Target the Right People More Effectively with IBM SPSS AnswerTree

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How do you determine which customer, or citizen group, best matches your offerings or programs? What if you had a way to avoid spending a lot of money and time trying to reach people and instead could more efficiently reach them—and increase your return on investment?

Segmentation eliminates the guesswork

The segmentation capabilities in IBM SPSS AnswerTree enable you to more accurately target people and eliminate the guesswork that many direct mail software solutions impose. Results from IBM SPSS AnswerTree can complement your direct mail software and eliminate your need to send offers to arbitrary groups of people—or everyone—on your mailing list.

Four powerful decision trees—including CHAID—to fit your data

IBM SPSS AnswerTree enables you to more efficiently target the right groups of people. Use scalable decision trees to reveal segments and predict how groups will respond to your promotions and programs. IBM SPSS AnswerTree gives you the widest choice of decision trees available through four powerful algorithms, including CHAID, so you can choose the best fit for your data.

IBM SPSS AnswerTree visually displays decision tree models—so you can easily see the groups that matter. At-a-glance evaluation graphs enable you to act on results quickly. Answer Tree's unrivaled analytical power, scalability, and presentation features give you a smarter, more effective way to discover significant groups and create profiles.

IBM SPSS AnswerTree 3.1 is available in English, Japanese, French, German, Italian, and Spanish. Contact your local office to find out more.

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Turn data into strategic information

With IBM SPSS AnswerTree, you can easily detect segments and patterns, such as "high-profit customers who are likely to respond to Web offerings" or "students who miss more than 45 days of school a year are twice as likely to drop out."

IBM SPSS AnswerTree's four scalable decision-tree algorithms—the most comprehensive and flexible decision-tree package available—enable you to uncover this valuable information and solve business problems. Read more about how IBM SPSS AnswerTree can help you:

Define Variable Properties - create your labels once, and the Define Variable Properties tool copies and presents your labels to the entire dataset

Define Variable Properties

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IBM SPSS AnswerTree Brochure (613KB)

This brochure describes how you can use IBM SPSS AnswerTree to target the right people more effectively. By revealing segments, using one of four scalable decision trees, you can predict how groups will respond to your promotions and programs.

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What's New in IBM SPSS AnswerTree 3.0 (220KB)

This document describes what's new in IBM SPSS AnswerTree 3.0 and compares IBM SPSS AnswerTree 3.0 with previous versions.

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AnswerTree client

Operating system: Windows 98, 2000 or Windows NT 4.0 with Service Pack 5 or higher
Hardware: Pentium-class processor, SVGA monitor and CD-ROM drive for installation
Minimum free drive space: 70MB for software
Minimum RAM: 64MB or more
Microsoft Internet Explorer 5.0 for reading help documents

IBM SPSS AnswerTree server

Windows NT Server, Windows 2000 Server or Windows 2000 Advanced Server:
- Hardware: Pentium-class processor, SVGA monitor and CD-ROM drive for installation
- Minimum free drive space: 70MB
- Minimum RAM: 64MB or more
Solaris 2.6, 7 and 8:
- Hardware: Ultra Sparc 2 (or better) and CD-ROM drive for installation
- Minimum free drive space: 70MB
- Minimum RAM: 256 MB

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Training

Introduction to IBM SPSS AnswerTree

This two-day course covers the principles and practice of the tree-based classification and regression methods available in IBM SPSS AnswerTree.

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Models: Spot Important Segments and Patterns Easily

IBM SPSS AnswerTree's intuitive diagrams ensure you can see the outcomes you care about. Because the diagrams display a snapshot of the segments, patterns and relationships in your data, they enable you to confidently make decisions.

You don't need to be a specialist to get results in IBM SPSS AnswerTree. You can automatically generate trees all at once. Or, interactively create trees by identifying the factors yourself to work with groups as they are formed.

As you look from the top of your tree to the bottom, each branch represents the next-best predictor. Each node represents a unique segment—enabling you to see the groups in your data.

The information highlighted in gray shows the target variable, "payback," the percentage of people who repaid a previous loan. AnswerTree determined 75 percent of the people in this segment will repay loans.

A financial services company uses IBM SPSS AnswerTree to determine the best loan candidates. The information highlighted in gray shows the target variable, "payback," the percentage of people who repaid a previous loan. IBM SPSS AnswerTree determined 75 percent of the people in this segment will repay loans. By focusing on the segment that includes the highest percentage of people who pay back loans, the company can decrease exposure to debt.

IBM SPSS AnswerTree's model-building features help you quickly reach results:

Get the best fit for your models—choose simple defaults or fine-tune results with expert model-building options
Clearly see results—collapse and expand branches without having to delete branches in your tree
Zoom to specific nodes of interest to better manage large trees

Uncover more details for deeper understanding of each node using summary statistics, gains charts and evaluation graphs
Present results using a variety of formats—see everything you need to know about your nodes using dynamically linked bar charts, summary statistics and a data viewer

Scalability: Leverage Your Data Across Your Organization

Because IBM SPSS AnswerTree's algorithms are built with scalability in mind, you can work with your data more efficiently. But sometimes you need more processing power than your desktop computer provides—especially if you're working with large datasets, such as a catalog mailing list. If your data has outgrown your desktop computer, run IBM SPSS AnswerTree on a server.

You can leverage your IT investment when using a larger server machine with a client-server version of IBM SPSS AnswerTree installed. The distributed architecture means you process data where they can be handled more effectively. For example, if you have multiple users, you can analyze data on the server rather than running data on users' individual machines.

Act on Results Quickly and Efficiently

See the information that enables you to act on results quickly—using IBM SPSS AnswerTree's unique evaluation graphs, including gains, response, lift, profit and ROI charts.

These at-a-glance charts provide summaries of selected segments—giving you a clear picture of your results. For example, looking at a gains chart, a telecommunications company could determine what percentage of likely churners to target when creating a customer retention campaign.

$Lift charts and other types of evaluation graphs empower you to identify ideal cutoff points — such as the segment most likely to have good credit. Lift charts, in particular, enable you to see the gains summary table graphically and interpret results. In this example, credit ranking is the target variable, and the lift chart shows the \'good\' responses (Y-axis) relative to the entire population (X-axis). We see that the top 20 percent of the total population is twice as likely to belong in the \'good\' credit-ranking group.$

Lift charts and other types of evaluation graphs empower you to identify ideal cutoff points — such as the segment most likely to have good credit. Lift charts, in particular, enable you to see the gains summary table graphically and interpret results. In this example, credit ranking is the target variable, and the lift chart shows the "good" responses (Y-axis) relative to the entire population (X-axis). We see that the top 20 percent of the total population is twice as likely to belong in the "good" credit-ranking group.

Deployment: Put Your Model to Work for You

Once you have results, how do you ensure your organization uses them effectively? Take action based on your findings when you apply concrete decision rules to new data. For example, a financial services company might use IBM SPSS AnswerTree to discover a rule about bad credit risk. The company can write this information to a database or an SPSS file using SQL or SPSS syntax. The organization can then use these scores to determine which groups of people are most likely to repay loans.

Algorithms: Build Better Models with Unprecedented Analytical Power

Different types of data work better with different algorithms, and your organization likely has many types of data—which change over time. Therefore, you need the ability to try different types of decision-tree algorithms with your data to find the best fit.

IBM SPSS AnswerTree gives you four powerful algorithms that empower you to select the right one for your specific data. For example, you can choose one of the four algorithms and build a model, then compare it against another algorithm to determine which one works best for your dataset. Whether you're analyzing purchase amounts, product categories, demographics or satisfaction ratings, only IBM SPSS AnswerTree gives you the widest range of decision-tree algorithms available today:

CHAID

A fast, statistical, multi-way tree algorithm, which explores data quickly and efficiently and builds segments and profiles with respect to the desired outcome. A CHAID tree is a decision tree that is constructed by splitting subsets of the space into two or more child (nodes) repeatedly, beginning with the entire data set.

Exhaustive CHAID

A thorough, statistical, multi-way tree algorithm that explores data exhaustively. Exhaustive search CHAID was proposed by Biggs et al. (1991). Biggs suggests finding the best split by merging similar pairs continuously until only a single pair remains. The set of categories with the largest significance is taken to be the best split for that predictor variable.

Classification and Regression Tree (C&RT)

A complete binary tree algorithm, which partitions data and produces accurate homogeneous subsets. The C&RT method of Breiman et al. (1984) generates binary decision trees. The C&RT tree is constructed by splitting subsets of the data set using all predictor variables to create two child nodes repeatedly, beginning with the entire data set. The best predictor is chosen using a variety of impurity or diversity measures. The goal is to produce subsets of the data which are as homogeneous as possible with respect to the target variable.

QUEST

A statistical algorithm that selects variables without bias and builds an accurate binary tree quickly and efficiently. QUEST stands for Quick, Unbiased, Efficient, Statistical Tree. The original method is described in Loh and Shih (1997). It is a tree-structured classification algorithm that yields a binary decision tree like C&RT. A binary tree allows techniques such as pruning, direct stopping rules and surrogate splits to be used. Unlike CHAID and C&RT, which handle variable selection and split point selection simultaneously during the tree growing process, QUEST deals with them separately.

QUEST was demonstrated to be much better than exhaustive search methods in terms of variable selection bias and computational cost. In terms of classification accuracy, variability of split points and tree size, however, there is still no clear winner when univariate splits are used.

Learn more about IBM SPSS AnswerTree's four powerful algorithms in the IBM SPSS AnswerTree Algorithm Summary white paper.