Machine learning and other artificial intelligence technologies have been getting a lot of press lately, especially when it comes to how it can be used by marketers and advertisers. While it is pretty much common knowledge that these technologies are great for making customer service bots, choosing what ads to buy, and much more, new reports are showing that it can also be used to directly combat bots and other forms of digital ad fraud.
Bot nets, malware, and other things are used to generate billions of dollars worth of ‘fake’ clicks and views per year, which costs marketers dearly. New efforts are being made to have machine learning analyze ad views and other information to learn more about when a view is authentic, and when it is coming from a bot.
Using this advanced technology, it is possible for ad networks to develop better fraud detection that can precisely identify determine how and when bots are viewing ads. While it is not perfected yet, machine learning and artificial intelligence are great at gathering information and ‘learning’ from it without the need for humans to continuously work on identifying the bot traffic manually.
As this technology continues to improve, ad networks and marketers alike are hoping to see significant reductions in overall digital ad fraud.
