You want to create new audiences for your eCommerce site by segmenting users according to parameters that make sense for your business, like those who've made a purchase. Which of these approaches would provide you with a predictive audience?
You create an audience of users who added items to their purchase wishlist
You create an audience of users who made a purchase in the last 30 days
You create an audience of users who started checking out but didn't complete the purchase
You create an audience of users who are likely to purchase in the next seven days
Explanation
Analysis of Correct Answer(s)
The correct option identifies a predictive audience. In Google Analytics 4 (GA4), predictive audiences use machine learning to model user data and anticipate future actions.
- You create an audience of users who are likely to purchase in the next seven days: This is the definition of a predictive audience. It leverages one of GA4's predictive metrics, "purchase probability," to group users who are forecasted to convert soon. The key phrase is "likely to," which indicates a future prediction rather than a completed past action.
Analysis of Incorrect Options
The other options describe behavioral audiences, which are based on actions users have already taken, not on predictions about future behavior.
- You create an audience of users who made a purchase in the last 30 days: This is a historical segment. It groups users based on a specific past event (a purchase) within a defined timeframe. It does not predict future purchases.
- You create an audience of users who added items to their purchase wishlist: This is another example of a behavior-based audience. It segments users based on a specific past interaction with your site.
- You create an audience of users who started checking out but didn't complete the purchase: This is a classic "cart abandoner" segment. It is built on a sequence of past actions (or inactions) and is not predictive in the way GA4 defines it.