Kelvin NewmanFounder - BrightonSEO

Scary SERPs (and keyword creep)

@kelvinnewman http://www.slideshare.net/kelvinnewman

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So, who is this guy?

@kelvinnewman

Founder of BrightonSEO

@kelvinnewman

kelvin@brightonseo.com

http://www.slideshare.net/kelvinnewman

Kelvin Newman

@kelvinnewman

Shhhhh, but I don’t live in Brighton

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Actually; I live in Worthing

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Which is famous for one thing…

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Birdman Competition where people see how far they can jump of the pier

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So what is this presentation about?

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Well, this presentation isn’t about…

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@kelvinnewman

So, if you use the Google Keyword Planner you can find

some excellent keywords

““

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It’s more about getting you to think differently about the future

of keywords.

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One True AnswerPart 1

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Start with a story

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Peter A. Shulman

Historian of sci, tech, and American politics. Author of Coal & Empire.

Associate Professor of History 

Lecturing on the reemergence of the Ku Klux

Klan in the 1920s when a student asked an odd

question:

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Was President Warren Harding a member of the KKK?

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He wasn’t

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This isn’t an isolated occurrence

https://theoutline.com/post/1192/google-s-featured-snippets-are-worse-than-fake-news

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https://theoutline.com/post/1192/google-s-featured-snippets-are-worse-than-fake-news

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http://searchengineland.com/googles-one-true-answer-problem-featured-snippets-270549

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Bad on desktop, terrible on voice

https://theoutline.com/post/1192/google-s-featured-snippets-are-worse-than-fake-news

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Easy to mock but what can we learn from this

Preference for “one true answer”

http://searchengineland.com/googles-one-true-answer-problem-featured-snippets-270549

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Risk for Google but opportunity for us

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End of Keyword PrecisionPart 2

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Not-Bloody-Provided

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Keyword Bloody Planner Estimates

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Close-Bloody-Variants

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Query Re-writing

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It would seem Machine Learning is involved in Query Re-writing

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Machine learning is sexy

And Artificial Intelligence, Deep Learning and other sort of related things along those lines.

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I studied media studies at Uni not computer science or anything like it…

Now feels like a good time to share

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Machine Learning Machine Learning at its most basic is the practice of using algorithms to parse data, learn from it, and then make a determination or prediction

about something in the world.

So rather than hand-coding software routines with a specific set of instructions to accomplish a particular task, the machine is “trained” using

large amounts of data and algorithms that give it the ability to learn how to perform the task.

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Deep Learning A branch of machine learning based on a set of algorithms that attempt to model high level abstractions in data by using a deep graph with multiple

processing layers, composed of multiple linear and non-linear transformations.

Seeing the connections

below the surface

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So what are the actions?

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Use some off the shelf

options

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https://algorithmia.com/algorithms/nlp/Word2Vec

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Tutorials on use Machine Learning on over 1M hotel

reviews finds interesting insights

https://blog.monkeylearn.com/machine-learning-1m-hotel-reviews-finds-interesting-insights

Or wait for SEO tool suites to start doing this properly

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Easiest solution is to know the space and know your

customers

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But just writing for users is a lazy suggestion.

We can better understand our users needs if we can better understand how other websites are writing about a topic

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To optimise a page now you need more than add keyphrases.

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You need to have all the phrases and words they’d expect

Is the search query on the page and does deserve to rank?

Old Model

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Does it contain the search query and phrases used be other pages that rank for the term and does deserve to rank?

New Model

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Two hacky & clunky way of seeing those you’d need

include.

Method 1

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Take the top ten results for your query and extract the text using

something like textise.net

Method 1

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Bung the copy from all the pages into a Word Cloud

Tool

I like jasondavies.com/wordcloud/

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Treat the most common words like bingo

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Take the top 3 results for your query and extract the text using

something like textise.net

Method 2

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Create a list of all the single words used on the page

using something like writewords.org.uk/

word_count.asp

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Create a Venn Diagram of the overlap

Method 2

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kelvin@brightonseo.com

http://www.slideshare.net/kelvinnewman

Thanks