IBM SPSS Modeler vs. InMoment Text Analytics

Overview
ProductRatingMost Used ByProduct SummaryStarting Price
IBM SPSS Modeler
Score 7.8 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
InMoment Text Analytics
Score 9.0 out of 10
N/A
InMoment’s text analytics, powered by our Lexalytics, is a software-as-a-service specializing in cloud-based text analytics and sentiment analysis. The tool unlocks insights and sentiment analysis from large amounts of unstructured text.
$999
per month
Pricing
IBM SPSS ModelerInMoment Text Analytics
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
System Cost
$10,000.00
Offerings
Pricing Offerings
IBM SPSS ModelerInMoment Text Analytics
Free Trial
YesYes
Free/Freemium Version
NoNo
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
Best Alternatives
IBM SPSS ModelerInMoment Text Analytics
Small Businesses
Saturn Cloud
Saturn Cloud
Score 9.1 out of 10
IBM Watson Studio
IBM Watson Studio
Score 8.0 out of 10
Medium-sized Companies
Mathematica
Mathematica
Score 8.3 out of 10
PG Forsta HX Platform
PG Forsta HX Platform
Score 9.0 out of 10
Enterprises
Alteryx
Alteryx
Score 9.0 out of 10
PG Forsta HX Platform
PG Forsta HX Platform
Score 9.0 out of 10
All AlternativesView all alternativesView all alternatives
User Ratings
IBM SPSS ModelerInMoment Text Analytics
Likelihood to Recommend
10.0
(6 ratings)
9.0
(4 ratings)
Support Rating
10.0
(1 ratings)
-
(0 ratings)
User Testimonials
IBM SPSS ModelerInMoment Text Analytics
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
InMoment
Its compatibility with Microsoft Excel makes it a great platform. It is a powerful tuning, workbench, and reporting application that resides within Microsoft Excel. This ability helps data analysts instantly gain actionable and valuable insights.
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
InMoment
  • assign sentiment score
  • word cloud
  • Categorization
  • multilingual
  • has good visualization
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
InMoment
  • Sentence parsing can be even better
  • Sometimes cant predicts the sentiments
  • Reporting can be even better with best histograms and diagrams
  • Dash is somewhat difficult to understand
Read full review
Support Rating
IBM
The online support board is helpful and the free add ons are incredibly appreciated.
Read full review
InMoment
No answers on this topic
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
InMoment
It offers extensive text analysis capabilities and you can easily create a visual representation.
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
InMoment
  • Diffbot content extraction
  • The application integrates text analysis efficiently. I can identify changes and detect trends by evaluating posts, comments, tweets and other documentation on social media platforms and in the digital realm in general.
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.