Friday 31st of July 2020
After a core update earlier in May, followed by a page experience update, Google recently released two new features aimed at giving accurate audience and purchase predictions to website and app owners.
The idea is to help you make informed decisions on whether you should or shouldn’t try to retain certain audiences through Google Ads, and on how to allocate your budget depending on your audience’s behaviour. Luckily for your marketing budget, this new service is entirely free, courtesy of Google. All it requires is your consent to give Google every single piece of your website data, and to be fair, this seems pretty simple and worthwhile. In this article, we will tell you why you need to activate these features, and how to activate them.
What are the new predictive metrics?
Predictive metrics are simply Google using machine learning (ML) to analyse your website data and then give you predictions on future actions that people may take. The two predictive metrics introduced recently are Purchase Probability and Churn Probability. The first one, Purchase Probability, aims at predicting “the likelihood that users who have visited your app or site will purchase in the next seven days”, whereas the second one, Churn Probability, aims at predicting “how likely it is that recently active users will not visit your app or site in the next seven days”.
What is the purpose of these metrics?
Firstly, predictive metrics can help you build new audiences in Google Ads. Google will automatically suggest audiences to you, so that you can easily target users who are most likely to purchase in the next seven days, active users who are not likely to visit your site or app in the next seven days, or even users who are likely to make their first purchase in the next seven days. Targeting this kind of audience can sometimes help people in their buying process, and eventually make them click the buy button. Although this targeting method is similar to targeting users who previously visited your site and abandoned their shopping carts, the difference is that this new approach includes people who never selected an item, but are likely to convert in the future due to their online behaviour.
Secondly, predictive metrics can help you analyse your data. For example, say you have different ad campaigns running and you want to allocate your budget more efficiently. If you don’t know what information to base your budget allocation on, predictive metrics can be very useful. Imagine you find out that your remarketing campaign helped you acquire more users with the highest purchase probability than your search campaign, you now have a solid argument to allocate a larger part of your budget towards remarketing.
How to get the new predictive metrics?
First of all, you need to have a website or an app that is connected to Google Analytics. This can sound a bit more technical but the following steps are essential if you want your predictive metrics to be available. You will need to have benchmarking enabled within your data-sharing options, and your websites will also need to be collecting purchase events data.
The main thing to bear in mind is, obviously, the more purchase activity, the more accurate your predictions will be. Even though your website or app may qualify for these new features, they may not be activated just yet for the simple reason that Google needs to collect enough data to create accurate predictions. In short, there is nothing to worry about, once you will reach a specific threshold the predictive metrics will automatically become available to you.
What do you think about this new tool? Let us know, and get in touch if you need any assistance!