Lessons From Google And Facebook On The Rise Of Machine Learning

While both platforms are hurriedly building out machine-learning capabilities in an effort to entice more budgetary allocation from marketers, their approaches to doing so have been a study in contrast.

From “Rise Of Machine Learning: Lessons From Google And Facebook” on Forbes.com

Google and Facebook have been quietly introducing machine learning algorithms to their platforms for years, essentially kicking off the mainstreaming of AI in the process.

The last few years have shown us that this can create both positive and negative outcomes for both marketers and our audiences.

Either way, there’s a lot to learn from the big guys when it comes to integrating artificial intelligence into day to day business processes.

Google has always taken a “recommended but optional” approach to automation, which they typically manage with machine learning algorithms.

Facebook, in contrast, is much forceful when it rolls out updates to their user experience. Recently, Facebook announced that it will be forcing advertisers to use campaign budget optimization (CBO) and removing the ability to manually optimize between ad sets.

Different marketers feel differently about the switch but regardless which side you land on, it’s indicative of two very different ways of looking at the potential of AI technology.

Google treats AI as a way to deliver a more seamless experience that benefits users (when they want it). Facebook uses AI to exert more control over their users and advertisers.

Which do you think will prove to be the more effective strategy in the long term?

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