What is SEO?
SEO is the active practice of optimizing a web site by improving internal and external aspects in order to increase the traffic the site receives from search engines. Firms that practice SEO can vary; some have a highly specialized focus, while others take a more broad and general approach. Optimizing a web site for search engines can require looking at so many unique elements that many practitioners of SEO (SEOs) consider themselves to be in the broad field of website optimization (since so many of those elements intertwine).
This guide is designed to describe all areas of SEO - from discovery of the terms and phrases that will generate traffic, to making a site search engine friendly, to building the links and marketing the unique value of the site/organization's offerings.
The majority of web traffic is driven by the major commercial search engines - Yahoo!, MSN, Google & AskJeeves (although AOL gets nearly 10% of searches, their engine is powered by Google's results). If your site cannot be found by search engines or your content cannot be put into their databases, you miss out on the incredible opportunities available to websites provided via search - people who want what you have visiting your site. Whether your site provides content, services, products, or information, search engines are a primary method of navigation for almost all Internet users.
Search queries, the words that users type into the search box which contain terms and phrases best suited to your site, carry extraordinary value. Experience has shown that search engine traffic can make (or break) an organization's success. Targeted visitors to a website can provide publicity, revenue, and exposure like no other. Investing in SEO, whether through time or finances, can have an exceptional rate of return.
Why can't the search engines figure out my site without SEO help?
Search engines are always working towards improving their technology to crawl the web more deeply and return increasingly relevant results to users. However, there is and will always be a limit to how search engines can operate. Whereas the right moves can net you thousands of visitors and attention, the wrong moves can hide or bury your site deep in the search results where visibility is minimal. In addition to making content available to search engines, SEO can also help boost rankings so that content that has been found will be placed where searchers will more readily see it. The online environment is becoming increasingly competitive, and those companies who perform SEO will have a decided advantage in visitors and customers.
How Search Engines Operate
Search engines have a short list of critical operations that allows them to provide relevant web results when searchers use their system to find information.
Crawling the Web
Search engines run automated programs, called "bots" or "spiders", that use the hyperlink structure of the web to "crawl" the pages and documents that make up the World Wide Web. Estimates are that of the approximately 20 billion existing pages, search engines have crawled between 8 and 10 billion.
Once a page has been crawled, its contents can be "indexed" - stored in a giant database of documents that makes up a search engine's "index". This index needs to be tightly managed so that requests which must search and sort billions of documents can be completed in fractions of a second.
When a request for information comes into the search engine (hundreds of millions do each day), the engine retrieves from its index all the document that match the query. A match is determined if the terms or phrase is found on the page in the manner specified by the user. For example, a search for car and driver magazine at Google returns 8.25 million results, but a search for the same phrase in quotes ("car and driver magazine") returns only 166 thousand results. In the first system, commonly called "Findall" mode, Google returned all documents which had the terms "car", "driver", and "magazine" (they ignore the term "and" because it's not useful to narrowing the results), while in the second search, only those pages with the exact phrase "car and driver magazine" were returned. Other advanced operators (Google has a list of 11) can change which results a search engine will consider a match for a given query.
Once the search engine has determined which results are a match for the query, the engine's algorithm (a mathematical equation commonly used for sorting) runs calculations on each of the results to determine which is most relevant to the given query. They sort these on the results pages in order from most relevant to least so that users can make a choice about which to select.
Although a search engine's operations are not particularly lengthy, systems like Google, Yahoo!, AskJeeves, and MSN are among the most complex, processing-intensive computers in the world, managing millions of calculations each second and funneling demands for information to an enormous group of users.
Speed Bumps & Walls
Certain types of navigation may hinder or entirely prevent search engines from reaching your website's content. As search engine spiders crawl the web, they rely on the architecture of hyperlinks to find new documents and revisit those that may have changed. In the analogy of speed bumps and walls, complex links and deep site structures with little unique content may serve as "bumps." Data that cannot be accessed by spiderable links qualify as "walls."
Possible "Speed Bumps" for SE Spiders:
- URLs with 2+ dynamic parameters; i.e. http://www.url.com/page.php?id=4&CK=34rr&User=%Tom% (spiders may be reluctant to crawl complex URLs like this because they often result in errors with non-human visitors)
- Pages with more than 100 unique links to other pages on the site (spiders may not follow each one)
- Pages buried more than 3 clicks/links from the home page of a website (unless there are many other external links pointing to the site, spiders will often ignore deep pages)
- Pages requiring a "Session ID" or Cookie to enable navigation (spiders may not be able to retain these elements as a browser user can)
- Pages that are split into "frames" can hinder crawling and cause confusion about which pages to rank in the results.
Possible "Walls" for SE Spiders:
- Pages accessible only via a select form and submit button
- Pages requiring a drop down menu (HTML attribute) to access them
- Documents accessible only via a search box
- Documents blocked purposefully (via a robots meta tag or robots.txt file)
- Pages requiring a login
- Pages that re-direct before showing content (search engines call this cloaking or bait-and-switch and may actually ban sites that use this tactic)
The key to ensuring that a site's contents are fully crawlable is to provide direct, HTML links to each page you want the search engine spiders to index. Remember that if a page cannot be accessed from the home page (where most spiders are likely to start their crawl), it is likely that it will not be indexed by the search engines. A sitemap (which is discussed later in this guide) can be of tremendous help for this purpose.
Measuring Relevance and Popularity
Modern commercial search engines rely on the science of information retrieval (IR). That science has existed since the middle of the 20th century, when retrieval systems powered computers in libraries, research facilities, and government labs. Early in the development of search systems, IR scientists realized that two critical components made up the majority of search functionality:
- Relevance - the degree to which the content of the documents returned in a search matched the user's query intention and terms. The relevance of a document increases if the terms or phrase queried by the user occurs multiple times and shows up in the title of the work or in important headlines or subheaders.
- Popularity - the relative importance, measured via citation (the act of one work referencing another, as often occurs in academic and business documents) of a given document that matches the user's query. The popularity of a given document increases with every other document that references it.
These two items were translated to web search 40 years later and manifest themselves in the form of document analysis and link analysis.
In document analysis, search engines look at whether the search terms are found in important areas of the document - the title, the meta data, the heading tags, and the body of text content. They also attempt to automatically measure the quality of the document (through complex systems beyond the scope of this guide).
In link analysis, search engines measure not only who is linking to a site or page, but what they are saying about that page/site. They also have a good grasp on who is affiliated with whom (through historical link data, the site's registration records, and other sources), who is worthy of being trusted (links from .edu and .gov pages are generally more valuable for this reason), and contextual data about the site the page is hosted on (who links to that site, what they say about the site, etc.).
Link and document analysis combine and overlap hundreds of factors that can be individually measured and filtered through the search engine algorithms (the set of instructions that tells the engines what importance to assign to each factor). The algorithm then determines scoring for the documents and (ideally) lists results in decreasing order of importance (rankings).
Information Search Engines Can Trust
As search engines index the web's link structure and page contents, they find two distinct kinds of information about a given site or page - attributes of the page/site itself and descriptives about that site/page from other pages. Since the web is such a commercial place, with so many parties interested in ranking well for particular searches, the engines have learned that they cannot always rely on websites to be honest about their importance. Thus, the days when artificially stuffed meta tags and keyword-rich pages dominated search results (pre-1998) have vanished and given way to search engines that measure trust via links and content.
The theory goes that if hundreds or thousands of other websites link to you, your site must be popular, and thus, have value. If those links come from very popular and important (and thus, trustworthy) websites, their power is multiplied to even greater degrees. Links from sites like NYTimes.com, Yale.edu, Whitehouse.gov, and others carry with them inherent trust that search engines then use to boost your ranking position. If, on the other hand, the links that point to you are from low-quality, interlinked sites or automated garbage domains (aka link farms), search engines have systems in place to discount the value of those links.
The most well-known system for ranking sites based on link data is the simplistic formula developed by Google's founders - PageRank. PageRank, which relies on a mathematical formula (based around finding a given document in a random pattern of clicking on links), is described by Google in their technology section:
PageRank relies on the uniquely democratic nature of the web by using its vast link structure as an indicator of an individual page's value. In essence, Google interprets a link from page A to page B as a vote, by page A, for page B. But, Google looks at more than the sheer volume of votes, or links a page receives; it also analyzes the page that casts the vote. Votes cast by pages that are themselves "important" weigh more heavily and help to make other pages important.
Google uses a PageRank “proxy” value, which logarithmically translates the actual PageRank of a document to a value between 1 and 10, to rank Web sites listed in its directory (which offers a PageRank order or an Alphabetical order for listings) and in its toolbar.
Here's a small list of the most important factors search engines look at when attempting to value a link:
The Anchor Text of Link
Anchor text describes the visible characters and words that hyperlink to another document or location on the web. For example, in the phrase "CNN is a good source of news, but I actually prefer the BBC's take on events," two unique pieces of anchor text exist - "CNN" is the anchor text pointing to http://www.cnn.com, while "the BBC's take on events" points to http://news.bbc.co.uk. Search engines use this text to help them determine the subject matter of the linked-to document. In the example above, the links would tell the search engine that when users search for "CNN", SEOmoz.org thinks that http://www.cnn.com is a relevant site for the term "CNN" and that http://news.bbc.co.uk is relevant to "the BBC's take on events". If hundreds or thousands of sites think that a particular page is relevant for a given set of terms, that page can manage to rank well even if the terms NEVER appear in the text itself (for example, see the BBC's explanation of why Google ranks certain pages for the term "Miserable Failure").
Global Popularity of the Site
More popular sites, as denoted by the number and power of the links pointing to them, provide more powerful links. Thus, while a link from SEOmoz may be a valuable vote for a site, a link from bbc.co.uk or cnn.com carries far more weight. This is one area where PageRank (assuming it was accurate) could be a good measure, as it's designed to calculate global popularity.
Popularity of Site in Relevant Communities
In the example above, the weight or power of a site's vote is based on its raw popularity across the web. As search engines became more sophisticated and granular in their approach to link data, they acknowledged the existence of "topical communities"; sites on the same subject that often interlink with one another, referencing documents and providing unique data on a particular topic. Sites in these communities provide more value when they link to a site/page on a relevant subject rather than a site that is largely irrelevant to their topic.
Text Directly Surrounding the Link
Search engines have been noted to weight the text directly surrounding a link with greater important and relevant than the other text on the page. Thus, a link from inside an on-topic paragraph may carry greater weight than a link in the sidebar or footer.
Matter of the Linking Page
The topical relationship between the subject of a given page and the sites/pages linked to on it may also factor into the value a search engine assigns to that link. Thus, it will be more valuable to have links from pages that are related to the site/page's subject matter than those that have little to do with the topic.
Link metrics are in place so that search engines can find information to trust. In the academic world, greater citation meant greater importance, but in a commercial environment, manipulation and conflicting interests interfere with the purity of citation-based measurements. Thus, on the modern WWW, the source, style, and context of those citations is vital to ensuring high quality results.
The Anatomy of a HyperLink
A standard hyperlink in HTML code looks like this:
In this example, the code simply indicates that the text "Galbijim" (called the "anchor text" of the link) should be hyperlinked to the page http://www.galbijim.com. A search engine would interpret this code as a message that the page carrying this code believed the page http://www.galbijim.com to be relevant to the text on the page and particularly relevant to the term "Galbijim".
A more complex piece of HTML code for a link may include additional attributes such as:
<a href="http://www.galbijim.com" title="Galbijim Forums" rel="nofollow">Galbijim</a>
In this example, new elements such as the link title and rel attribute may influence how a search engine views the link, despite its appearance on the page remaining unchanged. The title attribute may serve as an additional piece of information, telling the search engine that http://www.galbijim.com, in addition to being related to the term "Galbijim", is also relevant to the phrase "Galbijim Forums". The rel attribute, originally designed to describe the relationship between the linked-to page and the linking page, has, with the recent emergence of the "nofollow" descriptive, become more complex.
"Nofollow" is a tag designed specifically for search engines. When ascribed to a link in the rel attribute, it tells the engine's ranking system that the link should not be considered an editorially approved "vote" for the linked-to page. Currently, 3 major search engines (Yahoo!, MSN, & Google) all support "nofollow". AskJeeves, due to its unique ranking system, does not support nofollow, and ignores its presence in link code. For more information about how this works, visit Danny Sullivan's description of nofollow's inception on the SEW blog.
<a href="redirect/jump.php?url=%2Fgro.zomoes.www%2F%2F%3Aptth" title="http://www.galbijim.com" target="_blank" class="postlink">Galbijim</a>
In this example, the redirect used scrambles the URL by writing it backwards, but unscrambles it later with a script and sends the visitor to the site. It can be assumed that this passes no search engine link value.
It's important to understand that, based on a link's anatomy, search engines can (or cannot) interpret and use the data therein. Whereas the right sort of links can provide great value, the wrong sort will be virtually useless (for search ranking purposes).
Keywords and Queries
Search engines rely on the terms queried by users to determine which results to put through their algorithms, order, and return to the user. But, rather than simply recognizing and retrieving exact matches for query terms, search engines use their knowledge of semantics (the science of language) to construct intelligent matching for queries. An example might be a search for loan providers that also returned results that did not contain that specific phrase, but instead had the term lenders.
The engines collect data based on the frequency of use of terms and the co-occurrence of words and phrases throughout the web. If certain terms or phrases are often found together on pages or sites, search engines can construct intelligent theories about their relationships. Mining semantic data through the incredible corpus that is the Internet has given search engines some of the most accurate data about word ontologies and the connections between words ever assembled artificially. This immense knowledge of language and its usage gives them the ability to determine which pages in a site are topically related, what the topic of a page or site is, how the link structure of the web divides into topical communties, and much, much more.
Search engines' growing artificial intelligence on the subject of language means that queries will increasingly return more intelligent, evolved results. This heavy investment in the field of natural language processing (NLP) will help to achieve greater understanding of the meaning and intent behind their users' queries. Over the long term, users can expect the results of this work to produce increased relevancy in the SERPs (Search Engine Results Pages) and more accurate guesses from the engines as to the intent of a user's queries.
Sorting the Wheat from the Chaff
In the classic world of Information Retrieval, when no commercial interests existed in the databases, very simplistic algorithms could be used to return high quality results. On the world wide web, however, the opposite is true. Commercial interests in the SERPs are a constant issue for modern search engines. With every new focus on quality control and growth in relevance metrics, there are thousands of individuals (many in the field of SEO) dedicated to manipulating these metrics in order to control the SERPs, typically by aiming to list their sites/pages first.
The worst kind of results are what the industry refers to as "search spam" - pages and sites with little real value that contain primarily re-directs to other pages, lists of links, scraped (copied) content, etc. These pages are so irrelevant and useless that search engines are highly focused on removing them from the index. Naturally, the monetary incentives are similar to email spam - although few visit and fewer click on the links (which are what provide the spam publisher with revenue), the sheer quantity is the decisive factor in producing income.
Other "spam" results range from sites that are of low quality or affiliate status that search engines would prefer not to list, to high quality sites and businesses that are using the link structure of the web to manipulate the results in their favor. Search engines are focused on clearing out all types of manipulation and hope to eventually achieve fully relevant and organic algorithms to determine ranking order. So-called "search engine spammers" engage in a constant battle against these tactics, seeking new loopholes and methods for manipulation, resulting in a never-ending struggle.
This guide is NOT about how to manipulate the search engines to achieve rankings, but rather how to create a website that search engines and users will be happy to have ranking permanently in the top positions, thanks to its relevance, quality, and user friendliness.
Paid Placement and Secondary Sources in the Results
The search engine results pages contain not only listings of documents found to be relevant to the user's query, but other content, including paid advertisements and secondary source results. Google, for example, serves up ads from its well-known AdWords program (which currently fuels more than 99% of Google's revenues), as well as secondary content from its local search, product search (called Froogle), and image search results.
The sites/pages ranking in the "organic" search results receive the lion's share of searcher eyeballs and clicks - between 60-70%, depending on factors such as the prominence of ads, relevance of secondary content, etc. The practice of optimization for the paid search results is called SEM, or Search Engine Marketing, while optimizing to rank in the secondary results requires unique, advanced methods of targeting specific searches in arenas such as local search, product search, image search, and others. While all of these practices are a valuable part of any online marketing campaign, they are beyond the scope of this guide.
How to Conduct Keyword Research
Keyword research is critical to the process of SEO. Without this component, your efforts to rank well in the major search engines may be mis-directed to the wrong terms and phrases, resulting in rankings that no one will ever see. The process of keyword research involves several phases:
- Brainstorming- Thinking of what your customers/potential visitors would be likely to type in to search engines in an attempt to find the information/services your site offers (including alternate spellings, wordings, synonyms, etc).
- Surveying Customers - Surveying past or potential customers is a great way to expand your keyword list to include as many terms and phrases as possible. It can also give you a good idea of what's likely to be the biggest traffic drivers and produce the highest conversion rates.
- Applying Data from KW Research Tools - Several tools online (including Wordtracker & Overture - both described below) offer information about the number of times users perform specific searches. Using these tools can offer concrete data about trends in keyword selection.
- Term Selection - The next step is to create a matrix or chart that analyzes the terms you believe are valuable and compares traffic, relevancy, and the likelihood of conversions for each. This will allow you to make the best informed decisions about which terms to target. SEOmoz's KW Difficulty Tool can also aid in choosing terms that will be achievable for the site.
- Performance Testing and Analytics - After keyword selection and implementation of targeting, analytics programs (like Indextools and ClickTracks) that measure web traffic, activity, and conversions can be used to further refine keyword selection.
Currently, the two most popular sources of keyword data are Wordtracker, whose statistics come primarily from use of the meta-search engine Dogpile (which has ~1% of the share of searches performed online) and Overture (recently re-branded as Yahoo! Search Marketing), which offers data collected from searches performed on Yahoo!'s engine (with a 22-28% share). While neither's data is flawless or entirely accurate, both provide good methods for measuring comparative numbers. For example, while Overture and Wordtracker may disagree on numbers and say that "red bicycles" gets 240 vs. 380 searches per day (across all engines), both will generally indicate that this is a more popular term than "scarlet bicycles", "maroon bicycles", or even "blue bicycles."
In Wordtracker, which provides more detail but has a considerably smaller share of data, terms and phrases are separated by capitalization, plurality, and word ordering. In the Overture tool, multiple search phrases are combined. For example, Wordtracker would independently show numbers for "car loans", "Car Loans", "car loan", and "cars Loan", whereas Overture would give a single number that encompasses all of these. The granularity of data can be more useful for analyzing searches that may result in unique results pages (plurals often do and different word orders almost always do), but capitalization is of less consequence as the search engines don't deliver different results based on capitalization.
Remember that Wordtracker and Overture are both useful tools for relative keyword data, but can be highly inaccurate when compared to the actual number of searches performed. In other words, use the tools to select which terms to target, but don't rely on them for predicting the amount of traffic you can achieve. If your goal is estimating traffic numbers, use programs like [Google's https://adwords.google.com/ Adwords] and Yahoo! Search Marketing to test the number of impressions a particular term/phrase gets.
Targeting the Right Terms
Targeting the best possible terms is of critical importance. This encompasses more than merely measuring traffic levels and choosing the highest trafficked terms. An intelligent process for keyword selection will measure each of the following:
- Conversion Rate - the percent of users searching with the term/phrase that converts (click an ad, buy a product, complete a transaction, etc.)
- Predicted Traffic - An estimate of how many users will be searching for the given term/phrase each month
- Value per Customer - An average amount of revenue earned per customer using the term or phrase to search - comparing big-ticket search terms vs. smaller ones.
- Keyword Competition - A rough measurement of the competitive environment and the level of difficulty for the given term/phrase. This is typically measured by metrics that include the number of competitors, the strength of those competitors' links, and the financial motivation to be in the sector. SEOmoz's Keyword Difficulty Tool can assist in this process.
Once you've analyzed each of these elements, you can make effective decisions about the terms and phrases to target. When starting a new site, it's highly recommended to target only one or possibly two unique phrases on a single page. Although it is possible to optimize for more phrases and terms, it's generally best to keep separate terms on separate pages, as you can provide individualized information for each in this manner. As websites grow and mature, gaining links and legitimacy with the engines, targeting multiple terms per page becomes more feasible.
The Long Tail of Search
The "long tail" is a concept pioneered by Chris Anderson (the editor-in-chief of Wired magazine, who runs the Long Tail blog). From Chris's description:
The theory of the Long Tail is that our culture and economy is increasingly shifting away from a focus on a relatively small number of "hits" (mainstream products and markets) at the head of the demand curve and toward a huge number of niches in the tail. As the costs of production and distribution fall, especially online, there is now less need to lump products and consumers into one-size-fits-all containers. In an era without the constraints of physical shelf space and other bottlenecks of distribution, narrowly-targeted goods and services can be as economically attractive as mainstream fare.
This concept relates exceptionally well to keyword search terms in the major engines. Although the largest traffic numbers are typically for broad terms at the "head" of the keyword curve, great value lies in the thousands of unique, rarely used, niche terms in the "tail." These terms can provide higher conversion rates and more interested and valuable visitors to a site, as these specific terms can relate to exactly the topics, products, and services your site provides.
||# of Searches per Month
|armani men's suit
|italian men's suit
|Jones New York Men's Suit
|Men's 39S Suit
|Gucci Men's Suit
|Versace Men's Suit
|Hugo Boss Men's Suit
|Men's Custom Made Suit
|*Source - Overture Keyword Selection Tool (Sept. '05 data)
In the scenario in the table above, the traffic for the term "men's suit" may be far greater, but the value of more specific terms is greater. A searcher for "Hugo Boss Men's Suit" is more likely to make a purchase decision than one searching for simply a "men's suit." There are also thousands of other terms, garnering far fewer monthly searches, that, when taken together, have a value greater than the terms garnering the most searches. Thus, targeting many dozens or hundreds of smaller terms individually can be both easier (on a competitive level) and more profitable.
Sample Keyword Research Chart
The following chart diagrams how many professional SEO firms do keyword research. (OV=Overture; WT=Wordtracker):
||Top OV Bid
||OV Mthly Pred. Traf.
||WT Mthly Pred. Traf.
|San Diego Zoo
|Starsky and Hutch
|Search Engine Marketing
|Interest Only Mortgage Loan
- KW Difficulty - The score from SEOmoz's tool
- Top OV Bid - The bid amount from the top listings in Yahoo!'s PPC results
- Overture Monthly Predicted Traffic - The amount of traffic estimated via Overture for the previous month's data
- Wordtracker Monthly Predicted Traffic - The amount of traffic estimated via Wordtracker (note that you must add up all terms in their database that match and multiply by the number of days in the month - the "exact/precise search" function can help make this easier)
- Relevance Score - The % of searchers using this term/phrase that you feel are likely to be interested in your site's products/services/offerings. Although this is a subjective number, you can use conversion rates or click-through rates from previous campaigns to more accurately estimate this in the future.
In selecting final terms, those with lower difficulty, higher relevance, and more traffic will offer the greatest value.
SEO and Galbijim
One thing that Galbijim has is lots of content, and yes, people do find it. But our articles are far from being written in ways to get noticed by search engines. This guide will act as a primer for how articles should aim to be written, in hopes to improve our SE rankings and in turn, our traffic.
Firstly, some old habits have to go.
1. Using Wikipedia to supplement some pages. Although only about 200-300 of our pages are borrowing wikipedia extensively, we have a lot of pages that I've noticed that might share a paragraph of borrowed content, even though the rest of the page was fresh content. That all has got to go. All borrowed pages must be re-worded and all pages that once had wikipedia content but maybe only a paragraph, must also remove that paragraph or re-word it. A lot of these pages are not ranking, due to Google bots recognizing the duplicate content. Take for example the Daegu page. I've put a lot of work into that, but it still is not ranking well (#38 on Google). That's partly because there is still a borrowed paragraph or two in there, which negates the keyword value in that content. The keyword 'Daegu' gets searched for 42 times a day, that's 42 targeted users who would benefit from our content. Or 289 new visitors a week. Or over 1000 visitors a month. Many might even save as a bookmark and come back again for other content. Or end up writing some. Or add our site to their links on their blog, which will further bolster our PageRank and improve search rankings. Daegu is just one example. We have lots of pages with borrowed content that are missing the boat.
2. Adding keyword rich content. Having heaps of content is not necessarily required to get high rankings. Having the right content is more ideal. We must know what keywords get searched often and optimize pages for that. Take a look at Gamja jorim. We're currently ranked #7 on Google for "Gamja Jorim". This keyword set is not a competitive one compared to 'Seoul', so that's likely we are ranking high for it, and shouldn't be too hard to move higher. Although keyword research has no results for it, that keyword set likely gets searched a few times a week. But we'll optimize anyways. I've added Gamja Jorim a few times to the page, as well as 'recipes', 'recipe', 'Korean side dish', 'food', 'making'. So we open ourselves up to improved ranking on other keyword sets, such as 'gamja jorim recipe', 'gamja jorim side dish', 'making gamja jorim', etc...You get the picture. Plus, I feel that it's important that we go after Korean food, hence why 'Korean' and 'food' should be in there. Daily searches for 'Korean food' and 'Korean recipes' get over 380 searches a day combined. That's the same amount as the total combined daily searches for 'Seoul', 'Busan', and 'Daegu'. And food bloggers love to link to recipe sites or new sites they find. So this is why we should emphasize SEO of our food articles, moreso than many other keyword sets we would think would be worth pursuing.
Here, I'll explain how to do keyword research, so you can assess which keywords are worth targeting when building articles.
- Firstly, type in the keywords you are wanting to research at Wordtracker. This will show you daily search volumes (if any) and suggested alternatives. I'd recommend using excel or at least copy pasting results into a word doc at this point, to organize your research. Don't just focus on the top keyword results, as they might be too competive to rank well in a short amount of time (more on assessing Keyword Competitiveness later). Keep searching all alternate keywords related to your subject, using whatever you can think of.
- What does this mean for Galbijim Wiki SEO guidance? Well, as mentioned mediawiki software takes care of our meta tags. And if we make sure that the article name that we choose to write is also our targeted keyword, then our title tag will be optimized, too. But as we have no ability to add page description in source code, the description defers to the first few sentences of the article. When I mean page description, take a look at a Google Search Results page (or SERP for short). You'll see that every result has a title, followed by descriptive text. Galbijim's descriptive text is generated from the first few sentences that we right. Therefore, it's extremely important that that first sentence sums up what the page is about and why a targeted user would want to click it. Users are going to be weighing our page description against other ones in the SERP. So this is where we need to stand out, to acquire that click.
Case Study (Korean food)
||Galbijim Rank (as of Dec.5/07)
|Korean food recipes
|north korean food
|Korean dessert recipes
|south korean food
|recipes for korean side dishes & desserts
|korean soup recipes
|south korean traditional foods
|south korean recipes
|korean food recipe
|korean traditional food
|traditional korean food
|traditional korean cuisine
Case Study (Teaching english in Korea)
||Galbijim Rank (as of Dec.5/07)
|jobs in south korea
|jobs in seoul south korea
|Teaching English in Korea
|jobs in korea
|teach english in korea
|teach english in south korea
|english jobs in south korea
|esl jobs in south korea
|english teaching jobs in korea
|teaching english in south korea
||298 searches/day (65 are target traffic)