Mobile Retargeting: How to Measure Performance
Measuring the effectiveness of advertising campaigns for the purchase of traffic more or less learned. Many people know how to calculate ROI and know how to apply cohort analysis. But when you add retargeting, things get more complicated.
For several months now at Getloyal we have been doing mobile retargeting for clients from all over the world. In this post we will describe how to measure the effectiveness of retargeting companies using simple examples.
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Let's start with a simple example, when we do only User Acquisition, without retargeting. Suppose you have an application for the delivery of food. In January, you attracted 10,000 installations for $ 10,000. Over the course of the year, 600 of these 10,000 users made the first order (6% conversion). Some of these users made only 1 order per year, some 20, but on average, it turned out that each of these 600 users made 4 orders per year. The average earnings from one order was $ 5. The advertising campaign's ROI for the first year was 120%.
In reality, it rarely happens that the economy converges head-on, but in general, this is possible if we have a cool application and targeted traffic.
ROI 120% is good, but you want more, and you decide to apply retargeting. Strictly speaking, you have two options on which to target:
Take the first case - we will target only those who have not yet made the first order. As soon as the user makes the first order, he disappears from our audience.
To begin with, let's look at an example when we target users who are no longer converting themselves. For example, we attracted 10,000 users a year ago. 600 of them were converted into first orders. The remaining 9,400 have since never made their first order. Most likely, they will never make this order if we do nothing, because a lot of time has passed. In this case, we are ready to pay for the return of these users almost as much as for the new user.
Here is what our model will look like in this case:
We divided 10,000 users, attracted a year ago, into two groups: 600 and 9,400. In the second group, we consider costa for traffic equal to zero - after all, before that, we had already spent $ 10,000 and received 600 paying users. The remaining 9,400 users are a side effect of this campaign.
According to this model, it is clear that with the help of retargeting we managed to convert 133 additional users, and the retargeting ROI turned out to be higher than from the usual User Acquisition campaign. In real life, this will not always be the case; not all retargeting campaigns work effectively, however, there are cases when retargeting really helps to return users cheaper than to bring new ones.
In practice, it rarely happens that we know for sure that users will never convert themselves for sure. It makes sense to catch up with retargeting the user immediately after he has installed the application. In this case, his interest is still alive, and retargeting will be most effective. However, we will never know who we really attracted by retargeting, and who was already going to make an order. The user could simply click on our link, but in fact, and so it would convert without any retargeting. This effect is called cannibalization.
In this case, the notorious A / B test will help us. Take half of the users (group A) and launch retargeting for them. The second half of users (group B) will be left as is, without paid retargeting. Over time, let's compare the cost of the first order and the ROI in one and in the other group. If in the group with retargeting the ROI was no lower, then retargeting is justified.
This is how our model will look like in this case:
Here we can compare and see that as a result, CAC (Customer Acquisition Cost) in the group with retargeting turned out to be lower than in the group without retargeting, and ROI is higher. In this case, we can say that the retargeting is effective.
If the final results in the group with retargeting are lower than in the control group, the retargeting campaign should be optimized.
Of course, this model is simplified, and in reality we are dealing with a much larger number of different metrics, with more complex funnels, with a large number of different channels with different cost of traffic. However, the basic principles will always remain the same.
1. In an amicable way, for each type of retargeting and for each advertising channel it is necessary to conduct your A / B test. This requires quite a lot of time and resources. But the picture becomes clear, and retargeting campaigns can be carried out, already knowing the general numbers.
2. If the costs of retargeting are within 1-2% of the total budget, then there is no point in carrying out an A / B test — you will not see anything on such small numbers. However, with such volumes in most cases cannibalization can be neglected.
3. It is impossible to consider separately the cost of attraction through the retargeting channel - this information will not give anything. This cost will always be lower than the cost of attracting a new traffic! Because this cost includes both those users whom we returned by retargeting, and those who would return as well. Therefore, it makes sense to summarize the costumes for attraction with the costals for retargeting.
4. If we are doing retargeting on organic traffic, which in fact came to us for free, then the results of retargeting will always be worse if you look at the cost of attraction. Because even the lowest cost is higher than zero. So you can not compare. If we retarget organic traffic, we must assume that the final ROI is already.
5. It is dangerous to mix different cohorts of users. Those who came to us this month and those who came 12 months ago are different audiences. For those who came a long time ago, and still have not made a single order, we are ready to pay as for a new user. For those who have come recently, we are willing to pay less, because they are likely to convert and so.
Careful and painstaking work with retargeting requires a lot of time and resources - it is necessary to test different audiences and take many measurements. Doing it manually is quite expensive, so automated tools specially created for mobile applications come to the rescue. We already talked about them in the article “Mobile retargeting: setting in trackers and traffic sources” .
If you want to start returning users to the app and earn more with mobile retargeting, contact us at Getloyal .
For several months now at Getloyal we have been doing mobile retargeting for clients from all over the world. In this post we will describe how to measure the effectiveness of retargeting companies using simple examples.
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Pure User Acquisition
Let's start with a simple example, when we do only User Acquisition, without retargeting. Suppose you have an application for the delivery of food. In January, you attracted 10,000 installations for $ 10,000. Over the course of the year, 600 of these 10,000 users made the first order (6% conversion). Some of these users made only 1 order per year, some 20, but on average, it turned out that each of these 600 users made 4 orders per year. The average earnings from one order was $ 5. The advertising campaign's ROI for the first year was 120%.
In reality, it rarely happens that the economy converges head-on, but in general, this is possible if we have a cool application and targeted traffic.
ROI 120% is good, but you want more, and you decide to apply retargeting. Strictly speaking, you have two options on which to target:
- For those who have not converted even in the first order (we will grow C1).
- Those who made the first order (we will grow Orders per user).
Take the first case - we will target only those who have not yet made the first order. As soon as the user makes the first order, he disappears from our audience.
Net retargeting
To begin with, let's look at an example when we target users who are no longer converting themselves. For example, we attracted 10,000 users a year ago. 600 of them were converted into first orders. The remaining 9,400 have since never made their first order. Most likely, they will never make this order if we do nothing, because a lot of time has passed. In this case, we are ready to pay for the return of these users almost as much as for the new user.
Here is what our model will look like in this case:
We divided 10,000 users, attracted a year ago, into two groups: 600 and 9,400. In the second group, we consider costa for traffic equal to zero - after all, before that, we had already spent $ 10,000 and received 600 paying users. The remaining 9,400 users are a side effect of this campaign.
According to this model, it is clear that with the help of retargeting we managed to convert 133 additional users, and the retargeting ROI turned out to be higher than from the usual User Acquisition campaign. In real life, this will not always be the case; not all retargeting campaigns work effectively, however, there are cases when retargeting really helps to return users cheaper than to bring new ones.
User Acquisition + Retargeting
In practice, it rarely happens that we know for sure that users will never convert themselves for sure. It makes sense to catch up with retargeting the user immediately after he has installed the application. In this case, his interest is still alive, and retargeting will be most effective. However, we will never know who we really attracted by retargeting, and who was already going to make an order. The user could simply click on our link, but in fact, and so it would convert without any retargeting. This effect is called cannibalization.
In this case, the notorious A / B test will help us. Take half of the users (group A) and launch retargeting for them. The second half of users (group B) will be left as is, without paid retargeting. Over time, let's compare the cost of the first order and the ROI in one and in the other group. If in the group with retargeting the ROI was no lower, then retargeting is justified.
This is how our model will look like in this case:
Here we can compare and see that as a result, CAC (Customer Acquisition Cost) in the group with retargeting turned out to be lower than in the group without retargeting, and ROI is higher. In this case, we can say that the retargeting is effective.
If the final results in the group with retargeting are lower than in the control group, the retargeting campaign should be optimized.
Of course, this model is simplified, and in reality we are dealing with a much larger number of different metrics, with more complex funnels, with a large number of different channels with different cost of traffic. However, the basic principles will always remain the same.
What else is important to consider
1. In an amicable way, for each type of retargeting and for each advertising channel it is necessary to conduct your A / B test. This requires quite a lot of time and resources. But the picture becomes clear, and retargeting campaigns can be carried out, already knowing the general numbers.
2. If the costs of retargeting are within 1-2% of the total budget, then there is no point in carrying out an A / B test — you will not see anything on such small numbers. However, with such volumes in most cases cannibalization can be neglected.
3. It is impossible to consider separately the cost of attraction through the retargeting channel - this information will not give anything. This cost will always be lower than the cost of attracting a new traffic! Because this cost includes both those users whom we returned by retargeting, and those who would return as well. Therefore, it makes sense to summarize the costumes for attraction with the costals for retargeting.
4. If we are doing retargeting on organic traffic, which in fact came to us for free, then the results of retargeting will always be worse if you look at the cost of attraction. Because even the lowest cost is higher than zero. So you can not compare. If we retarget organic traffic, we must assume that the final ROI is already.
5. It is dangerous to mix different cohorts of users. Those who came to us this month and those who came 12 months ago are different audiences. For those who came a long time ago, and still have not made a single order, we are ready to pay as for a new user. For those who have come recently, we are willing to pay less, because they are likely to convert and so.
Conclusion
Careful and painstaking work with retargeting requires a lot of time and resources - it is necessary to test different audiences and take many measurements. Doing it manually is quite expensive, so automated tools specially created for mobile applications come to the rescue. We already talked about them in the article “Mobile retargeting: setting in trackers and traffic sources” .
If you want to start returning users to the app and earn more with mobile retargeting, contact us at Getloyal .
Source: https://habr.com/ru/post/330970/
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