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If you are a writer or researcher in the organic optimization field, contact us to see if you quality for courtesy Dataline Credits (for non-commercial use only).

Overview
Major search engines gather between 100 and 150 web page metrics for each page in their index. These metrics fall into three primary categories or attributes:

  • On-page factors similar to keyword density
  • Backlink, or in-link, reputation and quality
  • PageRank, or a measure of page interconnectivity

Their proprietary algorithms blend these attributes in an attempt to rank website pages in order of keyword relevancy.

SE ANALYST is a comprehensive data-mining and benchmarking tool specifically designed to measure primary search engine optimization attributes of top-ranked web pages and user-defined or custom URLs. The tool gathers more than 30 metrics in the three primary attributes, then blends these metrics to calculate page value relative to a keyword.

The resultant data is vital in the development of a winning keyword strategy.

SE ANALYST employs a robust user interface with a wide range of input variables that control the data-mining and compiling process. Each row of data, or ‘Dataline’, is representative of one ranked or custom URL. User-defined weights are applied to each metric value. Weighted data is then added up to develop weighted averages for each of the three primary attributes. A user-definable non-linear algorithm is then applied to each of the weighted averages to produce a score value. Finally, these score values are combined to produce a grand score for each URL or Dataline, which represents the SEO strength of each page.
Dataline values are grouped in order to minimize the influence of outliers. These metrics quantify the SEO intensity of the group (e.g. 1-5 ranked websites; 6-10; 11-15; etc.).


Grouped scores provide a mechanism to evaluate the relative strength of each SEO attribute. When measured relative to a target website page (custom URL), it is possible to compare SEO attributes with those representing the top groups. The comparison reveals what combination of SEO attributes may be necessary to compete with those currently representing the group.
Input Variables
Users have considerable control over the data-mining process and the way data is compiled. Three distinctive areas are notable.

Input Variables

Users have considerable control over the data-mining process and the way data is compiled. Three distinctive areas are notable.

First, keywords may be entered with variations in order to accommodate plural and synonym terms. For example, consider the keyword “dog food”. The logical keyword has two physical terms: “dog” and “food”. Each term may have root, plural/singular or synonym versions that search engines may consider as equal.

SE ANALYST employs a simple keyword syntax that permits the gathering of top-ranked websites based on the actual search keyword, but performs SEO attribute analysis on a combination of root and variations. For example, “dog food” may be entered as:

dog (dogs, dog’s, canine, canine:, k9) food (nutrition, bones & biscuits, milk-bones)

Each term within the parenthesis becomes a logical OR condition. Therefore, when searching for SEO attributes, matches such as:

  • Dog biscuits
  • Dogs nutrition
  • Canine bones
  • Etc.

Are all considered equal matches.

SE ANALYST calculates keyword density based on three match types: phrase, broad, and part. Phrase match is similar to exact or precise except that all terms are considered lower case.

A broad match condition is satisfied when the keyword terms are found within a user-definable number of characters. For example, the keyword “dog food” has a broad match within 30 characters.



Dog lovers feed their dogs good food

Likewise, part matches count physical term matches. In the above example, “dog” is found once and “food” is found once. Each occurrence counts as a part match.

SE ANALYST allows users to define up to five backlink filters. Each filter is applied to a statistical sampling of backlinks supplied by one of two search engines. And each filter may be customized to attain unique backlink characteristics.

  • Minimum PageRank
  • Unique IP (none, IP, or Class C IP)
  • Max links on page (min: 10; max: 200)
  • Keyword Found
  • Body (x-anchor)
  • Head
  • Anchor
  • Other
  • Exclude Reciprocals (future)

Each of the filter criteria are logical AND conditions with the exception of the ‘Keyword Found’ fields, which are logical OR conditions.



Each filter produces three metrics:

  • External Backlinks (internal links excluded)
  • Calculated PageRank (internal links included for interior page rankings)
  • PageRank Kurtosis

Both Backlinks and PageRank values are computed and prorated based on the number of samples and search engine total reported number of external Backlinks.

Kurtosis is used to identify abnormal PR distributions among the sample set which could be symptomatic of an outlier condition.

Detail Data Report
The Detail Data Report covers raw data as well as compiled data in accordance with the job setup profile. Users define how many ranked positions (rank depth) SE ANALYST is to retrieve from a specific search engine. Additionally, users may add custom URLs that may not otherwise be found within a defined rank depth. Each row, or Dataline, represents a single dataset for either a top-ranked web page or custom URL.

User-definable weights are applied to each metric value. These weighted metrics are combined to create total weighted values for the three basic SEO attributes.

A non-linear algorithm is applied to each of the total weighted values to produce a score. These score values are expressions of the SEO strength of each of the three basic SEO attributes. When added together, they create a Grand Score value. This value is an expression of the total SEO strength for a specific URL relative to a specific keyword.

Although a rank position and correlation coefficient may be calculated from each Dataline Grand Score, and 0.40 to 0.65+ correlation coefficients are common, the data is subject to variations in the backlink sampling process and outliers. For this reason, Datalines are grouped in the Summary Data Report.

Summary Data
Summary Data is where Datalines are grouped into distinctive ranges to reduce the impact of outliers and sampling errors.
A common range is every five (5) ranked positions. In this case, medians and averages are computed for the first five ranked websites. In the same manner, averages and medians are computed for data from the second group of five ranked websites (6-10). The grouping may continue for as many ranked positions that the user has requested. However, a ranking depth of 20 seems to be a reasonable lower limit, as data beyond the 20th rank position appears to become more “noisy.”

Summary data metrics are more robust and more accurately represent the SEO strength of websites ranking in a specific group.

Keyword Strategy
The reason for benchmarking a competitive website page is to develop a winning keyword strategy. Although the mapping of a strategy may take several forms and formats, the basic principle of matching keywords to specific pages is fundamental.

SE ANALYST extends this principle by permitting the incorporation of competitive SEO attributes. Then, current conditions for a custom URL may be compared with competition. SEO attribute goals may be set to establish winning criteria for tactical implementation.



A Keyword Strategy involves mapping each keyword to a specific website page.


Sample Reports & Product Specifications
Actual report samples and test jobs are available at the guest login at www.seanalyst.com. Specifications and Reference Guide is available at http://www.seanalyst.com/help/index.htm.

SE ANALYST Pricing

Number of Datalines (per job)

Incremental Price

1-100

$1.75

101-1000

$1.40 (20%)

Greater than 1001

$1.05 (40%)

Pricing subject to change without notice.

Example: If a SE ANALYST job contained 350 Datalines, the first 100 Datalines would be priced at $1.75 each and the remaining 250 Datalines would be priced at $1.40 each. The total job would have a cost of $525.00.


Advanced Dataline credits are available for purchase at the following prices (six-month expiration).

Number of Datalines (Advanced Credits)

Price

100 Dataline credits

$140.00 (20% discount)

1000 Dataline credits

$1050.00 (40% discount)

Advanced Datalines credits may be applied to any SE ANALYST job regardless of the number of total Datalines.


Total Datalines = number of keywords x (rank depth + number of custom URLs).  Example: 10 keywords; 20 deep, 2 custom URLs = 10 x (20+2) = 220.





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