Google will help advertisers deliver targeted ads to you using machine learning

Machine learning is a major field of artificial intelligence and computer science that Google has lately been utilizing in its various products and services. In 2017, it announced that it is using technology based on machine learning to save users some bandwidth. More recently, at its I/O 2018 conference, it also showcased some intelligent capabilities of Android P that utilize this branch of computer science.

Today, the company has announced that it is "putting machine learning in the hands of every advertiser" to deliver you targeted ads.

At its Google Marketing Live event today, the firm announced responsive search ads, which will present the most suitable advertisements to users. This will be made possible by marketers providing Google up to 15 headlines and four lines of description, after which the company's algorithm will autonomously determine which combination of ads in search results best suit your business. The firm says that responsive search ads through machine learning deliver 15% more clicks as compared to regular ads. The feature is available in beta, and will be rolled out to advertisers over the next few months.

Google will also be using machine learning to deliver better ads on its YouTube platform under the "Maximize lift" moniker. This is available now in beta as well, and will be generally available later this year.

Apart from the aforementioned features, the company has announced Local campaigns too, which it describes as follows:

A new campaign type designed to drive store visits exclusively. Provide a few simple things—like your business locations and ad creative—and Google automatically optimizes your ads across properties to bring more customers into your store. Local campaigns will roll out to advertisers globally over the coming months.

Lastly, Google is also bringing machine learning's capabilities to optimize its Smart Shopping campaign, allowing marketers to maximize their revenue. You can find out more by visiting Google's blog post here.

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