IntroductionIBM Predictive Customer Intelligence gives you the information and insight that you need to provide proactive service to your customers. The information can help you to develop a consistent customer contact strategy and improve your relationship with your customers.IBM Predictive Customer Intelligence brings together, in a single solution, the ability to do the following tasks:Determine the best offer for a customer.Retain customers that are likely to churn.Segment your customers, for example, by family status and salary.Identify the most appropriate channel to deliver an offer, for example, by email, telephone call, or application.This solution ensures that all interactions with customers are coordinated and optimized. IBM Predictive Customer Intelligence gives you the ability to sift quickly through millions of customers and know who to contact, when, and with what action.The following steps define the process:Understand the customer. Predictive modeling helps you to understand what market segments each customer falls into, what products they are interested in, and what offers they are most likely to respond to.Define possible actions and the rules and models that determine which customers are eligible for which offers.After the best action is identified, deliver the recommendation to the customer. AudienceThis guide is intended to provide users with an understanding of how the IBM Predictive Customer Intelligence solution works. It is designed to help people who are planning to implement IBM Predictive Customer Intelligence know what tasks are involved. Finding information To find product documentation on the web, including all translated documentation, access IBM Knowledge Center (www.ibm.com/support/knowledgecenter/SSCJHT_1.1.1). PDF versions of the documents are available from the Predictive Customer Intelligence version 1.1.1 product documentation page (www.ibm.com/support/docview.wss?uid=swg27048306). Accessibility features Accessibility features help users who have a physical disability, such as restricted mobility or limited vision, to use information technology products. Some of the components included in the IBM Predictive Customer Intelligence have accessibility features.IBM Predictive Customer Intelligence HTML documentation has accessibility features. PDF documents are supplemental and, as such, include no added accessibility features. Forward-looking statements This documentation describes the current functionality of the product. References to items that are not currently available may be included. No implication of any future availability should be inferred. Any such references are not a commitment, promise, or legal obligation to deliver any material, code, or functionality. The development, release, and timing of features or functionality remain at the sole discretion of IBM. Samples disclaimer Sample files may contain fictional data manually or machine generated, factual data compiled from academic or public sources, or data used with permission of the copyright holder, for use as sample data to develop sample applications. Product names referenced may be the trademarks of their respective owners. Unauthorized duplication is prohibited.

Introduction

IBM® Predictive Customer Intelligence gives you the information and insight that you need to provide proactive service to your customers. The information can help you to develop a consistent customer contact strategy and improve your relationship with your customers.

IBM Predictive Customer Intelligence brings together, in a single solution, the ability to do the following tasks:

Determine the best offer for a customer.

Retain customers that are likely to churn.

Segment your customers, for example, by family status and salary.

Identify the most appropriate channel to deliver an offer, for example, by email, telephone call, or application.

This solution ensures that all interactions with customers are coordinated and optimized. IBM Predictive Customer Intelligence gives you the ability to sift quickly through millions of customers and know who to contact, when, and with what action.

The following steps define the process:

Understand the customer. Predictive modeling helps you to understand what market segments each customer falls into, what products they are interested in, and what offers they are most likely to respond to.

Define possible actions and the rules and models that determine which customers are eligible for which offers.

After the best action is identified, deliver the recommendation to the customer.

Audience

This guide is intended to provide users with an understanding of how the IBM Predictive Customer Intelligence solution works. It is designed to help people who are planning to implement IBM Predictive Customer Intelligence know what tasks are involved.

Finding information

To find product documentation on the web, including all translated documentation, access IBM Knowledge Center (www.ibm.com/support/knowledgecenter/SSCJHT_1.1.1).

PDF versions of the documents are available from the Predictive Customer Intelligence version 1.1.1 product documentation page (www.ibm.com/support/docview.wss?uid=swg27048306).

Accessibility features

Accessibility features help users who have a physical disability, such as restricted mobility or limited vision, to use information technology products. Some of the components included in the IBM Predictive Customer Intelligence have accessibility features.

IBM Predictive Customer Intelligence HTML documentation has accessibility features. PDF documents are supplemental and, as such, include no added accessibility features.

Forward-looking statements

This documentation describes the current functionality of the product. References to items that are not currently available may be included. No implication of any future availability should be inferred. Any such references are not a commitment, promise, or legal obligation to deliver any material, code, or functionality. The development, release, and timing of features or functionality remain at the sole discretion of IBM.

Samples disclaimer

Sample files may contain fictional data manually or machine generated, factual data compiled from academic or public sources, or data used with permission of the copyright holder, for use as sample data to develop sample applications. Product names referenced may be the trademarks of their respective owners. Unauthorized duplication is prohibited.

Extend your solutions with the IBM Predictive Customer Intelligence Usage ReportUse the IBM Predictive Customer Intelligence Usage Report to monitor the effectiveness of your IBM Predictive Customer Intelligence solution.The IBM Predictive Customer Intelligence Usage Report displays the number of offers that are presented to customers and can be configured to show the number of offers that are accepted and rejected.Functional accelerator artifactsThe IBM Predictive Customer Intelligence Usage Report functional accelerator includes the following artifacts.

Extend your solutions with the IBM Predictive Customer Intelligence Usage Report

Use the IBM® Predictive Customer Intelligence Usage Report to monitor the effectiveness of your IBM Predictive Customer Intelligence solution.

The IBM Predictive Customer Intelligence Usage Report displays the number of offers that are presented to customers and can be configured to show the number of offers that are accepted and rejected.

Functional accelerator artifacts
The IBM Predictive Customer Intelligence Usage Report functional accelerator includes the following artifacts.

Functional accelerator artifactsThe IBM Predictive Customer Intelligence Usage Report functional accelerator includes the following artifacts.IBM Cognos Business Intelligence reportsPCI_PCIReports_Usage_CognosContent.zip PCI_PCIReports_Usage_FMProject.zip PCI_Images.zip The report is described in IBM Predictive Customer Intelligence Usage ReportThe IBM Predictive Customer Intelligence Usage Report monitors the number of offers or recommendations that are provided. The report also records the response rates that are broken down by type of response..IBM DB2 databasePCI_PCIReports_Usage_Data.zipExtend your solutions with the IBM Predictive Customer Intelligence Usage ReportUse the IBM Predictive Customer Intelligence Usage Report to monitor the effectiveness of your IBM Predictive Customer Intelligence solution.

Functional accelerator artifacts

The IBM® Predictive Customer Intelligence Usage Report functional accelerator includes the following artifacts.

IBM Cognos® Business Intelligence reports

PCI_PCIReports_Usage_CognosContent.zip

PCI_PCIReports_Usage_FMProject.zip

PCI_Images.zip

The report is described in IBM Predictive Customer Intelligence Usage Report.

IBM DB2® database

PCI_PCIReports_Usage_Data.zip

Parent topic: Extend your solutions with the IBM Predictive Customer Intelligence Usage Report

Functional accelerator installationThe IBM Predictive Customer Intelligence Usage Report functional accelerator is for use with IBM Predictive Customer Intelligence.The functional accelerator package contains the following parts:IBM DB2 databases.IBM Cognos Business Intelligence reports and Framework Manager models and packages.To install the functional accelerator, you must perform the following steps:Download the functional accelerator from IBM AnalyticsZone (www.ibm.com/analyticszone).Create the sample databases on the data node computer.Install the IBM Cognos Content on the Cognos Analytics node.Functional accelerator prerequisitesBefore you install the functional accelerator, you must have a fully configured environment.Download the functional acceleratorYou must download the IBM Predictive Customer Intelligence accelerators from IBM AnalyticsZone.Creating the databaseTo use the IBM Predictive Customer Intelligence functional accelerator, you must create a database.Deploy the IBM Cognos contentFor IBM Cognos Business Intelligence, you must catalog the database, create a data source connection, and then deploy the content files for the IBM Predictive Customer Intelligence functional accelerator.Copying the functional accelerator license files to each computerAfter you install the functional accelerator, you must copy the license folder to each computer on which you use the IBM Predictive Customer Intelligence functional accelerator.

Functional accelerator installation

The IBM® Predictive Customer Intelligence Usage Report functional accelerator is for use with IBM Predictive Customer Intelligence.

The functional accelerator package contains the following parts:

IBM DB2® databases.

IBM Cognos® Business Intelligence reports and Framework Manager models and packages.

To install the functional accelerator, you must perform the following steps:

Download the functional accelerator from IBM AnalyticsZone (www.ibm.com/analyticszone).

Create the sample databases on the data node computer.

Install the IBM Cognos Content on the Cognos Analytics node.

Functional accelerator prerequisites
Before you install the functional accelerator, you must have a fully configured environment.

Download the functional accelerator
You must download the IBM Predictive Customer Intelligence accelerators from IBM AnalyticsZone.

Creating the database
To use the IBM Predictive Customer Intelligence functional accelerator, you must create a database.

Deploy the IBM Cognos content
For IBM Cognos Business Intelligence, you must catalog the database, create a data source connection, and then deploy the content files for the IBM Predictive Customer Intelligence functional accelerator.

Copying the functional accelerator license files to each computer
After you install the functional accelerator, you must copy the license folder to each computer on which you use the IBM Predictive Customer Intelligence functional accelerator.

Functional accelerator prerequisitesBefore you install the functional accelerator, you must have a fully configured environment.You must have administration rights and have the ability to copy files between computers.Functional accelerator installationThe IBM Predictive Customer Intelligence Usage Report functional accelerator is for use with IBM Predictive Customer Intelligence.

Functional accelerator prerequisites

Before you install the functional accelerator, you must have a fully configured environment.

You must have administration rights and have the ability to copy files between computers.

Parent topic: Functional accelerator installation

Download the functional acceleratorYou must download the IBM Predictive Customer Intelligence accelerators from IBM AnalyticsZone.Go to IBM AnalyticsZone (www.ibm.com/analyticszone).Click Downloads, and under Predictive Customer Intelligence Accelerators, click View all PCI downloads.Click More details for the accelerator that you want to download.If you are not signed in, click Sign In to Download. You must enter your IBM ID. If you do not have an IBM ID, you must register to create one.Click Download.Go to the directory where you downloaded the functional accelerator.Decompress the file.Functional accelerator installationThe IBM Predictive Customer Intelligence Usage Report functional accelerator is for use with IBM Predictive Customer Intelligence.

Download the functional accelerator

You must download the IBM® Predictive Customer Intelligence accelerators from IBM AnalyticsZone.

Procedure

Go to IBM AnalyticsZone (www.ibm.com/analyticszone).

Click Downloads, and under Predictive Customer Intelligence Accelerators, click View all PCI downloads.

Click More details for the accelerator that you want to download.

If you are not signed in, click Sign In to Download. You must enter your IBM ID. If you do not have an IBM ID, you must register to create one.

Click Download.

Go to the directory where you downloaded the functional accelerator.

Decompress the file.

Parent topic: Functional accelerator installation

Creating the databaseTo use the IBM Predictive Customer Intelligence functional accelerator, you must create a database. You run one script to create the database, and then run another script to populate the database.Copy the functional accelerator database content file from the computer where you downloaded them to the data node computer: The IBM Predictive Customer Intelligence Usage Report functional accelerator database file is PCI_1.0_PCIReports_Usage\Database\PCI_PCIReports_Usage_Data.zip. A database that is named PCI is created.On the data node computer, decompress the file.On Microsoft Windows operating systems, do the following steps:Log on to the data node computer as the DB2 instance owner user.Go to the folder where you decompressed the functional accelerator content files.In the uncompressed folder, double-click Install_DB.bat.Double-click Load_Data.bat.On Linux operating systems, do the following steps:Log on to the data node computer as root user.Open a terminal window, and go to the directory where you decompressed the functional accelerator content files.If you copied the content files to the home directory for the root user, you might have to move the files to another directory that is not in the root home directory so that you can run the scripts. Type the following command to change the permissions for the files:chmod -R 755 *sh Change to the database instance owner.For example, su db2inst1In the uncompressed folder, run sh ./Install_DB.sh.Run sh ./Load_Data.sh.Verify that the tables are created and the data is successfully loaded into the input tables by checking the out.log file. On Microsoft Windows operating systems, the log file is in the functional accelerator name folder. On Linux operating systems, the log file is in the db2inst1 home folder. Search for rows were rejected in the log file. The value should be zero, if it is not, there are data load issues.Functional accelerator installationThe IBM Predictive Customer Intelligence Usage Report functional accelerator is for use with IBM Predictive Customer Intelligence.

Creating the database

To use the IBM® Predictive Customer Intelligence functional accelerator, you must create a database.

You run one script to create the database, and then run another script to populate the database.

Procedure

Copy the functional accelerator database content file from the computer where you downloaded them to the data node computer:

The IBM Predictive Customer Intelligence Usage Report functional accelerator database file is PCI_1.0_PCIReports_Usage\Database\PCI_PCIReports_Usage_Data.zip. A database that is named PCI is created.

On the data node computer, decompress the file.

On Microsoft Windows operating systems, do the following steps:

Log on to the data node computer as the DB2® instance owner user.

Go to the folder where you decompressed the functional accelerator content files.

In the uncompressed folder, double-click Install_DB.bat.

Double-click Load_Data.bat.

On Linux operating systems, do the following steps:

Log on to the data node computer as root user.

Open a terminal window, and go to the directory where you decompressed the functional accelerator content files.

Note: If you copied the content files to the home directory for the root user, you might have to move the files to another directory that is not in the root home directory so that you can run the scripts.

Type the following command to change the permissions for the files:

chmod -R 755 *

sh

Change to the database instance owner. For example, su db2inst1

In the uncompressed folder, run sh ./Install_DB.sh.

Run sh ./Load_Data.sh.

What to do next

Verify that the tables are created and the data is successfully loaded into the input tables by checking the out.log file.

On Microsoft Windows operating systems, the log file is in the functional accelerator name folder. On Linux operating systems, the log file is in the db2inst1 home folder.

Search for "rows were rejected" in the log file. The value should be zero, if it is not, there are data load issues.

Parent topic: Functional accelerator installation

Deploy the IBM Cognos contentFor IBM Cognos Business Intelligence, you must catalog the database, create a data source connection, and then deploy the content files for the IBM Predictive Customer Intelligence functional accelerator.Functional accelerator installationThe IBM Predictive Customer Intelligence Usage Report functional accelerator is for use with IBM Predictive Customer Intelligence.Moving the IBM Cognos contentYou must copy the IBM Cognos content for the IBM Predictive Customer Intelligence functional accelerator to the appropriate locations in your IBM Cognos installation to be able to deploy the content.Creating a data source connection to the functional accelerator databaseYou must create a data source connection to the IBM Predictive Customer Intelligence functional accelerator database.Deploy the IBM Cognos reportsYou must deploy the IBM Predictive Customer Intelligence functional accelerator reports using IBM Cognos Administration.

Deploy the IBM Cognos content

For IBM® Cognos® Business Intelligence, you must catalog the database, create a data source connection, and then deploy the content files for the IBM Predictive Customer Intelligence functional accelerator.

Moving the IBM Cognos content
You must copy the IBM Cognos content for the IBM Predictive Customer Intelligence functional accelerator to the appropriate locations in your IBM Cognos installation to be able to deploy the content.

Creating a data source connection to the functional accelerator database
You must create a data source connection to the IBM Predictive Customer Intelligence functional accelerator database.

Deploy the IBM Cognos reports
You must deploy the IBM Predictive Customer Intelligence functional accelerator reports using IBM Cognos Administration.

Parent topic: Functional accelerator installation

Moving the IBM Cognos contentYou must copy the IBM Cognos content for the IBM Predictive Customer Intelligence functional accelerator to the appropriate locations in your IBM Cognos installation to be able to deploy the content.Copy the IBM Cognos content from the computer where you downloaded the functional accelerator to the Cognos_Install_location\Deployment folder on the Cognos Analytics node computer. The IBM Predictive Customer Intelligence Usage Report functional accelerator IBM Cognos content file is PCI_1.0_PCIReports_Usage\BI\PCI_PCIReports_Usage_CognosContent.zip.Decompress the IBM Cognos report image file where you downloaded the functional accelerator. The report images file is PCI_1.0_PCIReports_Usage\BI\PCI_Images.zip. If you are installing more than one accelerator, you do not have to replace the images. The PCI_Images.zip files contains all of the images that are used in all of the accelerator reports.Copy the PCI_Images folder to the Cognos_Install_location\webcontent\bi\PCI_Images folder that contains report images files on the Cognos Analytics node computer.Copy the IBM Cognos Framework Manager model files from the computer where you downloaded thefunctional accelerator to the computer where you installed IBM Cognos Framework Manager, and decompress the file. If you want to edit the Framework Manager models, you must catalog the functional accelerator database on the computer where you installed Framework Manager.Click StartIBM DB2DB2COPY1 (Default)DB2 Command Window - Administrator.Enter the following command to catalog the database node:db2 catalog tcpip node NODE_NAME remote data_node_name server PORT_NUMBER NODE_NAME can be any value. PORT_NUMBER is 50000 by default.Enter the following command to catalog the PCI database:db2 catalog database PCI at node NODE_NAME authentication server You must use the same node_name that you used in the db2 catalog database command.Deploy the IBM Cognos contentFor IBM Cognos Business Intelligence, you must catalog the database, create a data source connection, and then deploy the content files for the IBM Predictive Customer Intelligence functional accelerator.

Moving the IBM Cognos content

You must copy the IBM® Cognos® content for the IBM Predictive Customer Intelligence functional accelerator to the appropriate locations in your IBM Cognos installation to be able to deploy the content.

Procedure

Copy the IBM Cognos content from the computer where you downloaded the functional accelerator to the Cognos_Install_location\Deployment folder on the Cognos Analytics node computer.

The IBM Predictive Customer Intelligence Usage Report functional accelerator IBM Cognos content file is PCI_1.0_PCIReports_Usage\BI\PCI_PCIReports_Usage_CognosContent.zip.

Decompress the IBM Cognos report image file where you downloaded the functional accelerator.

The report images file is PCI_1.0_PCIReports_Usage\BI\PCI_Images.zip.

Note: If you are installing more than one accelerator, you do not have to replace the images. The PCI_Images.zip files contains all of the images that are used in all of the accelerator reports.

Copy the PCI_Images folder to the Cognos_Install_location\webcontent\bi\PCI_Images folder that contains report images files on the Cognos Analytics node computer.

Copy the IBM Cognos Framework Manager model files from the computer where you downloaded thefunctional accelerator to the computer where you installed IBM Cognos Framework Manager, and decompress the file.

If you want to edit the Framework Manager models, you must catalog the functional accelerator database on the computer where you installed Framework Manager.

Click Start > IBM DB2 > DB2COPY1 (Default) > DB2 Command Window - Administrator.

Enter the following command to catalog the database node:

db2 catalog tcpip node NODE_NAME remote data_node_name server PORT_NUMBER

NODE_NAME can be any value. PORT_NUMBER is 50000 by default.

Enter the following command to catalog the PCI database:

db2 catalog database PCI at node NODE_NAME authentication server

You must use the same node_name that you used in the db2 catalog database command.

Parent topic: Deploy the IBM Cognos content

Creating a data source connection to the functional accelerator databaseYou must create a data source connection to the IBM Predictive Customer Intelligence functional accelerator database.Open a web browser.Go to the IBM Cognos BI portal URL.For example, go to http://bi_node_name/ibmcognos/.On the Welcome page, click Administer IBM Cognos Content.Click the Configuration tab, and click Data Source Connections.Click the New Data Source button New data source icon.In the Name box, type PCI, and then click Next.In the connection page, select IBM DB2, ensure that Configure JDBC connection is selected, and click Next.In the DB2 database name field, type PCI.Leave DB2 connect string blank.Under Signons, select both Password and Create a signon that the Everyone group can use, and then type the user ID and password for the DB2 instance owner user that you used to create the database, and click Next.To test whether the parameters are correct, click Test the connection. After you test the connection, click OK to return to the connection page.In the Server name box, enter the name or IP address of your data node computer.In the Port number box, enter the DB2 port number. The default is 50000.In Database name, type PCI.To test whether the parameters are correct, click Test the connection. After you test the connection, click OK to return to the connection page.Click Finish.Deploy the IBM Cognos contentFor IBM Cognos Business Intelligence, you must catalog the database, create a data source connection, and then deploy the content files for the IBM Predictive Customer Intelligence functional accelerator.

Creating a data source connection to the functional accelerator database

You must create a data source connection to the IBM® Predictive Customer Intelligence functional accelerator database.

Procedure

Open a web browser.

Go to the IBM Cognos® BI portal URL. For example, go to http://bi_node_name/ibmcognos/.

On the Welcome page, click Administer IBM Cognos Content.

Click the Configuration tab, and click Data Source Connections.

Click the New Data Source button New data source icon.

In the Name box, type PCI, and then click Next.

In the connection page, select IBM DB2, ensure that Configure JDBC connection is selected, and click Next.

In the DB2 database name field, type PCI.

Leave DB2 connect string blank.

Under Signons, select both Password and Create a signon that the Everyone group can use, and then type the user ID and password for the DB2® instance owner user that you used to create the database, and click Next.

Tip: To test whether the parameters are correct, click Test the connection. After you test the connection, click OK to return to the connection page.

In the Server name box, enter the name or IP address of your data node computer.

In the Port number box, enter the DB2 port number. The default is 50000.

In Database name, type PCI.

Tip: To test whether the parameters are correct, click Test the connection. After you test the connection, click OK to return to the connection page.

Click Finish.

Parent topic: Deploy the IBM Cognos content

Deploy the IBM Cognos reportsYou must deploy the IBM Predictive Customer Intelligence functional accelerator reports using IBM Cognos Administration.Open a web browser.Go to the IBM Cognos BI portal URL.For example, go to http://bi_node_name/ibmcognos/.On the Welcome page, click Administer IBM Cognos Content.On the Configuration tab, click Content Administration.On the toolbar, click the New Import button.In the Deployment Archive pane, select deployment archive, and click Next. The deployment archive is named PCI_PCIReports_Usage_CognosContent.In the Specify a name and description pane, accept the default or enter a new name, and click Next.In the Select the public folders and directory dontent pane, select all of the packages in the table, leave the Options as default, and click Next.Ensure that the Disable after import option is cleared.In the Specify the general options pane, accept the defaults, and click Next.On the Review the summary page, click Next.On the Select an action page, select Save and run once, and click Finish.On the Run with options page, accept the defaults, and click Run, and then click OK.Select View the details of this import after closing this dialog and click OK.In IBM Cognos Administration, click the Home button.The content is available in Public FoldersPCI Industry Accelerators 1.0.Deploy the IBM Cognos contentFor IBM Cognos Business Intelligence, you must catalog the database, create a data source connection, and then deploy the content files for the IBM Predictive Customer Intelligence functional accelerator.

Deploy the IBM Cognos reports

You must deploy the IBM® Predictive Customer Intelligence functional accelerator reports using IBM Cognos® Administration.

Procedure

Open a web browser.

Go to the IBM Cognos BI portal URL. For example, go to http://bi_node_name/ibmcognos/.

On the Welcome page, click Administer IBM Cognos Content.

On the Configuration tab, click Content Administration.

On the toolbar, click the New Import button.

In the Deployment Archive pane, select deployment archive, and click Next.

The deployment archive is named PCI_PCIReports_Usage_CognosContent.

In the Specify a name and description pane, accept the default or enter a new name, and click Next.

In the Select the public folders and directory dontent pane, select all of the packages in the table, leave the Options as default, and click Next.

Note: Ensure that the Disable after import option is cleared.

In the Specify the general options pane, accept the defaults, and click Next.

On the Review the summary page, click Next.

On the Select an action page, select Save and run once, and click Finish.

On the Run with options page, accept the defaults, and click Run, and then click OK.

Select View the details of this import after closing this dialog and click OK.

In IBM Cognos Administration, click the Home button.

The content is available in Public Folders > PCI Industry Accelerators 1.0.

Parent topic: Deploy the IBM Cognos content

Copying the functional accelerator license files to each computerAfter you install the functional accelerator, you must copy the license folder to each computer on which you use the IBM Predictive Customer Intelligence functional accelerator. Do not rename the folders or files.Copy the license folder from the folder where you decompressed the functional accelerator to each computer on which an IBM Predictive Customer Intelligence component is installed.For example, copy the folder and contents so that you have a C:\IBM\PCI_IndustryAccelerators\1.0\license folder on Microsoft Windows operating systems or an /opt/IBM/PCI_IndustryAccelerators/1.0/license folder on Linux operating systems on each node computer.The folder contains the license files. The folder should exist on each server and client node computer.Functional accelerator installationThe IBM Predictive Customer Intelligence Usage Report functional accelerator is for use with IBM Predictive Customer Intelligence.

Copying the functional accelerator license files to each computer

After you install the functional accelerator, you must copy the license folder to each computer on which you use the IBM® Predictive Customer Intelligence functional accelerator.

Important: Do not rename the folders or files.

Procedure

Copy the license folder from the folder where you decompressed the functional accelerator to each computer on which an IBM Predictive Customer Intelligence component is installed. For example, copy the folder and contents so that you have a C:\IBM\PCI_IndustryAccelerators\1.0\license folder on Microsoft Windows operating systems or an /opt/IBM/PCI_IndustryAccelerators/1.0/license folder on Linux operating systems on each node computer.

The folder contains the license files. The folder should exist on each server and client node computer.

Parent topic: Functional accelerator installation

IBM Predictive Customer Intelligence Usage ReportThe IBM Predictive Customer Intelligence Usage Report monitors the number of offers or recommendations that are provided. The report also records the response rates that are broken down by type of response.The number of offers that are presented, accepted, and rejected are shown by channel (for example, website, mobile application) and by month. The numbers of offers that are purchased are shown by month. If you use IBM Enterprise Marketing Management (EMM) as the recommendation generator, the data comes from the system tables that are used for logging offers. If you use IBM Analytical Decision Management as the recommendation generator, only the number of offers that are presented is found in the log tables. In this case, if you want to capture acceptance and rejection, you can build custom extensions to your call center or web application.For information about populating the database for the IBM Predictive Customer Intelligence Usage Report, see Configure your environment for the IBM Predictive Customer Intelligence Usage ReportThe IBM Predictive Customer Intelligence Usage Report monitors the number of offers or recommendations that are provided..You can customize the report using IBM Cognos Report Studio. Cognos Report Studio is a report design and authoring tool. Report authors can use Report Studio to create, edit, and distribute a wide range of professional reports. For more information about how to use Report Studio, see the IBM Cognos Report Studio User Guide. You can obtain this user guide from IBM Knowledge Center, (www.ibm.com/support/knowledgecenter/SSEP7J_10.2.1/com.ibm.swg.ba.cognos.ug_cr_rptstd.10.2.1.doc/c_rs_introduction.html).The meta data that the report displays comes from the package that is created in IBM Cognos Framework Manager. The example Framework Manager project folder contains the compiled project file (.cpf). When you open the .cpf file, Framework Manager displays the modeled relationships of the data and the package definitions, which are made available to the reporting studios when published. You can modify the meta data for the report by using Framework Manager. For more information, see Modify the data model You use IBM Cognos Framework Manager to model the meta data for the IBM Predictive Customer Intelligence functional accelerator reports. .Running the IBM Predictive Customer Intelligence Usage ReportYou can run the IBM Predictive Customer Intelligence Usage Report from within IBM Cognos Connection. You can also filter the data that is displayed in the report. By default, the report is not filtered.Accessibility for the IBM Predictive Customer Intelligence Usage ReportThe IBM Predictive Customer Intelligence Usage Report has been designed to be accessible for those users who require the use of such technologies.

IBM Predictive Customer Intelligence Usage Report

The IBM® Predictive Customer Intelligence Usage Report monitors the number of offers or recommendations that are provided. The report also records the response rates that are broken down by type of response.

The number of offers that are presented, accepted, and rejected are shown by channel (for example, website, mobile application) and by month. The numbers of offers that are purchased are shown by month.

If you use IBM Enterprise Marketing Management (EMM) as the recommendation generator, the data comes from the system tables that are used for logging offers. If you use IBM Analytical Decision Management as the recommendation generator, only the number of offers that are presented is found in the log tables. In this case, if you want to capture acceptance and rejection, you can build custom extensions to your call center or web application.

For information about populating the database for the IBM Predictive Customer Intelligence Usage Report, see Configure your environment for the IBM Predictive Customer Intelligence Usage Report.

You can customize the report using IBM Cognos® Report Studio. Cognos Report Studio is a report design and authoring tool. Report authors can use Report Studio to create, edit, and distribute a wide range of professional reports. For more information about how to use Report Studio, see the IBM Cognos Report Studio User Guide. You can obtain this user guide from IBM Knowledge Center, (www.ibm.com/support/knowledgecenter/SSEP7J_10.2.1/com.ibm.swg.ba.cognos.ug_cr_rptstd.10.2.1.doc/c_rs_introduction.html).

The meta data that the report displays comes from the package that is created in IBM Cognos Framework Manager. The example Framework Manager project folder contains the compiled project file (.cpf). When you open the .cpf file, Framework Manager displays the modeled relationships of the data and the package definitions, which are made available to the reporting studios when published. You can modify the meta data for the report by using Framework Manager. For more information, see Modify the data model.

Running the IBM Predictive Customer Intelligence Usage Report
You can run the IBM Predictive Customer Intelligence Usage Report from within IBM Cognos Connection. You can also filter the data that is displayed in the report. By default, the report is not filtered.

Accessibility for the IBM Predictive Customer Intelligence Usage Report
The IBM Predictive Customer Intelligence Usage Report has been designed to be accessible for those users who require the use of such technologies.

Running the IBM Predictive Customer Intelligence Usage ReportYou can run the IBM Predictive Customer Intelligence Usage Report from within IBM Cognos Connection. You can also filter the data that is displayed in the report. By default, the report is not filtered.Open IBM Cognos Connection, and navigate to the location of the report. By default, this is Public FoldersPCI Industry Accelerators 1.0 ‎PCI Usage. Click the IBM Predictive Customer Intelligence Usage Report link. By default, the report is rendered in IBM Cognos Viewer in HTML format. You can filter the data that is displayed in the Recommendations by Channel crosstab by making selections in the prompt controls and then clicking Refresh to update the report. You can filter by Date, Response type, or by Channel.To hide the prompt controls click Filters. The prompt values selected are displayed when the controls are hidden, to ensure that the report context is maintained. You can print the report in PDF format. On the Cognos Viewer toolbar, click the Output icon and select View in PDF format (the icon displays the current output format, such as HTML).IBM Predictive Customer Intelligence Usage ReportThe IBM Predictive Customer Intelligence Usage Report monitors the number of offers or recommendations that are provided. The report also records the response rates that are broken down by type of response.

Running the IBM Predictive Customer Intelligence Usage Report

You can run the IBM® Predictive Customer Intelligence Usage Report from within IBM Cognos® Connection. You can also filter the data that is displayed in the report. By default, the report is not filtered.

Procedure

Open IBM Cognos Connection, and navigate to the location of the report. By default, this is Public Folders > PCI Industry Accelerators 1.0 ‎ > PCI Usage.

Click the IBM Predictive Customer Intelligence Usage Report link. By default, the report is rendered in IBM Cognos Viewer in HTML format.

You can filter the data that is displayed in the Recommendations by Channel crosstab by making selections in the prompt controls and then clicking Refresh to update the report. You can filter by Date, Response type, or by Channel.

To hide the prompt controls click Filters. The prompt values selected are displayed when the controls are hidden, to ensure that the report context is maintained.

You can print the report in PDF format. On the Cognos Viewer toolbar, click the Output icon and select View in PDF format (the icon displays the current output format, such as HTML).

Parent topic: IBM Predictive Customer Intelligence Usage Report

Accessibility for the IBM Predictive Customer Intelligence Usage ReportThe IBM Predictive Customer Intelligence Usage Report has been designed to be accessible for those users who require the use of such technologies.To enable accessibility options, do the following steps:In IBM Cognos Connection, click Run with options Run with options icon adjacent to the report.Select Enable accessibility support, and click Run.The report is rendered with the accessibility support enabled. This results in adjustments to the report layout to accommodate this support.IBM Predictive Customer Intelligence Usage ReportThe IBM Predictive Customer Intelligence Usage Report monitors the number of offers or recommendations that are provided. The report also records the response rates that are broken down by type of response.

Accessibility for the IBM Predictive Customer Intelligence Usage Report

The IBM® Predictive Customer Intelligence Usage Report has been designed to be accessible for those users who require the use of such technologies.

To enable accessibility options, do the following steps:

In IBM Cognos® Connection, click Run with options Run with options icon adjacent to the report.

Select Enable accessibility support, and click Run.

The report is rendered with the accessibility support enabled. This results in adjustments to the report layout to accommodate this support.

Parent topic: IBM Predictive Customer Intelligence Usage Report

Configure your environment for the IBM Predictive Customer Intelligence Usage ReportThe IBM Predictive Customer Intelligence Usage Report monitors the number of offers or recommendations that are provided.If you use IBM Enterprise Marketing Management as the recommendation generator, the data comes from the system tables that are used for logging offers. If you use IBM Analytical Decision Management as the recommendation generator, only the number of offers that are presented is found in the log tables. In this case, if you want to capture acceptance and rejection, build custom extensions to your call center or web application.To configure your environment for the IBM Predictive Customer Intelligence Usage Report, you must first configure the logging of events, and then you must populate the IBM Predictive Customer Intelligence database. The steps to do this differ depending on whether you are using IBM Enterprise Marketing Management or IBM Analytical Decision Management as the recommendation generator.Database tables used by the IBM Predictive Customer Intelligence Usage ReportThe following database tables and attributes are used by the IBM Predictive Customer Intelligence Usage Report.The Framework Manager model for the IBM Predictive Customer Intelligence Usage ReportThe IBM Cognos Framework Manager model contains the metadata for the IBM Predictive Customer Intelligence Usage ReportConfiguring logging in IBM Enterprise Marketing ManagementIf you use IBM Enterprise Marketing Management as the recommendation generator, you must configure the logging of events for different categories for the IBM Predictive Customer Intelligence Usage Report.Configure logging in IBM SPSS Collaboration and DeploymentIf you use IBM Analytical Decision Management as the recommendation generator, you cannot get the campaign, channel, customer, offer, or response from the IBM SPSS database tables for the IBM Predictive Customer Intelligence Usage Report. This information must be obtained from another application, and then used as inputs to the decision model to be available for logging.

Configure your environment for the IBM Predictive Customer Intelligence Usage Report

The IBM® Predictive Customer Intelligence Usage Report monitors the number of offers or recommendations that are provided.

If you use IBM Enterprise Marketing Management as the recommendation generator, the data comes from the system tables that are used for logging offers. If you use IBM Analytical Decision Management as the recommendation generator, only the number of offers that are presented is found in the log tables. In this case, if you want to capture acceptance and rejection, build custom extensions to your call center or web application.

To configure your environment for the IBM Predictive Customer Intelligence Usage Report, you must first configure the logging of events, and then you must populate the IBM Predictive Customer Intelligence database. The steps to do this differ depending on whether you are using IBM Enterprise Marketing Management or IBM Analytical Decision Management as the recommendation generator.

Database tables used by the IBM Predictive Customer Intelligence Usage Report
The following database tables and attributes are used by the IBM Predictive Customer Intelligence Usage Report.

The Framework Manager model for the IBM Predictive Customer Intelligence Usage Report
The IBM Cognos® Framework Manager model contains the metadata for the IBM Predictive Customer Intelligence Usage Report

Configuring logging in IBM Enterprise Marketing Management
If you use IBM Enterprise Marketing Management as the recommendation generator, you must configure the logging of events for different categories for the IBM Predictive Customer Intelligence Usage Report.

Configure logging in IBM SPSS Collaboration and Deployment
If you use IBM Analytical Decision Management as the recommendation generator, you cannot get the campaign, channel, customer, offer, or response from the IBM SPSS® database tables for the IBM Predictive Customer Intelligence Usage Report. This information must be obtained from another application, and then used as inputs to the decision model to be available for logging.

Database tables used by the IBM Predictive Customer Intelligence Usage ReportThe following database tables and attributes are used by the IBM Predictive Customer Intelligence Usage Report.CAMPAIGNThe CAMPAIGN master data table contains the campaigns that an offer belongs to.CAMPAIGNColunData TypeCAMPAIGN_IDINTEGER(4)LANGUAGE_IDINTEGER(4)CAMPAIGN_CDVARGRAPHIC(50)CAMPAIGN_NAMEVARGRAPHIC(200)CAMPAIGN_DESCRIPTIONVARGRAPHIC(500)START_DATEDATE(4)END_DATEDATE(4)CHANNELThe CHANNEL master data table contains the communication channels that interact with customers.CHANNELColumnData TypeCHANNEL_IDINTEGER(4)LANGUAGE_IDINTEGER(4)CHANNEL_CDVARGRAPHIC(50)CHANNEL_NAMEVARGRAPHIC(200)KEY_LOOKUPThe KEY_LOOKUP master data table contains the foreign keys.KEY_LOOKUPColumnData TypeKEY_LOOKUP_IDBIGINT(8)TABLE_NAMEVARGRAPHIC(50)KEY_LOOKUP_CDVARGRAPHIC(50)PCI_CALENDARThe PCI_CALENDAR master data table contains the calendar.PCI_CALENDARColumnData TypePCI_DATEDATE(4)LANGUAGE_IDINTEGER(4)YEAR_NOINTEGER(4)MONTH_NOINTEGER(4)QUARTER_NOINTEGER(4)MONTH_NAMEVARGRAPHIC(20)QUARTER_NAMEVARGRAPHIC(20)WEEKDAY_NOINTEGER(4)WEEKDAY_NAMEVARGRAPHIC(10)YEAR_CAPTIONVARGRAPHIC(10)PERIOD_NOINTEGER(4)PERIOD_NAMEVARGRAPHIC(25)WEEK_IN_PERIODINTEGER(4)WEEK_IN_PERIOD_CAPTIONVARGRAPHIC(25)PCI_LANGUAGEThe PCI_LANGUAGE master data table contains the language codes that are used for globalization.PCI_LANGUAGEColumnData TypeLANGUAGE_IDINTEGER(4)LANGUAGE_CDVARGRAPHIC(50)LANGUAGE_NAMEVARGRAPHIC(50)PCI_TIMEThis master data table contains the time, down to the second.PCI_TIMEColumnData TypeTIME_OF_DAYTIME(3)HOUR_NOINTEGER(4)HOUR_CAPTIONVARCHAR(5)AM_OR_PMVARGRAPHIC(25)TIME_OF_DAY_TEXTVARCHAR(50)OFFER_MADEThe OFFER_MADE fact table records the number of offers that are made by date and time.OFFER_MADEColumnData TypeCAMPAIGN_IDINTEGER(4)CHANNEL_IDINTEGER(4)LOG_DATETIMETIMESTAMP(10)LOG_DATEDATE(4)LOG_TIMETIME(3)OFFER_COUNTINTEGER(4)OFFER_RESPONSEThe OFFER_RESPONSE fact table records the number of responses that are received by type, date, and time.OFFER_RESPONSEColumnData TypeCAMPAIGN_IDINTEGER(4)CHANNEL_IDINTEGER(4)RESPONSE_TYPE_IDINTEGER(4)LOG_DATETIMETIMESTAMP(10)LOG_DATEDATE(4)LOG_TIMETIME(3)OFFER_COUNTINTEGER(4)OFFER_TARGET_MONTHThe OFFER_TARGET_MONTH fact table contains a record of how many recommendations were purchased by month in a given year. It is populated during installation if required.Usually each row in OFFER_TARGET_MONTH has one twelfth of the recommendations in OFFER_TARGET_YEAR for the same year, but that value can be overridden.OFFER_TARGET_MONTHColumnData TypePURCHASE_YEARINTEGER(4)PURCHASE_MONTHINTEGER(4)RECOMMENDATION_COUNTINTEGER(4)OFFER_TARGET_YEARThe OFFER_TARGET_YEAR fact table contains a record of how many recommendations were purchased by year. It is populated during installation if required.OFFER_TARGET_YEARColumnData TypePURCHASE_YEARINTEGER(4)RECOMMENDATION_COUNTINTEGER(4)RESPONSE_TYPEThe RESPONSE_TYPE master data table contains the range of response types to an offer.RESPONSE_TYPEColumnData TypeRESPONSE_TYPE_IDINTEGER(4)LANGUAGE_IDINTEGER(4)RESPONSE_TYPE_CDVARGRAPHIC(50)RESPONSE_TYPE_NAMEVARGRAPHIC(200)Configure your environment for the IBM Predictive Customer Intelligence Usage ReportThe IBM Predictive Customer Intelligence Usage Report monitors the number of offers or recommendations that are provided.

Database tables used by the IBM Predictive Customer Intelligence Usage Report

The following database tables and attributes are used by the IBM® Predictive Customer Intelligence Usage Report.

CAMPAIGN

The CAMPAIGN master data table contains the campaigns that an offer belongs to.

Table 1. CAMPAIGN

Colun | Data Type
CAMPAIGN_ID | INTEGER(4)
LANGUAGE_ID | INTEGER(4)
CAMPAIGN_CD | VARGRAPHIC(50)
CAMPAIGN_NAME | VARGRAPHIC(200)
CAMPAIGN_DESCRIPTION | VARGRAPHIC(500)
START_DATE | DATE(4)
END_DATE | DATE(4)

CHANNEL

The CHANNEL master data table contains the communication channels that interact with customers.

Table 2. CHANNEL

Column | Data Type
CHANNEL_ID | INTEGER(4)
LANGUAGE_ID | INTEGER(4)
CHANNEL_CD | VARGRAPHIC(50)
CHANNEL_NAME | VARGRAPHIC(200)

KEY_LOOKUP

The KEY_LOOKUP master data table contains the foreign keys.

Table 3. KEY_LOOKUP

Column | Data Type
KEY_LOOKUP_ID | BIGINT(8)
TABLE_NAME | VARGRAPHIC(50)
KEY_LOOKUP_CD | VARGRAPHIC(50)

PCI_CALENDAR

The PCI_CALENDAR master data table contains the calendar.

Table 4. PCI_CALENDAR

Column | Data Type
PCI_DATE | DATE(4)
LANGUAGE_ID | INTEGER(4)
YEAR_NO | INTEGER(4)
MONTH_NO | INTEGER(4)
QUARTER_NO | INTEGER(4)
MONTH_NAME | VARGRAPHIC(20)
QUARTER_NAME | VARGRAPHIC(20)
WEEKDAY_NO | INTEGER(4)
WEEKDAY_NAME | VARGRAPHIC(10)
YEAR_CAPTION | VARGRAPHIC(10)
PERIOD_NO | INTEGER(4)
PERIOD_NAME | VARGRAPHIC(25)
WEEK_IN_PERIOD | INTEGER(4)
WEEK_IN_PERIOD_CAPTION | VARGRAPHIC(25)

PCI_LANGUAGE

The PCI_LANGUAGE master data table contains the language codes that are used for globalization.

Table 5. PCI_LANGUAGE

Column | Data Type
LANGUAGE_ID | INTEGER(4)
LANGUAGE_CD | VARGRAPHIC(50)
LANGUAGE_NAME | VARGRAPHIC(50)

PCI_TIME

This master data table contains the time, down to the second.

Table 6. PCI_TIME

Column | Data Type
TIME_OF_DAY | TIME(3)
HOUR_NO | INTEGER(4)
HOUR_CAPTION | VARCHAR(5)
AM_OR_PM | VARGRAPHIC(25)
TIME_OF_DAY_TEXT | VARCHAR(50)

OFFER_MADE

The OFFER_MADE fact table records the number of offers that are made by date and time.

Table 7. OFFER_MADE

Column | Data Type
CAMPAIGN_ID | INTEGER(4)
CHANNEL_ID | INTEGER(4)
LOG_DATETIME | TIMESTAMP(10)
LOG_DATE | DATE(4)
LOG_TIME | TIME(3)
OFFER_COUNT | INTEGER(4)

OFFER_RESPONSE

The OFFER_RESPONSE fact table records the number of responses that are received by type, date, and time.

Table 8. OFFER_RESPONSE

Column | Data Type
CAMPAIGN_ID | INTEGER(4)
CHANNEL_ID | INTEGER(4)
RESPONSE_TYPE_ID | INTEGER(4)
LOG_DATETIME | TIMESTAMP(10)
LOG_DATE | DATE(4)
LOG_TIME | TIME(3)
OFFER_COUNT | INTEGER(4)

OFFER_TARGET_MONTH

The OFFER_TARGET_MONTH fact table contains a record of how many recommendations were purchased by month in a given year. It is populated during installation if required.

Usually each row in OFFER_TARGET_MONTH has one twelfth of the recommendations in OFFER_TARGET_YEAR for the same year, but that value can be overridden.

Table 9. OFFER_TARGET_MONTH

Column | Data Type
PURCHASE_YEAR | INTEGER(4)
PURCHASE_MONTH | INTEGER(4)
RECOMMENDATION_COUNT | INTEGER(4)

OFFER_TARGET_YEAR

The OFFER_TARGET_YEAR fact table contains a record of how many recommendations were purchased by year. It is populated during installation if required.

Table 10. OFFER_TARGET_YEAR

Column | Data Type
PURCHASE_YEAR | INTEGER(4)
RECOMMENDATION_COUNT | INTEGER(4)

RESPONSE_TYPE

The RESPONSE_TYPE master data table contains the range of response types to an offer.

Table 11. RESPONSE_TYPE

Column | Data Type
RESPONSE_TYPE_ID | INTEGER(4)
LANGUAGE_ID | INTEGER(4)
RESPONSE_TYPE_CD | VARGRAPHIC(50)
RESPONSE_TYPE_NAME | VARGRAPHIC(200)

Parent topic: Configure your environment for the IBM Predictive Customer Intelligence Usage Report

The Framework Manager model for the IBM Predictive Customer Intelligence Usage ReportThe IBM Cognos Framework Manager model contains the metadata for the IBM Predictive Customer Intelligence Usage ReportA view of the database layer in the IBM Cognos Framework Manager Content Explorer shows the relationships between the database tables.Database layer in the IBM Predictive Customer Intelligence modeldatabase layerA view of Offers Made that shows the relationships between the tables responsible for the Offers Made report is shown in the following figure.A view of the Offer Made tablesoffers madeA view of Offer Responses that shows the relationships between the tables responsible for the Offer Responses that are shown in the IBM Predictive Customer Intelligence Usage Report is shown in the following figure.A view of the Offer Response tablesA view of Offer Response shows the relationships between the tables responsible for the offer responses that are shown in the IBM Predictive Customer Intelligence Usage ReportConfigure your environment for the IBM Predictive Customer Intelligence Usage ReportThe IBM Predictive Customer Intelligence Usage Report monitors the number of offers or recommendations that are provided.

The Framework Manager model for the IBM Predictive Customer Intelligence Usage Report

The IBM® Cognos® Framework Manager model contains the metadata for the IBM Predictive Customer Intelligence Usage Report

A view of the database layer in the IBM Cognos Framework Manager Content Explorer shows the relationships between the database tables.

Figure 1. Database layer in the IBM Predictive Customer Intelligence model

A view of Offers Made that shows the relationships between the tables responsible for the Offers Made report is shown in the following figure.

Figure 2. A view of the Offer Made tables

A view of Offer Responses that shows the relationships between the tables responsible for the Offer Responses that are shown in the IBM Predictive Customer Intelligence Usage Report is shown in the following figure.

Figure 3. A view of the Offer Response tables

Parent topic: Configure your environment for the IBM Predictive Customer Intelligence Usage Report

Configuring logging in IBM Enterprise Marketing ManagementIf you use IBM Enterprise Marketing Management as the recommendation generator, you must configure the logging of events for different categories for the IBM Predictive Customer Intelligence Usage Report. Communication channels are configurable in IBM Enterprise Marketing Management. Part of the configuration includes setting up logging of events for different categories. The default category of Get Offer must be logged for acceptance and rejection. If there are user-defined categories for acceptance and rejection, they must also be set to log for acceptance or rejection.Log in as administrator to the IBM Campaign Manager console.Select Campaign, and then Interactive Channels.Select and edit each interactive channel:Click the Events tab.Select the event Get Offer, or any other user-defined event for accepting or rejecting an offer.Select Log Offer Made, Log Acceptance, and Log Rejection.Configure your environment for the IBM Predictive Customer Intelligence Usage ReportThe IBM Predictive Customer Intelligence Usage Report monitors the number of offers or recommendations that are provided.Populate the IBM Predictive Customer Intelligence database from IBM Enterprise Marketing ManagementIf you use IBM Enterprise Marketing Management as the recommendation generator, the data for the IBM Predictive Customer Intelligence Usage Report comes from the system tables that are used for logging offers.

Configuring logging in IBM Enterprise Marketing Management

If you use IBM® Enterprise Marketing Management as the recommendation generator, you must configure the logging of events for different categories for the IBM Predictive Customer Intelligence Usage Report.

Communication channels are configurable in IBM Enterprise Marketing Management. Part of the configuration includes setting up logging of events for different categories. The default category of Get Offer must be logged for acceptance and rejection. If there are user-defined categories for acceptance and rejection, they must also be set to log for acceptance or rejection.

Procedure

Log in as administrator to the IBM Campaign Manager console.

Select Campaign, and then Interactive Channels.

Select and edit each interactive channel:

Click the Events tab.

Select the event Get Offer, or any other user-defined event for accepting or rejecting an offer.

Select Log Offer Made, Log Acceptance, and Log Rejection.

Populate the IBM Predictive Customer Intelligence database from IBM Enterprise Marketing Management
If you use IBM Enterprise Marketing Management as the recommendation generator, the data for the IBM Predictive Customer Intelligence Usage Report comes from the system tables that are used for logging offers.

Parent topic: Configure your environment for the IBM Predictive Customer Intelligence Usage Report

Populate the IBM Predictive Customer Intelligence database from IBM Enterprise Marketing Management If you use IBM Enterprise Marketing Management as the recommendation generator, the data for the IBM Predictive Customer Intelligence Usage Report comes from the system tables that are used for logging offers.The following tables show how the data must be mapped between the IBM Predictive Customer Intelligence database and the IBM Enterprise Marketing Management database.Map the UA_CAMPAIGN table to the CAMPAIGN tablePredictive Customer Intelligence Column: CAMPAIGNEnterprise Marketing Management Column: UA_CAMPAIGNTransformationsCAMPAIGN_ID<Assigned by system>CAMPAIGN_CDCAMPAIGNIDConvert number to vargraphicCAMPAIGN_NAMENAMECAMPAIGN_DESCRIPTIONDESCRIPTIONSTART_DATESTARTDATEEND_DATEENDDATEMap the UACI_INTCHANNEL table to the CHANNEL tablePredictive Customer Intelligence Column: CHANNELEnterprise Marketing Management Column: UACI_INTCHANNELTransformationsCHANNEL_IDICIDCHANNEL_CDICIDConvert number to vargraphicCHANNEL_NAMENAMEMap the UACI_EVENTACTIVITY table to the OFFER_MADE tablePredictive Customer Intelligence Column: OFFER_MADEEnterprise Marketing Management Column: UACI_EVENTACTIVITY tableTransformationsCHANNEL_IDICIDCAMPAIGN_IDN/AOFFER_COUNTOCCURRENCESSumLOG_DATETIMEDATEID + TIMEIDConcatenate and convert to datetimeFilters:EVENTNAME = 'Get Offer'Group by ICID, DATEID, TIMEIDMap the UACI_EVENTACTIVITY table to the OFFER_RESPONSE tablePredictive Customer Intelligence Column: OFFER_RESPONSE tableEnterprise Marketing Management Column: UACI_EVENTACTIVITYTransformationsCHANNEL_IDICIDCAMPAIGN_IDN/ARESPONSE_TYPE_IDEVENTIDOFFER_COUNTOCCURRENCESSumLOG_DATETIMEDATEID + TIMEIDConcatenate and convert to datetimeFilters:CATEGORYNAME = ‘Response’Group by ICID, DATEID, TIMEIDMap the UACI_EVENTACTIVITY table to the RESPONSE_TYPE tablePredictive Customer Intelligence Column: RESPONSE_TYPEIBM Enterprise Marketing Management Column: UACI_EVENTACTIVITYTransformationsRESPONSE_TYPE_IDEVENTIDRESPONSE_TYPE_CODEEVENTIDConvert number to vargraphicRESPONSE_TYPE_NAMEEVENTNAMEFilters:distinct EVENTIDCATEGORYNAME= 'Response'Configuring logging in IBM Enterprise Marketing ManagementIf you use IBM Enterprise Marketing Management as the recommendation generator, you must configure the logging of events for different categories for the IBM Predictive Customer Intelligence Usage Report.

Populate the IBM Predictive Customer Intelligence database from IBM Enterprise Marketing Management

If you use IBM® Enterprise Marketing Management as the recommendation generator, the data for the IBM Predictive Customer Intelligence Usage Report comes from the system tables that are used for logging offers.

The following tables show how the data must be mapped between the IBM Predictive Customer Intelligence database and the IBM Enterprise Marketing Management database.

Table 12. Map the UA_CAMPAIGN table to the CAMPAIGN table

Predictive Customer Intelligence Column: CAMPAIGN | Enterprise Marketing Management Column: UA_CAMPAIGN | Transformations
CAMPAIGN_ID | <Assigned by system> |
CAMPAIGN_CD | CAMPAIGNID | Convert number to vargraphic
CAMPAIGN_NAME | NAME |
CAMPAIGN_DESCRIPTION | DESCRIPTION |
START_DATE | STARTDATE |
END_DATE | ENDDATE |

Table 13. Map the UACI_INTCHANNEL table to the CHANNEL table

Predictive Customer Intelligence Column: CHANNEL | Enterprise Marketing Management Column: UACI_INTCHANNEL | Transformations
CHANNEL_ID | ICID |
CHANNEL_CD | ICID | Convert number to vargraphic
CHANNEL_NAME | NAME |

Table 14. Map the UACI_EVENTACTIVITY table to the OFFER_MADE table

Predictive Customer Intelligence Column: OFFER_MADE | Enterprise Marketing Management Column: UACI_EVENTACTIVITY table | Transformations
CHANNEL_ID | ICID |
CAMPAIGN_ID | N/A |
OFFER_COUNT | OCCURRENCES | Sum
LOG_DATETIME | DATEID + TIMEID | Concatenate and convert to datetime

Filters:

EVENTNAME = 'Get Offer'

Group by ICID, DATEID, TIMEID

Table 15. Map the UACI_EVENTACTIVITY table to the OFFER_RESPONSE table

Predictive Customer Intelligence Column: OFFER_RESPONSE table | Enterprise Marketing Management Column: UACI_EVENTACTIVITY | Transformations
CHANNEL_ID | ICID |
CAMPAIGN_ID | N/A |
RESPONSE_TYPE_ID | EVENTID |
OFFER_COUNT | OCCURRENCES | Sum
LOG_DATETIME | DATEID + TIMEID | Concatenate and convert to datetime

Filters:

CATEGORYNAME = ‘Response’

Group by ICID, DATEID, TIMEID

Table 16. Map the UACI_EVENTACTIVITY table to the RESPONSE_TYPE table

Predictive Customer Intelligence Column: RESPONSE_TYPE | IBM Enterprise Marketing Management Column: UACI_EVENTACTIVITY | Transformations
RESPONSE_TYPE_ID | EVENTID |
RESPONSE_TYPE_CODE | EVENTID | Convert number to vargraphic
RESPONSE_TYPE_NAME | EVENTNAME |

Filters:

distinct EVENTID

CATEGORYNAME= 'Response'

Parent topic: Configuring logging in IBM Enterprise Marketing Management

Configure logging in IBM SPSS Collaboration and DeploymentIf you use IBM Analytical Decision Management as the recommendation generator, you cannot get the campaign, channel, customer, offer, or response from the IBM SPSS database tables for the IBM Predictive Customer Intelligence Usage Report. This information must be obtained from another application, and then used as inputs to the decision model to be available for logging.The following views are available in IBM SPSS Collaboration and Deployment Services when logging is configured:IBM SPSS logging viewsSPSSSCORE_V_LOG_HEADER contains the scoring models that are configured for real-time decisions. SPSSSCORE_V_LOG_INPUT contains the attributes that are used in assessing the scenario and rendering a recommendation.SPSSSCORE_V_LOG_OUTPUT contains the attributes that are returned from the decision model, which can include some of the inputs and the recommendation.Configure logging in IBM SPSS You can configure logging in IBM SPSS down to the attribute level. Consider the following points: The channel must be an input field to the model and must be set up for logging.The campaign must be an input field to the model and must be set up for logging.Any other dimensions that are required by the dashboard, such as campaign, must be both inputs and logged outputs of the model. Configure a model for scoring by using IBM SPSS Deployment Manager. During scoring configuration, you can select any input or output field for logging. The customer data determines what is available for logging.For more information, see IBM SPSS Deployment Manager User's Guide (www.ibm.com/support/knowledgecenter/SS69YH_6.0.0/com.spss.mgmt.content.help/model_management/thick/idh_dlg_scoring_configuration_logging.html).Configure your environment for the IBM Predictive Customer Intelligence Usage ReportThe IBM Predictive Customer Intelligence Usage Report monitors the number of offers or recommendations that are provided.Populate the IBM Predictive Customer Intelligence database from IBM SPSSIf you use IBM Analytical Decision Management as the recommendation generator for the IBM Predictive Customer Intelligence Usage Report, only the number of offers that are presented is found in the log tables.

Configure logging in IBM SPSS Collaboration and Deployment

If you use IBM® Analytical Decision Management as the recommendation generator, you cannot get the campaign, channel, customer, offer, or response from the IBM SPSS® database tables for the IBM Predictive Customer Intelligence Usage Report. This information must be obtained from another application, and then used as inputs to the decision model to be available for logging.

The following views are available in IBM SPSS Collaboration and Deployment Services when logging is configured:

SPSSSCORE_V_LOG_HEADER contains the scoring models that are configured for real-time decisions.

SPSSSCORE_V_LOG_INPUT contains the attributes that are used in assessing the scenario and rendering a recommendation.

SPSSSCORE_V_LOG_OUTPUT contains the attributes that are returned from the decision model, which can include some of the inputs and the recommendation.

Configure logging in IBM SPSS

You can configure logging in IBM SPSS down to the attribute level. Consider the following points:

The channel must be an input field to the model and must be set up for logging.

The campaign must be an input field to the model and must be set up for logging.

Any other dimensions that are required by the dashboard, such as campaign, must be both inputs and logged outputs of the model.

Configure a model for scoring by using IBM SPSS Deployment Manager. During scoring configuration, you can select any input or output field for logging. The customer data determines what is available for logging.

For more information, see IBM SPSS Deployment Manager User's Guide (www.ibm.com/support/knowledgecenter/SS69YH_6.0.0/com.spss.mgmt.content.help/model_management/thick/idh_dlg_scoring_configuration_logging.html).

Populate the IBM Predictive Customer Intelligence database from IBM SPSS
If you use IBM Analytical Decision Management as the recommendation generator for the IBM Predictive Customer Intelligence Usage Report, only the number of offers that are presented is found in the log tables.

Parent topic: Configure your environment for the IBM Predictive Customer Intelligence Usage Report

Populate the IBM Predictive Customer Intelligence database from IBM SPSSIf you use IBM Analytical Decision Management as the recommendation generator for the IBM Predictive Customer Intelligence Usage Report, only the number of offers that are presented is found in the log tables.In IBM SPSS, there are no dedicated system tables for channel, response type, and offers. Custom database tables must be used for the channel, response type, and offers.The following tables show how the data must be mapped between the IBM Predictive Customer Intelligence database, and IBM SPSS database tables.CAMPAIGN table for IBM Predictive Customer Intelligence mapped to the custom database tables from IBM SPSSIBM Predictive Customer Intelligence ColumnSPSS ColumnFilters CAMPAIGN_IDSequentially generated numberThese are distinct rows because Campaigns do not repeat.CAMPAIGN_CDI.INPUT_VALUEH.CONFIGURATION_NAME = ‘name of model’;I.INPUT_NAME = ‘campaign cd’;CAMPAIGN_NAMEI.INPUT_VALUEH.CONFIGURATION_NAME = ‘name of model’;I.INPUT_NAME = ‘campaign name’;Replace the filters in quotation marks with the names for the database attributes.SPSS view:SPSSSCORE_V_LOG_HEADER AS H Join SPSSSCORE_V_LOG_INPUT AS I on H.SERIAL = I.SERIALCHANNEL table for IBM Predictive Customer Intelligence mapped to the custom database tables from IBM SPSSIBM Predictive Customer Intelligence ColumnSPSS ColumnFiltersCHANNEL_IDSequentially generated numberDistinct rows so channels do not repeatCHANNEL_CDI.INPUT_VALUEH.CONFIGURATION_NAME = ‘name of model’;I.INPUT_NAME = ‘channel cd’;CHANNEL_NAMEI.INPUT_VALUEH.CONFIGURATION_NAME = ‘name of model’;I.INPUT_NAME = ‘channel name’;Replace the filters in quotation marks with the names for the database attributes.SPSS view:SPSSSCORE_V_LOG_HEADER AS H Join SPSSSCORE_V_LOG_INPUT AS I on H.SERIAL = I.SERIALOFFER_MADE table for IBM Predictive Customer Intelligence mapped to the custom database tables from IBM SPSSIBM Predictive Customer Intelligence ColumnSPSS ColumnFiltersCHANNEL_ID *I.INPUT_VALUEH.CONFIGURATION_NAME = ‘name of model’;I.INPUT_NAME = ‘channel cd’;CAMPAIGN_ID *I.INPUT_VALUEH.CONFIGURATION_NAME = ‘name of model’;I.INPUT_NAME = ‘campaign cd’;OFFER_COUNTCount (distinct H.STAMP)H.CONFIGURATION_NAME = ‘name of model’;I.INPUT_NAME = ‘channel cd’;LOG_DATETIMEH.STAMPH.CONFIGURATION_NAME = ‘name of model’;I.INPUT_NAME = ‘channel cd’; IBM Predictive Customer Intelligence columns that are marked with * contain transformations using Lookup ID from CD.Replace the filters in quotation marks with the names for the database attributes.SPSS View:SPSSSCORE_V_LOG_HEADER AS h join SPSSSCORE_V_LOG_OUTPUT on h.SERIAL = o.SERIAL left outer join dbo.SPSSSCORE_V_LOG_INPUT li on h.SERIAL = li.serialOFFER_RESPONSE table for IBM Predictive Customer IntelligenceIBM Predictive Customer Intelligence ColumnCHANNEL_IDCAMPAIGN_IDRESPONSE_IDOFFER_COUNTLOG_DATETIMEYou cannot get the customer response from IBM Analytical Decision Management. The customer response must be loaded from the channel application by using custom code.RESPONSE_TYPE table for IBM Predictive Customer Intelligence mapped to the custom database tables from IBM SPSSIBM Predictive Customer Intelligence ColumnSPSS ColumnFiltersRESPONSE_TYPE_IDSequentially generated numberDistinct rows so Response Types do not repeatRESPONSE_TYPE_CDI.INPUT_VALUEH.CONFIGURATION_NAME = ‘name of model’;I.INPUT_NAME = ‘response type cd’;RESPONSE_TYPE_NAMEI.INPUT_VALUEH.CONFIGURATION_NAME = ‘name of model’;I.INPUT_NAME = ‘response type name’;IBM SPSS view:SPSSSCORE_V_LOG_HEADER AS H join SPSSSCORE_V_LOG_INPUT AS I on H.SERIAL = I.SERIALConfigure logging in IBM SPSS Collaboration and DeploymentIf you use IBM Analytical Decision Management as the recommendation generator, you cannot get the campaign, channel, customer, offer, or response from the IBM SPSS database tables for the IBM Predictive Customer Intelligence Usage Report. This information must be obtained from another application, and then used as inputs to the decision model to be available for logging.

Populate the IBM Predictive Customer Intelligence database from IBM SPSS

If you use IBM® Analytical Decision Management as the recommendation generator for the IBM Predictive Customer Intelligence Usage Report, only the number of offers that are presented is found in the log tables.

In IBM SPSS®, there are no dedicated system tables for channel, response type, and offers. Custom database tables must be used for the channel, response type, and offers.

The following tables show how the data must be mapped between the IBM Predictive Customer Intelligence database, and IBM SPSS database tables.

Table 17. CAMPAIGN table for IBM Predictive Customer Intelligence mapped to the custom database tables from IBM SPSS

IBM Predictive Customer Intelligence Column | SPSS Column | Filters
CAMPAIGN_ID | Sequentially generated number | These are distinct rows because Campaigns do not repeat.
CAMPAIGN_CD | I.INPUT_VALUE | H.CONFIGURATION_NAME = ‘name of model’;
I.INPUT_NAME = ‘campaign cd’;
CAMPAIGN_NAME | I.INPUT_VALUE | H.CONFIGURATION_NAME = ‘name of model’;
I.INPUT_NAME = ‘campaign name’;

Replace the filters in quotation marks with the names for the database attributes.

SPSS view:

SPSSSCORE_V_LOG_HEADER AS H
Join
SPSSSCORE_V_LOG_INPUT AS I on H.SERIAL = I.SERIAL

Table 18. CHANNEL table for IBM Predictive Customer Intelligence mapped to the custom database tables from IBM SPSS

IBM Predictive Customer Intelligence Column | SPSS Column | Filters
CHANNEL_ID | Sequentially generated number | Distinct rows so channels do not repeat
CHANNEL_CD | I.INPUT_VALUE | H.CONFIGURATION_NAME = ‘name of model’;
I.INPUT_NAME = ‘channel cd’;
CHANNEL_NAME | I.INPUT_VALUE | H.CONFIGURATION_NAME = ‘name of model’;
I.INPUT_NAME = ‘channel name’;

Replace the filters in quotation marks with the names for the database attributes.

SPSS view:

SPSSSCORE_V_LOG_HEADER AS H
Join
SPSSSCORE_V_LOG_INPUT AS I on H.SERIAL = I.SERIAL

Table 19. OFFER_MADE table for IBM Predictive Customer Intelligence mapped to the custom database tables from IBM SPSS

IBM Predictive Customer Intelligence Column | SPSS Column | Filters
CHANNEL_ID * | I.INPUT_VALUE | H.CONFIGURATION_NAME = ‘name of model’;
I.INPUT_NAME = ‘channel cd’;
CAMPAIGN_ID * | I.INPUT_VALUE | H.CONFIGURATION_NAME = ‘name of model’;
I.INPUT_NAME = ‘campaign cd’;
OFFER_COUNT | Count (distinct H.STAMP) | H.CONFIGURATION_NAME = ‘name of model’;
I.INPUT_NAME = ‘channel cd’;
LOG_DATETIME | H.STAMP | H.CONFIGURATION_NAME = ‘name of model’;
I.INPUT_NAME = ‘channel cd’;

IBM Predictive Customer Intelligence columns that are marked with * contain transformations using Lookup ID from CD.

Replace the filters in quotation marks with the names for the database attributes.

SPSS View:

SPSSSCORE_V_LOG_HEADER AS h
join SPSSSCORE_V_LOG_OUTPUT on h.SERIAL = o.SERIAL
left outer join dbo.SPSSSCORE_V_LOG_INPUT li
on h.SERIAL = li.serial

Table 20. OFFER_RESPONSE table for IBM Predictive Customer Intelligence

IBM Predictive Customer Intelligence Column

CHANNEL_ID

CAMPAIGN_ID

RESPONSE_ID

OFFER_COUNT

LOG_DATETIME

You cannot get the customer response from IBM Analytical Decision Management. The customer response must be loaded from the channel application by using custom code.

Table 21. RESPONSE_TYPE table for IBM Predictive Customer Intelligence mapped to the custom database tables from IBM SPSS

IBM Predictive Customer Intelligence Column | SPSS Column | Filters
RESPONSE_TYPE_ID | Sequentially generated number | Distinct rows so Response Types do not repeat
RESPONSE_TYPE_CD | I.INPUT_VALUE | H.CONFIGURATION_NAME = ‘name of model’;
I.INPUT_NAME = ‘response type cd’;
RESPONSE_TYPE_NAME | I.INPUT_VALUE | H.CONFIGURATION_NAME = ‘name of model’;
I.INPUT_NAME = ‘response type name’;

IBM SPSS view:

SPSSSCORE_V_LOG_HEADER AS H
join SPSSSCORE_V_LOG_INPUT AS I on H.SERIAL = I.SERIAL

Parent topic: Configure logging in IBM SPSS Collaboration and Deployment

Troubleshooting a problemIBM Predictive Customer Intelligence| Troubleshooting a problemTroubleshooting is a systematic approach to solving a problem. The goal of troubleshooting is to determine why something does not work as expected and how to resolve the problem.Review the following table to help you or customer support resolve a problem.Troubleshooting actions and descriptionsActionsDescriptionA product fix might be available to resolve your problem.Apply all known fix packs, or service levels, or program temporary fixes (PTF).Look up error messages by selecting the product from the IBM Support Portal, and then typing the error message code into the Search support box (www.ibm.com/ support/entry/portal/).Error messages give important information to help you identify the component that is causing the problem.Reproduce the problem to ensure that it is not just a simple error.If samples are available with the product, you might try to reproduce the problem by using the sample data.Ensure that the installation successfully finished.The installation location must contain the appropriate file structure and the file permissions. For example, if the product requires write access to log files, ensure that the directory has the correct permission.Review all relevant documentation, including release notes, technotes, and proven practices documentation.Search the IBM Knowledge Center to determine whether your problem is known, has a workaround, or if it is already resolved and documented.Review recent changes in your computing environment.Sometimes installing new software might cause compatibility issues.If the items in the table did not guide you to a resolution, you might need to collect diagnostic data. This data is necessary for an IBM technical-support representative to effectively troubleshoot and assist you in resolving the problem. You can also collect diagnostic data and analyze it yourself.Troubleshooting resourcesTroubleshooting resources are sources of information that can help you resolve a problem that you are having with an IBM product.

Troubleshooting a problem

Troubleshooting is a systematic approach to solving a problem. The goal of troubleshooting is to determine why something does not work as expected and how to resolve the problem.

Review the following table to help you or customer support resolve a problem.

Table 22. Troubleshooting actions and descriptions.

Actions | Description
A product fix might be available to resolve your problem. | Apply all known fix packs, or service levels, or program temporary fixes (PTF).
Look up error messages by selecting the product from the IBM Support Portal, and then typing the error message code into the Search support box (www.ibm.com/ support/entry/portal/). | Error messages give important information to help you identify the component that is causing the problem.
Reproduce the problem to ensure that it is not just a simple error. | If samples are available with the product, you might try to reproduce the problem by using the sample data.
Ensure that the installation successfully finished. | The installation location must contain the appropriate file structure and the file permissions. For example, if the product requires write access to log files, ensure that the directory has the correct permission.
Review all relevant documentation, including release notes, technotes, and proven practices documentation. | Search the IBM Knowledge Center to determine whether your problem is known, has a workaround, or if it is already resolved and documented.
Review recent changes in your computing environment. | Sometimes installing new software might cause compatibility issues.

If the items in the table did not guide you to a resolution, you might need to collect diagnostic data. This data is necessary for an IBM® technical-support representative to effectively troubleshoot and assist you in resolving the problem. You can also collect diagnostic data and analyze it yourself.

Troubleshooting resources
Troubleshooting resources are sources of information that can help you resolve a problem that you are having with an IBM product.

Troubleshooting resourcesIBM Predictive Customer Intelligence | Troubleshooting resourcesTroubleshooting resources are sources of information that can help you resolve a problem that you are having with an IBM product.Support PortalThe IBM Support Portal is a unified, centralized view of all technical support tools and information for all IBM systems, software, and services. The IBM Support Portal lets you access all the IBM support resources from one place. You can tailor the pages to focus on the information and resources that you need for problem prevention and faster problem resolution. Familiarize yourself with the IBM Support Portal by viewing the demo videos (https://www.ibm.com/blogs/SPNA/entry/the_ibm_support_portal_videos). Find the content that you need by selecting your products from the IBM Support Portal (www.ibm.com/support/entry/portal).Before contacting IBM Support, you will need to collect diagnostic data (system information, symptoms, log files, traces, and so on) that is required to resolve a problem. Gathering this information will help to familiarize you with the troubleshooting process and save you time.Service requestService requests are also known as Problem Management Reports (PMRs). Several methods exist to submit diagnostic information to IBM Software Technical Support.To open a PMR or to exchange information with technical support, view the IBM Software Support Exchanging information with Technical Support page (www.ibm.com/software/support/exchangeinfo.html).Fix CentralFix Central provides fixes and updates for your system's software, hardware, and operating system.Use the pull-down menu to navigate to your product fixes on Fix Central (www.ibm.com/systems/support/fixes/en/fixcentral/help/getstarted.html). You may also want to view Fix Central help.IBM developerWorksIBM developerWorks provides verified technical information in specific technology environments.As a troubleshooting resource, developerWorks provides easy access to the most popular practices, in addition to videos and other information: developerWorks (www.ibm.com/developerworks).IBM RedbooksIBM Redbooks are developed and published by the IBM International Technical Support Organization, the ITSO. IBM Redbooks (www.redbooks.ibm.com) provide in-depth guidance about such topics as installation and configuration and solution implementation.Software support and RSS feedsIBM Software Support RSS feeds are a quick, easy, and lightweight format for monitoring new content added to websites.After you download an RSS reader or browser plug-in, you can subscribe to IBM product feeds at IBM Software Support RSS feeds (https://www.ibm.com/software/support/rss).Log filesLog files can help you troubleshoot problems by recording the activities that take place when you work with a product.Error messagesThe first indication of a problem is often an error message. Error messages contain information that can be helpful in determining the cause of a problem.Troubleshooting a problemTroubleshooting is a systematic approach to solving a problem. The goal of troubleshooting is to determine why something does not work as expected and how to resolve the problem.

Troubleshooting resources

Troubleshooting resources are sources of information that can help you resolve a problem that you are having with an IBM® product.

Support Portal

The IBM Support Portal is a unified, centralized view of all technical support tools and information for all IBM systems, software, and services.

The IBM Support Portal lets you access all the IBM support resources from one place. You can tailor the pages to focus on the information and resources that you need for problem prevention and faster problem resolution. Familiarize yourself with the IBM Support Portal by viewing the demo videos (https://www.ibm.com/blogs/SPNA/entry/the_ibm_support_portal_videos).

Find the content that you need by selecting your products from the IBM Support Portal (www.ibm.com/support/entry/portal).

Before contacting IBM Support, you will need to collect diagnostic data (system information, symptoms, log files, traces, and so on) that is required to resolve a problem. Gathering this information will help to familiarize you with the troubleshooting process and save you time.

Service request

Service requests are also known as Problem Management Reports (PMRs). Several methods exist to submit diagnostic information to IBM Software Technical Support.

To open a PMR or to exchange information with technical support, view the IBM Software Support Exchanging information with Technical Support page (www.ibm.com/software/support/exchangeinfo.html).

Fix Central

Fix Central provides fixes and updates for your system's software, hardware, and operating system.

Use the pull-down menu to navigate to your product fixes on Fix Central (www.ibm.com/systems/support/fixes/en/fixcentral/help/getstarted.html). You may also want to view Fix Central help.

IBM developerWorks

IBM developerWorks® provides verified technical information in specific technology environments.

As a troubleshooting resource, developerWorks provides easy access to the most popular practices, in addition to videos and other information: developerWorks (www.ibm.com/developerworks).

IBM Redbooks

IBM Redbooks® are developed and published by the IBM International Technical Support Organization, the ITSO.

IBM Redbooks (www.redbooks.ibm.com) provide in-depth guidance about such topics as installation and configuration and solution implementation.

Software support and RSS feeds

IBM Software Support RSS feeds are a quick, easy, and lightweight format for monitoring new content added to websites.

After you download an RSS reader or browser plug-in, you can subscribe to IBM product feeds at IBM Software Support RSS feeds (https://www.ibm.com/software/support/rss).

Log files

Log files can help you troubleshoot problems by recording the activities that take place when you work with a product.

Error messages

The first indication of a problem is often an error message. Error messages contain information that can be helpful in determining the cause of a problem.

Parent topic: Troubleshooting a problem

NoticesThis information was developed for products and services offered worldwide.This material may be available from IBM in other languages. However, you may be required to own a copy of the product or product version in that language in order to access it. IBM may not offer the products, services, or features discussed in this document in other countries. Consult your local IBM representative for information on the products and services currently available in your area. Any reference to an IBM product, program, or service is not intended to state or imply that only that IBM product, program, or service may be used. Any functionally equivalent product, program, or service that does not infringe any IBM intellectual property right may be used instead. However, it is the user's responsibility to evaluate and verify the operation of any non-IBM product, program, or service. This document may describe products, services, or features that are not included in the Program or license entitlement that you have purchased. IBM may have patents or pending patent applications covering subject matter described in this document. The furnishing of this document does not grant you any license to these patents. You can send license inquiries, in writing, to: IBM Director of Licensing IBM Corporation North Castle Drive Armonk, NY 10504-1785 U.S.A. For license inquiries regarding double-byte (DBCS) information, contact the IBM Intellectual Property Department in your country or send inquiries, in writing, to: Intellectual Property Licensing Legal and Intellectual Property Law IBM Japan Ltd. 19-21, Nihonbashi-Hakozakicho, Chuo-ku Tokyo 103-8510, Japan The following paragraph does not apply to the United Kingdom or any other country where such provisions are inconsistent with local law: INTERNATIONAL BUSINESS MACHINES CORPORATION PROVIDES THIS PUBLICATION "AS IS" WITHOUT WARRANTY OF ANY KIND, EITHER EXPRESS OR IMPLIED, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF NON-INFRINGEMENT, MERCHANTABILITY OR FITNESS FOR A PARTICULAR PURPOSE. Some states do not allow disclaimer of express or implied warranties in certain transactions, therefore, this statement may not apply to you. This information could include technical inaccuracies or typographical errors. Changes are periodically made to the information herein; these changes will be incorporated in new editions of the publication. IBM may make improvements and/or changes in the product(s) and/or the program(s) described in this publication at any time without notice. Any references in this information to non-IBM Web sites are provided for convenience only and do not in any manner serve as an endorsement of those Web sites. The materials at those Web sites are not part of the materials for this IBM product and use of those Web sites is at your own risk. IBM may use or distribute any of the information you supply in any way it believes appropriate without incurring any obligation to you.Licensees of this program who wish to have information about it for the purpose of enabling: (i) the exchange of information between independently created programs and other programs (including this one) and (ii) the mutual use of the information which has been exchanged, should contact: IBM Software Group Attention: Licensing 3755 Riverside Dr. Ottawa, ON K1V 1B7 Canada Such information may be available, subject to appropriate terms and conditions, including in some cases, payment of a fee. The licensed program described in this document and all licensed material available for it are provided by IBM under terms of the IBM Customer Agreement, IBM International Program License Agreement or any equivalent agreement between us.Any performance data contained herein was determined in a controlled environment. Therefore, the results obtained in other operating environments may vary significantly. Some measurements may have been made on development-level systems and there is no guarantee that these measurements will be the same on generally available systems. Furthermore, some measurements may have been estimated through extrapolation. Actual results may vary. Users of this document should verify the applicable data for their specific environment. Information concerning non-IBM products was obtained from the suppliers of those products, their published announcements or other publicly available sources. IBM has not tested those products and cannot confirm the accuracy of performance, compatibility or any other claims related to non-IBM products. Questions on the capabilities of non-IBM products should be addressed to the suppliers of those products. All statements regarding IBM's future direction or intent are subject to change or withdrawal without notice, and represent goals and objectives only. This information contains examples of data and reports used in daily business operations. To illustrate them as completely as possible, the examples include the names of individuals, companies, brands, and products. All of these names are fictitious and any similarity to the names and addresses used by an actual business enterprise is entirely coincidental. If you are viewing this information softcopy, the photographs and color illustrations may not appear.This Software Offering does not use cookies or other technologies to collect personally identifiable information.©

Notices

This information was developed for products and services offered worldwide.

This material may be available from IBM in other languages. However, you may be required to own a copy of the product or product version in that language in order to access it.

IBM may not offer the products, services, or features discussed in this document in other countries. Consult your local IBM representative for information on the products and services currently available in your area. Any reference to an IBM product, program, or service is not intended to state or imply that only that IBM product, program, or service may be used. Any functionally equivalent product, program, or service that does not infringe any IBM intellectual property right may be used instead. However, it is the user's responsibility to evaluate and verify the operation of any non-IBM product, program, or service. This document may describe products, services, or features that are not included in the Program or license entitlement that you have purchased.

IBM may have patents or pending patent applications covering subject matter described in this document. The furnishing of this document does not grant you any license to these patents. You can send license inquiries, in writing, to:

IBM Director of Licensing

IBM Corporation

North Castle Drive

Armonk, NY 10504-1785

U.S.A.

For license inquiries regarding double-byte (DBCS) information, contact the IBM Intellectual Property Department in your country or send inquiries, in writing, to:

Intellectual Property Licensing

Legal and Intellectual Property Law

IBM Japan Ltd.

19-21, Nihonbashi-Hakozakicho, Chuo-ku

Tokyo 103-8510, Japan

The following paragraph does not apply to the United Kingdom or any other country where such provisions are inconsistent with local law: INTERNATIONAL BUSINESS MACHINES CORPORATION PROVIDES THIS PUBLICATION "AS IS" WITHOUT WARRANTY OF ANY KIND, EITHER EXPRESS OR IMPLIED, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF NON-INFRINGEMENT, MERCHANTABILITY OR FITNESS FOR A PARTICULAR PURPOSE. Some states do not allow disclaimer of express or implied warranties in certain transactions, therefore, this statement may not apply to you.

This information could include technical inaccuracies or typographical errors. Changes are periodically made to the information herein; these changes will be incorporated in new editions of the publication. IBM may make improvements and/or changes in the product(s) and/or the program(s) described in this publication at any time without notice.

Any references in this information to non-IBM Web sites are provided for convenience only and do not in any manner serve as an endorsement of those Web sites. The materials at those Web sites are not part of the materials for this IBM product and use of those Web sites is at your own risk.

IBM may use or distribute any of the information you supply in any way it believes appropriate without incurring any obligation to you.

Licensees of this program who wish to have information about it for the purpose of enabling: (i) the exchange of information between independently created programs and other programs (including this one) and (ii) the mutual use of the information which has been exchanged, should contact:

IBM Software Group

Attention: Licensing

3755 Riverside Dr.

Ottawa, ON

K1V 1B7

Canada

Such information may be available, subject to appropriate terms and conditions, including in some cases, payment of a fee.

The licensed program described in this document and all licensed material available for it are provided by IBM under terms of the IBM Customer Agreement, IBM International Program License Agreement or any equivalent agreement between us.

Any performance data contained herein was determined in a controlled environment. Therefore, the results obtained in other operating environments may vary significantly. Some measurements may have been made on development-level systems and there is no guarantee that these measurements will be the same on generally available systems. Furthermore, some measurements may have been estimated through extrapolation. Actual results may vary. Users of this document should verify the applicable data for their specific environment.

Information concerning non-IBM products was obtained from the suppliers of those products, their published announcements or other publicly available sources. IBM has not tested those products and cannot confirm the accuracy of performance, compatibility or any other claims related to non-IBM products. Questions on the capabilities of non-IBM products should be addressed to the suppliers of those products.

All statements regarding IBM's future direction or intent are subject to change or withdrawal without notice, and represent goals and objectives only.

This information contains examples of data and reports used in daily business operations. To illustrate them as completely as possible, the examples include the names of individuals, companies, brands, and products. All of these names are fictitious and any similarity to the names and addresses used by an actual business enterprise is entirely coincidental.

If you are viewing this information softcopy, the photographs and color illustrations may not appear.

This Software Offering does not use cookies or other technologies to collect personally identifiable information.

©

© Product Information This document applies to IBM Predictive Customer Intelligence Version 1.0.1 and may also apply to subsequent releases. Copyright Licensed Materials - Property of IBM © Copyright IBM Corp. 2015, 2016. US Government Users Restricted Rights – Use, duplication or disclosure restricted by GSA ADP Schedule Contract with IBM Corp. IBM, the IBM logo and ibm.com are trademarks or registered trademarks of International Business Machines Corp., registered in many jurisdictions worldwide. Other product and service names might be trademarks of IBM or other companies. A current list of IBM trademarks is available on the Web at Copyright and trademark information at www.ibm.com/legal/copytrade.shtml. Notices

©

Product Information

This document applies to IBM Predictive Customer Intelligence Version 1.0.1 and may also apply to subsequent releases.

Copyright

Licensed Materials - Property of IBM

© Copyright IBM Corp. 2015, 2016.

US Government Users Restricted Rights – Use, duplication or disclosure restricted by GSA ADP Schedule Contract with IBM Corp.

IBM, the IBM logo and ibm.com are trademarks or registered trademarks of International Business Machines Corp., registered in many jurisdictions worldwide. Other product and service names might be trademarks of IBM or other companies. A current list of IBM trademarks is available on the Web at " Copyright and trademark information " at www.ibm.com/legal/copytrade.shtml.

Parent topic: Notices