What the heck is machine learning, and why should I care?

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There are many uses for machine learning and AI in the world around us, but today I’m going to talk about search. So, assuming you’re a business owner with a website or an SEO, the big question you’re probably asking is: what is machine learning and how will it impact my rankings?

The problem with this question is that it relies on a couple of assumptions that may or may not be correct: First, that machine learning is something you can optimize for, and second, that there will be rankings in any traditional sense.

So before we get to work trying to understand machine learning and its impact on search, let’s stop and ask ourselves the real question that needs to be answered:

What is Google trying to accomplish?

It is by answering this one seemingly simple question that we gain our greatest insights into what the future holds and why machine learning is part of it. And the answer to this question is also quite simple. It’s the same as what you and I both do every day: try to earn more money.

This, and this alone, is the objective — and with shareholders, it is a responsibility. So, while it may not be the feel-good answer you were hoping for, it is accurate. With this in mind, we can now quickly ponder what Google needs to accomplish this.

There are a variety of ways Google can increase its revenue. Here are some of the more obvious:

  • Increase their users
  • Increase the number of times each user returns
  • Increase the revenue generated per user
  • Reduce the need for users to leave their sites to complete an action
  • Increase the number of ways a user can be reached

So, Google needs to be present in as many places as possible; they need users to rely on them consistently and frequently; they need to hold their users in their sphere of influence so as to increase their ability to advertise to them; and they need to find ways to increase their revenue from the users they have performing the tasks they’re already doing.

Some opinions expressed in this article may be those of a guest author and not necessarily Marketing Land. Staff authors are listed here.


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