machine learning steven j davies content writing

Machine Learning And The Future Of Web Content

To stay in front of the opposition, to stay relevant and useful for searchers and advertisers, Google and Microsoft invest heavily in machine learning technologies. Why? It helps to analyze annd understand searcher intent. Artificial intelligence is not something that most web content writers concern themselves with, but they need to start.

As people are more familiar with Google Search algorithm updates, mostly because Google announces them with a fanfare while others just go about their business, let’s talk about them. It should be noted however that the finer points also apply to Microsoft and Bing.

The Hummingbird update was the first one trumpted by Google that put emphasis on getting to grips with natural language. This was also the update that had a lot of people in a blind panic, “they’ve killed keywords” and “SEO as we know it is dead” among others.

Hummingbird saw the death of keyword stuffed content, finally, and forced content producers into creating web content that was ultimately more valuable for the end user. The next update was RankBrain which built upon Hummingbird, adding artificial intelligence and machine learning.

These two updates together tackle two distinct issues: Understanding user intent, to enable engines to deliver more relevant results, and evaluating quality of content so that only the best pages are offered up to the user.

We also know that Google (and other engines) are interested in leveraging user satisfaction/user engagement data as well. Though it’s less clear exactly what signals they will key in on, it seems likely that this is another place for machine learning to play a role.

 

Quality of Content

 

Displaying high-quality content in SERPs (search engine results pages) is obviously crtiical for the success of search engines, whichever company is behind them. To that end, Machine Learning solutions, just like RankBrain, have improved in their ability to inderstand the nuances of human language. One way in which this has been improved upon is the way that search queries are actually treated.

Prior to RankBrain, certain words would have been simply ignored. One reason for this was expediency, and also because certain words appear in a very high frequency ratio – otherwise known as stop words. More likely though it was simply because search engines were not yet ‘smart enough’ to use the whole string in any meaningful way.

Longtail keyword use has seen an improvement in understanding user intent and delivering more relevant results. This is where the quality of the content itself is also brought under the microscope.

Keyword usage has been scrutines anyway over the past few years, and for good reason, but many people still aren’t ‘getting’ it. This is especially true post-RankBrain. Despite all of the posts, articles and updates that are out there, people are still not really writing for the searcher.

When search engines are looking at the whole search string, trying to answer a specific question, they are looking through their index for specific answers. Not only that, they are actively filtering out poor content. Content that attempts to rank by smattering the text with keywords is likely going to be ignored.

When was the last time you had a converstaion with somebody and every sentence or so, you mentioned their name and the topic of the conversation? You wouldn’t because it’s annoying as hell and that person will dread you walking into the room from that moment on.

Instead of being the person that everybody avoids, be the person that everybody wants to consult. Listen to what they are saying and answer in proper grown-up sentences, as best you can. In text, the longtail keywords will  come naturally and fluently, with zero effort on your part – if you’re doing it correctly.

The majority of people today ask full questions when using search engines, rather than throwing in keywords as they used to – like hashtags on social media. The search engines now also understand much better than they ever did the nuances of language. Use that knowledge to your advantage and stop being the boring guy in the room.

 

What does quality content do / look like?

 

Longtail keywords aside, how else can content creators and businesses ensure that search engines and searchers see their pages as being valuable? The following is true whether the viewer is an AI or a searcher:

 

  • The product/service/information they are looking for is present on the page.
  • They can find it with relative ease on the page.
  • Supporting products/services/information they want can also be easily found on the page.
  • The page/website gives them confidence that you’re a reputable source to interact with.
  • The overall design offers an engaging experience.

 

As machine learning continues to grow and advance, they are going to get better at understanding page content itself and it’s value to the searcher. What does this mean for content writers and businesses? It means they are going to have to start creating content that is engaging, easy to understand and answers the actual question being posed.

If the above points are taken into consideration for every page created, you are going to have an edge in the digital marketing stakes. You need to rethink what it means to write SEO content, and you need to start today.

If you have any thoughts or questions, I would love to hear from you.

 

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