With the current privacy restrictions, it is becoming difficult for companies to track user actions within apps and collect quality data, which is crucial in optimizing campaigns and properly allocating advertising budgets.
One of the fields of artificial intelligence (AI) comes to the rescue, namely machine learning, which, based on searching for relationships in data according to established rules, imitates intelligent behavior. This allows for processing data, solving more complex problems, and automating time-consuming tasks.
In campaigns promoting mobile applications, machine learning algorithms are mainly used in programmatic advertising, where the purchase and sale of advertising space are done automatically. This type of advertising has many advantages useful in optimizing campaigns and promoting applications.
First of all, thanks to the use of the aforementioned algorithms, programmatic advertising is transparent and measurable. They also allow for precise targeting of messages and optimization of targeting based on the analysis of a huge amount of data and “concluding” from them. Based on the available set of data on user behavior, the campaign can be directed to people who are more likely to download and use the application, which directly affects the acquisition of active users.
Thanks to the use of AI, marketers can optimize advertising budgets by displaying ads only to those users who are more likely to interact with them and therefore install the application. Furthermore, based on data collected by machine learning algorithms, it is possible to identify the most effective ads, to which it is worth allocating the budget, which is crucial for optimizing campaigns promoting applications and increasing ROAS.
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