Today, in the post-IDFA era, Apple Search Ads (ASA) remains the unique traffic source for which full attribution is available. It allows you to track performance and optimize your campaigns on the keyword level.
In this article, we'll take a look at:
So let's review the key metrics of campaign performance.
To calculate the ASA ROI of acquired users, you can use 2 different approaches. The first option is to compare all campaign/customer costs to their total revenue. This approach can provide a general understanding of traffic profitability.
But to compare the cost of acquired users from different geo/keywords, to compare the effectiveness of Apple Search Ads with other paid channels, it is more convenient to count the cost per install (CPI) and the average revenue per user (ARPU).
To estimate how much a purchased user costs us, we usually use the CAC (Customer Acquisition Cost) metric. However, as mentioned earlier, for ASA we are more interested in Cost Per Install, or CPI.
In this example from Apple Analytics, we can see that the cost per install (Apple calls this metric CPA) is calculated as follows:
CPI = Spent / Installs
i.e. the ratio of money spent to the number of target actions (installations).
In addition to CPI, it is also important to understand how much we can earn from the group of users we acquire.
In our case, LTV is a metric that reflects the average revenue from a user over the lifetime of that user. It is also irrelevant whether the user is a paying user or not, as we are optimizing for installs. Therefore, in this case, we calculate LTV based on ARPU.
An important point is that we can calculate LTV not only for the entire lifetime of a cohort of users but also for the Nth day. Thus, we can understand the exact moment when the acquired users start to pay off and bring profit.
Now let's look at the LTV graph aggregated by keywords.
In this case, we can see that users coming from different keywords initially bring about the same revenue. However, over time, the revenue from users coming from the first keyword (blue graph) starts to significantly exceed the revenue from users coming from the second keyword. We are starting to scale user acquisition from the first keyword.
Now that we understand the cost of engagement and how much revenue users are bringing us, we can calculate the return on our investment (ROI) for our Apple Search Ads campaigns. The ROAS calculation in percentages is shown below.
ROAS = Revenue (total ad revenue) / Cost (total ad spend) x 100%
If ROAS is less than 100%, we have made a loss; if it is more than 100%, we have made money.
How can analyzing LTV, for example by keyword, in Apple Search Ads help you find the most effective traffic?
Let's take a look at a simple spreadsheet that you can easily create yourself. In this case, we'll use Google Sheets.
So here are the step-by-step instructions on how to fill in this table. Suppose we take all the data from the user cohorts by day (Date column).
The values of the other columns are:
Data for calculations:
The cost for each key can be taken from the Apple Search Ads cabinet as shown in the screenshot above.
The number of installs and LTV on the nth day is available in Apphud, Cumulative LTV graph.
So, as we can see, Apple Search Ads, along with other popular traffic channels, can attract valuable users to the application and bring significant profit.
An important advantage of ASA is the fact that this channel allows us to get accurate data on user attribution (at the level of a campaign or even a single keyword). That's why Apple Search Ads ROI calculation is a necessary action for your strategy.
Thus, we have a full opportunity to analyze the effectiveness of marketing efforts in detail.
With the help of Apphud, you can effectively measure the LTV of ASA campaigns and correctly calculate the ASA ROI in order to make the right decisions. Sign up for Apphud today and let's grow your app revenue together!