What is a customer verbatim and how to use it to improve your CX


Improve CX with customer feedback analysis

Customer feedback is a mine of information for your company. Numerical or qualitative, one-off or regular, it is a real lever for improvement. You may already be converting them into customer relations indicators: conversion rate, loyalty rate, NPS...

But what do you do with semantic data known as "verbatims"? How do you interpret the opinions posted on your website or the written responses to your customer satisfaction surveys? It's a much tougher task for corporate marketing departments, but it would be a shame to ignore the voice of the consumer.

At Zaion, we're convinced that customer verbatims are a veritable goldmine for strengthening your customer knowledge, driving your organization forward and improving your CX (Customer Experience).

Discover the definition, benefits and methodology of customer verbatim analysis.

What is a verbatim?

Verbatim refers to a customer's raw comments or opinions about a company, product or service. This faithful account, anonymous or not, can be used to justify a rating or give a detailed opinion. Verbatim is semantic data taken from a free text field.

In a marketing campaign or Customer Experience improvement initiative, verbatim is generally collected via a satisfaction questionnaire, in response to an open-ended question. However, the sources of verbatims are not limited to surveys conducted by a company. Comments about a product, a service or a brand abound on the Internet, often uncontrollably. Indeed, verbatims are legion on social networks (Facebook, Twitter, Youtube), review-gathering applications (Tripadvisor, Critizr), e-commerce site product sheets (Avis Vérifiés), discussion forums, complaint e-mails, and so on.

As a result, the verbatims are classified into two categories:

  • Solicited customer verbatim: the company questions its customers directly to obtain their opinions. The verbatim collection strategy is defined by the customer journey and customer knowledge, in order to obtain a high and reliable response rate;
  • Spontaneous customer verbatim: customers share their opinions without having been solicited by the brand, on the communication channel of their choice, positively or negatively altering the brand's e-reputation.


Why analyze verbatims?

Due to a lack of resources and time, verbatim is often overlooked by companies. And yet, it reflects the customer's voice more sincerely and explicitly than a simple numerical note. The consumer has taken the time to write it, and has used his or her own words. A free text field gives them the opportunity to share their feelings, unfiltered, to inform other consumers or the brand itself. It would be wrong to miss out on such a rich and reliable source of information. What's more, a customer is more likely to write a negative review on the web than a positive one, especially anonymously. Verbatim analysis is therefore a powerful lever for improving your Customer Experience, while also giving you greater control over your e-reputation. It exposes your strengths and weaknesses from an outside perspective. It also enables you to interact with your customers to better understand their needs and buying patterns.

Collecting and analyzing customer verbatims is therefore essential to enhance customer knowledge, monitor e-reputation and brand image, and improve customer relations.

How do you analyze verbatims?

Verbatim analysis enables us to understand customers' expectations and behaviors based on what they say. There are two main methodologies: "manual" coding analysis and "automatic" semantic analysis.

Manual coding analysis of verbatims

Traditionally used with the post-codification method, manual analysis consists of reading customer reviews one by one, then grouping them according to subject and assigning them a number. Assigning a unique number is part of the coding operation, usually performed in an Excel file. This produces statistics similar to closed questions such as NPS.

Many companies use an Excel spreadsheet to do the coding work. Manual analysis focuses on an open-ended question, such as "Are you satisfied with the product you bought?" and then collects the themes that emerge in the responses, e.g. product quality, price, delivery time. Then simply list the themes or type of comment (positive, neutral, negative) and assign a number to each. This way, you'll know which issues your customers raise the most, and how they feel about them, so you can prioritize your improvement actions.

It's also interesting to follow the evolution of this data over time, by regularly conducting new surveys on the same open question. Manual analysis is ideal if the sample of verbatims is small, but it remains ad hoc and very time-consuming. What's more, with software such as Excel, the words and expressions will be isolated, without their context, making the analysis less refined.

Semantic analysis of verbatims thanks to the power of AI

Unlike coding analysis, semantic or lexical analysis is carried out in real time. It uses specific artificial intelligence software to record customer feedback and analyze every word expressed on a platform or on the web. Verbatims are automatically grouped into categories according to their content and the criteria defined by the company. The algorithm also distinguishes between positive and negative comments. This customizable software deploys visual assessments that directly highlight areas for improvement in the customer experience.

At Zaion, the Voice Analytics platform is developed using our AI technologies to extract and enhance all the information from conversations with your customers. This solution enables the recording, transcription and analysis of voice signals, as well as the detection of emotions in voice and text thanks toemotional AI.

Here are the main benefits of our Voice Analytics platform:

  • productivity gains and reduced operating costs thanks to shorter average processing times (APT) and better understanding of customer demand
  • gains in service quality and improved customer service, thanks to rapid detection of areas for improvement in agents' discourse and behavior
  • strong, differentiating branding to reinforce the perception of your brand among your target audience

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