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Process documentation Customer Interaction Optimization with Real-Time Analytics Locate the document in its SAP Library structure

Purpose

You can use this business process to provide optimal recommendations and personalized services to the customers interacting with the SAP CRM application using real-time analytics. It describes the process model for optimal personalization in real time. Real-time analytics enables you to apply the knowledge derived from known customer behavior to predict the behavior of a single customer in real-time.

It also offers Key Performance Indicators (KPI) lookup that helps you to optimize personalization in real time. You use the SAP CRM Intelligence Connector to integrate the intelligence stored in the analytical systems like SAP BW to the SAP CRM and provide real-time analytical functions to CRM applications such as Campaign Automation, Interaction Center or Internet Sales. Similarly, you can also have business processes with process models for prediction and KPI lookup.

Prerequisites

Technical Prerequisites

·          SAP CRM 4.0 support package 01

·          SAP BW Release 3.2

Customizing Prerequisites

You need to maintain the customizing table entries for settings URL for Intelligence Connector Workbench for the SAP CRM Intelligence Connector.

Process Flow

This graphic is explained in the accompanying text

1.       System captures clickstream data (SAP BW)

The clickstream data is collected in SAP BW through various sources such as SAP CRM, SAP R/3 Enterprise, external sources.

2.       System provides customer master data and customer profiles (SAP CRM)

3.       System provides activities and sales orders (SAP CRM)

4.       System updates data in customer knowledge base ( SAP BW)

By regularly extracting data from SAP CRM and SAP R/3 into SAP BW, the system updates the data in the customer knowledge base in SAP BW. All available customer data is combined here so that it can be applied in different analyses and in data mining methods.

5.       Create and train data mining model (scoring or decision trees) (SAP BW)

You create a model for a data mining method to specify what is to be predicted and which data should form the basis of the prediction. You then train the model using historic data from a training source. The training result is used for prediction.

6.       Make model available in the Intelligence Connector (SAP CRM)

You deploy the trained model created in the SAP BW in the SAP CRM Intelligence Connector. After deployment, this model is available for prediction in applications. You create a prediction task or a KPI task to specify the mapping. After this, the task can be used in the application.

7.       Include model into interaction rules and define outcoming actions (SAP CRM)

Using the prediction capabilities of the SAP CRM Intelligence Connector and based on the prediction results obtained, suitable actions can be defined for the application.

8.       Customer logs on

When the customer logs on, the application collects the input data to execute the real-time task. Based on this input, there is a predicted outcome for the customer.

9.       System records all relevant online data required for prediction (SAP CRM)

The system records online data which would be uploaded to the SAP BW to be used for further prediction(data mining) analysis.

10.   Systems processes predictive values  (SAP CRM)

The system processes the predicted values. Based on the predicted outcome for a customer, the system defines an action plan.

  1. System triggers personalized action

Based in the customer type predicted, personalized action is triggered.

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