PRODUCT FEATURES - FASTSTATS

Matrix believes that FastStats is the ideal analytics tool for any Financial-Clarity clients who have Market Insight or Data Analysis teams. FastStats is a pioneering data visualisation tool for train of thought analysis. FastStats employs an easy to use Windows interface, enabling analysts to gain valuable insight which increases the speed and efficiency of everyday tasks.

FastStats
Matrix FastStats Interface

FastStats allows the user to:

  • Analyse target segments with easy data selections and cross tabulations;
  • Produce stunning charts and Venn diagrams;
  • Create customer and market segments directly from visualisations;
  • Produce PDF reports and transfer analysis into Excel, Word and PowerPoint;
  • View and sort sample data on grids;
  • Export data in a wide variety of formats for linkage with other systems;
  • Perform basket and transaction analysis;
  • Create algorithmic expressions and use wizards to derive new variables without the need for IT assistance, and
  • Create and save templates and reports for quicker analysis and distribution of regular tasks.

Matrix FastStats Interface

Ease of Use

Using a consistent and intuitive “drag and drop” approach throughout, FastStats provides a unique combination of speed and power for data exploration and understanding. Every drag and drop action automatically results in a query that can be saved and reused with ease. FastStats analysis options are virtually unlimited as any technique can be applied to any results in any order.

FastStats contains a number of key analysis tools to fulfill segmentation and targeting requirements. Standard tools include Selections, Cubes, Trees, Charts, Venn diagrams and Data Grids. These tools can be used to develop analysis workbooks that the user can save and use to create reports for distribution. Highly targeted analysis can be created by highlighting areas of visualisations and creating new segments using interactive drag and drop.

Venn Diagrams and Data Grids

The base module can also be extended with Microsoft MapPoint integration allowing for geographic analysis and segmentation within a mapping environment. This allows users to overlay bespoke regions and individual branches for detailed analysis.

Venn Diagrams and Data Grids

Venn Diagrams and Data Grids

Wizard driven processes

FastStats includes easy-to-follow, step-by-step wizards for transaction and basket analysis. It also lets you upload third party datasets without the need for an underlying database model change.

Additional wizards provide help with data aggregation, geographic analysis and new variable creation. All wizards are aimed at speeding up analysis and allowing users to maximise what they can achieve within FastStats without the need for 3rd party involvement from IT resources.

Optional Modelling Module

Understanding the characteristics of customers and strengths and weaknesses across market sectors is a prerequisite of any market analytics. The Modelling Module within FastStats uses market penetration, customer profiling, Predictive Weight of Evidence (PWE) scoring, clustering and decision trees (including CHAID) to help inform decisions.

Data modelling using FastStats is not only powerful, but fast, intuitive and simple to use. Profiling allows comparison between your current customers and any data universe within the RMS data. Processing millions of records in just a few seconds, FastStats produces a profile report which highlights the characteristics that are statistically most prevalent within your existing customer base or any subset selection.

FastStats also allows you to compare two groups of customers that have been acquired from different channels e.g. direct versus intermediary, comparing regions, mortgage types, or brands. This means that significant characteristics can be identified to drive smarter distribution and integration strategies.

Market Penetration and Potential reports within FastStats show the sectors in which you are under- and over- represented. This enables you to develop strategies for those markets offering the largest potential opportunities and avoid those that are already saturated.

Data modelling – predict the behaviour of customers

Once your customer profile has been created a model can be applied which scores, ranks and segments every record in the RMS data. FastStats offers three main modelling techniques:

Profiling

Using a patented Predictive Weight of Evidence (PWE) method that combines widely recognised Information Theory and Bayesian Probability, this technique scores individual customers and is fast, automatic and requires a minimum of user input.

Profiling

Decision Tree Models (including CHAID)

Using a patented Predictive Weight of Evidence (PWE) method that combines widely recognised Information Theory and Bayesian Probability, this technique scores individual customers and is fast, automatic and requires a minimum of user input.

Decision Tree Models (including CHAID)

Clustering

Clustering uses the well-proven K-Means technique to allocate each point to its nearest cluster centre. However, the FastStats implementation introduces a number of powerful options including a multi-stage (Divisive or Agglomerative) clustering process. The user can also control the maximum number of iterations allowed, calculate the cluster proximity measure using Euclidean or City Block approaches, and finally define how the initial cluster centres are calculated (Frequency or Random).

Clustering

The Modelling Module is available as a per named user bolt-on and is simple to deploy at any time.