According to Google, 15% of search queries are new, and users generate them every day. This statistic is based on low-frequency queries. Because of the refinement or more complex formulation of the intent, users create new search queries. And they affect the ranking algorithms.
Part of the reason so many low-frequency queries are appearing is due to the popularity of voice search. Accessories, voice assistants, and products like Google Home have driven the need for natural language search.
Search engines have begun to better understand the context of phrases, slang, and adjust to the “conversational” style of queries. Colloquial speech is evolving dynamically, so the algorithms of the systems are constantly being refined to correctly recognize queries in voice search.
Its popularization also works in the opposite direction: the constant generation by users of variations of the same query or phrase causes search engines to mistake them for the same ones. This happens to compensate for the increasing number of queries in the search.
In addition to voice inquiries, people often use questions. And they can ask the same one in different ways (using introductory words, clarifying details). And search algorithms learn to understand these LT.
In doing so, the systems may take variations of the same query as the same. How do you figure out when this happens and why?
Do an N-gram analysis. An N-gram is a particular sequence of n elements. In the context of keywords:
- the query “music” is a 1-gram;
- the query “what music can be used in a tiktok” is a 6-gram (a sequence of 6 words).
Representing a query with an N-gram allows you to understand its naturalness, as well as the weight of each element n within the phrase.
Let’s say you want to optimize content for low-frequency queries within the subject “exercise bicycles. The query “which inexpensive exercise bicycle is better to buy” is better to break down by n-gram. And do an incomplete n-gram analysis – manually change each individual word in the phrase and see how and how much the search results change.
In some cases, you can use paid and free tools for n-gram analysis in SEO. For example:
- NGram Analyzer.
Specifically in the case of exercise bikes, replacing the words “inexpensive” with “budget”, “exercise bike” with “exercise bike” and even “buy” with “choose” will not play a significant role.
In any case, when analyzing the results, it should be taken into account that the basis of the subject of the query depends on the word “exercise bike”, as it fully characterizes the content.
Presenting queries with N-grams is not a panacea, nor is adjusting for voice search. But they do show that the long-tail is relevant to the search. Statistics and the behavior of search engines are already giving a signal to SEO-specialists – the use of low-frequency queries in promotion is worth considering as a method with great potential.
Efficiency and benefits of long-tail SEO
In addition to adaptability to voice search, promotion by long-tail keywords implies at least three distinct advantages.
Most sites are promoted by high-frequency queries. In Ukraine, the query “buy ayfon 12” on Google shows 21.5 thousand results, and the query “ayfon 12 128 gb buy” – up to 100. A small number of competitors in the search results may allow easier and faster access to the top, but this does not mean that there will be no competition at all.
Despite the low frequency, consumer demand may be at the average and high level. Therefore, when promoting low-frequency keywords, check the changes in the output and the level of competition.
High conversion rate
his feature can be viewed from the angle of the sales funnel.
- Awareness. At this stage, the user learns about a particular product and the possibility of buying it.
- Interest. The user develops interest in the product and the need to buy it.
- Desire. The need is formed, and user wants to buy the product.
- Action. The person buys the product, satisfying the need.
For example, with the query “buy a toothbrush” the user is not yet at the stage of full awareness of his need, he does not know the types of toothbrushes and has not selected a specific model. But with the query “buy electric toothbrush oral bi” the first two stages of the funnel are passed, the person knows exactly what he wants, and is a few steps away from the purchase.
The specifics of low-frequency requests is that they are more targeted: the user can be more specific in formulating their needs, and therefore more attuned to the target action.
There are additional advantages of promoting exactly by LT.
Promotion by general keywords of a specific topic
For the disclosure of this feature, promotion by complementary long-tail queries is most suitable, as it implies the presence of the main thematic high-frequency queries. Search engines understand the subject of the query and can identify similar keywords that relate to the same intent. Therefore, the result of the output by LT may include some results and for the main key.
But there is a reverse process, which should be considered: with proper optimization low-frequency queries can raise the position of the site for the main high-frequency queries.
All three advantages of long-tail promotion can be represented through the principle of competitiveness:
- Top positions for high-frequency queries are not always attainable, especially in highly competitive niches with large budgets for promotion.
- These difficulties encourage SEO-specialists to abandon the simple, trivial and ill-considered strategy of direct competition with sites in the top and pay attention to not quite attractive at first glance long-tail queries.
- By choosing a more “subtle” promotion strategy in a highly competitive niche using low-frequency keywords, you can achieve more targeted traffic and, as a consequence, more targeted actions.