Tag Archives: Google Analytics

Search Engine Optimization techniques

Devin Bost

2/23/2014

One may ask, “How do we measure the results of our search engine marketing/optimization?” Measuring data requires Google Analytics. In this article, we will assume that Google Analytics has already been configured. According to what data Google Analytics provides, the process for improving site metrics is as follows:

  1. First, we setup filters.  We use filters to isolate traffic in the following areas (in order of importance from highest to lowest):
    1. Organic search results;
    2. Paid search results (this only applies when using pay per click advertising with Google AdWords);
    3. Unique new visitors from non-search engine sources.
  2. Second, we set our metrics (external variables). We should setup different metrics for each advertising campaign. We should also setup different metrics for organic search traffic. There are several benchmarks (variables) I like to collect data for:
    1. Number of unique visitors, or unique visitor count;
    2. Unique page view count, partitioned by ;
    3. Hit count, partitioned by landing page URL (filtered to display only pages generating one or more unique visits);
    4. Hit count, partitioned first by keyword phrase (the search term used to land on a page); then, partitioned by landing page URL (the URL the search brought them to);
    5. Relative position of ranked pages on Google, weighted according to their position (with an exponential decay model I developed);
    6. Return visit count, partitioned by IP address;
    7. Bounce rates:
      1. Partitioned by keyword phrase, then landing page URL, then by number of internal links (aka layer count) clicked on;
      2. Partitioned by landing page URL, then keyword phrase;
    8. Visitor count, partitioned by backlink URL. These are visitors that landed on our site by following a link from someone else’s website, and according to (Brin & Page, 1998), backlinks have been important since the creation of Google’s search algorithm.
  3. Third, we set our internal variables. These are what we generate internally. This technique becomes invaluable once our external variables begin exhibiting acceleration; then, we may use mathematical techniques to gain insights into how our changes to page content (internal variables) affect our external variables. It is very important that changes to site content are tracked. It can become very hard to assess rankings when it is unclear which version of a particular page was responsible for obtaining a top ranking. For this reason, it is very important that revision control is tracked across the site. HTML tags must be analyzed and tracked. Here are descriptions of how these are used:
    1. Title tag: It defines the page title and it communicates what the page is about to the search engines. The target keyword must be included in this tag. It is displayed to Google search users, so it is important that we apply some practical psychology here;
    2. Description meta tag: It provides a summary description of the web page and its contents. Also, this description appears (in most cases) in Google search results, just below the title; target keyword must be included in this tag;
    3. URLs: An optimized URL is one that is self-explanatory and self-documenting; target keyword must be included in this tag;
    4. Heading tags: These tags are used to emphasize important text and a hierarchical structure of keywords on the web page. Heading tags also inform the search engines how the page content is organized. The <h1> tag defines the most important keywords and <h6> defines the least important keywords;
    5. Keyword placement: This data will be more relevant when we start clustering keywords for strategic optimization on keyword stems. There are several techniques which may be used on this data, depending on how we implement clustering. We can use neural networks and natural language processing for this later on. Using language processing techniques is very easy when content is stored in a database that offers out-of-the-box text processing features;
    6. Content keyword density: According to (Parikh & Deshmukh, 2013), search algorithms place great emphasis on keyword density. It is important that targeted keywords have greater density in the content involved;
    7. Use of robots.txt: The robots.txt file gives directions to search engines regarding which pages or directories should be crawled. Having this file configured correctly will make sure all optimized pages will get indexed;
    8. Images: Using the image alt attribute to provide an accurate description of the image being used; target keyword should be used in the description, if possible. The alt attribute from the <img> tag specifies the alternate text of what the image contains if the image is displayed incorrectly or doesn’t load. It is also used by content readers for people with disabilities;
    9. Use of the “rel=nofollow” attribute: In a HTML anchor tag <a>, the rel attribute defines the relationship between the current page and the page being linked to by the anchor. The nofollow value signals web spiders not to follow the link. In other words, it tells Google that your site is not passing its reputation to the page or pages linked to;
    10. Sitemaps: Keeping the sitemap updated is key for good site rankings. Search engines depend upon sitemaps to tell them what the current web pages are for the website;
    11. Time interval. This is the frequency by which we take measurements. Monthly is fine initially. Once we have enough data to observe our rates of change, we can change our interval to weekly;
  4. We will track internal links and external links once we have traffic that doesn’t bounce. We will discuss this more later. External linking is considered off-site SEO. Important factors, although rather difficult to track are:
    1. Keyword in the backlink: Google’s ranking algorithm places high value on the text that appears within the link. The text within the link gets associated with the page and describes the page it links to. For this reason, it’s important to have the target keyword within the text of the backlink;
    2. Gradual link-building: It’s important to build backlinks in a gradual manner. The link-building process should be natural and steady. It is for this reason that SEO takes a lot of work and patience to implement Furthermore, it’s an intentional part of Google’s strategy for gradual reputation building that it not be quick or overnight. In fact, if a site were to acquire dozens or hundreds of backlinks overnight, Google would almost certainly consider this a red flag (spam) that most likely will get your site penalized. But if the site content is compelling, people can find it through search (or through other means) and link to it. If this occurs, the site owner has no control of the amount of backlinks that the site will generate, and certainly Google can detect that these backlinks weren’t intentional.
    3. Writing articles to establish domain authority: Writing articles and getting them published on other reputable sites, is a strategy that can help your site get backlinks. Getting an article published on trusted sites such as About.com, Wikipedia.org or NewYorkTimes.com and getting a backlink in return, will help increase your website’s reputation and achieve higher rankings;
    4. Personal networking to establish a reputation: It is recommended that we make efforts to reach out to those in the site’s community, particularly sites, “that cover topic areas similar to [ours]. Opening up communication with these sites is usually beneficial.” (www.google.com/webmasters/docs/search-engine-optimization-starter-guide.pdf) Contacting sites that are related to what your site is about is a great way to network, promote and increase your site’s exposure;
    5. Finding your website’s natural affinity group: Find websites that are related or cover similar topics as yours for potential networking opportunities. Getting backlinks off-topic sites do not count as much as links from sites that have related content to yours.

References

Brin, S., & Page, L. (1998). The anatomy of a large-scale hypertextual Web search engine. Computer networks and ISDN systems, 30(1), 107-117.

Parikh, A., & Deshmukh, S. (2013, November). Search Engine Optimization. International Journal of Engineering Research and Technology, 2(11), 3146-3153.

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