How to use semantic analysis to improve customer experience?

Published on April 27, 2022  - Updated on December 05, 2023

How to use semantic analysis to improve customer experience ?

It's possible! The comments left by your customers are often a mine of information about your experience and customer journey. It's important to use them to their fullest potential. That's what semantic analysis is for!

With the multiplication of the number of reviews and comment sources, it is one of the best ways to identify your improvement points and priority actions.

But first of all, what is semantic analysis?

1 - What is semantic analysis?

In this article, we will not deal with lexical analysis, which aims to study each element or symbol of a word.
First of all, it is necessary to define what semantic analysis is and, first of all, what is semantic? It is simply the study of language, of the meaning of words in the context of sentences. 
Unlike lexical analysis, the semantic analysis focuses on sentences to understand the overall meaning of a text. 
When we refer to semantic analysis, we often think of natural language processing (NLP) techniques.

Indeed, this is what most semantic analysis tools on the market use to process large volumes of text. 
The best tools couple semantic analysis with Machine Learning in order to maximize the reliability of the analysis over time and the number of verbatims processed. At Q°emotion, our algorithm now achieves a reliability rate of over 90% in the analysis and classification of verbatims.
You can read our article about how automatic semantic analysis works to learn more.

Nevertheless, you may be wondering what the point of semantic analysis is in the context of customer relations.

2 - Why and how to combine semantic analysis and customer experience?

a) Better understand customer needs

What is the point of semantically analyzing customer feedback? 
Because behind the words, there is a need.

"A good way to approach customer experience requires a complete view of the customer's need."  Fanderl

Who better to tell you about their experience with your brand than your customers? So the feedback they leave you is a real opportunity to understand their needs and improve your customer experience.
Indeed, you need to base your conclusions on concrete data and you can't imagine yourself the real experience of your customers, you need to use concrete feedback from your customer base. 
By using semantic analysis, you will be able to extract the information contained in the verbatims left by your customers. Its efficiency relies on the volume of comments.

b) Identifying the most talked-about topics

The first concrete application of this information extraction process is to identify the most talked-about topics. Indeed, it's possible to get an idea of these themes simply by reading the reviews, but if the volume of comments is substantial, this can quickly become complex. That's why the semantic analysis tool comes into its own when the volume of reviews is large enough to make manual analysis too time-consuming.

Having an exhaustive view of all the topics raised and their importance will have a definite impact on your understanding of your customers' experience, and therefore on improving it.

c) Detecting weak signals and areas for improvement

Directly linked to the previous point, having a global view of the issues raised by customers will also enable you to potentially identify emerging subjects (or weak signals) and anticipate irritants before they have too much impact. It's this kind of action that goes a long way to reducing attrition and building customer loyalty.

So how does it work? Well, it's quite simple. By regularly monitoring the analysis of your reviews and the associated themes, you'll easily notice when a new topic starts to appear in customer verbatims. The most powerful semantic analysis tools also allow you to set up alerts so that you are automatically notified when a new topic begins to be mentioned a certain number of times in customer comments.

d) Prioritize actions

Another important benefit of semantic analysis of customer comments is the prioritization of actions to be taken. Once you've identified the actions you need to take to optimize the customer experience, it's sometimes difficult to know which tasks have priority.

That's why at Q°emotion we combine semantic and emotional analysis. Thanks to the detection of 6 primary emotions (joy, surprise, fear, sadness, anger, disgust), when a customer expresses disgust or anger, there's a good chance that this subject is more critical than the others, and therefore a priority to deal with.

e) Time-saving verbatim analysis

Finally, as a direct consequence of automation, the use of a semantic analysis tool saves considerable time when processing verbatims. On average, our customers save 100 man-days per year.

Now that we've looked at the benefits of semantic analysis for the customer experience, the question is how to implement it?

3 - How to combine semantic analysis and customer experience?

How to collect customer reviews?

In order to perform a semantic analysis of customer comments, it is necessary to have comments and therefore to generate volume.
We have already seen that the greater the volume of comments, the more relevant the analysis will be, so how do you collect customer reviews?

The most relevant method that will bring you the most results is the satisfaction survey. To do this, you must, first of all, determine the target and the control point of the satisfaction survey.

Will it be addressed to all your customers? To some of your customers who are at a specific stage of your journey? Only customers who have left you? By determining the target of your survey, you can then define its objective. What is the purpose of the survey? This will be the basis of the project and will determine the quality of the results that you will obtain afterwards. 

Once you have your target and your objective, it is time to create the questionnaire! 

Nowadays, it is easy to create satisfaction surveys for your customers. There are over a hundred tools that can help you create surveys. It is a little more complicated to automate the emails and keep track of the information for your CRM etc... The most advanced tools offer surveys via several channels: mobile applications, SMS, website and emails, etc. Of course, in the digital age, never use paper to launch a survey, it would be too difficult and expensive to exploit the data. 

And above all: be concise!

Limit yourself to less than 5 minutes of answers: the time of your customers is precious, do not cause frustration with a questionnaire that is too long, no one wants to answer an endless survey! For example: you should reduce your survey to 10 questions maximum with a quantitative score and 3 open questions maximum. 

Test the average response time yourself before launching your survey! For your most engaged customers, open-ended questions (comment responses) allow for a more complete feedback. 

Of course, there are other relevant sources of feedback to analyze that we do not detail in this article. If you are interested in the subject, read our article: the top 5 sources of customer reviews to analyze.

Now let's talk about strategy, how to perform an efficient semantic analysis?

4 - What is the best semantic analysis strategy?

When you have a large volume of customer reviews to process, manual semantic analysis is far too time-consuming to be viable. That's why in this case, it's wise to look at automatic analysis tools, but which tool to choose?

Most semantic analysis solutions are based on sentiment analysis. At Q°emotion, we believe that this approach is not accurate enough.

We have therefore developed a unique multilingual emotional dictionary containing over 50 million words and expressions. 

Thus, with Q°emotion technology, it is now possible to obtain the emotions behind the words. And behind these emotions, an intrinsic need is expressed. To meet this need, we need to understand in depth the signals given by customers, which is called "emotional intelligence". 

It is easy to understand that a customer expressing fear will not need the same response as an angry customer. Without this emotional layer, with for example only an analysis of the feelings, it will be extremely difficult to respond correctly to the customer's expectation(s). 

Imagine a customer expressing disgust for a product. If you offer him a discount to buy this product, it won't work, for 2 main reasons: 
- because the customer is already looking for a complete change
- because this emotion is often uncontrollable, stronger than their mind and will. 

Offering the same answer over and over again is like saying: "I don't understand what you're telling me".

By coupling the analysis of emotions with the classic indicators of CSAT (Customer Satisfaction) and NPS (Net Promoter Score), you will have a complete and precise vision of the experience of your customers.

This will make it easier for you to prioritize the actions to be taken to improve the customer experience and the customer journey.