Google has added some new predictive audience tools into Google Analytics. Which seeks to help businesses connect with website visitors and app users. That is increasingly likely to take certain, defined actions. In order to then guide your marketing activities based on those predictions.
Extend Predictive Audiences in Google Ads
As explained by Google:
“Analytics will now suggest new predictive audiences that you can create in the Audience Builder. For example, using Purchase Probability, we will suggest the audience “Likely 7-day purchasers” which includes users who are most likely to purchase in the next seven days.”
In the past, if you wanted to reach people most likely to purchase, you’d probably build an audience of people who had added products to their shopping carts but didn’t purchase. However, with this approach, you might miss reaching people who never selected an item but are likely to purchase in the future. Predictive audiences automatically determine which customer actions on your app or site might lead to a purchase.
That could be handy, right?
If you had a fair inkling as to which of your website visitors were likely to make a purchase soon. You could target them with relevant ads or offers to encourage that action.
So how does Google determine people likely to make a purchase?
The process utilizes Google’s advanced prediction capacity, based on your website data, in order to evaluate the likely response actions from each visitor.
“For example, users who have studied product details or added items to their carts. And have given strong signals that they’re already taking ownership of those products. Analytics goes beyond these simple signals and uses machine learning to find deep patterns of behavior. That is unique to your property and show that a user is likely to convert.”
What are Data Requirements?
There are, of course, some data requirements to facilitate such.
First off, websites need to be connected to Google Analytics (obviously), and also have benchmarking enabled within your data-sharing options. Websites also need to be collecting purchase (and/or “in_app_purchase”) events data. While Google’s system also needs a lot of activity to provide accurate predictions.
- A minimum number of positive and negative examples of purchasers or churned users. In order to be eligible, it is required that 1,000 users triggered the relevant predictive condition and that 1,000 users did not.
- Model quality must be sustained over a period of time to be eligible.
So, it won’t be for every business, but if your website meets these requirements, it could be a valuable addition. Google’s new predictive audience options able to highlight specific subsets of people who are likely to make a purchase within the next week. As well as those likely to stop visiting your site, which you can focus on with re-engagement campaigns.
Analysis Module
In addition to this, Google’s predictive metrics can also be used within your general marketing research process. Using the analysis module within Google Analytics, the data can highlight. Which of your campaigns helped you acquire users with the highest Purchase Probability, based on the same calculations.
New predictive audience options
There are two predictive audience options based on these new metrics:
- Purchase Probability audiences: Likely 7-day purchasers and Likely first-time 7-day purchasers.
- Churn Probability audiences: Likely 7-day churning purchasers and Likely 7-day churning users. Give past site visitors reason to come back.
Analyze using predictive metrics
Using the Analysis module, you can use these new predictive metrics to build reports such as understanding which marketing campaigns brought in users deemed to have the highest Purchase Probability.
Why we care
Machine learning-driven audiences aren’t new in Google Analytics. Smart Lists debuted way back in 2014 but these updates offer more options and flexibility. Expect more to come.
Google says the new metrics and audiences will be available in the coming weeks. You’ll need to have purchase events set up or automatically measuring in-app purchases in your App + Web property.
