how does the change looks like.
Read full review
Likelihood to Renew
IBM
No answers on this topic
Google
It is the simplest and least expensive way for us to automate our reporting at this time. I like the ability to customize literally everything about each report, and the ability to send out reports automatically in emails. The only issue we have been having recently is a technical glitch in the automatic email report. Sadly, there is almost no support for this tool from Google, but is also free, so that is important to take into consideration
Read full review
Usability
IBM
The ability to do predictive modeling, text analytics for both structured & unstructured data, decision management, optimization, and support for various data sources
Read full review
Google
It is not ideal and requires time and dedication to understand how to work with it. Also, it has a lot of limitations around data it can accept. But in most cases, this tool is sufficient for everyday tasks of product and marketing departments. I wouldn't say that the interface is very user-friendly, but for people who regularly work with analytical tools, it must be ok.
Read full review
Support Rating
IBM
The online support board is helpful and the free add ons are incredibly appreciated.
Read full review
Google
I give it a lower support rating because it seems like our Dev team hasn't gotten the support they need to set up our database to connect. Seems like we hit a roadblock and the project got put on pause for dev. That sucks for me because it is harder to get the dev team to focus on it if they don't get the help they need to set it up.
Read full review
Alternatives Considered
IBM
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.
Read full review
Google
The free version of Looker Studio is still better than the leading enterprise-embedded BI tools, despite its weaknesses. The leading embedded BI platforms have terrible visualizations that can be spotted a mile away. They are also primarily locked to a grid, making it very hard to fully customize. The price point is also a major deterrent, since users end up paying for lots of features they might never use. Looker Studio has weaknesses on the blending and modeling side, but we've been able to get by via connection to GBQ and transformation done in dbt.
Read full review
Return on Investment
IBM
  • Positive - Ease of decision making and reduction in product life cycle time.
  • Positive - Gives entirely new perspective with the help of right team. Helps expanding the portfolio.
  • Negative - Needs to have good understanding about mathematical modelling, of which talent is rare and expensive. Hence, increase the costs for R&D and manpower.
Read full review
Google
  • Free, so the only investment is time
  • Because it doesn't have native support of non-Google sources, it can cost more money than Tableau
  • The time spent formatting the templates or building connectors can have a negative impact on ROI
  • As a agency, charging for the reporting service is profitable after the first month or two after building the dashboard.
Read full review
ScreenShots

IBM SPSS Modeler Screenshots

Screenshot of Use a single run to test multiple modeling methods, compare results and select which model to deploy. Quickly choose the best performing algorithm based on model performance.Screenshot of Explore geographic data, such as latitude and longitude, postal codes and addresses. Combine it with current and historical data for better insights and predictive accuracy.Screenshot of Capture key concepts, themes, sentiments and trends by analyzing unstructured text data. Uncover insights in web activity, blog content, customer feedback, emails and social media comments.Screenshot of Use R, Python, Spark, Hadoop and other open source technologies to amplify the power of your analytics. Extend and complement these technologies for more advanced analytics while you keep control.