Google yesterday published a post on  how they fought spam on the webmaster blog. Google mentioned, we fight spam through a combination of algorithms and manual reviews to ensure that sites don’t rise in search results through deceptive or manipulative behavior, especially because those sites could harm or mislead users.

Some important web spam insights Google gathered in 2015:

• Huge no. of websites being hacked. 180% increase compared to the previous year.
• Increase in the no. of  websites having thin or low quality content.

Actions taken by Google:

• One of the algorithmic updates helped to remove the amount of hacked spam in search results.
• Google sent more than 4.3 million messages to webmasters to notify them of manual actions they took on their site and to help them identify the issues.
• There was a 33% increase in the number of sites that went through spam clean-up efforts towards a successful reconsideration process.
• Users submitted more than 4,00,000 spam reports to Google. Google acted on 65% of them, and considered 80% of those acted upon to be spam.
• Google conducted more than 200 online office hours and live events around the world in 17 languages.
• Webmasters had tens of thousands of questions answered, including over 35,000 by users designated as Webmaster Top Contributors.  webmaster help forum continued to be an excellent source of webmaster support.
• Google believes, fighting web spam is one of the many ways they can  maintain search quality at Google and Google thanked all those who  submitted reports and contributed towards a cleaner web ecosystem!

The successful story you see or read online is the result of efforts made on the basis of the analysis. Writers, online marketers, SEO (Search Engine Optimizations) Professionals keep a close eye on various metrics to come out the strategy boosting their ranking and views.

Content Writers, content marketers who are running their own blogs or writing for their employers need to have an update check of these metrics. Here are the most common metrics every content writer should track to make a good online marketing strategy.

Before opening the list, let us tell you that different metrics work in a different manner. Some are better reviews weekly, some are best reviews monthly. And, before everything, you must know what are you targeting and which metrics you should track.

1. Number of views on the Post

Post Views are a great way to get a feedback on your uploaded articles. If you picked a hot and trending topic, which is well written and presented then you are likely to get more views on it. If the views are not much even after all the efforts, then consider it has not acceptable by your audience. But, the story doesn’t end there.

 

2. Number of Search Visitors

These are the visitors who search something particular on Google and ended up viewing your blog. This result directly points towards whether you are writing a trending topic (that people are searching) or not. Keeping track of the keywords related to the topic is always a good idea to write searchable content. By inserting focusing keywords in your content, you are bridging the gap between your content and your target audience. Following this after a couple of dozen of posts, you will know that you are better writing on which topics. You can then focus on your niches better.

3. Backlinks

Backlink traffic is the measure of activity going to your pages from external websites. Backlinks, particularly from respectable blogs and websites, are the affirmation that your content has the valuable potential. Backlinking activity builds your exposure and scope, and chances to convert. They hold a viable opportunity to get a new business. A business mind takes full advantage of such opportunities

Backlinks are a crucial factor for Google ranking.

If you have a Google analytics account then you can check backlink or referral activity on your blog via Acquisition -> Overview -> Referral

 

4. Average Time Spent on Page by the visitors

In the point under Post Views, we wrote, ‘but the story doesn’t there’. It is because view count is nothing if your viewer is staying just for seconds on your page. If it is a well-written content then they must read it and the view time must be at least a couple of minutes. That’s where average time spent on your page by the viewers matter. By knowing the average time spent by the viewers on your page, you can know whether the viewers are reading your content or just visiting the page and bouncing out of the page quickly. You need to tune up your content if the average time is less. Blog pages that have better average time mean people are reading that content. Try to tune up your other pages the same way to increase the average time.

 

5. Bounce Rate

More the average time, lesser the bounce rate or more the bounce rate lesser the average time!

Bounce rate is the percentage of visitors who navigate away after viewing only single page of your website or blog. If the bounce rate is high that means people/visitors are just coming in and going out of the page doing nothing. It is either they are not reading the content or they do not like it and after reading only one or two lines they are leaving the page. Both the cases indicate that you need to improve your content’s quality. Follow various SEO strategies as per the content creation. Increase the reader-friendliness of the page. Don’t overload it with advertisements and links.

 

6. Social Media Reach

Take advantage of what is available for free online and social media marketing is one of them. Posting on Facebook, twitter, Pinterest, Google+ money wise is free. It only takes a few minutes to write and post on these channels about your content. You can get an adequate amount of traffic from these channels. Keep track of traffic from these channels is very helpful. Channel from where you are getting more traffics post your content frequently on that. You can develop a genuine fan base from these channels who would actually read your content when you post about it on them. You can even engage with them and have a healthy conversation that would help you build strong relationships with your fans and followers.

 

7. Number of Returning Visitors

Observing returning visitors can let you know how captivating your content is and can go about as a rule for content creation for the future. Returning visitors are the ones on which you don’t have to spend your time and money for marketing.

Realizing that the visitor returned, regardless of the possibility that they didn't convert, implies that your content is drawing enough attention to keep them returning and may even imply that your no conversion could be because of something else.

 

8. Monthly Target

After reviewing your week’s performance you should set your monthly target of visitors, returning page visitors, social media reach, and average time spent on page, and the bounce rate. Set a monthly goal and work hard to achieve it in a month. This will motivate you on every step. Try some experiments and see the changes in the result.

And, we are done with our list. These metrics options would be good to give you a head start in content marketing. And, you will learn more as you move forward in this line of work. Make it a habit of not missing any of these metrics.

 

Last year two important major announcements made by Google in February 2015 blog post were:

• Starting April 21 2015, we will be expanding our use of mobile-friendliness as a ranking signal, meaning more mobile-friendly sites in search results.
• We will begin to use information from indexed apps as a factor in ranking for signed-in users who have the app installed

Focusing on the point that Getting good, relevant answers when you search shouldn’t depend on what device you’re using, Google has announced that,  “Beginning of May 2016, we’ll start rolling out an update to mobile search results that increases the effect of the ranking signal to help our users find even more pages that are relevant and mobile-friendly.”

Google recommends checking out the Mobile-Friendly Test and the Webmaster Mobile Guide, both of which provide guidance on how to improve your mobile site.

If you've already made your site mobile-friendly, you will not be impacted by this update. The blog post also mentions that the intent of the search query is still a very strong signal and if the content of the page is very superior and in-depth related to the search query then a page which is not mobile-friendly, may rank in the search results.

With online marketing becoming the norm for all businesses today, Google on the webmasters blog has published a few guidelines on how the businesses can safeguard their websites when reviewing free products they receive from companies.

Google says, Whether you are the company supplying the product or the blogger writing the post, below are a few best practices to ensure that this content is both useful to users and compliant with Google Webmaster Guidelines.

3 points Google mentions on the blog are:

1.  Use the nofollow tag where appropriate.
2.  Disclose the relationship.
3.  Create compelling, unique content.

The nofollow tag should be used because the link that is given in such a review is not an organic one. This review is written because the free product was received. Hence it does not fall in the category of the earned links or genuine links.

Secondly, Users want to know when they’re viewing sponsored content. Also, there are laws in some countries that make disclosure of sponsorship mandatory.

Lastly, Google says, Creating compelling and informative content is something which will add value to the whole post/review. As the write-up should give a lot of information about the product, but should also weigh its pros and cons.

The review should help the user to get a correct idea about the product and help him/her to take a decision. This will also offer a compelling reason for the users to come back for more such reviews.

This kind of an approach will in the long run benefit the user, the blogger and also the company who has offered the free product.

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.