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SEO SEO theory

What a web promoter learns from a Trojan site infection

I noted yesterday that the visits to a website of mine had multiplied 5 fold in a day. After feeling some satisfaction on the success of my promotion efforts, I noticed something unusual: the requested subjects had nothing to do with my main theme, but with foods and drinks. And when you visited one of those pages, you were redirected to a malware site.

I entered my sites by FTP and I found many offending pages that some bot had placed there. And when I say many, I mean about 5000 files in dozens of directories in several sites accross 3 servers… Many hours were needed to clean up.

Of course I had to clean my PC from malware, apparently coming from a mailing software that I had downloaded 2 weeks ago.

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Uncategorized

Results of the 3rd Positioning Experiment

Once completed the “Familia Raimundez” positioning experiment, results were available in just 10 days, what makes them very interesting and convenient compared to those times when one had to wait 45 days for an indexation cycle.
The results matched the previous ones, as some domains seem to be penalized in an arbitrary way. And I say in an arbitrary way because there is no obvious sign in the website for it to be penalized for: no black hat techniques, no links to questionable sites, no keyword abuse or obvious content duplication.

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Domains SEO SEO theory

Results of the Antolinez Family Experiment

In only 10 days I got results for the experiment that tried to detect Goog penalization. It turned out that 2 domains are penalized with a -20 fall.

The other result refers to the extent of indexation. It seems that penalized sites receive only superficial indexation. For instance, if a site is well indexed, all the word strings will be indexed, and searching for phrases within quotes will find them. If the site is badly indexed due to penalization, only individual words will be indexed, and the strings will not be detected. Interesting…

The other result is that penalization covers all subjects, even those unrelated to the main one. For instance, a domain penalized for duplicate content will be penalized for content that has nothing to do with the abused content.

However, I am not making a difference between penalization types, which probably exists. In the next test I will include one domain that was penalized for duplicates and other penalized for linking to bad neighbourhood. Let’s see if the penalizations are similar.

I am now working on a new experiment (3rd of my controlled series) using more domains, mixing penalized with healthy domains.  

On the other hand, I am analyzing the directories I use for submission with reciprocal link exchange. It seems that some of them are considered bad neighbours, maybe because they include black hat sites, or they sell links, or whatever. My analysis includes only existing factors, because I am not free to upload test pages to them.

There are a few factors that warn you against bad directories: bad ranking in Google while searching for their own Home Page Title or Description, as compared with Yahoo or MSN. Also, few indexed incoming links, and other parameters. We are trying to establish the most reliable of those parameters.

For all the Penalization Detection experiments we need to focus on keywords that have 10-200 results. Less, is not enough to detect a fall in rankings. More, are difficult to detect and count.

We plan to offer a Standard Penalization Detection service (exact value), and a Penalization Diagnosis which will try to find an explanation for the issue. In most cases we detect bad linking, code problems or duplicate contents that explained the problem and could be corrected.