Boost sales Encourage users who are likely to convert within seven days to make a purchase. Increase Revenue Incentivize users who are likely to spend the most in the next 28 days to make a purchase. Retain new customers Incentivize users who are likely to make their first Where the customer purchase from you within 14 days to make a purchase. Reactivation Encourage users who are unlikely to visit your website in the next 28 days to come back to your website. You can imagine that with a little creativity you can advertise even more specifically and effectively than with the previous (remarketing) target groups.
Marketing plan 2022, here we go!
There are some requirements to use predictive target groups. Predictive Audience Requirement In order to create the predictive target groups, you must have sufficient data. A minimum of 1000 users must have met the predictive condition for 28 days. In addition, 1000 users must also not have met the predictive condition. For example, do you Morocco Phone Number want to target a predictive audience that is likely to make a purchase within seven days? Then, in the past 28 days, at least 1000 users must have completed the ‘purchase’ and/or ‘in_app_purchase’ event, or the conversion purchase. If you comply with this, the machine learning has enough data to make predictions. Can’t get to 1000 conversions?
Consumers are willing to pay more
Then you can, for example, use micro-conversions or steps earlier in the funnel as an event. How do you create predictive audiences? Now that you know what predictive audiences are, it’s time to discover them for yourself. They are quite easy and quick to create. Follow the following steps: Access your Google Analytics 4 property at https://analytics.google.com/ . Via the menu, click on configure . Then click on audiences in the submenu . Click on new audience . Then go to the predictive tab . Then click on the target group you want to create. custom predictive audiences google analytics 4 Google Analytics 4 itself creates the target groups based on user behavior on the site.