Let’s Try to Find All 200 Parameters in Google Algorithm

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Ann Smarty
Ann Smarty
Let’s Try to Find All 200 Parameters in Google Algorithm

I am sure Googlers should be enjoying this: hardly can they say a word, there follows a wealth of guessed and speculations. This time Matt Cutts is said to have mentioned that their 200 variables in Google algorithm and already plenty of people started looking for them.

Anyway, I stumbled across this forum thread and made up my mind to share this discussion at SEJ by providing my own list of variables (the SEO perspective, please note that, like one of my best friends pointed out, this post is not intended as the list of search algorithm variables but rather as the list of SEO parameters) and asking you to contribute.

Currently there are fewer than 120 130 variables in the list, try to make it 200 🙂


I’ve published the copy here (We think we will set up a poll to vote for the variables in empty columns):

200 Parameters in Google Algorithm

Parameters we are almost sure (with different level of confidence) to be included in the algorithm (for your convenience I linked some of them to our previous discussions on the topic):

Domain: 13 factors

  1. Domain age;
  2. Length of domain registration;
  3. Domain registration information hidden/anonymous;
  4. Site top level domain (geographical focus, e.g. com versus;
  5. Site top level domain (e.g. .com versus .info);
  6. Sub domain or root domain?
  7. Domain past records (how often it changed IP);
  8. Domain past owners (how often the owner was changed)
  9. Keywords in the domain;
  10. Domain IP;
  11. Domain IP neighbors;
  12. Domain external mentions (non-linked)
  13. Geo-targeting settings in Google Webmaster Tools

Server-side: 2 factors

  1. Server geographical location;
  2. Server reliability / uptime

Architecture: 8 factors

  1. URL structure;
  2. HTML structure;
  3. Semantic structure;
  4. Use of external CSS / JS files;
  5. Website structure accessibility (use of inaccessible navigation, JavaScript, etc);
  6. Use of canonical URLs;
  7. “Correct” HTML code (?);
  8. Cookies usage;

Content: 14  factors

  1. Content language
  2. Content uniqueness;
  3. Amount of content (text versus HTML);
  4. Unlinked content density (links versus text);
  5. Pure text content ratio (without links, images, code, etc)
  6. Content topicality / timeliness (for seasonal searches for example);
  7. Semantic information (phrase-based indexing and co-occurring phrase indicators)
  8. Content flag for general category (transactional, informational, navigational)
  9. Content / market niche
  10. Flagged keywords usage (gambling, dating vocabulary)
  11. Text in images (?)
  12. Malicious content (possibly added by hackers);
  13. Rampant mis-spelling of words, bad grammar, and 10,000 word screeds without punctuation;
  14. Use of absolutely unique /new phrases.

Internal Cross Linking: 5 factors

  1. # of internal links to page;
  2. # of internal links to page with identical / targeted anchor text;
  3. # of internal links to page from content (instead of navigation bar, breadcrumbs, etc);
  4. # of links using “nofollow” attribute; (?)
  5. Internal link density,

Website factors: 7 factors

  1. Website Robots.txt file content
  2. Overall site update frequency;
  3. Overall site size (number of pages);
  4. Age of the site since it was first discovered by Google
  5. XML Sitemap;
  6. On-page trust flags (Contact info ( for local search even more important), Privacy policy, TOS, and similar);
  7. Website type (e.g. blog instead of informational sites in top 10)

Page-specific factors: 9 factors

  1. Page meta Robots tags;
  2. Page age;
  3. Page freshness (Frequency of edits and
    % of page effected (changed) by page edits);
  4. Content duplication with other pages of the site (internal duplicate content);
  5. Page content reading level; (?)
  6. Page load time (many factors in here);
  7. Page type (About-us page versus main content page);
  8. Page internal popularity (how many internal links it has);
  9. Page external popularity (how many external links it has relevant to other pages of this site);

Keywords usage and keyword prominence: 13 factors

  1. Keywords in the title of a page;
  2. Keywords in the beginning of page title;
  3. Keywords in Alt tags;
  4. Keywords in anchor text of internal links (internal anchor text);
  5. Keywords in anchor text of outbound links (?);
  6. Keywords in bold and italic text (?);
  7. Keywords in the beginning of the body text;
  8. Keywords in body text;
  9. Keyword synonyms relating to theme of page/site;
  10. Keywords in filenames;
  11. Keywords in URL;
  12. No “Randomness on purpose” (placing “keyword” in the domain, “keyword” in the filename, “keyword” starting the first word of the title, “keyword” in the first word of the first line of the description and keyword tag…)
  13. The use (abuse) of keywords utilized in HTML comment tags

Outbound links: 8 factors

  1. Number of outbound links (per domain);
  2. Number of outbound links (per page);
  3. Quality of pages the site links in;
  4. Links to bad neighborhoods;
  5. Relevancy of outbound links;
  6. Links to 404 and other error pages.
  7. Links to SEO agencies from clients site
  8. Hot-linked images

Backlink profile: 21 factors

  1. Relevancy of sites linking in;
  2. Relevancy of pages linking in;
  3. Quality of sites linking in;
  4. Quality of web page linking in;
  5. Backlinks within network of sites;
  6. Co-citations (which sites have similar backlink sources);
  7. Link profile diversity:
    1. Anchor text diversity;
    2. Different IP addresses of linking sites,
    3. Geographical diversity,
    4. Different TLDs,
    5. Topical diversity,
    6. Different types of linking sites (logs, directories, etc);
    7. Diversity of link placements
  8. Authority Link (CNN, BBC, etc) Per Inbound Link
  9. Backlinks from bad neighborhoods (absence / presence of backlinks from flagged sites)
  10. Reciprocal links ratio (relevant to the overall backlink profile);
  11. Social media links ratio (links from social media sites versus overall backlink profile);
  12. Backlinks trends and patterns (like sudden spikes or drops of backlink number)
  13. Citations in Wikipedia and Dmoz;
  14. Backlink profile historical records (ever caught for link buying/selling, etc);
  15. Backlinks from social bookmarking sites.

Each Separate Backlink: 6 factors

  1. Authority of TLD (.com versus .gov)
  2. Authority of a domain linking in
  3. Authority of a page linking in
  4. Location of a link (footer, navigation, body text)
  5. Anchor text of a link (and Alt tag of images linking)
  6. Title attribute of a link (?)

Visitor Profile and Behavior: 6 factors

  1. Number of visits;
  2. Visitors’ demographics;
  3. Bounce rate;
  4. Visitors’ browsing habits (which other sites they tend to visit)
  5. Visiting trends and patterns (like sudden spiked in incoming traffic)
  6. How often the listing is clicked within the SERPs (relevant to other listings)

Penalties, Filters and Manipulation: 12 factors

  1. Keyword over usage / Keyword stuffing;
  2. Link buying flag
  3. Link selling flag;
  4. Spamming records (comment, forums, other link spam);
  5. Cloaking;
  6. Hidden Text;
  7. Duplicate Content (external duplication)
  8. History of past penalties for this domain
  9. History of past penalties for this owner
  10. History of past penalties for other properties of this owner (?)
  11. Past hackers’ attacks records
  12. 301 flags: double re-directs/re-direct loops, or re-directs ending in 404 error

More Factors (6):

  1. Domain registration with Google Webmaster Tools;
  2. Domain presence in Google News;
  3. Domain presence in Google Blog Search;
  4. Use of the domain in Google AdWords;
  5. Use of the domain in Google Analytics;
  6. Business name / brand name external mentions.


Featured Image: lucidwaters via Depositphotos

Ann Smarty

Ann Smarty

Brand amd Community Manager at Internet Marketing Ninjas

Ann Smarty is the blogger and community manager at Internet Marketing Ninjas. Ann's expertise in blogging and tools serve as ... [Read full bio]