Amit Singhal, veteran who oversees Google search, has retired. Notably, Singhal will be replaced by John Giannandrea, who leads Google’s artificial intelligence (AI) practice.
What may Giannandrea—who has been building tools that act like neurons in the human brain—do with search? Well, the fact is that AI and machine learning are already transforming Google search, and with Giannandrea at the head, this evolution could accelerate.
Back in October, Google announced that it was using a new AI system, RankBrain, in organic search. RankBrain is a machine-learning system that can teach itself what to surface based on what it has previously encountered. This enables Google search to deliver results based on consumer intent, even when consumers don’t use the right words in their queries. Such intelligence can be more reliable than search algorithms, which cannot continually teach themselves. According to Google, RankBrain is already processing a “very large fraction” of queries.
FUTURE IMPLICATIONS for SEARCH MARKETING
The process of “searching” is exploding far beyond text typed into the traditional desktop Google search bar. We’re searching with voice spoken to our phones, car dashboards or voice command devices (e.g. the Amazon Echo). We’re searching with visuals, like via Pinterest’s new Visual Search. And soon, we’ll be searching with no command at all (e.g. a smart refrigerator knows when you’re out of yogurt and buys some more, without you needing to ask).
Neural nets can learn to understand voice commands, interpret images and predict intent. Unlike algorithms, they get smarter as they’re exposed to more information. Because they better understand consumer intent, they’re able to become increasingly efficient at delivering relevant answers/results better aligned to that intent.
We’re in the very early stages of how AI and machine learning will impact search experiences. However, it’s clear that neural nets will foster search accuracy, at least by delivering results more aligned to consumer patterns, preferences or past behavior. Voice command systems, like Siri and Amazon Echo, will get better at understanding us.
For marketers, the rise of AI in search requires a change in mindset. Today, many marketers optimize to algorithms. SEO—and paid search marketing, to an extent—was founded on pleasing and optimizing towards human-created algorithms. But what happens when an ever-learning neural net is making the decisions? For us, this future hinges on intent. Neural nets will enable search engines (whatever their form) to better understand and cater to consumer intent.
And as the systems better understand consumer intent, brands must possess content that aligns with that intent (not necessarily content that aligns with algorithms). This requires that brands understand, at the foundation of every campaign, how consumers decide—to click, like, share and ultimately purchase.