Why Google’s Predictive Audiences Feature Matters to Advertisers
Google Analytics 4 (GA4) is more than an upgrade to Universal Analytics (UA). GA4 is a whole new analytics solution available now. Businesses should switch from from Universal Analytics (UA) to GA4 now in order to capitalize on GA4’s many features such as Predictive Audiences in Google Ads campaigns. Predictive Audiences relies on artificial intelligence (AI) to drive better results than currently possible with UA.
What Is Predictive Audiences?
Predictive Audiences makes it possible to classify users who are likely to perform an action in the near future based on a predictive metric. For example, a business might build an audience for “likely 7-day purchasers” that includes users who are likely to make a purchase in the next 7 days; or “likely 7-day churning users” for purchasing users who are not likely to visit your website in the next 7 days, just to cite two examples.
Predictive Audiences are automatically shared with any Google Ads accounts you have linked to your property.
AI is not new to Google Analytics. UA properties have Smart Lists, which are audiences Google automatically builds using machine learning. However, Smart Lists are much more limited than the new Predictive Audiences available in GA4. Whereas Smart Lists are not customizable by advertisers, Predictive Audiences can be built with custom traffic/activity filters, as well as a membership duration that is anywhere between 1 and 540 days.
What Are Some Applications of Predictive Audiences?
With Predictive Audiences, an advertiser can improve marketing campaigns to target users before they take an action, potentially increasing conversions. For instance:
- As remarketing audiences. A shopper who is considering your product but not ready to become a customer is a hot lead. For example, someone who has added a product to a shopping cart but has not yet made a purchase might be ready to buy, but they also might be checking out the competition. It’s important that the merchant act on those leads – to strike while the iron is hot. GA4 uses machine learning to find deep patterns of behavior that are unique to your property and show that a user is likely to convert. A persuasive follow-up from you via a well-crafted remarketing campaign can provide that last nudge they need to complete the process.
- In re-engagement campaigns. Shoppers who are likely to churn are signaling a waning interest in your business. But they have also previously demonstrated engagement with your business. Why give up on them? Predictive Audiences makes it possible to approach them again with reminders of the value you offer in terms of product variety, quality, and price, or convenient shipping and return options.
Why Does Predictive Audiences Matter?
Predictive Audiences illustrates how Google is using machine learning to understand future actions of a user. This gives marketers more ways to reach potential customers and increase revenue. When a machine teaches itself with minimal programming needed, it can ingest vast sets of consumer data and use it to determine things such as the best times to send emails or to run an ad. Proponents say machine learning can identify the clients or customers that would be most receptive to given messages.
Google continues to invest in machine learning to make marketing more effective. However, we caution against simply automating advertising. Human judgment is needed to ensure that a marketing campaign is adaptable and flexible as the behavior of users changes.
How Does an Advertiser Get Started with Predictive Analytics?
Availability of Predictive Audiences depends on the underlying predictive metrics being eligible for use by meeting all prerequisites. If you have exported Predictive Audiences to linked product accounts, those audiences will not accumulate new users if the property becomes ineligible for the predictive metric and new predictions are not generated. Google shares more insight on how to use suggested audience templates to create your own audiences with conditions based on those predictions.
Getting started with Predictive Analytics is but one of many steps an advertiser will need take in order to make the transition to GA4. Don’t wait until July 2023 to get ready. Only by acting now will an advertiser prepare itself to capitalize on the new features available in GA4.
True Interactive can help you do that. Read more about GA4 in this blog post.
Contact True Interactive
To succeed with online advertising, contact True Interactive. We design and develop successful marketing and advertising campaigns and know how to track results, including the use of Google. Read about some of our client work here.
Photo by Hannah Wei on UnsplashAnalytics