Over-optimization (search spam) is the excessive use of keywords on pages in an attempt to try and rank better for these keywords vs just placing the keywords naturally in the text and answering the user’s question. Keyword over-optimization mainly consists of (but is not limited to) keyword stuffing titles, body content, heading tags, meta tags, and excessive use of strong/bold.
Search engines started to penalize over-optimization after SEO’s fragrantly abused this tactic and were consistently over-using keywords in an attempt to manipulate their weighting for an artificial increase in page relevance which then resulted in increased search rankings.
Search engines tend to take a localized approach to penalizing pages with over-optimized text and will just reduce the rankings of particular pages that are over-optimized vs the entire site. However, consistent and fragrant abuses of this tactic on a site-wide basis can result in drastically decreased rankings site-wide.
Labrika’s report shows all types of over-optimization. This helps you find all the potentially “bad” pages that are liable to be penalized for over-optimization. Not all pages found with issues will be over-optimized but you should check any pages listed with infractions to be sure. Context is very important here.
Please note: correcting over-optimization will not necessarily always result directly in an increase in rankings. You will need to make sure that in addition to not over-optimizing your text, that your page is truly useful to the user and will help them satisfy their search intent.
Types of over-optimization found by Labrika:
Stuffing of single keywords in the content (excessive use of single keyword vs competitors ranking content).
Stuffing of bigrams (two-word phrases) and trigrams (three-word phrases) in the content.
Keyword used multiple times in one sentence (normally unnatural).
High density of keywords in META-tags.
High density of keywords in headings.
Duplicate H2, H3, H4 heading tag content.
Excessive use of headings.
<a>tags in headings.
Overuse of bold type.
Keyword stuffing in the content
For analysis of keyword stuffing, Labrika uses an academic formula which measures the density/frequency of the word/phrase used in relation to the total volume of text.
The answer is displayed in a percentage and is calculated by the following formula:
[Number of the word repetitions in the text] / [total number of words in the text] * 100%.
Attention! Every keyword has its own “normal” density in natural written text. In some types of texts, the density of some keywords may be higher than usual (i.e. technical or legal literature). Likewise, on commercial websites, a high density of keywords (10% and higher) can be seen in price-lists and product catalogues. However, that does not mean that it would be acceptable for other types of pages.
Labrika’s report shows all the words with a high density. In order to ascertain whether high keyword density is expected for this word our algorithm will cross-examine other top10 sites ranking for these keywords and analyze their keyword density to find out the optimal density.
We only check competitors’ sites for keyword density for words added in the analysis manually. For other words, the warning is shown only if usual density is exceeded by our formula but without additionally checking competitors’ sites.
Context is critical here, if you are answering the users question without thinking about inserting the keyword, it is quite likely you will automatically use the keyword and other related words to answer the question in a completely natural way and thus, use the keyword the correct amount of times.
A word of caution; while a high percentage of keyword usage in relation to the total volume of text can result in an over-optimization penalty, too little keyword usage in relation to the total volume of text, can lead to your content being seen as irrelevant to the keyword by search engines.
When our report recommends reducing certain keyword density/frequency we would recommend introducing synonyms to replace any instances of keywords removed.
Stuffing of bigrams and trigrams in the content
Earlier, sanctions were imposed for high density of separate keywords, but after implementation of Baden-Baden Yandex filter, excessive use of bigrams (two-word phrases) and trigrams (three-word phrases) is also punished, especially, if these word combinations include typical modifiers. For example, “to buy”, “price”, or “best”.
Keyword used multiple times in one sentence
Repetitions of a word in one sentence complicates reading and the natural flow of the text. Labrika scans and highlights such hard-to-read fragments of text. Word repetition is more acceptable in legal and technical documents, and also seen prevalently in breadcrumbs. If the repetitions are not generally expected in your industries type of content, then they should be removed. For example, in the screenshot below, the words “power station” are repeated three times in just one sentence. To avoid needless repetitions, you only need to mention
“types of power stations” once and then state the different types of power stations.
High density of keywords in META-tags and headings
Labrika can also check and indicate a high density of words found in headings and META-tags. As these elements contain some of the most important information on a page, search engines give them greater SEO significance than the rest of the text published on the page. As such, over-optimization is especially undesirable here and should be avoided.
If over-optimization is already present in the main body content of the page, then its additional excessive usage in headings and META-tags increases substantially the chances of your site receiving an over-optimization penalty.
Duplicate H2, H3, H4 headings and excessive use of headings
Duplicate headings refer to repetitions of H2, H3, H4 heading tags on the same page. This can be considered as over-optimization and violates established standards for how to implement the different categorization of headings. It also interrupts the natural flow and readability of text for the user (which is not what you want). Content is made for users, so if users can’t understand your content properly then you are likely to have poor engagement metrics and also be penalized by search engines.
Formatting/link tags found in the headings
Labrika can search and find the following tags in the headlines:
<b> (bold ‒) – makes the inserted text bold.
<strong> (strong ‒) – used for highlighting an important fragment of the text which should be read by the user. It also shows the text in bold.
<i> (italic text) – used for italicizing a part of the text.
<u> - contains highlighted text.
<a> (anchor) – used for link creation.
Including tags in the headline text increases its weight significantly. Inclusion of words in (Н1, Н2) also increases their significance for search engines. So, the combination of these two is considered excessive and can be seen as over-optimization.
We would recommend keep heading tags free from formatting/link tags and just include useful headings providing an overview of the content found below its heading.
Overuse of bold type
Labrika shows the pages with a high percentage of bold text.
It is fine to highlight text like this but only in exceptional cases. For example, when you need to highlight and draw attention to an especially important bit of information or heading. However, too much bold text on the page is considered as an attempt to artificially influence the search results, as the bolding of keywords increases their significance when crawlers crawl your page.