The mobile app ecosystem is growing towards acquiring high lifetime value (LTV) users. To keep up with the rapid pace of this change, app marketers need to find new and innovative solutions for solving new challenges. One of the key solutions to ensure that you target the best users is leveraging suppression lists.
To prove the effectiveness of suppression lists, we analyzed a card game app over a period of 24 days.
The Objective and the Challenge
We launched the campaign with a clear objective of acquiring high LTV users at an optimal cost per install (CPI). The new strategy was designed to enable us to acquire quality users with a high probability of app engagement.
To reach the high LTV users for the app, we built suppression lists to exclude existing users from the bid. But to get a better understanding of the process, let’s discuss the terms first:
Suppression list is an audience list that we exclude on campaigns for efficient target capabilities and ad spend. There are two types of Suppression Lists: Static and Dynamic.
A Static suppression list is provided as a CSV or DAT file at the onset of the campaign. The list is composed of all past user installs. While working with static lists, we compare the data in the suppression list with the bid requests in the ad exchanges. If the data matches, we exclude that match and bid on non-matching users to avoid showing the ad to past users.
The other type of suppression list, dynamic, is composed of organic users and users acquired through all other paid marketing activity. This list is provided via real-time install postbacks, Aarki audience API, or MMP audience builder. When the advertiser through their attribution partner enables the dynamic suppression list, the matching users are excluded from the bid and the users who have already seen the ad through other media are not targeted.
For this particular campaign, we leveraged a dynamic suppression list to exclude existing users from the bid.
By leveraging a dynamic suppression list, we ensured that we're not targeting users who had already installed the app through another medium. So we had more quality users hitting the advertiser’s CPI goal. The results speak for themselves: CPI had a considerable decrease of 59.26%. Conversion rate (CR) performance, likewise, kept on improving, as the dynamic suppression list grew and provided new device IDs to exclude—the conversion rate (CR) increased by 11.63% from the start of the campaign.
Positive Impact on Cost Per Install
Suppression lists prove to be highly effective at boosting overall campaign performance. By leveraging Aarki’s machine learning algorithms, we improve campaign performance across various metrics and ensure that your advertising budget is spent on the right user.