How to gain insight into the customer experience without a questionnaire

The customer experience (CX) is still one of the most important factors determining the success of a company, which is why more and more effort is being made to keep improving it. Customers are continuously asked – sometimes ad nauseam – to what extent they are satisfied with the product they purchased, the service they received, or the customer-friendliness of the contact centre employee they interacted with. Is that really the only way companies can obtain information about the customer experience? Fortunately not!

Smart technology is increasingly being used to gain better insight into the wishes and needs of the customer, without explicitly asking them. With the right technology, you can not only improve the customer experience and drive loyalty, but also sharpen your employees’ skills. One such technology is conversational analytics.

Conversational analytics now offers almost limitless potential for companies looking to understand their customers on a deeper level. In this blog, we explain what it is and what the benefits are.

Grasping the context

Conversation analytics is all about mapping speech and text-based interactions, such as phone and chat conversations, emails, social media discussions, and reviews. It doesn’t only cover interactions with contact centre employees, but also those with voice and chatbots.

In a nutshell, it amounts to computers being able to understand human speech and text thanks to Natural Language Processing (NLP), and artificial intelligence (AI) making it possible to organise and understand the enormous amounts of data that come out of this. Thus these technologies are applied to analyse conversations for customer sentiment, and to find patterns in them that can be useful for better understanding customer behaviour.

Unlike speech analytics, which more broadly deals with spoken interactions, conversation analytics focuses on understanding the context of interactions that take place across multiple channels.

Its purpose is to gain insight into the enormous numbers of customer interactions, in order to extract useful data that you can actually do something with. And that is of course invaluable, especially in the contact centre.

What type of feedback do conversation analytics include?

When it comes to collecting customer feedback, many companies immediately think of a survey. And while surveys can provide valuable information, they only involve explicit feedback. This is structured, requested feedback, where a company asks a question and the customer provides an answer or score. In the vast majority of cases, this way of information gathering remains on the surface of customer behaviour.

Moreover, this type of data often gives a distorted or skewed picture. Not everyone responds to a survey, and customers who do respond are usually very motivated to do so, because of a very positive experience or a negative one. So while this kind of feedback can be very valuable, it rarely gives a complete picture.

Implicit feedback digs a lot deeper. This type of feedback is also known as unstructured, unsolicited feedback. It provides insight into how customers think, and how they feel and behave. That kind of feedback can really only be found through conversation analysis.

It refers to the information that is difficult to collect, such as social media discussion topics about a particular brand or company, third-party reviews, and customer interactions through various channels, both with bots and with human employees.

It addresses aspects of the customer experience that may seem irrelevant at first glance and are therefore rarely covered in a survey, but that are definitely crucial.

Understanding customer emotions and behaviour

For example, by identifying customer emotions, employees can show the right level of empathy during an interaction, with which they can influence the course of the conversation. Sometimes this is difficult in the moment itself, but in those cases conversation analysis can still be used for training purposes, to teach agents how to de-escalate difficult conversations before they get out of hand, for example by learning to recognise certain triggers.

In addition, conversation analysis helps to map trends in customer behaviour, for example by recognising keywords or signs of emotion. With this knowledge you can, for example, adjust customer profiles and create better scripts for employees and bots to follow.

In addition, interaction analytics can make it easier to identify security risks. We recently wrote a blog about data security in the contact centre, and one of the risk factors we identified was social engineering, where agents are unknowingly manipulated or tricked into giving fraudsters access to accounts, transferring money or sharing personal information. Interaction analytics can identify these types of fraud attempts and automatically alert agents as the call progresses.

First priority: the customer experience

Ultimately, of course, it is about getting as complete a picture of the customer as possible. The advantage of conversation analysis is that you do not burden your customers with it, so they don’t need to complete yet another survey. All the information you collect is obtained through conversations that the customer himself has initiated.

This is the only way you learn to better understand the customer, their feelings, motivations and behaviour, so you can figure out not only what the customer tells you, but also what he is not telling you. By responding to the insight gained in this way, you have the tools to improve the customer experience and to increase the chance of his loyalty.

Do you wonder how to apply conversation analytics in your contact centre? How artificial intelligence can help you make sense of the overload of data that arises from countless interactions? How to improve the customer experience and therefore the business results? Then book an appointment with one of our experts. 

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