Google announced recently that RankBrain is Google’s name for a machine-learning artificial intelligence system that’s used to help process its search results. They also added that RankBrain is one of the “hundreds” of signals that go into an algorithm that determines what results appear on a Google search page and where they are ranked. In the few months it has been deployed, RankBrain has become the third-most important signal contributing to the result of a search query. We have been also recently been talking about the semantic web .In one of our previous blog posts http://www.webpro.in/how-the-semantic-web-html5-microformats-and-seo-are-inter-linked/  the 4 quadrants which  explain the information and social connectivity very effectively have the semantic web and artificial intelligence in the same quadrant. The semantic web connects knowledge.

Semantics is about "real objects and imaginary concepts and the particular relations between them!" (cf. Berners-Lee 94) And the field that knows how to do this is AI (Artificial Intelligence)! (We call it "knowledge representation"!) According to James Hendler in one of his presentation about the semantic web he says: knowledge representation … is currently in a state comparable to that of hypertext before the advent of the web: it is clearly a good idea, and some very nice demonstrations exist, but it has not yet changed the world. It contains the seeds of important applications, but to unleash its full power it must be linked into a single global system. -- Berners-Lee, Hendler, Lassila, 2001. RankBrain the machine-learning artificial intelligence system is a software which is integrated into the algorithm to mathematically connect words and phrases. An interesting paper on Distributed Representations of Words and Phrases and their Compositionality  explains the way words and phrases can be mathematically connected. In this paper Google has mentioned :

• Distributed representations of words in a vector space help learning algorithms to achieve better performance in natural language processing tasks by grouping similar words
• Word representations are limited by their inability to represent idiomatic phrases that are not compositions of the individual words. For example, “Boston Globe” is a newspaper, and so it is not a natural combination of the meanings of “Boston” and “Globe”
• Other techniques that aim to represent meaning of sentences by composing the word vectors, such as the recursive autoencoders , would also benefit from using phrase vectors instead of the word vectors.
• The extension from word based to phrase based models is relatively simple. First we identify a large number of phrases using a data-driven approach, and then we treat the phrases as individual tokens during the training. To evaluate the quality of the phrase vectors, we developed a test set of analogical reasoning tasks that contains both words and phrases. A typical analogy pair from our test set is “Montreal”:“Montreal Canadiens”::“Toronto”:“Toronto Maple Leafs”. It is considered to have been answered correctly if the nearest representation to vec(“Montreal Canadiens”) - vec(“Montreal”) + vec(“Toronto”) is vec(“Toronto Maple Leafs”).  We found that simple vector addition can often produce meaningful results. For example, vec(“Russia”) + vec(“river”) is close to vec(“Volga River”), and vec(“Germany”) + vec(“capital”) is close to vec(“Berlin”). This compositionality suggests that a non-obvious degree of language understanding can be obtained by using basic mathematical operations on the word vector representations.
• A very interesting result of this work is that the word vectors can be somewhat meaningfully combined using just simple vector addition. Another approach for learning representations of phrases presented in this paper is to simply represent the phrases with a single token. Combination of these two approaches gives a powerful yet simple way how to represent longer pieces of text, while having minimal computational complexity. Our work can thus be seen as complementary to the existing approach that attempts to represent phrases using recursive matrix-vector operations .

According to Google's senior research scientist Greg Corrado Once RankBrain analyzes the text through vectors, it can isolate words or phrases it doesn't understand. It can then guess the meaning based on similar words and phrases and filter the results accordingly. When a search takes place on Google, the search query now will be accessed by the RankBrain program/software to deliver more relevant search results. Especially if the query is a rare one. By making the query accessible to software (RankBrain), the software will essentially become able to understand knowledge, think about knowledge via mathematical computations using word and phrase vectors, and create new knowledge. In other words, software will be able to be more intelligent – not as intelligent as humans perhaps, but more intelligent than say, the word to word mapping is today. Especially for rare queries which need to be understood to deliver results. As Semantics adds extra information to help you with the meaning of the information. Websites using Schemas will be able to get more correlated to the contextual content.

Why schemas will become increasingly important from the SEO perspective?

The Semantic Web does not only exist on Web pages.Web 3.0 works inside of applications and databases, not just on Web pages. Calling it a “Web” is a misnomer of sorts — it’s not just about the Web, it’s about all information, data and applications. More information on http://www.w3.org/DesignIssues/LinkedData.html As the data on the web goes on expanding and the snowball of data gradually becoming an avalanche , as James Hendler says, a little semantic will go a long way.

The Semantic Web isn't just about putting data on the web. It is about making links, so that a person or machine can explore the web of data.  With linked data, when you have some of it, you can find other, related, data.

In the video below James Hendler mentions that  Mr. Guha who started Schema.org said that Google uses the RDF/Microformats and he mentioned at the WWW conference that 20%  (5 million domains) have schemas on it (Video 41:48).  He says in 2001 Google had said that they would not be using schemas in a big way but now they have integrated it in the search algorithm. The knowledge graph is one such example.  Google Turning Its Lucrative Web Search Over to AI Machines (Bloomberg Video) // In this new quality era of search we have to move our focus away from keywords and focus more on the keyness factor of the content which has the potential to correlate to searches made on the search engines as the semantic web adds more meaning to the query for a search rather than just mapping words during the search process. (Note: I know there is no such word as "keyness" but by the "keyness factor" I mean the the correlation, relevance, and the essence of the content rather than the actual word to word keyword mapping.)

As you can see in the image above, we have URI and Unicode as the basis of the web. This can be called the first step which adds the keyness to the webpage and the content of that page that you want to promote organically on search engines or on the web. The keyness factor can be derived from the context of the terms, terminolgy and text used in the content of URl, title, headings, anchor text of the inbound links, alt text used on images, schema codes, meta tags, microformats and body text. If we focus on the keyness factor and try to cater to correlate to a wide range of keyword data rather than focusing on the keywords alone in the URLs, titles and descriptions it gets passed on to the next layer of the emerging web, making the pages pass on more correlation and relevance and also syncs the on page signals with the off-page signals which get directly indexed in the search engines in the form of feeds and sitemaps. More about keyness, Semantic Web and correlation  on http://searchenginewatch.com/sew/opinion/2214849/googles-knowledge-graph-implications-for-search-seo Of course the web today is also about mobility, security and interaction (Social Media) but as an SEO I think representing content in the form of structured data as much as possible will surely be one of the ways to future proof the search presence of any website as  datasets of any schema surely add meaning to the content for any crawler in the form of the meaningful records and fields.

The Bloomberg article a few days back reported that  Greg Corrado, a senior research scientist at Google outlined for the first time the emerging role of AI in search.

Greg Corrado said:

RankBrain uses artificial intelligence to embed vast amounts of written language into mathematical entities -- called vectors -- that the computer can understand. If RankBrain sees a word or phrase it isn’t familiar with, the machine can make a guess as to what words or phrases might have a similar meaning and filter the result accordingly, making it more effective at handling never-before-seen search queries.

“Search is the cornerstone of Google,” Corrado said. “Machine learning isn’t just a magic syrup that you pour onto a problem and it makes it better. It took a lot of thought and care in order to build something that we really thought was worth doing.”

RankBrain is Google’s name for a machine-learning artificial intelligence system that’s used to help process its search results, as was reported by Bloomberg and also confirmed to Search Engine Land by Google.

 

 What Is Artificial Intelligence (AI)?

AI is the science and engineering of making intelligent machines, especially intelligent computer programs. It is related to the similar task of using computers to understand human intelligence. Intelligence involves mechanisms, and AI research has discovered how to make computers carry out some of them.

What Is RankBrain?

Corrado said, RankBrain is one of the “hundreds” of signals that go into an algorithm that determines what results appear on a Google search page and where they are ranked. In the few months it has been deployed, RankBrain has become the third-most important signal contributing to the result of a search query.

Danny Sullivan in his article on SEL wrote:

it seems much more likely that RankBrain is somehow helping Google better classify pages based on the content they contain. RankBrain might be able to better summarize what a page is about than Google’s existing systems have done. (But Google isn’t saying anything other than there’s a ranking component involved.)

As Google told SEL, it can see patterns between seemingly unconnected complex searches to understand how they’re actually similar to each other. This learning, in turn, allows it to better understand future complex searches and whether they’re related to particular topics. Most important, from what Google told us, it can then associate these groups of searches with results that it thinks searchers will like the most.

Google didn’t provide examples of groups of searches or give details on how RankBrain guesses at what are the best pages. But the latter is probably because if it can translate an ambiguous search into something more specific, it can then bring back better answers.

People around the world make more than 3.5 billion Google searches every day and 15% of these queries have never been made before. RankBrain helps Google deal with these 15% f queries. During tests Google engineers who design the algorithms correctly ranked 70% of sites from a range of search terms while, RankBrain achieved a score of 80%.

An interesting paper on Distributed Representations of Words and Phrases and their Compositionality  explains the way words and phrases can be mathematically connected.

A lot is written about keyword research and there are many websites which give a list of probable search queries related to a particular service / product / industry.  But, to determine the perfect list of search queries which the targeted segment is actually using and which will maximize the inbound traffic  is a challenging task for the  website owners and SEOs .

The next daunting task is to keep the blog active with regular, topical, relevant  and fresh content which  calls for preparing a list of blog post ideas to fill the editorial calendar.

I am not a type of SEO who spends a lot of time on keyword research as I think if the content on the website is written keeping the user in mind, then half the battle is won. The other half which is the search engines is taken care of if the content is informative, unique and the technical SEO is up to the mark.

As the competition on the web goes on increasing and the search engine index goes on widening multi-fold on a daily or rather hourly basis, achieving an extensive search presence for a business and at the same time  getting that presence correlated to increasing number of search queries on a regular basis is becoming more and more important.

Hence, instead of focusing on coming up with a list of probable keywords  you want to rank for, let us divert our attention to the categories in which the search queries can be divided. Each category will have a list of key phrases you want the website to rank for.

Every industry more or less has the following categories for the search queries:

 

• Brand Searches
• Questions about the product / service / brand
• Differentiation between two or more products of the same company or different companies
• Same product referred to by different names across the globe
• Exact Match Searches
• Phonetic Spelling Mistakes
• Need Based Search Queries
• Descriptive / adjective based searches
• Local intent search queries or queries with a mention of  a country name.
• Queries which have a mention of a specific format of content.
• People’s names searches ( team members and their profiles)
• Price Related Searches
• Review & Ratings Searches
• Profession Search Queries 

Brand Searches:

Brand searches are the most common type of searches from people who already know about your brand  or from those people who have heard about your brand via some friends or social media. As the number of brand searches increase, it positively impacts SEO.  Hence if you are not having a prominent search presence for your brand search query then you need to work on that first. If people who have heard about your brand , search your brand name and cannot find your presence on the first page of the search engine then they will stop looking further and if they find your website URL , social media URLs , blog post URLs, etc. On the first page then they will look no further .

 

Questions about the product / service / brand

These type of searches have shown an increasing trend recently. Search has become more conversational and people consider a search engine as an assistant and what it to answer the questions they have. Right from a primary school kid who has questions about the project that he has to submit to his teacher to the high end professional who needs to take decisions on critical matters , all turn to Google for answers.

Hence, if people have questions about  the product you deal then having  a search presence for questions related to it is highly important. As it is always better that the people seeking answers to their queries related to your product get their answers from your company website only. This increases the trust factor and you are also assured that the information gathered by the searcher about your product is correct.

We have written a detailed blog post on :

How Brand + Product/Category Search Queries Have An Impact On Search Results. 

Queries regarding differentiation between two or more products of the same company or different companies

It is very common for people to search how one product is different from another.

For example:

• Samsung Galaxy s6 v/s iphone 6
• Samsung Galaxy s6 v/s Samsung Galaxy s6 Edge

Hence when a company launches a new product it is important to have content regarding how the new product compares as to the previous product the company has. If you have a search presence for  this type of a query then again the people get the information from your website rather than from some other general website which curates content regarding these topics and ranks better on search engines.

Same product referred to by different names across the globe :

Many times a single product is referred to by different names across different countries. For e.g:

Edible oil is referred as cooking oil or vegetable oil in many countries. So if you want to target the global market and your site is about edible oil refineries then care should be taken to see that the website has a good search presence for edible oil refineries , cooking oil refineries and vegetable oil refineries.

Exact Match Searches:

These are very common type of searches for products which are very famous or are in vogue. For example a teenager searching for Air Max 2015 Black Running Shoes will search for the exact term. Having a good search presence for these type of queries again helps the website owner to target this segment and get inbound traffic to the site. With the number of eCommerce sites mushrooming these days. This kind of segment will  get diverted to the third party eCommerce sites which are ranking well for this product.

Phonetic Spelling Mistakes:

There are many terms which are spelt in different ways . For e.g  jewelry or jewellery.  Trying  to have a presence for both the terms helps in reaching out to  a wider inbound  audience .

Need Based Search Queries:

Every product caters to a certain need of the potential buyer . But, sometimes the searches can be specific as per the immediate requirement. For e.g : green lace bridesmaid dresses, red woollen jacket with black leather sleeves, etc.

These type of search queries cannot be focused on but the content on the site can be specific and in details so that the particular page having this kind of a product can have a chance of  catering to these kind of queries on the search engines.

Descriptive / adjective Based Searches:

This is similar to the previous type but here the searcher is not very specific of his need. He may/may not be specific about the color but may just need a dark  colored jacket with leather sleeves. Or may just add one adjective to look for a product like – glossy paper , long dresses, beautiful designer sarees, etc.

Local intent search queries or queries with a mention of  a country name

Local search   of course is different than organic search and the factors too vary but if you want to target the local market then one cannot rely only by having a good presence in the local search results but also focus on organic search for search queries which have a local intent.

For e.g: if you have a page 1 presence in the local search results for SEO Ahmedabad then it is good but as the local search results are volatile in nature,ranking  for such a query in the organic search results also is a wise decision. Many people ignore this in favour of  targeting the global market which is not a wise decision.

Queries which have a mention of a specific format of content:

Many people search for something and they want it in PDF format or some other specific format. For e.g  leave application form pdf format , what is a blog – ppt, etc.

Having content in various formats like text, videos, podcasts, PDFs, PPTs, etc. And having a good search presence for all these formats also helps in reaching out to a wider audience. It is not necessary to have the same content in different formats on one website but these formats should by published  on relevant platforms like the videos on the Youtube channel of the company, PPTs on slideShare, PDFs in the downloads section of the website, etc. This way the digital assets of the company also increase and the company has a wider presence across the web.

People’s names/Proper Noun  Searches:

We all know that people do Google names to find out more about  them. Hence , if your website has a page for team members or their names are mentioned on the contact page then the relevant page have a potential for search presence when those names are searched. Hence, updating the pages as and when people are appointed or when they leave the organization is advisable. Else, people searching for those names can get a right/wrong impression about the company .

Price Related Searches:

People do search for products specifying the price or the range of the price that they want to buy the product for. Hence, if microformats are used for specifying pricing the potential for ranking for such search queries increases.

Review & Ratings Searches:

With social media becoming the rage on the web, people want to rely more on what others have to say about the product/service  rather than what the company has to say about their product/service. Hence , having a ratings and reviews section where people can login and publish their opinion is always beneficial and having microformats on the page for ratings and reviews helps search engines index them in the right format and correlate it for a better search presence.

Profession Search Queries:

There are many searches made related to professions . For e.g -  Eye Surgeons in India, doctors in New York,  Neurologists, etc. getting backlinks If you run a hospital and perform LASIK surgeries the most common search term targeted would be LASIK eye surgery , Laser eye surgery, etc. But if the website page which has the detailed biodata of the doctor also ranks for the queries like eye surgeons, ophthalmologists, eye doctor, etc.   it helps in reaching out to a wider inbound audience.

 

How to determine the topics for the next editorial calendar after the search query analysis:

Once the type of search queries you think you want your  online presence to cater to is decided, the next step is to determine the landing pages which can be selected for the search queries category-wise .

• Check which pages are already having a good search presence for which search query.
• List out the search queries which are not having a search presence.
• Try to improvise on the content of the existing pages shortlisted thus or add new pages to target them.
• If you think that adding more content on the website is not possible then write blog posts focusing those search queries which are not yet having the desired search presence.
• Select a topic related to that search query, write in-depth content on it and publish the blog post.

This exercise not only gives us clarity about the targeted search presence which has yet to be achieved but also gives us an idea to  plan the  topics for the content calendar.

The blog is a platform where you can write fresh content on a regular basis. If the content is fresh, unique, in-depth and informative then the search presence surely gets a boost by targeting additional search queries. This also helps in establishing the identity of the company as a thought leader for that relevant industry.

Recently everyone had their eyes wide open when they read  that Google wants to hire a SEO Manager.

I think it is a very logical thing as Google  also needs to be as per the World Wide Web Consortium (W3C) norms. The World Wide Web Consortium (W3C) is an international community where Member organizations, a full-time staff, and the public work together to develop Web standards. Led by Web inventor Tim Berners-Lee and CEO Jeffrey Jaffe, W3C's mission is to lead the Web to its full potential.

Search engines are not the WWW. They are a subset of the WWW superset. http://www.webpro.in/google-also-needs-seo-because-it-is-the-world-wide-web-consortium-w3c-org-which-is-a-standard-and-not-google/ http://www.webpro.in/google-also-needs-seo-because-it-is-the-world-wide-web-consortium-w3c-org-which-is-a-standard-and-not-google/ http://www.webpro.in/google-also-needs-seo-because-it-is-the-world-wide-web-consortium-w3c-org-which-is-a-standard-and-not-google/ http://www.webpro.in/google-also-needs-seo-because-it-is-the-world-wide-web-consortium-w3c-org-which-is-a-standard-and-not-google/ http://www.webpro.in/google-also-needs-seo-because-it-is-the-world-wide-web-consortium-w3c-org-which-is-a-standard-and-not-google/Search engine algorithms try to get quality signals from the web and constantly endeavour to improve the search results so that they can cater quality search results to the user.

Search engines either integrate web standards like XML sitemaps, Schemas, Meta tags,etc. or they create their own standards like the Google created the Authorship Markup.

W3C laid the foundations of today’s Web with standards such as HTML (in 1997) and XML (in 1998).

For example Microformats is not a new concept www.microformats.org domain was registered on 26th January 2005 and since then the site is adding content on how microdata can be added to the websites.

But, it is in 2012 when Google launched the Knowledge Graph that the SEOs started focusing their attention on microdata and made it a well known norm.

From the time the term SEO has been coined, SEOs have been executing repair functions on the websites to make them search engine friendly but its high time we move on from thinking about search engines and start thinking about the quality standards which are friendly to the web eco system and build and structure our online presence (earned and owned) as per the web standards before they get accepted by the search engines.

By giving importance only to the Google algorithms we are paving the way for Google algorithms to become the standard and helping it to monopolize the web.

Hence, Google also needs to futureproof its web presence and websites as per the w3c standards and be prepared to face any kind of competition in future.

Looking for a new job?

Google wants to hire a SEO Manager to improve its organic search presence.

Google published the vacancy on the Google careers Portal :

https://www.google.com/about/careers/search#!t=jo&jid=120105001 .

It says:

As a Program Manager for Technical SEO, you will work with cross-functional teams across Marketing, Sales, Product Development, Engineering and more to help drive organic traffic and business growth. You will take part in website development and optimization, help shape blog and social strategy, improve website code hygiene and define web architecture for international websites.

The Google Cloud Platform (GCP) is driving the next wave of cloud computing. From lightning fast IaaS to innovate container technology to massive data analysis, GCP is pushing the envelope.http://www.webpro.in/looking-for-a-new-job-google-is-looking-for-program-manager-search-engine-optimization/ As the Cloud SEO program manager, you will be a member of both the Google Cloud Platform Marketing team and the Cloud Web Development team responsible for optimizing the customer journey through search. You will work on projects that require broad cross-functional coordination coupled with a deep knowledge of the cloud computing space.

Responsibilities

• Architect, design, develop and maintain innovative, engaging and informative sites for a worldwide audience.
• Maintain and develop the web code to ensure quality, content and readability by search engines.
• Keep pace with SEO, search engine and internet marketing industry trends and developments and report changes as needed.
• Advise, collaborate with, and synthesize feedback from Marketing, Product and Engineering partners to push for technical SEO best practices.

Minimum qualifications

• BA/BS degree in Computer Science, Engineering or equivalent practical experience.
• 4 years of experience developing websites and applications with SQL, HTML5, and XML.
• 2 years of SEO experience.
• Experience with Google App Engine, Google Custom Search, Webmaster Tools and Google Analytics and experience creating and maintaining project schedules using project management systems.

Preferred qualifications

• Experience working with back-end SEO elements such as .htaccess, robots.txt, metadata and site speed optimization to optimize website performance.
• Experience in quantifying marketing impact and SEO performance and strong understanding of technical SEO (sitemaps, crawl budget, canonicalization, etc.).
• Knowledge of one or more of the following: Java, C/C++, or Python.
• Excellent problem solving and analytical skills with the ability to dig extensively into metrics and analytics.

Think before you say... SEO IS DEAD. Even the Search Giant is serious about its organic search presence

It is 2015 and SEO is very much alive and in fact according to my opinion is gaining its true existence and importance like never before.

But, even today when website owners want to evaluate the success of an SEO campaign, they first check the rankings and many times only the rankings.

This has always been a myopic view of the SEO results and now with the current scenario its all the more short sighted and does not give the true picture. Focusing on the larger picture especially in the first 2 years of the SEO campaign is more important.

When I say larger picture, I mean the other parameters which need to be monitored in the initial stages of the SEO campaign.

First let us list the stages in the SEO campaign.
• SEO Audit (on-page and off-page)
• Corrective actions taken on the audit results
• Working on the Local Search presence
• Monitoring the results of the actions taken via WMT and GA

Once the action has been taken on all the factors or while the SEO efforts are in progress the focus should be on how the content is getting correlated to the search queries targeted. Google has got certain parameters in GA and GWMT which give a correct idea.
Recently Google has introduced a detailed Search Analytics Report in GWMT which gives an in-depth idea about these parameters.

Starting with a SEO campaign is like sowing a seed. One needs to nurture it with corrective on-page factors and enrich it with regular informative content to make the search presence grow.

When you sow a seed you do not expect it to be a full-fledged tree in a short duration but you nurture it till it is growing and also protect it once it is fully grown.

Data from Search Analytics OF GWMT and Search Engine Optimization metrics of GA should be tracked to get an idea about the success of the SEO effort put in.
Rankings and a good search presence with a good outreach is the long term goal for SEO. But during the initial stages of the SEO campaign one has to see how closer we are to the goal each day rather than checking if we have reached the goal.

Hence the Search Analytics data , other data from the WMTs and the Search Engine Optimization data helps us measure and monitor how efficiently we are marching ahead towards our goal.

There are some differences between Search Analytics and Search Queries. Data in the Search Analytics report is much more accurate than data in the older Search Queries report, and it is calculated differently.

The Search Analytics Report shows :

• How often your site appears in Google search results.
• See how your search traffic changes over time, where it’s coming from, and what search queries are most likely to show your site.
• Learn which queries are made on smartphones, and use this to improve your mobile targeting.
• See which pages have the highest (and lowest) click-through rate from Google search results.

The following metrics are available in the Search Analytics Report :

• Clicks - Count of clicks from a Google search results page that landed the user on your property.
• Impressions - How many links to your site a user saw on Google search results, even if the link was not scrolled into view. However, if a user views only page 1 and the link is on page 2, the impression is not counted.
• CTR - Click-through rate: the click count divided by the impression count.
• Position - The average position of the topmost result from your site. So, for example, if your site has three results at positions 2, 4, and 6, the position is reported as 2. If a second query returned results at positions 3, 5, and 9, your average position would be (2 + 3)/2 = 2.5.

Grouping your data

This data are grouped in the table by selecting a grouping category at the top of the report; for example, choose "Queries" to group data by search query terms, or "Pages" to group by the canonical page returned by search results.

Group by query

Group results by query strings that users searched for on Google. Only searches that returned your site will be included. Very rare queries are not shown in these results to protect the privacy of the user making the query.
Common uses:
• Review the Query list for expected keywords. If keywords that you expect to see don't appear, your site might not have enough useful content relevant to those keywords. If unexpected words (like "Viagra" or "casino") appear, it's likely that your site has been hacked.
• Find queries with high impressions and low CTR. These queries can help identify where you can improve your content to satisfy your user’s interests.

Group by page

Group results by individual page on your property that were returned by search results. Grouping by page can change the metric calculation for CTR, impressions, and clicks.

Group by country

Group results by the country where the search came from; for example, Canada or Mexico.

Group by device

Group results by the device making the search; for example, desktop, tablet, or mobile. If you have separate mobile and desktop sites, for example m.example.com and www.example.com, the metrics for each site will be reported separately in Search Analytics. If you don't have a separate mobile version of your website—for example, you dynamically detect the user agent and adjust the site layout accordingly in a single site—you must group by device to compare the clicks and impressions you get from mobile devices compared to clicks and impressions from desktop users.

Group by date

Shows a graph of your selected metrics over the selected time span. Default time span is four weeks. The data table is not shown when grouping by date.

The Search Engine Optimization reports in Google Analytics use four metrics specific to Google Web Search data:

• Impressions -the number of times any URL from your site appeared in search results viewed by a user, not including paid AdWords search impressions
• Clicks—the number of clicks on your website URLs from a Google Search results page, not including clicks on paid AdWords search results
• Average Position—the average ranking of your website URLs for the query or queries. For example, if your site's URL appeared at position 3 for one query and position 7 for another query, the average position would be 5 ((3+7)/2).
• CTR—clickthrough rate, calculated as Clicks / Impressions * 100
  The SEO Geographical Summary Report
• The Geographical Summary report provides a general view of Impressions, Clicks, and CTR by country.

At a glance, you can see which countries are generating the most search activity for your site on Google search. You can also selectGoogle Property as a primary dimension to see a breakdown of search activity on Google search by the following:
• Web search
• Mobile search
• Video search
• Image search

The SEO Queries Report

The Queries report shows the Google search queries that generated the most impressions for your website URLs. You can sort by other columns—such as clicks—to order queries in descending/ascending rank by those metrics.

By using this report, you can identify search queries for which your site has a good average position, but poor click through rates. These are queries for which your pages get attention, so improved content could lead to more traffic.

The SEO Landing Pages Report

The Landing Pages report shows the URLs to your website that have generated the most impressions in Google Web search results. With this report, you can identify landing pages on your site that have good click through rates (CTR), but have poor average positions in search results. These could be pages that people want to see, but have trouble finding.
In addition, a single URL is typically associated with many unique queries. For this reason, the average position ranking for a given page can be influenced by more generic queries, and if you are comparing the top landing pages to the top queries with respect to Average Position, you should keep this in mind.

For example, for a website dedicated to classic automobiles, a query such as classic automobiles might return the URL for the home page only, whereas a query such as classic automobiles Ford might return the URL for the home page as well as other pages in the site.In this case, the generic query improves the position ranking for the home page over the ranking of pages that are more specific in nature.

Before the website starts appearing on page 1 search results for targeted search queries, it has to get crawled, indexed, correlated to relevant content and win the trust factor of the search engine.

Hence, as a website owner instead of only checking rankings ask the following questions to the SEO :

• Are the no. of impressions for the site in the search results increasing?
• Are these impressions from relevant search queries?
• Is the geographic reach increasing?
• Are the landing pages increasing in no.?
• Are the impressions of these landing pages in the search results relevant to the search queries targeted for that page?
• The CTR (click thru rate) gives you an idea about the relevance of the title tag and the description tag. Can the CTR rate increase if the meta tags are rewritten with more compelling content ?
• If our site is responsive then are we getting clicks from mobile devices?
• Is the ‘Mobile Friendly’ label visible for the site for mobile search results?
• Also check the indexing, crawling rate and the crawl errors in the WMT.
• Check if there are any errors or warnings for the XML sitemaps submitted?

Once the answers to these queries are sort and corrective actions taken for improvement then check the rankings and the inquiries from the web via the contact age or the call to action on the various pages to determine the success of the SEO campaign and organic search presence.

Including mobile friendliness as one of the ranking factors has surely made the SEOs and website owners busy . They are all working on making their sites responsive and gain the Mobile-Friendly badge for search results.

All this is ok but is it justified that all the posts on this topic are referring this update as Mobilegeddon. This is so misleading Google has not called it ‘Mobilegeddon’ but every post you find on the web on this topic is referring this update by this name.

Clients call you up and ask questions about the Mobilegeddon Update.  By just reading a few posts some of them  exhibit an aura of  see I know it all.  Its all over the web .

But, has Google announced in any of their blog posts that they are calling this change as the Mobilegeddon Update, The way they announced the Panda and the Penguin algorithm? The answer is NO.

Search Engine Land has nicknamed it as Mobilegeddon . See the snapshot of the SEL Blog Post  below.

You can see the no. of posts referring to this change as the 'Mobilegeddon' in the image below:

Please note that this name is given to this change by Search Engine Land and not by Google. 

It reminds me of how the Local search Update got famous as the Pigeon Algorithm or Pigeon Update because Search Engine Land named it so.