2020 yılında seo: yapay zeka ve makine Öğrenme dünyasında seo'nun geleceği

2020 Yılında SEO:

data-driven SEO agency

Yapay Zeka Dünyasında SEO’nun Geleceği

Yapay Zeka Dünyası SEO'nun GeleceğiSEO endüstrisinin liderlerinin görüşleriyle, 2020 yılında SEO nerede olacak?

Rand Fishkin & Marcus Tober’e sağladıkları veri paylaşım izninden ötürü teşekkür ederiz.

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SEO’nun Geleceğini Anlamak için, Geçmişe Bir Bakış Atmalıyız

Bu sunumda verilerini kullandığımız, Rand Fishkin, Marcus Tober, Hatem Mahmoud, Yashwanth Korla ve Dharmesh Shah’a teşekkürler!

+ + =

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Geleceği Görmek için Önce Geçmişi İnceleyelim

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Burada Genel Geçer Bir Başlık Var ve Bunu Değişiriz

Burada da konuyla alakalı bazı güzel mesajlar var dostlar.Burası da ikinci satır.

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Geleceği Görmek için Önce Geçmişi İnceleyelim

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3key pointsof 2020’s SEO


Semantics


Semantics Content


Semantics Content MachineLearning


Semantics(be part of Web 3.0

conversion)

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Don’t forget it:Google is getting smarter day by day


Content(especially 10x

content)


Content(especially 10x content)


MachineLearning

Google’s Last 3 Years of Advancements Erased a Decade of Old School SEO Practices

They Finally Launched Effective Algorithms to Fight Manipulative Links & Content

Via Google

http://www.google.com/search/about/insidesearch/howsearchworks/fighting-spam.html

And They Leveraged Fear + Uncertainty of Penalization to Keep Sites Inline

Via Moz Q+A

http://moz.com/community/q/search?utf8=%E2%9C%93&query=penalty&commit=Search

Google Figured Out Intent

Rand probably doesn’t just want webpages filled with the word

“beef”

They Looked at Language, not Just Keywords

Oh… I totally know this one!

They Figured Out When We Wanted Freshness

Old pages on this topic probably aren’t relevant

anymore

Google Learned to ID Entities of Knowledge

During These Advances, Google’s Search Quality Team Underwent a Revolution

Early On, Google Rejected Machine Learning in the Organic Ranking Algo

Via Datawocky, 2008

http://anand.typepad.com/datawocky/2008/05/are-human-experts-less-prone-to-catastrophic-errors-than-machine-learned-models.html

By 2013, It Was Something Google’s Search Folks Talked About Publicly

Via SELand

http://searchengineland.com/matt-cutts-at-pubcon-174906

Google is Public About How They Use ML in Image Recognition & Classification

Potential ID Factors(e.g. color, shapes, gradients,

perspective, interlacing, alt tags, surrounding text, etc)

Training Data(i.e. human-labeled images)

Learning Process

Best Match Algo

Google is Public About How They Use ML in Image Recognition & Classification

Via Jeff Dean’s Slides on Deep Learning; a Must Read for SEOs

http://static.googleusercontent.com/media/research.google.com/en/us/people/jeff/CIKM-keynote-Nov2014.pdf

Deep Learning is Even More Advanced:

Dean says by using deep learning, they don’t have to tell the system what a cat is, the machines learn, unsupervised, for themselves…

We’re Talking About Algorithms that Build Algorithms(without human intervention)

Machine Learning in Search Could Work Like This:

Potential Ranking Factors

(e.g. PageRank, TF*IDF,Topic Modeling, QDF, Clicks,

Entity Association, etc.)

Training Data(i.e. good & bad search results)

Learning Process

Best Fit Algo

Training Data(e.g. good search results)

This is a good SERP – searchers rarely bounce, rarely short-click, and rarely need to enter other queries or go to page 2.

Training Data(e.g. bad search results!)

This is a bad SERP – searchers bounce often, click other results, rarely long-click, and try other queries. They’re definitely not happy.

What Does Deep Learning Mean for SEO?

The Query Success Metrics Will Be All That Matters to the Machines

Long to Short Click Ratio Relative CTR vs. Other Results

Rate of Searchers Conducting Additional, Related Searches

Metrics of User Engagement on the Page

Metrics of User Engagement Across the Domain

Sharing/Amplifcation Rate vs. Other Results

The Query Success Metrics Will Be All That Matters to the Machines

Long to Short Click Ratio Relative CTR vs. Other Results

Rate of Searchers Conducting Additional, Related Searches

Metrics of User Engagement on the Page

Metrics of User Engagement Across the Domain

Sharing/Amplifcation Rate vs. Other Results

If lots of results on a SERP do these well, and higher results outperform lower results, our deep learning algo will consider it a success.

OK… Maybe in the future. But, do those kinds of metrics really affect SEO today?

Remember Our Queries & Clicks Test from 2014?

Via Rand’s Blog

https://moz.com/rand/queries-clicks-influence-googles-results/

Since then, it’s been much harder to move the needle with raw queries and clicks…

Case closed! Google says they don’t use clicks in the rankings.Via Linkarati’s Coverage of SMX Advanced

http://linkarati.com/smx-2015-ama-google-search-garyillyes-dannysullivan/

But, what if we tried long clicks vs.

short clicks?

Note SeriousEats, ranking #4 here

11:39am on June 21st,I sent this tweet:

40 Minutes & ~400 Interactions Later

Moved up 2 positions after 2+ weeks of the top 5 staying static.

70 Minutes & ~500 Interactions Total

Moved up to #1.

Stayed ~12 hours, when it fell to #13+ for ~8 hours,

then back to #4.

Google? You messing with us?

Via Google Trends, we can see the relative impact of the test on query volume

~5-10X normal volume over 3-4 hours

BTW – This is hard to replicate. 600+ real searchers using a variety of devices, browsers, accounts, geos, etc. will not look the same to Google as a Fiverr buy, a clickfarm, or a bot. And note how G penalized the page after the test… They might not put it back if they thought the site itself was to blame for the click manipulation.

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It is not just machine learningIt is about experience!

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Google is not a search company.It is an AI company!

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2020 yılında seo: yapay zeka ve makine Öğrenme dünyasında seo'nun geleceği

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