Overview

There are two main methods of building an audience in the Ascent360 platform:

1. Audience Builder

a. “Advanced Query” within Audience Builder

2. Complex Audience Builder

When to use “Audience Builder”?

  • For one-time communication/promotions
  • For “testing” audiences to where you need audience counts
  • If you need to mix transaction data with customer information, for example:
    • Lodging guests who are emailable
    • Season Pass holders in California
    • Lift tickets purchasers with Total Lifetime Spend greater than $400

When to use “Advanced Query” function within “Audience Builder”

  • If you have an export field that's not a default output
  • If the export field doesn’t apply to ALL audiences in your complex audience
  • If you have a more complicated audience request but you only need the audience for a one-time send 

Note: To create an “Advanced Query,” toggle it to the “On” position in Audience Builder

When to use “Complex Audience Builder”?

  • If you need the contact list refreshed on an ongoing basis
    • If you will be using a contact list periodically throughout the season, consider scheduling the audience so that it is refreshed regularly
    • Common examples include current season pass holders, lodging or products on the books for the current season, etc.
  • If you need to combine data from different sources
    • Your data flows in from multiple sources and is stored in separate tables before it is brought into the CDP
    • The following data types are stored separately and thus, can only be combined in the Complex Audience Builder
      • Lodging Data
      • Transaction Data i.e. lift ticket, lesson, rental purchases
      • Lift Scans
    • For example,
      • Lodging guests who have a season pass (Lodging and Products live in different tables)
      • Season Pass holders who have scanned this season (Transactions and Scans live in different tables)
      • Lift ticket purchasers with Total Lifetime Spend > $400 (Total Lifetime Spend aggregation occurs separately from transaction data flow)