Longer and more complex questions featuring long-tail keywords are more frequently used. This is as a result of these questions being asked using natural language. This reveals a more focused search intent from customers, with a clear idea of what they want and what they are searching for.Search engines have even evolved to be able to actually answer these longer, more natural language questions too. This new phenomenon allows the customer to ask these natural questions. They can then get the desired response as a result of developments in AI (artificial intelligence) technology.
Google’s BERT and the Natural Language of Customers
Google’s BERT (Bidirectional Encoder Representations from Transformers) has also developed this technique for natural language processing. This means that BERT prioritises natural language over keywords. It can also decipher the context of words in search queries too.This means that using natural language when conveying information to your customers is the best way to create conversions. This allows your customers to find the information you provide them naturally via search engine queries.
Long-Tail Keywords are Less Competitive
However, long-tail keywords are also less competitive to rank for. This means that they give rise to businesses that use them more frequently. The longer, and more specific, the term, the easier it is to rank for these keywords in search engines.
Schema Markup and Microdata for Customers
In order to rise above other SEO competitors, schema markup must be used.
What is schema markup?
Schema markup is a specification that helps data to be embedded inside HTML documents. It is basically data that is readable for computers. Searches are often in the form of questions, either using a typed keyword or a voice search. Consequently, relevant content should be created with natural language in mind for these searches to be found.This creates a better browsing experience for customers as it aids the production of relevant results in the form of snippets.
