How to measure the effectiveness of mobile retargeting
Many app marketers already learned how to evaluate the performance of user acquisition campaigns. Most of them know how to calculate ROI and how to use cohort analysis. But when you add retargeting, it gets complicated. Since it is still rather new and not many app marketers actively use it, it is not well-known how to understand whether your retargeting campaign is effective. In this article, I’ll look at basic examples of how to measure the performance of retargeting campaigns.
Just to clarify, when we talk about retargeting, we mean advertising campaigns that are not targeted at acquiring new users, but at returning users who have previously installed the app.
Pure user acquisition
To start, let’s look at a simple example that focuses on user acquisition without retargeting. Let’s say you have an app for food delivery. In January, you attracted 10,000 installations for $10,000.
Over the course of the year, 600 users out of these 10,000 made their first order (6% conversion). Some of these users only made one order while some made 20, but on average, each of these 600 users made four orders during the year. You earned $5 on average per order.
ROI for the ad campaign during the first year was 120%.
This is a pretty good model — in real life, things don’t usually work out this well. But it’s possible if you have a great app and very targeted traffic. ROI of 120% is decent, but it could be better, so you decide to apply retargeting.
Pure retargeting
Strictly speaking, you have two options for who to target:
- The users who have not made the first order yet (increase C1).
2. The users who have already made an initial order (increase orders per user).
Let’s take the first case and target just the users who haven’t made an order yet. As soon as a user makes an order, they aren’t part of the target audience anymore (you can customize this).
To begin with, let’s look at an example when we target users who are definitely not going to convert themselves. For example, we attracted 10,000 users a year ago, and 600 of them converted to their first orders. The remaining 9,400 still haven’t made an order. They’re probably never going to make their first order if we don’t do anything because it’s been a long time now.
In this case, we are willing to pay almost as much to get these users back as we would for a new user.
This is what our model will look like in this situation:
We have split 10,000 users into two groups of 600 and 9,400 users. For the second group, the traffic cost is assumed to be $0 because we have already spent $10,000 on the user acquisition campaign and got 600 paying users. We can treat the other 9,400 as a “side effect” of this campaign.
This model shows that we have managed to get 133 additional paying users by spending $2,000 on retargeting, and the retargeting ROI turned out to be higher than the previous user acquisition campaign.
In reality, this won’t always be the case — not every retargeting campaign is effective. But in many cases, it is indeed more cost-efficient to return users via retargeting than to acquire new ones.
User Acquisition + Retargeting
In real life, you can’t afford to wait one year and see if the user did or did not make the first order. You need to retarget users right after the install when they haven’t lost interest yet. This is when retargeting is most effective. But in this case, you have no way of knowing whether you helped them by retargeting or they just returned to the app on their own. Users might just click your retargeting banner when they were actually ready to make the order without any retargeting. This effect is called cannibalization.
This is where the famous A/B test comes to your aid. Take half of the users (group A) and run retargeting for them. Leave the second half (group B) as they are, without any retargeting. After some time, compare the CAC and the ROI in both groups. If group A has a better ROI, retargeting makes sense.
This is what the model will look like:
Comparing the two groups, you can see that CAC (cost per first order) in group A is lower than in group B, while the ROI is higher. In this case, you can conclude that retargeting is effective. If the results in group A were worse than in group B, you would need to optimize the retargeting campaign.
This is a simple way to measure the effectiveness of the retargeting. Of course, this is an overly simplified model, in real life, you are dealing with more metrics, more complicated funnels, and a variety of traffic channels with different traffic costs.
But the basic principles remain the same.
What else is important?
If you have different types of retargeting, it’s better to run A/B testing for each of them. This does require a lot of time and resources. But when you do it, you get a clear picture so that you can run future campaigns with an understanding of the general numbers.
If the retargeting spend is less than 2% of the entire budget, A/B tests can be tricky, since you will hardly see any difference when such small numbers are involved. On the other hand, with these volumes, the cannibalization might also be negligible.
It is wrong to measure CAC (cost per first order) for the retargeting campaign alone. This metric doesn’t give you any real information. The CAC for retargeting will always be lower than the CAC for new traffic because it includes not only the users who were returned by retargeting but also users who would have come back by themselves. The correct approach is to add the retargeting costs to the user acquisition costs and calculate them together.
If you retarget organic users and try to measure CAC, the results with retargeting will always be worse than without retargeting, because organic traffic doesn’t cost anything. In this scenario, you need to calculate total ROI instead of CAC.
Blending various cohorts of users is dangerous. Those who installed the app last month and those who came onboard one year ago are entirely different sets of users. You might be prepared to pay a lot for the users who installed a long time ago and still haven’t made an order. But you probably don’t want to pay so much for the relatively new users, because chances are they will make the order without any help.
Thorough work with a retargeting campaign demands a lot of time and resources. You need to analyze various audiences, run tests and track a lot of metrics. But it’s worth it. Once done, these calculations will help you spend money wisely and scale your retargeting campaigns in the future. Don’t forget to use automated solutions created specifically for mobile apps — they will save you some time.
Just remember, if you are looking for retargeting campaigns, you can get in touch anytime!
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