Global Report Filter (Top-level Filter Section)

Located on the “report details panel”

• Very Important: Global report filter only applies to UNIQUE USERS and COMPANIES and not specific data points
  • To filter a COMPANY or a UNIQUE USER is to filter those objects (we call them entities) by their properties and, in HockeyStack, by their actions. When you see “who have done” this is filtering a Unique User of a Company by an Action that they/it performed.
• Function: Global filters apply to the entire report; it is the last filter one would add to the report. These are high-level filters that restrict the data shown across all columns of the report.
• Use Case: You use global filters to include or exclude specific user actions (user in HockeyStack is an umbrella term for Unique Users and Companies), time-periods, behaviors, filtering a set of accounts like region-specific accounts or target accounts etc at a universal level.
• Example: In the screenshot below, the filter is set to Users who have done "enter site" Last Month, meaning that the entire report will only show data related to users who have performed the action "enter site" on last month. Reminder: “Users” is an umbrella term that can mean either Unique Users or Companies. One would choose either option based on the properties the goal is built from - this is specifc to using “who have done”. Otherwise you’d select User properties or Companies properties to specify the type of user

Column-level Filters (In Columns Section)

• Function: The Column-level filters are used to filter data points. What is a data point you ask? A data point is an Action often represented by a goal (but not always). An example of a data points is an MQL. An MQL is a goal that represents the action of “becoming an MQL”. Another example is a Website Session or Amount of Ad Spend. These are not goals in your library but are still Actions in the HockeyStack System.

• Use Case:

  • Main use case: filtering datapoints
  • Secondary Use Case: filter on a particular metric or segment within a column while allowing other columns to remain unfiltered or differently filtered. Unlike the “top level filter” the column-level filter can be used to filter anything, deal, users, companies, sessions etc

• Example: Suppose in one column you’re counting the MQA, you could add a filter to that specific column to just include users who had not submitted any form. A subsequent column might include all MQAs, those who had submitted forms, and those who had not.

  

Breakdown Filters

• The Breakdwon filter filters the touchpoints represented by various defined properties. During set up, you organized your touchpoints into defined properties for 2 reasons:

  1. to group them by category according to the touchpoint hierarchy for easy reporting
  2. to attach an action to the object-based model data, thus converting it to an action-based data model so it can be used in attribution

  Best practice is to set up your defined properties in a way to be easily filterable by adding prefix to group types of data. Ex: all paid mapping start with “Paid-[channel]”

• Use Case: This is useful for drilling down into details and segmenting the data into more meaningful insights by UTM source, action types, and integration data.

• Example: You could break down the report by Unified Channel, which would give you data segmented by the channels you’ve defined in your channel property.

Summary of Differences:

• Global Filters: Apply to the entire report and filter all the data based on the criteria set (e.g., time period, specific actions). This can only be used to filter Actions from Unique Users or Companies.