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Use Case - Creating a new clickstream summary

2 Tasks

30 mins

Visible to: All users
Intermediate Pega Customer Decision Hub '23 Next Best Action English
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Scenario

The technical team has successfully developed the infrastructure for streaming web activity data, and the Pega Customer Decision Hub™ application contains an installation of the accelerator component.

As a result, the U+ Comms website is now streaming the web activity of subscriptions to the Clickstream data set. The integration team provides the following information:

  1. The website creates clickstream events only if the user has successfully authenticated on the U+ Comms website and has a valid cookie.
  2. Currently, the website creates clickstream events only for the Account page and the Home page. However, the product pages will begin streaming events in a later phase of the project.
  3. The following example shows a sample JSON payload for the clickstream service:
    {
    "CustomerID":"1111111111",
    "InterestedIn":"",
    "InterestLevel":"",
    "DeviceType":"PC",
    "Event":"PageView",
    "PageType":"Account",
    "PageViewActiveTime":"45",
    "CookieID":""
    }
  1. The integration team also shares the following data structure with you:
    Field ID Description Type List of Values

    CustomerID

    CustomerID

    The unique ID of the Subscription. Maps to the SubscriptionID in Customer Decision Hub.

    Text

    1111111111, 2222222222….

    Interested in

    InterestedIn

    Currently not used.

    Currently not used.

    Unavailable

    Interest level

    InterestLevel

    Currently not used.

     

    Unavailable

    Device type

    DeviceType

    The type of device used for the login to the website.

    Text

    PC
    Mobile

    Event

    Event

    Type of event that occurred:
    PageView when the user is authenticated and logs in to the website.

    Text

    PageView

    Page type

    PageType

    The type of page that the visitor visited.

    Text

    Home (the login page in U+Comms)
    Account (the page after successful login)
    Offer (the page after clicking on an action)

    Page view active time

    PageViewActiveType

    The time in seconds the visitor spent on the page

    Integer

    123, 234….

    Cookie ID

    CookieID

    Currently not used.

    Currently not used.

    Unavailable

    Tip: A variation of this scenario exists in Creating new aggregates on streamable data.

 

You must initiate your own Pega instance to complete this Challenge.

Initialization may take up to 5 minutes so please be patient.

Detailed Tasks

1 Other details

  1. In the Profile Data Sources, create a new Summary named UComms Clickstream that aggregates the data in the Clickstream data set for each CustomerID.
  2. In the UComms Clickstream summary, create the following aggregations:
    Aggregate Name ID Detail

    Avg Active Secs Acct Last 1 Day

    AvgActiveSecsAcctLast1Day

    Calculates in seconds the average time spent on the Account page over the last day.

    Avg Active Secs Home Last 1 Day

    AvgActiveSecsHomeLast1Day

    Calculates in seconds the average time spent on the Home page over the last day.

    Last Page

    LastPage

    Calculates the last page type visited by the subscriber over all time.

  1. Associate the UComms Clickstream Summary with the Subscription entity, where SubscriptionID maps to CustomerID.
  2. Using Prediction Studio, add the newly defined aggregates to the Web Click Through Rate Subscription adaptive model.
  3. On the exercise landing page, log in to the U+ Comms website with the following profiles to generate clickstream data:
    Use Appswitcher to launch UComms
    1. Log in to the U+ Comms website as Bhuvi.
      Ucomms website
    2. Log out from the U+ Comms website.
    3. Log back into the U+ Comms website as Bhuvi.
  4. Confirm the aggregates are calculated for Bhuvi (SubscriptionID: 1111111111) on the Behavioral data tab, in the Customer Profile Viewer.

2 Acceptance criteria

  1. Use Customer Profile Viewer to confirm that the values in the UComms Clickstream dataset for Bhuvi are aggregated correctly.
  2. The predictors are added to the Web Click Through Rate Subscription adaptive model.


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