NOTE: It is assumed you know how to create custom Dashboards and Charts, and have an understanding of chart Types, Presets, and Metrics.
If not, read this article before proceeding.
When building your own Dashboard Charts, you can pull data from various data sources to view different types of analytics events.
In this article, we're going to focus on the Export data source.
This data source tracks usage of the Export Personal Information feature your users can use from their profiles to download a JSON export of their own activity from your Higher Logic Vanilla (Vanilla) community.
Use this data source when you want to answer questions like:
- How many users are exporting their personal activity over time?
- How many unique users are using the personal export feature?
- Which user segments (Roles, Ranks, etc.) are most likely to request exports?
- Are there patterns in when and how frequently users request exports?
Filter Chart data
Controlling what data is shown in a Chart is accomplished via the Group By and Filter options.
- The Group By options (available for pie graphs, line graphs, bar graphs, and tables) enable you to define the "broad strokes" of what data to view,
- while Filters let you drill into or exclude specific types of data to fine-tune it.
TIP: You can add one or multiple Group By and Filter options to dissect the data how you see fit. Generally speaking, you'll select Group By options to view a specific slice of data, and, if needed, use Filters to dig deeper.
Let's learn about each of the available Group By and Filter options.
NOTE: These options can be used both to group and filter data.
Export-level data
- Type: Distinguishes the kind of export event that occurred for a user’s personal-activity data (e.g., an export being requested vs. the file being downloaded). Use this when you want to see whether people are just initiating exports or actually retrieving the files.
- Domain: The site/domain on which the user triggered the export. This is most useful for multi-domain or multi-site setups where you want to compare export usage across different front-ends.
- Export Types: The specific kind of personal-data export that was requested (e.g., Personal Activity JSON export vs. any other user-data export types that may be added in the future). Use this to compare adoption of different export experiences.
- Export Date: The date/time the export was requested. Grouping by Export Date shows how usage of the personal export feature changes over time (daily, weekly, monthly, etc.).
User data
- User Name: The display name of the user who requested their export. Group by this to see which individual users are using the feature most.
- User ID: The internal numeric ID of the user. This is stable even if the user changes their display name, and is useful for auditing or troubleshooting specific accounts.
- User UUID: The globally unique identifier for the user. Use this when you care about unique users and need a stable key that won’t change.
- User Role Type: The high-level type of Role the user has (e.g., Member vs. Staff/Admin). Grouping by this helps you answer questions like “Are regular users or staff using personal exports more often?”
- User Role Names: The name(s) of the specific Role(s) assigned to the user (e.g., Moderator, Customer, Super User). Use this to compare export usage across different permission or user segments.
- User Role IDs: The internal IDs of the roles assigned to the user. This is mainly useful if you’re joining Analytics data to external systems or need a stable, non-label identifier for roles.
- User Rank: The name(s) of the specific Rank(s) assigned to the user. Use this to compare export usage across different permission or customer segments.