What is a search engine?  Good question.  Well, a search engine is basically a program that looks for information on the internet and organises it according to a set of rules to give this information to you in logical order.  Search engines are constantly looking at the world wide web for content and other information.  They log this information and revisit new and old sites at regular intervals to update their information.  You type in what you're looking for, and the search engine tries to match it.  Simple really.  Read on below for more details.




Nelson Kruschandl - "Search tools are fab"











A search engine is a program designed to help find information stored on a computer system such as the World Wide Web, or a personal computer. The search engine allows one to ask for content meeting specific criteria (typically those containing a given word or phrase) and retrieves a list of references that match those criteria. Search engines use regularly updated indexes to operate quickly and efficiently. Without further qualification, search engine usually refers to a Web search engine, which searches for information on the public Web. Other kinds of search engine are enterprise search engines, which search on intranets, personal search engines, which search individual personal computers, and mobile search engines.


Some search engines also mine data available in newsgroups, large databases, or open directories like Unlike Web directories, which are maintained by human editors, search engines operate algorithmically. Most web sites which call themselves search engines are actually front ends to search engines owned by other companies.





The very first tool used for searching on the Internet was called "Archie". (The name stands for "archives" without the "v", not the kid from the comics). It was created in 1990 by Alan Emtage, a student at McGill University in Montreal. The program downloaded the directory listings of all the files located on public anonymous FTP (File Transfer Protocol) sites, creating a searchable database of filenames.


While Archie indexed computer files, "Gopher" indexed plain text documents. Gopher was created in 1991 by Mark McCahill at the University of Minnesota. (The program was named after the school's mascot). Because these were text files, most of the Gopher sites became Web sites after the creation of the World Wide Web.


Two other programs, "Veronica" and "Jughead," searched the files stored in Gopher index systems. Veronica (Very Easy Rodent-Oriented Net-wide Index to Computerized Archives) provided a keyword search of most Gopher menu titles in the entire Gopher listings. Jughead (Jonzy's Universal Gopher Hierarchy Excavation And Display) was a tool for obtaining menu information from various Gopher servers.


The first Web search engine was "Wandex", a now-defunct index collected by the World Wide Web Wanderer, a web crawler developed by Matthew Gray at MIT in 1993. Another very early search engine, Aliweb, also appeared in 1993, and still runs today. The first "full text" crawler-based search engine was WebCrawler, which came out in 1994. Unlike its predecessors, it let users search for any word in any web page, which became the standard for all major search engines since. It was also the first one to be widely known by the public. Also in 1994 Lycos (which started at Carnegie Mellon University) came out, and became a major commercial endeavor.


Soon after, many search engines appeared and vied for popularity. These included Excite, Infoseek, Inktomi, Northern Light, and AltaVista. In some ways, they competed with popular directories such as Yahoo!. Later, the directories integrated or added on search engine technology for greater functionality.


Search engines were also known as some of the brightest stars in the Internet investing frenzy that occurred in the late 1990s. Several companies entered the market spectacularly, recording record gains during their initial public offerings. Some have taken down their public search engine, and are marketing enterprise-only editions, such as Northern Light.

Before the advent of the Web, there were search engines for other protocols or uses, such as the Archie search engine for anonymous FTP sites and the Veronica search engine for the Gopher protocol. More recently search engines are also coming online which utilise XML or RSS. This allows the search engine to efficently index data about websites without requiring a complicated crawler. The websites simply provide an xml feed which the search engine indexes. XML feeds are increasingly provided automatically by weblogs or blogs. Examples of this type of search engine are feedster, with niche examples such as LjFind Search providing search services for Livejournal blogs.




note: "Launch" refers only to web
availability of original crawl-based
web search engine results.


















Launch (part of DEC)











Ask Jeeves



Northern Light












Objects Search



Yahoo! Search

Final launch


MSN Search

Beta launch


MSN Search

Final launch



Beta Launch


FinQoo Meta Search

Final launch












Around 2001, the Google search engine rose to prominence. Its success was based in part on the concept of link popularity and 'Page Rank'. How many other web sites and web pages link to a given page is taken into consideration with Page Rank, on the premise that good or desirable pages are linked to more than others. The PageRank of linking pages and the number of links on these pages contribute to the Page Rank of the linked page. This makes it possible for Google to order its results by how many web sites link to each found page. Google's minimalist user interface was very popular with users, and has since spawned a number of imitators.


Google and most other web engines utilize not only PageRank but more than 150 criteria to determine relevancy. The algorithm "remembers" where it has been and indexes the number of cross-links and relates these into groupings. PageRank is based on citation analysis that was developed in the 1950s by Eugene Garfield at the University of Pennsylvania. Google's founders cite Garfield's work in their original paper. In this way virtual communities of webpages are found. Teoma's search technology uses a communities approach in its ranking algorithm. NEC Research Institute has worked on similar technology. Web link analysis was first developed by Dr. Jon Kleinberg and his team while working on the CLEVER project at IBM's Almaden research lab. Google is currently the most popular search engine.



Yahoo! Search


In 2002, Yahoo! acquired Inktomi and in 2003, Yahoo! acquired Overture, which owned AlltheWeb and AltaVista. Despite owning its own search engine, Yahoo initially kept using Google to provide its users with search results on its main web site However, in 2004, Yahoo! launched its own search engine based on the combined technologies of its acquisitions and providing a service that gave pre-eminence to the Web search engine over the directory.





The most recent major search engine is MSN Search, owned by Microsoft, which previously relied on others for its search engine listings. In 2004 it debuted a beta version of its own results, powered by its own web crawler (called msnbot). In early 2005 it started showing its own results live. This was barely noticed by average users unaware of where results come from, but was a huge development for many webmasters, who seek inclusion in the major search engines.


At the same time, Microsoft ceased using results from Inktomi, now owned by Yahoo.

This meant the market was now dominated by Google, Yahoo, and Microsoft. The other large (self described) search engines tend to be "portals" that merely show the results another company's search engine (like MSN Search used to do). The other "true" search engines (those that provide their own results), like Gigablast, have vastly less market presence than the big three. However, since site usage is proprietary information, it's often difficult to determine which sites are most popular.



Challenges faced by search engines

  • The web is growing much faster than any present-technology search engine can possibly index (see ).

  • Many web pages are updated frequently, which forces the search engine to revisit them periodically.

  • The queries one can make are currently limited to searching for key words, which may result in many false positives.

  • Dynamically generated sites may be slow or difficult to index, or may result in excessive results from a single site.

  • Many dynamically generated sites are not indexable by search engines; this phenomenon is known as the invisible web.

  • Some search engines do not order the results by relevance, but rather according to how much money the sites have paid them.

  • Some sites use tricks to manipulate the search engine to display them as the first result returned for some keywords. This can lead to some search results being polluted, with more relevant links being pushed down in the result list.


How search engines work


A search engine operates, in the following order

  1. Crawling

    1. Deep Crawling Depth-first search (DFS)

    2. Fresh Crawling Breadth-first search (BFS)

  2. Indexing

  3. Searching

Web search engines work by storing information about a large number of web pages, which they retrieve from the WWW itself. These pages are retrieved by a web crawler (sometimes also known as a spider) — an automated web browser which follows every link it sees, exclusions can be made by the use of robots.txt


The contents of each page are then analyzed to determine how it should be indexed (for example, words are extracted from the titles, headings, or special fields called meta tags). Data about web pages is stored in an index database for use in later queries. Some search engines, such as Google, store all or part of the source page (referred to as a cache) as well as information about the web pages, whereas some store every word of every page it finds, such as AltaVista. This cached page always holds the actual search text since it is the one that was actually indexed, so it can be very useful when the content of the current page has been updated and the search terms are no longer in it. 


This problem might be considered to be a mild form of linkrot, and Google's handling of it increases usability by satisfying user expectations that the search terms will be on the returned web page. This satisfies the principle of least astonishment since the user normally expects the search terms to be on the returned pages. Increased search relevance makes these cached pages very useful, even beyond the fact that they may contain data that may no longer be available elsewhere.


When a user comes to the search engine and makes a query, typically by giving key words, the engine looks up the index and provides a listing of best-matching web pages according to its criteria, usually with a short summary containing the document's title and sometimes parts of the text. Most search engines support the use of the boolean terms AND, OR and NOT to further specify the search query. An advanced feature is proximity search, which allows you to define the distance between keywords.


The usefulness of a search engine depends on the relevance of the results it gives back. While there may be millions of Web pages that include a particular word or phrase, some pages may be more relevant, popular, or authoritative than others. Most search engines employ methods to rank the results to provide the "best" results first. How a search engine decides which pages are the best matches, and what order the results should be shown in, varies widely from one engine to another. The methods also change over time as Internet usage changes and new techniques evolve.


Most web search engines are commercial ventures supported by advertising revenue and, as a result, some employ the controversial practice of allowing advertisers to pay money to have their listings ranked higher in search results.


The vast majority of search engines are run by private companies using proprietary algorithms and closed databases, the most popular currently being Google, MSN Search, and Yahoo! Search. However, Open source search engine technology does exist, such as ht://Dig, Nutch, Senas, Egothor, OpenFTS, DataparkSearch and many others.



Storage costs and crawling time


A modern search engine can operate with stunningly modest storage requirements. Assuming a 500GB drive costs $100 USD (2006 prices), and that an average web page compresses to less than 10K, 10B pages would compress to 100TB, thus using 200 hard drives and cost around $20K. If kept 4 drives per server, we would need no more than 50 servers to store these 10B pages, which at $250/computer would cost under $12.5K. Thus it is possible to have 10B pages held on a server farm with no more than $25K of hardware. Most search engines, in order to serve millions of search queries, serve ads and process the crawl have considerably more resources than this, and allow for significant redundancy to handle disruptions in service.


Crawling 10B pages with 100 machines crawling at 100 pages/second would take 1M seconds, or 11.6 days. Most search engines crawl a small fraction of the web (10-20B pages) at around this frequency or better, but also crawl dynamic web sites (e.g. news sites and blogs) at a much higher frequency.



Geospatially enabled search engines


A recent enhancement to search engine technology is the addition of geocoding to the processing of the ingested documents. Geocoding attempts to match any found references to locations and places to a geospatial frame of reference, such as a street address, gazetteer locations, or to an area (such as a polygonal boundary for a municipality). Through this geocoding process, latitudes and longitudes are assigned to the found places, and these latitudes and longitudes are indexed for later spatial query and retrieval. This can enhance the search process tremendously by allowing a user to search for documents within a given map extent, or conversely, plot the location of documents matching a given keyword to analyze incidence and clustering, or any combination of the two. One company that has developed this type of technology is MetaCarta, which makes its search technology also available as an XML Web Service to allow deep integration into existing applications.


MetaCarta also provides an extension for desktop GIS software such as ESRI's ArcGIS, to allow analysts to interactively query the search engine and retrieve documents in an advanced geospatial and analytical context.













Search engine optimization (SEO) is a set of methods aimed at improving the ranking of a website in search engine listings. The term also refers to an industry of consultants that carry out optimization projects on behalf of clients' sites.


Using search engines, visitors can find sites in a variety of ways: via paid-for advertisements in the search engine results pages (SERPs), via third parties who are listed in the search engines, or via "organic" listings, i.e. the results the search engines present users. SEO is primarily concerned with improving the visibility of a site in the organic search results.

High rankings in the organic search results can provide targeted traffic for a site. Obtaining that traffic by other means can potentially be expensive. For particularly competitive terms, the cost per click can run several dollars, or more, when pay per click advertising or are used. For even moderately competitive terms the cost can range from a few cents to several tens of dollars per visitor. Given those costs, it often makes sense for site owners to optimize their sites for organic search.


Not all sites have identical goals in mind when they optimize for search engines. Some sites are seeking any and all traffic, and may be optimized to rank highly for common search phrase. This can be a poor marketing strategy for a business because it can generate a large volume of low-quality inquiries that cost money to handle, yet result in little business. The "shotgun approach" to search optimization can possibly work well for a site that has broad interest, such as a periodical, a directory, or site that displays advertising with a CPM revenue model.

Other sites target a specific population, with particular needs or interests. Many businesses try to optimize their sites for large numbers of highly specific keywords that indicate a prospective customer who is ready to buy their product. Focusing on desired traffic can generate more high-quality sales leads, and fewer time-wasting inquiries.

Origins of the Term




SEO began in the mid-1990s, as the first search engines were cataloging the early Web. Initially, all a webmaster needed to do was submit a site to the various engines which would run spiders, programs to "crawl" the site, and store the collected data. The search engines then sorted the information by topic, and serve results based on pages they had spidered. As the number of documents online kept growing, and more webmasters realised the value of organic search listings, it became imperative for search engines to sort the vast collection of pages they had spidered and display the most relevant pages first. This was the start of a search engine vs. SEO struggle that continues to this day.


Initially, search engines were guided by the webmasters themselves. Early versions of search algorithms relied on webmaster-provided information like meta tags. Meta tags provided a guide to each page's content and relevant keywords. Soon some webmasters began to abuse meta tags, causing their pages to rank for irrelevant searches. In response, search engines developed more complex algorithms, taking into account a wider range of factors, but they still relied largely on what are today known as "on-site" factors. Examples of on-site factors include:

  • Keywords in the domain name

  • Keywords in the site's directory and file names

  • Page titles and tags: for example, a phrase marked up as an H1 (heading) element was considered to contain keywords relevant to the page

  • Ratio of the keyword(s) to other words on the page, the keyword density

  • Proximity of individual keywords that appear in the search phrase to each other in the text, also known as "keyword proximity"

  • Content of alternate text provided in the form of Alt attributes for images, noframes text for browsers not able to display framed pages, etc.

The inherent flaw in relying so extensively on those factors was that webmasters and SEOs had full control over them and could "optimize" their pages for better rankings. Search engines had to adapt again to ensure their SERPs showed the most relevant pages rather than the best optimized ones.


A new search engine emerged with a new kind of thinking. Google was started by two PhD students at Stanford University, Sergey Brin and Larry Page, and brought a new concept to ranking web pages. This concept, called Page Rank, was, for many years, the mainstay of the Google algorithm [1]. PageRank relied heavily on incoming links and used the logic that each link to a page is a vote for that page's value. The more incoming links a page had the more "worthy" it was. The value of each incoming link itself varied directly based on the PageRank of the page it was coming from and inversely on the number of outgoing links on that page. PageRank proved to be very good at serving relevant results. Google became the most popular and successful search engine. Because PageRank measured an off-site factor, it was more difficult to manipulate - at first.


But manipulated it was. Given time, and the realization that PageRank was the new game in town, webmasters focused on exchanging, buying, and selling links on a massive scale. PageRank's reliance on the link as a vote of confidence in a page's value was undermined as many webmasters sought to garner links purely to influence Google into sending them more traffic, irrespective of whether the link was useful to human site visitors.


It was time for Google and other search engines to look at a wider range of off-site factors. There were other reasons to develop more intelligent algorithms. The Internet was reaching a vast population of non-technical users who were often unable to use advanced querying techniques to reach the information they were seeking and the sheer volume and complexity of the indexed data was vastly different from that of the early days. Search engines had to develop predictive, semantic, linguistic and heuristic algorithms.


The Page Rank metric itself is still displayed in the Google Toolbar, but it is only one of several factors that Google considers in ranking pages.


Today, most search engines keep their methods and ranking algorithms secret. A search engine may use hundreds of factors in ranking the listings on its SERPs; the factors themselves and the weight each carries may change continually.

Much current SEO thinking on what works and what doesn't is largely speculation and informed guesses. Some SEOs have carried out controlled experiments to gauge the effects of different approaches to search optimization.


The following, though, are some of the considerations search engines could be building into their algorithms, and the list of Google patents may give some indication as to what is in the pipeline:

  • Age of site

  • Length of time domain has been registered

  • Age of content

  • Regularity with which new content is added

  • Age of link and reputation of linking site

  • Standard on-site factors

  • Negative scoring for on-site factors (for example, a dampening for sites with extensive keyword meta tags indicative of having being SEO-ed)

  • Uniqueness of content

  • Related terms used in content (the terms the search engine associates as being related to the main content of the page)

  • Google Pagerank (Only used in Google's algorithm)

  • External links, the anchor text in those external links and in the sites/pages containing those links

  • Citations and research sources (indicating the content is of research quality)

  • Stem-related terms in the search engine's database (finance/financing)

  • Incoming backlinks and anchor text of incoming backlinks

  • Negative scoring for some incoming backlinks (perhaps those coming from low value pages, reciprocated backlinks, etc.)

  • Rate of acquisition of backlinks: too many too fast could indicate "unnatural" link buying activity

  • Text surrounding outward links and incoming backlinks. A link following the words "Sponsored Links" could be ignored

  • Use of "rel=nofollow" to suggest that the search engine should ignore the link

  • Depth of document in site

  • Metrics collected from other sources, such as monitoring how frequently users hit the back button when SERPs send them to a particular page

  • Metrics collected from sources like the Google Toolbar, Google AdWords/Adsense programs, etc.

  • Metrics collected in data-sharing arrangements with third parties (like providers of statistical programs used to monitor site traffic)

  • Rate of removal of incoming links to the site

  • Use of sub-domains, use of keywords in sub-domains and volume of content on sub-domains… and negative scoring for such activity

  • Semantic connections of hosted documents

  • Rate of document addition or change

  • IP of hosting service and the number/quality of other sites hosted on that IP

  • Other affiliations of linking site with the linked site (do they share an IP? have a common postal address on the "contact us" page?)

  • Technical matters like use of 301 to redirect moved pages, showing a 404 server header rather than a 200 server header for pages that don't exist, proper use of robots.txt

  • Hosting uptime

  • Whether the site serves different content to different categories of users (cloaking)

  • Broken outgoing links not rectified promptly

  • Unsafe or illegal content

  • Quality of HTML coding, presence of coding errors

  • Actual click through rates observed by the search engines for listings displayed on their SERPs

  • Hand ranking by humans of the most frequently accessed SERPs


The relationship between SEO and the search engines


In the early 2000, search engines and SEO firms attempted to establish an unofficial "truce." There are several tiers of SEO firms, and the more reputable companies employ content-based optimizations which meet with the search engines' (reluctant) approval. These techniques include improvements to site navigation and copywriting, designed to make websites more intelligible to search engine algorithms.


Search engines have also reached out to the SEO industry, and are frequent sponsors and guests at SEO conferences and seminars. In fact, with the advent of paid inclusion, search engines now have a vested interest in the health of the optimization community.


Getting discovered by search engines


New sites no longer need to be submitted to search engines to be listed. A simple link from an established site will get the search engines to visit the new site and spider its contents. It is rarely more than a few days from the acquisition of the link to all the main search engine spiders visiting and indexing the new site.


Naturally, this means that it is good practice to have some means (such as a site map, or plain hypertext links) so that once a spider finds part of a site, it can navigate to the rest. Otherwise, individual, isolated, dead-end pages must be found one-by-one from outside the site; any pages that are not linked to from outside can only be found by links internal to the site.


For those search engines, like Yahoo, who have their own paid submission, it may save some time to pay a nominal fee for submission.



Ethical methods


So-called "ethical" methods of SEO involve following the search engines' guidelines as to what is and what isn't acceptable. Their advice generally is to create content for the user, not the search engines; to make that content easily accessible to their spiders; and to not try to game their system. Often webmasters make critical mistakes when designing or setting up their web sites, and "poison" them so that they will not rank well. Ethical SEO attempts to discover and correct mistakes, such as machine-unreadable menus, broken links, temporary redirects, or a generally poor navigation structure that places pages too many clicks from the home page.


Because search engines are text-centric, many of the same methods that are useful for web accessibility are also advantageous for SEO. Methods are available for optimizing graphical content, even Flash animation (by placing a paragraph or division within, and at the end of the enclosing OBJECT tag), so that search engines can interpret the information.

Some methods considered ethical by the search engines:

  • Using a robots.txt file to grant permissions to spiders to access, or avoid, specific files and directories in the site

  • Using a short and relevant page title to name each page

  • Using a reasonably sized description meta tag without excessive use of keywords, exclamation marks or off topic comments

  • Keeping the page accessible via links from other pages on the site and, preferably, from a sitemap

  • Developing links via natural methods: Google doesn't elaborate on this somewhat vague guideline, but buying a link from an off-topic page purely because it has a high PageRank is probably not considered acceptable. Dropping an email to a fellow webmaster telling him about a great article you've just posted, and requesting a link, is most likely acceptable.

  • Using a clean css layout with the content near the top of the source


Unethical methods


As search engines operate in a highly automated way it is often possible for webmasters to use methods and tactics not approved by search engines to gain better ranking. These methods often go unnoticed unless an employee from the search engine manually visits the site and notices the activity, or a change in ranking algorithm causes the site to lose the advantage thus gained. Sometimes a company will employ an SEO consultant to evaluate competitor's sites, and report "unethical" optimization methods to the search engines.

So-called "unethical" methods may include:


Keyword spamming (or keyword stuffing) involves the insertion of hidden, random text on a webpage to raise the keyword density or ratio of keywords to other words on the page. Hiding text out of view of the visitor's screen is done in many different ways. A popular technique is text colored to blend with the background. Using CSS "Z" positioning to place text "behind" an image -- and therefore out of view of the visitor -- is also common. Other ways include using CSS absolute positioning to have the text positioned several feet away from the page center and, again, out of physical view of the visitor but plainly text that any search engine would pick up in a crawl of the page. Invisible text is a bad idea, as of 2005, because top search engines apparently can detect it.


Abusing NOSCRIPT tags is another way to place hidden content within a page so that the search engines will index it, but the visitor won't see the content. NOSCRIPT tags are also a valid optimization method for displaying an alternative representation of JavaScript content, such as dynamic methods. The NOSCRIPT tags is not unethical by itself, only if misused.

The inserted text sometimes includes words that are frequently searched (such as "sex") even if those terms bear little connection to the content of the page. The goal in these cases is plainly to increase traffic at all costs whether that traffic is relevant or not. Once traffic comes to the page, the unethical webmaster may hope to monetize the traffic by displaying ads.


Spamdexing is the promotion of irrelevant, chiefly commercial, pages through abuse of the search algorithms. Many search engine administrators consider any form of search engine optimization used to improve a website's page rank as spamdexing. However, over time a widespread consensus has developed in the industry as to what are and are not acceptable means of boosting one's search engine placement and resultant traffic.


Cloaking refers to any of several means to serve up a different page to the search-engine spider than will be seen by human users. It can be an attempt to mislead search engines regarding the content on a particular web site. It should be noted, however, that cloaking can also be used to ethically increase accessibility of a site to users with disabilities, or to provide human users with content that search engines aren't able to process or parse. It is also used to deliver content based on a user's location; Google themselves use IP delivery, a form of cloaking, to deliver results.


Link spam is the placing or solicitation of links randomly on other sites, placing a desired keyword into the hyperlinked text of the inbound link. Guest books, forums, blogs and any site that accepts visitors comments are particular targets and are often victims of drive by spamming where automated software creates nonsense posts with links that are usually irrelevant and unwanted.


The following techniques are also widely acknowledged as being spam, or "black hat":

Some SEOs argue that the terms ethical and unethical should not be applied to the work they do. They maintain that on the principle of basic freedom everybody should be free to post whatever they choose on a site they own, as long as they stay within the law. The responsibility to block search engines access to that content is not one the webmaster should automatically assume. SEOs then explain that typically search engines visit sites uninvited and help themselves to the entire content of that site. Should the search engine then apply some software to "digest" that content and use it in their search results (often monetized with their own advertising) then pinning an "unethical" label on the webmaster is neither fair nor accurate. The flip side is that when a webmaster submits a site to a search engine he is actually inviting the search engine over. However, nowadays, the invitation is unnecessary as search engine spiders are aggressive in finding links to new pages and in crawling that new content, often within hours or minutes, unless they have specifically been excluded by a webmaster-prepared robots.txt file, or a robots exclusion meta tag.



High quality web sites typically rank well


A webmaster who wants to maximize the value of a web site can read the guidelines published by the search engines, as well as the coding guidelines published by the World Wide Web Consortium. If the guidelines are followed, and the site presents frequently updated, useful, original content, and a few meaningful, useful inbound links are established, it is usually possible to obtain a significant amount of organic search traffic.


When a site has useful content, other webmasters will naturally place links to the site, increasing its PageRank and flow of visitors. When visitors discover a useful web site, they tend to refer other visitors by emailing or instant messaging links.

As a result, SEO practices that improve web site quality are likely to outlive short term practices that simply seek to manipulate search rankings. The top SEOs recommend targeting the same thing that search engines seek to promote: relevant, useful content for their users. Means of improving web site quality include:

  1. Clean, fast loading websites, that are content rich, and frequently updated.

  2. Websites that follow the web's simpler conventions (short and descriptive titles, easy navigation, no disabling of browser buttons, no keyword stuffing or other blatant SEO work).

  3. Natural-looking link building: a few links from directories, very minimal reciprocal or three-way linking, no apparent buying or selling of links, no attempted PR manipulation (buying/selling/hogging), no outward links to less reputable sites.

  4. No auto-generated nonsense content and no machine translated content, but original, useful material.

  5. No technical errors, no duplicate pages, a valid robots.txt, a sitemap, and custom error pages.


Related fields


Internet marketing is a field that includes SEO, as well as other methods of improving web site traffic, including content development, graphic design, public relations, online advertising, newsletters.











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