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How to Get Googlebot to “Teach You” Advanced SEO

I recently worked on an enterprise-level client’s non-SEO related project where the goal was to confirm or deny that their new product:

1)  Was not doing anything that could be considered black hat.

2)  Was providing any SEO benefit for their clients.

The problems you face with projects like this is that Google doesn’t provide enough information, and you cannot post corner-case questions like this in public Webmaster forums. To do so would violate your NDA, and potentially reveal your client’s intellectual property. So, what option do you have left? Well, you set up a honeypot!

A honeypot is a term that comes from the information security industry. Honeypots are a set of files that, to an automated program, appear like regular files, but they allow for the monitoring and “capturing” of specific viruses, e-mail harvesters, etc. In our case, we set up a honeypot with the purpose of detecting and tracking search engine bot behavior in specific circumstances. We also wanted to track the outcome (positive, neutral or negative) in the search engine results pages (SERPs).

Let me walk you trough a few ways you can learn advanced SEO by using a honeypot. Read more

Log based link analysis for improved PageRank

While top website analytics packages offer pretty much anything you might needto find actionable data to improve your site, there are situations where we need to dig deeper to identify vital information.

One of such situations came to light in a post by randfish of Seomoz.org.He writes about the problem with most enterprise-size websites, they have many pages with no or very few incoming links and fewer pages that get a lot of incoming links.He later discusses some approaches to alleviate the problem, suggesting primary linking to link-poor pages from link-rich ones manually, or restructuring the website.I commented that this is a practical situation where one would want to use automation.

Log files are a goldmine of information about your website: links, clicks, search terms, errors, etcIn this case, they can be of great use to identify the pages that are getting a lot of links and the ones that are getting very few.We can later use this information to link from the rich to the poor by manual or automated means.

Here is a brief explanation on how this can be done.

Here is an actual log entry to my site tripscan.com in the extended log format: 64.246.161.30 – – [29/May/2007:13:12:26 -0400] “GET /favicon.ico HTTP/1.1″ 206 1406 “http://www.whois.sc/tripscan.com” “SurveyBot/2.3 (Whois Source)” “-”

First we need to parse the entries with a regex to extract the internal pages — between GET and HTTP — and the page that is linking after the server status code and the page size.In this case, after 206 and 1406.

We then create two maps: one for the internal pages — page and page id, and another for the external incoming links page and page id as well.After that we can create a matrix where we identify the linking relationships between the pages. For example: matrix[23][15] = 1, means there is a link from external page id 15 to internal page id 23.This matrix is commonly known in information retrieval as the adjacency matrix or hyper link matrix.We want an implementation that can be preferably operated from disk in order to be able to scale to millions of link relationships.

Later we can walk the matrix and create reports identifying the link-rich pages, the pages with many link relationships, and the link-poor pages with few link relationships. We can define the threshold at some point (i.e. pages with more or less than 10 incoming links.)