Have you received a Google Webmaster notice? Here’s what to do.

During the last few weeks, Google sent many webmaster notification messages about unnatural links. If you have received such a message, here’s what you have to do to make sure that your website doesn’t get penalized.

What is this Google unnatural links message?

Google has sent the following message to many webmasters:

“Dear site owner or webmaster of example.com.

We’ve detected that some of your site’s pages may be using techniques that are outside Google’s Webmaster Guidelines.

Specifically, look for possibly artificial or unnatural links pointing to your site that could be intended to manipulate PageRank. Examples of unnatural linking could include buying links to pass PageRank or participating in link schemes.

We encourage you to make changes to your site so that it meets our quality guidelines. Once you’ve made these changes, please submit your site for reconsideration in Google’s search results.

If you find unnatural links to your site that you are unable to control or remove, please provide the details in your reconsideration request.

If you have any questions about how to resolve this issue, please see our Webmaster Help Forum for support.

Sincerely,
Google Search Quality Team”

What will happen when you get such a message?

Webmasters who received such a message observed that many sites were penalized 3-4 weeks after the message. The penalty is for the keywords that are included in the unnatural links.

If most of the links that point to the website are unnatural links then the whole website might be penalized.

What are unnatural links?

There are several backlink types that Google finds unnatural:

  1. Public backlink networks:Google doesn’t like fully automated or paid backlink networks. If you participate in a backlink network that can be joined by anyone (even for a fee) then it is very likely that Google has already penalized the network or that the network is a target for the near future.If you can find the backlink network, Google’s engineers can find it, too.
  2. Private backlink networks: some SEO agencies have private backlink networks. Google probably has the technology to detect these networks without creating accounts.
  3. Paid sidebar links: if your website has too many backlinks from the sidebars of other websites, Google might find them unnatural.
  4. Over-optimized anchor text: if the links to your website all use exactly the same anchor text, it is likely that Google might reconsider the rankings of the linked pages.
  5. Fake forum and social media links: some tools create fake forum and social media site accounts to get backlinks to your website. Chances are that Google can detect that type of link.

What should you do?

If you used one of the methods above to get backlinks to your website, try to get rid of these links as quickly as possible.

The formula to high rankings on Google is very easy:

Good content + good backlinks + no spam = high rankings

Optimize the content of your web pages to make sure that Google and other search engines know what your website is about. Then get good backlinks to show search engines that your website can be trusted.

Google has become more aggressive regarding spammy backlinks. In the past, a website might get high rankings for several months until Google detected the site. Now it seems that the it takes a maximum of 3 months until Google detects the spammers.

Do not fall for SEO solutions that promise quick and easy backlinks. It doesn’t make sense to get high rankings for 2-3 months just to get penalized after that time. If you are serious about your business, you have to use strategies that deliver high rankings that will stay, even if it takes longer to get these rankings in the short term.

Google over the last month has made more than 50 updates to its algorithm

Here’s the list for March:

  • Autocomplete with math symbols.

[launch codename “Blackboard”, project codename “Suggest”]

When Google process queries to return predictions in autocomplete, Google generally normalize them to match more relevant predictions in Google’s database. This change incorporates several characters that were previously normalized: “+”, “-”, “*”, “/”, “^”, “(“, “)”, and “=”. This should make it easier to search for popular equations, for example [e = mc2] or [y = mx+b].

 

  • Improvements to handling of symbols for indexing.

[launch codename “Deep Maroon”]

Google generally ignore punctuation symbols in queries. Based on analysis of Google’s query stream, Google now started to index the following heavily used symbols: “%”, “$”, “\”, “.”, “@”, “#”, and “+”. Google continue to index more symbols as usage warrants.

 

  • Better scoring of news groupings.

[launch codename “avenger_2”]

News results on Google are organized into groups that are about the same story. Google have scoring systems to determine the ordering of these groups for a given query. This subtle change slightly improves Google’s scoring system, leading to better ranking of news clusters.

 

  • Sitelinks data refresh.

[launch codename “Saralee-76”]

Sitelinks (the links that appear beneath some search results and link deeper into the respective site) are generated in part by an offline process that analyzes site structure and other data to determine the most relevant links to show users. Google recently updated the data through Google’s offline process. These updates happen frequently (on the order of weeks).

 

  • Improvements to autocomplete backends, coverage.

[launch codename “sovereign”, project codename “Suggest”]

Google consolidated systems and reduced the number of backend calls required to prepare autocomplete predictions for your query. The result is more efficient CPU usage and more comprehensive predictions.

 

  • Better handling of password changes.

Google general approach is that when you change passwords, you’ll be signed out from your account on all machines. This change ensures that changing your password more consistently signs your account out of Search, everywhere.

 

  • Better indexing of profile pages.

[launch codename “Prof-2”]

This change improves the comprehensiveness of public profile pages in Google’s index from more than two-hundred social sites.

 

  • UI refresh for News Universal.

[launch codename “Cosmos Newsy”, project codename “Cosmos”]

Google refreshed the design of News Universal results by providing more results from the top cluster, unifying the UI treatment of clusters of different sizes, adding a larger font for the top article, adding larger images (from licensed sources), and adding author information.

 

  • Improvements to results for navigational queries.

[launch codename “IceMan5”]

A “navigational query” is a search where it looks like the user is looking to navigate to a particular website, such as [New York Times] or [wikipedia.org]. While these searches may seem straightforward, there are still challenges to serving the best results. For example, what if the user doesn’t actually know the right URL? What if the URL they’re searching for seems to be a parked domain (with no content)? This change improves results for this kind of search.

 

  • High-quality sites algorithm data update and freshness improvements.

[launch codename “mm”, project codename “Panda”]

Like many of the changes Google make, aspects of Google’s high-quality sites algorithm depend on processing that’s done offline and pushed on a periodic cycle. In the past month, Google pushed updated data for “Panda,” as Google mentioned in a recent tweet. Google also made improvements to keep Google’s database fresher overall.

 

  • Live results for UEFA Champions League and KHL.

 Google added live-updating snippets in Google’s search results for the KHL (Russian Hockey League) and UEFA Champions League, including scores and schedules. Now you can find live results from a variety of sports leagues, including the NFL, NBA, NHL and others.

 

  • Tennis search feature.

[launch codename “DoubleFault”]

Google introduced a new search feature to provide realtime tennis scores at the top of the search results page. Try [maria sharapova] or [sony ericsson open].

 

  • More relevant image search results.

[launch codename “Lice”]

This change tunes signals Google use related to landing page quality for images. This makes it more likely that you’ll find highly relevant images, even if those images are on pages that are lower quality.

 

  • Fresher image predictions in all languages.

[launch codename “imagine2”, project codename “Suggest”]

Google recently rolled out a change to surface more relevant image search predictions in autocomplete in English. This improvement extends the update to all languages.

 

  • SafeSearch algorithm tuning.

[launch codenames “Fiorentini”, “SuperDyn”; project codename “SafeSearch”]

This month Google rolled out a couple of changes to Google’s SafeSearch algorithm. Google updated Google’s classifier to make it smarter and more precise, and Google found new ways to make adult content less likely to appear when a user isn’t looking for it

 

  • Tweaks to handling of anchor text.

 [launch codename “PC”]

This month Google turned off a classifier related to anchor text (the visible text appearing in links). Google’s experimental data suggested that other methods of anchor processing had greater success, so turning off this component made Google’s scoring cleaner and more robust.

 

  • Simplification to Images Universal codebase.

[launch codename “Galactic Center”]

Google made some improvements to simplify Google’s codebase for Images Universal and to better utilize improvements in Google’s general web ranking to also provide better image results.

 

  • Better application ranking and UI on mobile.

When you search for apps on your phone, you’ll now see richer results with app icons, star ratings, prices, and download buttons arranged to fit well on smaller screens. You’ll also see more relevant ranking of mobile applications based on your device platform, for example Android or iOS.

 

  • Improvements to freshness in Video Universal.

[launch codename “graphite”, project codename “Freshness”]

Google improved the freshness of video results to better detect stale videos and return fresh content.

 

  • Fewer undesired synonyms.

[project codename “Synonyms”]

When you search on Google, Google often identify other search terms that might have the same meaning as what you entered in the box (synonyms) and surface results for those terms as well when it might be helpful. This month Google tweaked a classifier to prevent unhelpful synonyms from being introduced as content in the results set.

 

  • Better handling of queries with both navigational and local intent.

[launch codename “ShieldsUp”]

Some queries have both local intent and are very navigational (directed towards a particular website). This change improves the balance of results Google show, and helps ensure you’ll find highly relevant navigational results or local results towards the top of the page as appropriate for your query.

 

  • Improvements to freshness.

[launch codename “Abacus”, project codename “Freshness”]

Google launched an improvement to freshness late last year that was very helpful, but it cost significant machine resources. At the time Google decided to roll out the change only for news-related traffic. This month Google rolled it out for all queries.

 

  • Improvements to processing for detection of site quality.

[launch codename “Curlup”]

Google made some improvements to a longstanding system Google have to detect site quality. This improvement allows us to get greater confidence in Google’s classifications.

 

  • Better interpretation and use of anchor text.

Google improved systems Google use to interpret and use anchor text, and determine how relevant a given anchor might be for a given query and website.

 

  • Better local results and sources in Google News.

[launch codename “barefoot”, project codename “news search”]

Google deprecating a signal Google had to help people find content from their local country, and Google building similar logic into other signals Google use. The result is more locally relevant Google News results and higher quality sources.

 

  • Deprecating signal related to ranking in a news cluster.

[launch codename “decaffeination”, project codename “news search”]

Google deprecating a signal that’s no longer improving relevance in Google News. The signal was originally developed to help people find higher quality articles on Google News. (Note: Despite the launch codename, this project has nothing to do with Caffeine, Google’s update to indexing in 2010).

 

  • Fewer “sibling” synonyms.

[launch codename “Gemini”, project codename “Synonyms”]

One of the main signals Google look at to identify synonyms is context. For example, if the word “cat” often appears next to the term “pet” and “furry,” and so does the word “kitten”, Google’s algorithms may guess that “cat” and “kitten” have similar meanings. The problem is that sometimes this method will introduce “synonyms” that actually are different entities in the same category. To continue the example, dogs are also “furry pets” — so sometimes “dog” may be incorrectly introduced as a synonym for “cat”. Google been working for some time to appropriately ferret out these “sibling” synonyms, and Google’s latest system is more maintainable, updatable, debuggable, and extensible to other systems.

 

  • Better synonym accuracy and performance.

 [project codename “Synonyms”]

Google made further improvements to Google’s synonyms system by eliminating duplicate logic. Google also found ways to more accurately identify appropriate synonyms in cases where there are multiple synonym candidates with different contexts.

 

  • Retrieval system tuning.

[launch codename “emonga”, project codename “Optionalization”]

Google improved systems that identify terms in a query which are not necessarily required to retrieve relevant documents. This will make results more faithful to the original query.

 

  • Less aggressive synonyms.

 [launch codename “zilong”, project codename “Synonyms”]

Google heard feedback from users that sometimes Google’s algorithms are too aggressive at incorporating search results for other terms. The underlying cause is often Google’s synonym system, which will include results for other terms in many cases. This change makes Google’s synonym system less aggressive in the way it incorporates results for other query terms, putting greater weight on the original user query.

 

  • Update to systems relying on geographic data.

[launch codename “Maestro, Maitre”]

Google have a number of signals that rely on geographic data (similar to the data Google surface in Google Earth and Maps). This change updates some of the geographic data Google using.

 

  • Improvements to name detection.

 [launch codename “edge”, project codename “NameDetector”]

Google improved a system for detecting names, particularly for celebrity names.

 

  • Updates to personalization signals.

[project codename “PSearch”]

This change updates signals used to personalize search results.

 

  • Improvements to Image Search relevance.

[launch codename “sib”]

Google updated signals to better promote reasonably sized images on high-quality landing pages.

 

  • Remove deprecated signal from site relevance signals.

[launch codename “Freedom”]

Google removed a deprecated product-focused signal from a site-understanding algorithm.

 

  • More precise detection of old pages.

 [launch codename “oldn23″, project codename “Freshness”]

This change improves detection of stale pages in Google’s index by relying on more relevant signals. As a result, fewer stale pages are shown to users.

 

  • Tweaks to language detection in autocomplete.

[launch codename “Dejavu”, project codename “Suggest”]

In general, autocomplete relies on the display language to determine what language predictions to show. For most languages, Google also try to detect the user query language by analyzing the script, and this change extends that behavior to Chinese (Simplified and Traditional), Japanese and Korean. The net effect is that when users forget to turn off their IMEs, they’ll still get English predictions if they start typing English terms.

 

  • Improvements in date detection for blog/forum pages.

[launch codename “fibyen”, project codename “Dates”]

This change improves the algorithm that determines dates for blog and forum pages.

 

  • More predictions in autocomplete by live rewriting of query prefixes.

[launch codename “Lombart”, project codename “Suggest”]

In this change Google rewriting partial queries on the fly to retrieve more potential matching predictions for the user query. Google use synonyms and other features to get the best overall match. Rewritten prefixes can include term re-orderings, term additions, term removals and more.

 

  • Expanded sitelinks on mobile.

Google launched Google’s expanded sitelinks feature for mobile browsers, providing better organization and presentation of sitelinks in search results.

 

  • More accurate short answers.

[project codename “Porky Pig”]

Google updated the sources behind Google’s short answers feature to rely on data from Freebase. This improves accuracy and makes it easier to fix bugs.

 

  • Migration of video advanced search backends.

 Google migrated some backends used in video advanced search to Google’s main search infrastructure.

 

  • +1 button in search for more countries and domains.

This month Google internationalized the +1 button on the search results page to additional languages and domains. The +1 button in search makes it easy to share recommendations with the world right from your search results. As Google said in Google’s initial blog post, the beauty of +1’s is their relevance—you get the right recommendations (because they come from people who matter to you), at the right time (when you are actually looking for information about that topic) and in the right format (your search results).

 

  • Local result UI refresh on tablet.

Google updated the user interface of local results on tablets to make them more compact and easier to scan.

 

What is Page Rank

Google PageRank (PR)

is a numeric value that represents how important a website is online. Google becomes the idea that when a web site places a link (link) to another, is in fact a vote for the latter.

The more votes has a page will be considered more important by Google. Moreover, the importance of the page that casts the vote also determines the weight of this vote. In this way, Google calculates the importance of a page thanks to the votes received, taking into account the importance of each page that casts the vote.

PageRankTM (developed by the founders Larry Page and Sergey Brin)is the way Google decides the importance of a page. It is a valuable data because it is one of the factors that determine the position will have a page within the search results. It is not the only factor that Google uses to rank pages, but it is one of the most important.

Keep in mind that not all the links are taken into account by Google. For example, Google filters out and discards the links of pages devoted exclusively to put links (called ‘link farms’).

In addition, Google admits that a page can not control the links that point to it, but you can check the links page to other pages in place. Therefore, links to a page can not harm it, but it links a page to place penalized sites may be harmful to your PageRankTM.

If a site has PR0, it is usually a site penalized, and may not be intelligent to put a link to her.

One way to know a page is PageRankTM download it the Google search bar (only available for MS IExplorer). Bar appears in the one shown in green PageRankTM value on a scale of 0 to 10. PR10 websites are Yahoo, Microsoft, Adobe, Macromedia, and Google. You have a full list of PR10 sites.

Algorithm
The algorithm ‘PageRankTM’ was patented in the United States on 8 January 1998 by Larry Page. The original title is “Method for node ranking in a linked database ‘, and was assigned patent number 6,285,999.

PageRank is a probability distribution used to represent the likelihood that a person randomly clicking on links will arrive at any particular page. PageRank can be calculated for collections of documents of any size. It is assumed in several research papers that the distribution is evenly divided among all documents in the collection at the beginning of the computational process. The PageRank computations require several passes, called “iterations”, through the collection to adjust approximate PageRank values to more closely reflect the theoretical true value.

A probability is expressed as a numeric value between 0 and 1. A 0.5 probability is commonly expressed as a “50% chance” of something happening. Hence, a PageRank of 0.5 means there is a 50% chance that a person clicking on a random link will be directed to the document with the 0.5 PageRank.

SERP Rank

The Search engine results page (SERP) is the actual result returned by a search engine in response to a keyword query. The SERP consists of a list of links to web pages with associated text snippets. The SERP rank of a web page refers to the placement of the corresponding link on the SERP, where higher placement means higher SERP rank. The SERP rank of a web page is not only a function of its PageRank, but depends on a relatively large and continuously adjusted set of factors (over 200), commonly referred to by internet marketers as “Google Love”.Search engine optimization (SEO) is aimed at achieving the highest possible SERP rank for a website or a set of web pages

What is indexing?

Indexing is the processing of the pages scanned and is what creates the index that uses Google to give results when you search.

In fact, the robots do not keep our pages but the analysis and make an index of all the words they see and their location. In addition, process information in the TITLE tag and the ALT attribute content of the images, nor do they do with all that he has a page, for example, do not process the content of most Flash files or dynamic pages .
Just read HTML documents?

No, also extract index information or other files: PDF, PS (Adobe PostScript), leaves of Lotus (wk1, wk2, wk3, wk4, WK5, WKI, wks, wku, lwp) and Excel (xls), documents MW text, DOC, WRI, RTF, ANS, TXT, PowerPoint presentations (ppt) files, Microsoft Works (wks, wps, wdb) and swf.

This is done to give more results, in fact, can do a search indicating that we display only certain types of files, for example:
filetype: doc “search text”
In most cases, even when we do not have the software necessary to interpret, we show the option of seeing them as HTML or plain text.
Conversely, we can eliminate certain types of search results using a filter, for example:
-filetype: pdf “search text”

What are Google’s bots?

Google constantly seek out new pages and / or updated to add to your index and there is a charge of this program that is called Googlebot, the famous robots or spiders (spiders). So how Googlebots are calling the search bots whose sole mission in life is to collect web documents in order to build a database that is used by the search engine of its master.

The Googlebots employ a process based on algorithms that determine which sites to crawl, the frequency and number of pages to fetch from each site. These lists are comprehensive websites to identify links to other pages.

How does Google visit?

They say “regularly” but give no details, speak of many factors that can influence but, the truth is that often you access a site depends almost exclusively on PageRank you have. The higher, more will be visited regularly (wealth generates wealth). Then, they can do every day or take weeks.

Google PageRank and is proud of us know that is the heart of his whole system:

“The heart of Google’s software is PageRank ™, a system for ranking web pages developed by Google’s founders Larry Page and Sergey Brin at Stanford University. And while Google have dozens of engineers working to Improve every aspect of Google on a daily basis, PageRank continues to play a central role in many of our web search tools.