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Showing posts with label MCAE. Show all posts
Showing posts with label MCAE. Show all posts

Saturday, September 13, 2025

B2B Marketing Analytics: Account Engagement Email Datasets

To continue from the previous blog, if you get an error when creating the B2B Marketing Analytics app, once the app is created successfully, you will see a new app for the B2B Marketing Analytics app; the app name is based on what you entered when creating the app. 

Within the app, you will get many datasets available, starting with "Account Engagement". The datasets are updated daily by Salesforce from MCAE to CRM Analytics. You can monitor it from Jobs Monitor, look for jobs that start with "pd".



You will see the dataset in the B2B Marketing Analytics app, including when the data is refreshed.  

** To get the Prospect and Activity dataset, you need to enable "Get Prospect and Activity Data" in the B2B Marketing Analytics setup menu, which is under Optional Features for B2B Marketing Analytics, then select "Include Prospect and Activity dataset?" when creating the app.



The app comes with multiple dashboards, such as "Engagement," which shows MCAE data, such as:

  • List Email Engagement
  • Email Template Engagement
  • Forms Engagement
  • Landing Page Engagement
These include different metrics for each type of engagement.

In this blog, I want to discuss two of the datasets: the Account Engagement Emails dataset and the Account Engagement Email templates dataset.


Account Engagement Emails dataset 

As per this article, B2B Marketing Analytics Datasets, the dataset API Name is pdEmail. Each row represents 1 day of statistics for an individual list email. You can see the field description in the article above. Let's see some samples:

For Email ID = 2012421957, emails are sent on 2025-09-10, so you see the same Send On Date applied to rows 1 and 2. Some recipients open and click on the same day, and a few open on 2025-09-11. The same applies for Email ID = 2011677609; emails are sent on 2025-09-09 for rows 3, 4, and 5; some people open and click on the same day and the following days. So, this is aggregate data per day per email.

Stats ID is the unique key in the dataset.

Available metrics for this dataset:

  • Click To Open Ratio
  • Delivery Rate
  • Opt Out Rate
  • Spam Complaint Rate
  • Total Bounced
  • Total CTR
  • Total Clicks
  • Total Delivered
  • Total HTML Opens
  • Total Hard Bounced
  • Total Opt Outs
  • Total Queued
  • Total Sent
  • Total Soft Bounced
  • Total Spam Complaint
  • Unique CTR
  • Unique Clicks
  • Unique HTML Open Rate
  • Unique HTML Opens


Account Engagement Email Templates dataset 

From the same article above, the dataset API Name is pdEmailTemplate. Each row represents 1 day of statistics for an individual email template. Email metrics are based on the emails built on selected email templates. 

The email sent here are not from the list email, but automated email, such as the Autoresponder email in Completion Action or Engagement program emails. The email here are not sent at the same time, but only when the user submits a form or receives an auto email from the engagement program.

The Send on Date field is not present on this dataset. This is because templates are reusable email designs that are not tied to specific send events.


We can see the same pattern here: each row represents an Email ID for a day, the total emails sent in a day, email opens, and clicks. 

Similar to the Email dataset, Stats ID is the unique key in the dataset, and almost all metrics are also available in this dataset:
  • Delivery Rate
  • Opt Out Rate
  • Spam Complaint Rate
  • Total CTR
  • Total Clicks
  • Total Delivered
  • Total HTML Opens
  • Total Hard Bounced
  • Total Opt Outs
  • Total Queued
  • Total Sent
  • Total Soft Bounced
  • Total Spam Complaint
  • Unique CTR
  • Unique Clicks
  • Unique HTML Opens

Note: There is an issue with the "Unique HTML Opens" field in this dataset. Here is the KI and idea.



Reference:

Thursday, July 31, 2025

MCAE: Open Prospect user interface with Prospect ID

If you have the Prospect ID, you can open the Prospect detail with the following URL with parameters:

With the Pardot user interface:
https://pi.pardot.com/prospect/read/id/179597888
https://pi.pardot.com/prospect/read?id=179597888

With the Account Engagement user interface:
https://mydomain.lightning.force.com/lightning/page/pardot/prospect?pardot__path=%2Fprospect%2Fread%2Fid%2F179597888




Monday, July 28, 2025

B2B Marketing Analytics: sfdc_internal__B2BMA

B2B Marketing Analytics, a CRM Analytics app within Salesforce, is designed to analyze marketing and sales data. It leverages datasets from Account Engagement (formerly Pardot) and Salesforce to provide insights into campaign performance, prospect behavior, and overall marketing effectiveness. 

You can create the B2B Marketing Analytics app from Analytics Studio, select B2B Marketing Analytics, and follow the wizard.



You need to enter your Pardot Account ID, then select optional features, such as Account-Based Marketing, Multi-Touch Attribution, Prospect and Activity dataset, etc. If you stopped with the following error:

Unable to create app based on template: [sfdc_internal__B2BMA].

* Your org does not currently meet minimum data requirements to proceed. Please fix the following issues before creating a 'B2B Marketing Analytics' Application:

In the 'sfdcDigest_Contact_CWA' node, the 'pi__grade__c' field doesn't exist, is deprecated, or isn't accessible to the Integration User. In the 'sfdcDigest_Contact_CWA' node, the 'pi__score__c' field doesn't exist, is deprecated, or isn't accessible to the Integration User.

You need to adjust the fields in both Lead and Contact, the Account Engagement Score (pi__score__c) and the Account Engagement Grade (pi__grade__c) fields, to make them visible (read-only is sufficient) to the Analytics Cloud Integration User profile. 

From the object manager, open each field and update the field-level security settings to grant visibility to the Analytics Cloud Integration User profile. 

Re-create the B2B Marketing Analytics app from Analytics Studio, and you should be able to pass the error.

Once the app is created, it can also be seen in the "Auto-Installed Apps" in the setup menu.





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