Marketing Analytics with SPSS or How to Manage Your Data for Insights

I spent the morning at a workshop hosted by SPSS (an IBM company) — thanks a bunch for the invitation.  Marketing analytics with SPSS sure have changed in the last 20 years since I started using them — sure there’s still regression and logit and discriminant, but there are lots of new tools, too.

Today, I’ll give you an overview of the cool new modules and features of SPSS and, over the next couple of days, I’ll provide more details for each one.

Through development or acquisition, SPSS has a full line of tools for predictive analysis from data planning and data collection through analysis, reporting, and deployment of solutions.  The diversity of tools and ability to buy modules individually allows customizable solutions for a variety of business and non-profit problems.

A valuable feature of all the SPSS software is that the various modules fit together seamlessly and share a similar interface, making it easy to move between modules and reducing the learning curve.  The products also interface with other software products such as Excel.

Today’s session on predictive analytics dealt primarily with data collection, text analysis, new features of SPSS version 19, data mining, and Cognos Business Intelligence software.

Data Collection

This program, actually a group of related products, simplifies the process of designing visually appealing surveys and deploy them using wizards.  Surveys can be deployed through various media, including online and mail, and can be translated into various languages.

Text Analysis

Competing with more established products like nVivo and Hyperresearch, marketing analytics with SPSS developed a text analysis program that uses native language to search a variety of textual materials to find patterns in word use. The categories are then collapsed into thematic patterns.  These categories are then imported into SPSS Statistics and are coded as dummy variables. Doing marketing analytics with SPSS offers advantages over prior strategies for analyzing unstructured data, which IBM estimates are the largest chunk of data out there.

SPSS New Analytics Features

SPSS is getting ready to release version 19, so they presented new features of the software.  Primarily, improvements have been made to make analysis run faster.  Another improvement is the ability to add text block to graphs removing the necessity of exporting graphs to a word processing program to add interpretations or other descriptions to the graphs.

Other changes have been made to make sharing data and output easier and allow for some modification of analysis by other users with only a browser.

Data Mining

Modeling software allows users to analyze vast amounts of data searching for unexpected patterns hidden within the data.  At lunch, someone asked how this differs from the basic SPSS data analysis and the answer is that it makes no assumptions regarding the relationships between variables while basic analysis requires at least a superficial understanding of the relationship, for instance, whether it’s linear.

Modeling software can handle text data in the way discussed above.  It can also export data to a server when more power is needed to analyze large data sets.

Cognos

IBM recently acquired Cognos, which provides business intelligence (BI) to track a firm’s Key Performance Indicators (KPIs).  Cognos software provides highly customizable marketing dashboards to increase understanding of the data and displaying it graphically.

Additional analytics tools

In addition, SPSS offers new modules to handle direct marketing, which allows customized offers to customers based on past behavior, as well as calculates Customer Lifetime Value (CLV), which is important for grouping customers and determining how to market to them.  There are new analytics tools to handle missing values and other data preparation tools to remove outliers, etc.  SPSS has also acquired AMOS, one of the top software packages for Structural Equation Modeling (what used to be called Causal Modeling) used for simultaneously evaluating constructs and relationships between constructs.

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