Voice of the Customer

  • What is the Voice of the Customer (VoC)?
  • How is it collected and what is it used for?
  • What role does it play in holistic customer experience management?

Voice of the Customer - A definition

Voice of the Customer (VoC) generally refers to two different things that can be seen as gradations or manifestations of each other.

In a more literal sense, VoC refers to the opinions, attitudes and experiences that customers associate with a company or its products and services. The Voice of the Customer is therefore what customers think of a company.

In a broader - and mainly common - sense, VoC refers to the process and methods aimed at collecting and evaluating precisely this information from customers. VoC is therefore primarily aimed at understanding customers' expectations and experiences across the entire customer journey.

How is the Voice of the Customer measured?

There are numerous methods for collecting VoC - not all of them are suitable for every company.

Classic survey instruments include, for example

  • (Online) surveys
  • focus groups
  • interviews
  • Evaluation of reviews
  • Social media scraping/automatic text analysis
  • Provision of contact options

In order to obtain a complete picture of the VoC, a combination of the above-mentioned collection methods (or similar) should be used.

In addition, feedback should be collected at as many interaction points and through as many channels as possible.

In other words, sporadically conducting a satisfaction survey with a limited sample is not enough to set up a successful VoC program.

VoC requires continuous collection and analysis of feedback data. This is the only way to guarantee that developments in the opinions, assessments and needs of the target group are recognized in good time.

What is the Voice of the Customer used for?

VoC data can be used company-wide:

  • Product development: The feedback that customers have on products and services plays a particularly important role here. This can be used to identify and solve problems in the product range and draw attention to desired features.
  • Customer service/support: If the employees who have to deal directly with customer concerns - often after something has already gone wrong - have information about customers, this helps them to be better prepared for situations.
  • Marketing and sales: A central task of marketing and sales is to analyze and know a company's target group. Only in this way can messaging and offerings - together with product development - be tailored precisely to their needs.
  • Management: Setting priorities and making decisions about the direction of a company requires a solid understanding of the market. The most direct approach to this is to know what customers expect from the company.

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Practical tip: Ask the right questions, measure the right KPIs

Although there are various approaches to collecting VoC (see list above), the survey is certainly the most common.

Within surveys, either concrete KPIs, specific information or a mixture of both can be queried.

KPIs that are mainly used and have been tried and tested are the Net Promoter Score (NPS), the Customer Satisfaction Score (CSAT) and the Customer Effort Score (CES)

In addition to these quantitative instruments, there are questions such as:

  • How do you know our company?
  • What did you particularly like about our offer?
  • What did you not like at all? Why?

Efficiency drivers: Automatic text analysis and VoC

One way to obtain in-depth information from customers is to use automatic text analysis.

A well-functioning text analysis system allows the processing of large amounts of unsorted text data, such as those generated when answering open questions.

The three questions listed a few lines above are a good example of when and how automatic text analysis can be used.

The first of the questions - "How do you know our company?" - can be implemented comparatively well as a closed question, i.e. a question with predefined possible answers. This is because these potential answer options can be broken down into a manageable number, e.g:

  • From the Internet
  • From advertising
  • From acquaintances/friends

Even if each of these three general categories is subdivided into two or three more specific categories, the resulting list is no longer than for comparable questions that we have all stumbled across before.

The second and third questions are more difficult: "What did you particularly like about our offer?" and "What did you not like at all? Why?" are questions that allow a very wide range of possible answers. Especially when a questionnaire asks for the "why", i.e. a personal reason, it is difficult to estimate which possible reasons led customers to their respective evaluation.

A VoC system that wants to paint as uncolored and nuanced a picture as possible of customer opinion often cannot avoid the use of open questions and comment functions within the survey instruments. Automatic text analysis helps immensely with the evaluation of such questions.

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