To create predictive audiences for an eCommerce site, which approach would be effective?

Creating an audience of users who are likely to purchase in the next seven days is an effective approach for predictive audiences in eCommerce. This strategy leverages the predictive capabilities of Google Analytics 4, which uses machine learning to analyze user behavior and identify patterns that can indicate future purchasing activity. By targeting users identified as likely to convert shortly, you can tailor your marketing efforts, such as personalized promotions or reminders, to those users, increasing the chances of successful transactions.

This method specifically takes advantage of predictive analytics to focus on users who exhibit behaviors or characteristics that statistically correlate with upcoming purchases. This ensures that marketing resources are directed towards the individuals who are more inclined to engage with the site and make a purchase soon, optimizing campaign performance and potentially increasing revenue.

In contrast, other approaches may not effectively focus on immediate intent. For instance, targeting users who have purchased in the last month does not take advantage of predictive behaviors and may miss users who are ready to buy again soon. Similarly, reaching out to users unlikely to purchase or to those who visited without buying could dilute the intensity of your campaign focus, as these groups may not exhibit the same immediate buying intent that predictive audiences provide.