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Adding behavioral data to a customer profile

The Behavioral Data accelerator component, designed for use in your Pega Customer Decision Hub™ application, is available for download on the Pega Marketplace. This component is engineered to ingest a variety of behavioral data, including web clickstreams, customer intent and interests, and product usage behavior from multiple sources. It comprises all the essential artifacts required to promptly acquire industry-specific best practice clickstream summaries.



This demo shows you how to use the accelerator component to leverage industry-specific best practice clickstream summaries and extend the customer profile with behavioral data to improve the performance of the predictive models.

The U+ Bank technical team aims to improve the out-of-the-box best practices of Customer Profile Designer to capture clickstream data to extend a customer's profile and introduce powerful predictors to their existing adaptive models.

To capture clickstream data, download the Behavioral Data accelerator component from Pega Marketplace.

Pega marketplace


In Dev Studio, use the import wizard to import the downloaded component into the Pega application.

Navigate to the application definition to add the new component.
Next, click Manage components and enable the Behavioral Data component.

Manage components


Confirm that the component is displayed in the Enabled components section of the application rule, and then save your changes.
Now, in the Pega Customer Decision Hub portal, navigate to Data > Profile Data Sources to add the clickstream data source. Add the Process clickstream data data flow.

Adding process clickstream data


The data flow contains the Stream clickstream data set that the component provides to store customer interactions such as web clicks.

The behavioral data accelerator component includes several important artifacts:

  • A sample Behavioral Data Rest service that the system can invoke from a website.
  • A data structure to support the service payload.
  • A Stream clickstream data set for generic clickstream data.
  • Example summaries for aggregation of clickstreams on industry-specific web pages.

The number of summaries and aggregate conditions that the system allows are limited to ensure that there is no impact on system performance. You apply these limits through the dynamic system settings.

The maximum number of summary associations across all contexts (max_summary_associations_number) dynamic system setting shows the number of summaries that you can create in Customer Profile Designer. The default value is 10.

max aggregates number dss


The maximum number of aggregates per summary on CPD (max_aggregates_number) dynamic system setting is the number of aggregate conditions each summary can hold, which has a default value of 120.

You can change these limits if necessary, but analyze the performance impact.

It is important to note that the system cannot directly associate streaming data with the primary context and needs to summarize the data into meaningful aggregations.
On the Summaries tab, the Financial services clickstream summary is available. Note that the data source for this summary uses the Process Clickstream data dataflow.

Financial services clickstream


This setting means that every event that flows through the Process Clickstream data factors into the calculation of the aggregations in the Financial services clickstream summary rule.

Launch the Financial services clickstream summary rule, then click Save. The system begins a background process for creating the aggregate properties, dataflow scheduler, the corresponding class structure for the generated artifacts, and marking the properties as relevant for use in Next-Best-Action Designer.

This Financial services clickstream summary includes 90 aggregates, each with a unique aggregation condition. For example, select the Card page visits last 1 day aggregate to browse its condition. You can see that this aggregation counts the number of eventtypes received as PageView with a PageType of Card that occurred in the last one day.

Aggregate overview

With everything in place, associate this summary with your primary context in the Profile Designer.
Add a new summary to the associated data of the primary context. In this case, Financial services clickstream.
The Financial services clickstream summary rule has a single data source key, which is automatically mapped to the context key of the primary class.

Data source key and context key mapping

Once you add the summary as a new association, save your changes.
You are ready to test the configuration. In Dev Studio, search for the Behavioral Data service REST rule for testing.
Run the service with a sample JSON payload as if the web page invokes the service for a customer who is viewing the Cards page.



Now, in the Financial services clickstream summary rule that you associated with the customer, click the Records tab. Browse the aggregated data record that the system generates for the event.
You can now share the JSON structure and service endpoint with web developers.

The U+ Bank technical team has developed an integration between the website and Customer Decision Hub. Now, the customer's web activity streams in through the Behavioral data service that you previously tested.

Launch the U+ website and log in as Troy.
At the top of the screen, click Credit Cards to open the Cards page.
By logging in to the Account overview for Troy and navigating to the Credit Cards page, you create some web activity for Troy.

In Customer Decision Hub, review the records in the Financial services clickstream to verify that the events streamed and processed successfully.

Confirm that the aggregate CardPageVisitLast1Day has increased. Note that the system began calculating additional aggregates, such as the average active seconds spent on the page.

After reviewing the aggregates, launch Prediction Studio.
After completing the end-to-end testing, it is time to empower the adaptive models by leveraging the attributes that come with the summary rule. This task is typical for data scientists, but it is demonstrated to complete the use case.
In the Predict Web Propensity prediction, launch the Web_Click_Through_Rate adaptive model.

You can add new predictors on the Predictors tab of the adaptive model. Click the Add field list, and then select Add multiple fields to add more than one predictor.
The FSClickstream page in the Customer class contains all the predictors that the system calculates in the FSClickstream summary rule. Select all the properties, and then save your progress.

Adding predictors from FSClickstream

You have reached the end of this video. What did it show you?

  • How to install the Behavioral data accelerator component.
  • How to associate a Summary rule with the primary context.
  • How to test the Behavioral data service.
  • How to use the Behavioral data source as predictors.


Tip: To practice what you have learned in this topic, consider taking the Adding clickstream data to a customer profile challenge.


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