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Rudy De La Garza
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When I travel, I always use the guest room safe to store my personal belongings. They do the trick and I found out that if I forget my password, the hotel manager should be able to open it for me. But the cleaning staff do not have access to the safes. Good to know! 

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I wish #Google would also come out and say this for Desktop sites.  Would make my SEO consultant life easier.  In 2015, I still have to tell people that #interstitials  are not recommended for traffic from organic search.  At the very least, can you trigger the interstitial on exit?  SMH
App interstitial ban is here. Or it will be starting November 1. Apparently Yelp's plea in Search Engine Land didn't change any minds at Google.

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Everybody is scrambling to find answers for their clients and bosses about the Quality update.  +Bill Slawski knows where to look.
A Google patent discusses how a site might be labeled a low quality site by Google based upon the links from other pages pointed to the site, and how this can potentially reduce rankings for a page.

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I noticed this too recently and thought more about what an efficient use of the space it is.  Big reminder that the mobile #viewport is king.
Talk about instant answers! Has anyone else seen featured snippets in suggest like this?

Makes sense, as they guessed my intent immediately and gave me the answer I was looking for, not only without taking me to a webpage, but without even taking me to a SERP. Have previously only seen this with navigational queries and web sites.

Certainly not the death of SEO, but as with knowledge graph in general SEOs have to understand query intent more than ever before in order to be successful.
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Need to share this with a few co-workers and clients...

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The Art Of Creating Perfect Posts on Social Media - V5 infographic
To enlarge image: i.imgur.com/RFUuupI.png

Wondering, what does a perfect social media post look like? Then wonder no more. Save or bookmark the handy infographic below from  +mycleveragency  and reference it anytime you get befuddled.

It delineates in detail what engaging, effective and viral Facebook, Google+, Twitter, Pinterest, Instagram, LinkedIn and blog posts should include.

Pin it for later: http://www.pinterest.com/pin/381539399654578849/

Source: http://www.mycleveragency.com/blog/2014/06/create-perfect-posts-linkedin-blog-youtube-tumblr-vine-google-facebook-twitter-version-5-infographic/

#socialmediatips  
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+Katy Steinmetz  gives us a very nice interview with Roy Peter Clark on the subject of How to Write Short.  He gives some great examples of pieces that are 300 words or less that have impacted humanity.  The Preamble to the #Contstitution   and Psalm 23....both very short and powerful.

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Google's Fourth Version of a Patent on Paid Links Just Granted

It's taken more than a decade, but a continuation patent with newly updated claims addresses reducing or removing weight from paid links, affiliated links (from the same owners), and setting thresholds on how much weight some sites might pass along, including sites that might be rated highly on a trust/authority basis.

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Google Ranking Signals - Language Attributes

Google doesn't trust the meta tags people use to tell it what language a page is in, and would rather figure that out on their own. They tell us in the patent that people rarely use character set and language markup like the following, and that it's often wrong when it is used:

<META CHARSET=iso-latin-1>
<META LANG-=‘fr’>

This patent was filed in 2003, and it's possible that Google has been using this process for over a decade.  It's quite possible that Google might take passages like the following from many pages on the web and break them down into smaller pieces, often referred to as "n-grams" where "n" refers to a number. With a very large set of n-grams, the search engine might then be able to create statistics about languages, including which language is being used. So, this passage from the patent might be broken down as follows into tri-grams, or three word bites:

Search engines operate in two capacities, which both require identifying the language in which the content is expressed. First, search engines collect information about potentially retrievable Web content and news messages

Search engines operate
engines operate in
operate in two
in two capacities
two capacities, which
capacities, which both
which both require
.... and so on.

Statistics about the words used can be involved in the creation of models that can do things such as help identify paraphrases, find unnatural language such as spun or scraped content.

Documents might be classified through a method like this, and things like the meta language tags, and even the country code TLDs that a page is on can be ignored as clues.

The co-occurrence of words within these smaller pieces of content of a page can be used to help understand the language the page is in, and the meaning of the page.

If the word "football" is identified within a page, and the page is classified as being US English, it's likely tied to a different meaning than another page which is classified as British English, or one classified as Australian English.

The use of a language attribution model can also be used to identify pages that might be considered gibberish, and webspam - generated by scraping together different pieces of content from multiple pages, or generated from automated translation into one language, and then into another.

There is also a Google Books N-Gram Viewer that can be used to look at the appearance of different words in the English language and when they might have peaked in usage at different times over many generations of books:

https://books.google.com/ngrams

Building language models isn't a complete answer to information retrieval, but it is a useful avenue of exploration, and can impact how pages might be ranked in search results by providing more context for the words being used on a page.
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