StarDust Segmentation

Stardust Segmentation

Segmentation Models/Analysis


TIMi, the second-generation data mining software package, and its StarDust Module allow you to easily segment your customer base using the most advanced segmentation methodology.

StarDust allows you to visually explore in real-time, on your computer screen, the entire studied population. The rendering of the 3D display is performed using hardware-accelerated OpenGL libraries. These high-performance libraries allow to smooth display of millions of customers in real time.

A powerful visualization engine is very important inside segmentation analysis software (compared to software that creates predictions/classifications). Indeed, in a segmentation analysis, the only way to validate the segmentation that you are creating is to "visualize" the segmentation. This is why TIMi’s StarDust Module offers real-time visualization of your results using an engine that employs the latest advances in hardware-accelerated 3D  rendering. No other data mining software offers similar functionality.

StarDust’s analytical engine creates high-quality segmentation of large databases (several gigabytes) in just a few minutes. StarDust can easily process databases containing millions of customers.

This visual exploration allows you to:

  • Find interesting figures about your customers and data:
    • Detect (multivariate) outliers and non-valid data.
    • Find Segments of customers with similar behavior.
    • Validate from a business-perspective the different segments using intuitive bar charts easily comprehensible by a business-user.
    • Automatically create HTML reports that include many charts and histograms explaining your segments from a business-perspective.
    • Discover hidden multivariate patterns inside your data.
    • Explain the profile of your targets in more detail, as generated by the binary classification tool.
  • Create "Segmentation Models" that you can use later on to:
    • automatically select a subset of the population that is used to construct a (binary or continuous) predictive model.
    • automatically project the segmentation on an updated and/or larger apply dataset.
  • Perform text-mining analysis of a corpus of documents: you can automatically find the different "Themes" of the text documents (using latent semantic indexing (LSI)) and automatically assign new documents to a "theme".

Nearly anybody can easily create predictive models using TIMi. Creating a segmentation model with StarDust is slightly more complex because the user must visually validate all the segments from a business point-of-view. Thus, StarDust requires more analytical knowledge than TIM, which is fully automated. However, there are training videos and other resources available to get users started with StarDust.

The analytical engine of StarDust is very versatile because it integrates many small algorithms classically used for segmentation analysis, including, but not limited to: PCA algorithm, quantile-recoding algorithm, “Minimum spanning tree” algorithm, as well as many variations of “Ward's algorithm” and the “K-Means algorithm”. You can also use many distance definitions: Pearson-Distance, Cosine-Distance, Euclidean-Distance, and others. All these algorithms and options are easily accessed and applied with just a few mouse clicks!

With StarDust, segmentation-analysis has never been so fast and easy!


Contact 20Q Group to learn more about TIM Data Mining and Predictive Analytics Are you ready to learn more about StarDust can help you quickly and easily segment your customer base?

 Contact us here or call +1 414 367 9207.

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