The increasing number of mobile devices and the volume of applications on each phone mean a lot of information being created in the mobile world. Managing this large volume of data in a limited time with less advanced technologies is a hilarious task. At this point, machine learning (ML) becomes critical for mobile advertising. App-based advertising, location-based advertising, and advertising fraud protection are the key concerns in advertising for which ML stands an appropriate solution.
Smartphone users are bombarded with advertisements in most free applications. A long supply chain is involved in ad placement including agency choosing the right placement. Information about mobile phone and usage is needed to provide feedback to all the companies so that advertising can be better tracked and planned. Tracking includes information about clicks on the phone, and users clicking on an ad for a new app.
Location-based advertising holds the ability to quickly identify the location and provide information that will help advertisers offer immediate options to the user. The ability to identify location can improve the in-store advertising by offering coupons and ads relevant to the aisle the customer is currently walking through.
Malicious applications can monitor what the mobile user does and can send an attribution message so that the fraudulent software gets paid for the click. The providers of fraudulent applications can steal a lot of money in this way. Fraud detection can prevent loss.
To choose ads for the right apps, provide location-based ads, provide attribution for app downloads, and to identify malicious actors are all areas in which machine learning’s ability to analyze large volumes of data can have an impact.