What is semantic analysis? Definition and example

Using an artificial intelligence capable of understanding human emotions and the intent of a query may seem utopian. However, there is a technology that can lend a hand to AIs. In fact, this technology is designed toimprove exchanges between chatbots and humans. This is semantic analysis. It also allows you tooptimize your web content and SEO. Find out all you need to know about this indispensable marketing and SEO technique.

Semantic analysis: a pillar of success for all customer relations strategies

To understand the importance of semantic analysis in your customer relationships, you first need to know what it is and how it works.

Definition of semantic analysis

The semantic analysis follows from the language science. This marketing tool aims to determine the meaning of a text by going through the emotions that led to the formulation of the message. Like lexical analysis, it enables us toanalyze all forms of writing from an entity's consumers or potential customers.

So what's the difference between semantic and syntactic analysis? The former focuses on the emotions of the content's author, while the latter is concerned with grammatical structure. Thus, syntax is concerned with the relationship between the words that form a sentence in the content. Semantics, on the other hand, concerns the meaning of these words.

What's more, you need to know that semantic and syntactic analysis are inseparable in the Automatic Natural Language Processing or NLP. CRM is a fundamental discipline in customer relationship management. In fact, it's an approach aimed at improving better understanding of natural language.

Semantic analysis takes into account all the subjective elements of messages in order to understand your customers' intentions. Detecting certain points, such as position-taking or impatience, enables a better response to customers. But how does this technique actually work?

How semantic analysis works

Humans have no trouble understanding the meaning of a sentence. To do so, all we have to do is refer to punctuation marks and the intonation of the speaker used as he utters each word. For machines, on the other hand, the task is more difficult. That's where semantic analysis comes in.

At present, the semantic analysis tools Machine Learning algorithms are the most effective, as well as Natural Language Processing technologies. To help you better understand this marketing tool, here's some background.

Imagine a retailer receives a notice from a customer on its website and web pages. The message reads: "Contrary to my instructions, I got blue meat. The service is a big joke! Next time, I'll be on my way." You can see straight away that customer in question is dissatisfied. And this, even if he hasn't explicitly expressed his dissatisfaction. The machines, on the other hand, have to go through a semantic analysis to understand that here the customer is using the word "joke" in a negative context, even though this term generally has a positive connotation. Without this in-depth analysis of the semantic and lexical fields, dissatisfaction remains undetectable to artificial intelligence.

After analyzing the messages, the chatbot will classify all exchanges with customers by theme, intention or risk. In this way, the customer's message will appear under "Dissatisfaction" so that the company's internal teams can act quickly to correct the situation.

The challenges of semantic analysis in customer relationship management

Semantic analysis should play an important role in marketing strategy and your company's customer relations. In fact, this marketing tool ensures the quality of exchanges between humans and AI. Communication is one of the pillars of customer loyalty.

In addition, semantic analysis provides invaluable help for support services which receive an astronomical number of requests every day. Thanks to this SEO tool, there's no need for human intervention in the analysis and categorization of any information, however numerous.

It should also be noted that this marketing tool can be used for both written data than verbal data. What's moreanalysis of voice meaning is the key to optimizing your customer service.

In addition, semantic analysis goes beyond improving customer service, as it contributes to the consolidation of your company. In fact, this marketing tool helps your teams get to know your customers better.

Integrating semantic analysis into your marketing strategy: the benefits are numerous

Semantic analysis is a powerful ally for your customer service department, and for all your company's teams. It's a key marketing tool that has a huge impact on the customer experience, on many levels.

Improving customer knowledge

By analyzing the meaning of requests, semantic analysis helps you to know your customers better. In fact, it pinpoints the reasons for your customers' satisfaction or dissatisfaction, in addition to review their emotions. This understanding of sentiment then complements the traditional analyses you use to process customer feedback. Satisfaction surveys, online reviews and social network posts are just the tip of the iceberg.

In addition, semantic analysis helps you to advance your Customer Centric approach to build loyalty and develop your customer base. As a result, you can identify customers who are loyal to your brand and make them your ambassadors.

Customer satisfaction by accurately meeting their expectations

Semantic analysis uses machine learning and language processing to read content. Artificial intelligence, like Google's, can help you find areas for improvement in your exchanges with your customers. It receives relevant answers within a short timeframe. And that's sure to please them. What's more, with the evolution of technology, tools like ChatGPT are now available that reflect the the power of artificial intelligence. Don't hesitate to integrate them into your communication and content management tools.

Increase your company's productivity

Semantic analysis is a a real time-saver for your company. It gives you access to automatic data and content analysis. As a result, your teams can concentrate more on complex tasks for which human intervention is indispensable.

In addition, semantic analysis is a major asset for the efficient deployment of your self-care strategy in customer relations. The aim of this approach is to automatically process certain requests from your target audience in real time. Thanks to language interpretation, chatbots can deliver a satisfying digital experience without you having to intervene.

Optimizing your SEO strategy

Semantic analysis plays an important role in optimizing your SEO strategy. In this sense, it helps you understand the meaning of the queries your targets enter on Google. By referring to this data, you can produce optimized content that search engines will reference.

As a result, semantic analysis provides you with leads that can boost traffic on a web page while offering web users relevant content. In this way, it improves positioning your content in Google search results.

Concrete examples of the use of semantic analysis

Semantic analysis has become an integral part of many companies' development strategies. This integration can be achieved in a number of ways.

Semantic analysis and customer reviews

The use of semantic analysis in the processing of web reviews is becoming increasingly common. This technique is used by all the major brands. This system is infallible for identify priority areas for improvement based on feedback from buyers.

So.., semantic analysis of verbatims can be used to identify the factors driving consumer dissatisfaction and satisfaction. In the case of Cdiscount, for example, the company has succeeded in developing an action plan to improve information on some of its services. The company noticed that return conditions were often mentioned in customer reviews. Thanks to semantic analysis. Since then, Cdiscount has been proud to have succeeded in improve customer satisfaction.

Semantic analysis and social listening

Transport companies also see semantic analysis as a way of improving their business. The Uber company meticulously analyzes feelings every time it launches a new version of its application or web pages. This is known as "social listening". Uber's aim is to measure user satisfaction on the content of the proposed tools.

What's more, the company says it uses the technique on a daily basis. It enables it to understand how users feel when it makes changes to its tools. As soon as developers modify a feature, Uber learns what needs to be improved based on the feedback received.

Semantic analysis by Colibri and Google

The use of semantic analysis is not just for BtoB and BtoC companies. In fact, Google has also deployed its analysis system with a view to perfecting its understanding of the content of Internet users' queries.

This is how the Colibri algorithm appeared in 2013. The aim of this system is to provide relevant results to Internet users when they carry out searches. This algorithm also helps companies to develop their visibility through SEO. It's in the interests of these entities to produce quality content on their web pages. To achieve this, the use of relevant keywords is essential.