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Create a Facebook Page Insights Data Stream in Marketing Cloud Intelligence Data Pipelines

To track and view Facebook Page insights, create a Facebook Page Insights data stream.

Required Editions

User Permissions Needed
To create an API data stream: Admin

To create a Facebook Page Insights API data stream, you need a Valid Facebook user account with permissions to manage the page.

  1. On the Import tab, expand Data Streams.
  2. Click Add New.
  3. Select the Facebook Page Insights connector.
  4. In the General section, enter your credentials, and select the page that you want to pull data for. Selecting multiple pages results in a new data steam for each page selected.
  5. To add a data source authentication, click Add New and enter your Facebook credentials.
  6. Set the time period for the initial data fetch. You can process data up to the past 180 days.
  7. In the Extended Properties section, you can set these properties:
    • If the page requires manual page ID input, insert the page ID here. Only one ID can be entered at a time.
    • To add a breakdown, select one from the dropdown. Adding a breakdown adds granularity to your data allowing you to gain deeper insights. (Age & Gender breakdown dimensions must be mapped manually.)
    • To retrieve metrics collected over the course of 28 days select Get 28 Days Metrics.
    • To retrieve all the location pages you manage, as separate pages, select Get main page and additional locations pages. The main page is labeled Main Page.
  8. To change the mapping, click Mapping. Otherwise, you can always access mapping by selecting Map to Model at the bottom of the Create New Stream page.
  9. To define advanced settings, at the bottom of the screen, select Advanced Settings.
  10. Click Create.
  11. Quality check your data:
    1. Create a report on the Facebook Page Insights platform for the required date range.
    2. Process the relevant data stream in Marketing Cloud Intelligence Data Pipelines, filtered to the same date range.
    3. Create an identical report or pivot table in Marketing Cloud Intelligence Data Pipelines with the same date range, dimensions, and measurements.
    4. Compare the measurement totals to make sure that they’re aligned.