From the essentials to the most innovating, focus on the customer service control indicators – part 2

Focus on the customer service control indicators

Part. 2: Innovating indicators: perceived quality

In the first part of this article, I described several key indications of customer relations focusing on performance and control. As mentioned, these quantitative KPIs are meaningless if they are not measured against customer expectations. This is why indicators based on the customer’s voice, indicators of perceived quality, are developing at the same time.

Let’s take a broad look at them, bearing in mind that some of these indicators, which emerged quite recently (2003 for the NPS, 2010 for the CES), are already classics in the measurement of customer satisfaction.

Satisfaction surveys remain the basic method used to collect customer opinions. Apart from the usual satisfaction questions, they represent a true mine of information obtained by analysing customer verbatims. However, this analysis is extremely time-consuming and requires considerable resources.  Consequently, some companies decide not to give any space to customer expression.  These surveys can be conducted immediately after each customer contact and in this case are brief, or later, for example once or twice a year. In this case, they include more questions.


The customer satisfaction (CSAT) rate is measured through satisfaction surveys. It results from the question, “Are you satisfied?”. The respondents must choose between “dissatisfied”, “not very satisfied”, “satisfied” and “very satisfied”.  The satisfaction rate is calculated using the percentage of satisfied and very satisfied customers. It may be considered as a summary of the answers to all the questions asked during the satisfaction survey. It must be analysed in relation with the other items of the satisfaction survey. It is only by making a comparison with the other answers that a detailed analysis can be conducted and the points of (dis)satisfaction detected.
The satisfaction rate must be enhanced using the following two indicators which involve a larger share of the customer’s emotion and perception.


The Net Promoter Score (NPS) has become the norm in satisfaction surveys. It is based on a single question asked to the customer: “On a scale of 0 to 10, how would you recommend us to others, 0 being not at all and 10 very strongly”. This indicator provides information about the company’s reputation, the ability of the users to recommend it to their families and friends. It is a recommendation rate. The calculation formula is as follows: The Net Promoter Score is equal to the percentage of promoters (scores 9 and 10) minus the percentage of opponents (scores from 0 to 6). Users assigning scores from 7 to 8 are considered to be passive. They are not included in the NPS calculation since they have no impact on the company’s reputation. So, out of 100 respondents, if 22 give scores of 9 and 10, 45 of 7 and 8 and 33 between 0 and 6, the NPS will be -11 (i.e.  22 % of promoters minus 33 % of opponents). The aim is to monitor the NPS trend rather than the figure itself, since there is no rule to define a good or bad NPS. Most of the time, an NPS greater than 0 is considered to be good but depending on the product, service or brand, NPSs less than 0 are also considered to be satisfactory. For example, Apple has an NPS of 47 and Ikea an NPS of -9*.


The Customer Effort Score (CES) also results from a question asked to the customer, i.e. “How much effort did you have to put in to obtain an answer”. The answer to this question ranges on a scale from 1 (low) to 7 (high). This indicator highlights the degree of complexity of the customer path and how it was perceived by the customer. It measures the conformity of the service with the customer’s expectations. It complements the NPS. It is calculated either by the average of the marks or, using the NPS model, by the percentage difference between high-level effort and low-level effort. Still rarely used, this indicator is becoming more popular since it reflects customer loyalty.

Lastly, a few more marginal indicators which are progressively emerging are given below.


Speech/text analytics are built around customer verbatims in the recorded calls or written messages. They detect the words or expressions which arise frequently and are used to gain valuable customer insight.  They is used in the same way as verbatims from satisfaction surveys. They are used to identify trends on request themes, but also on the emotion detected during the conversation. The choice of words and the pace of the conversations reveal the feelings expressed by the customer. It is then possible to measure the proportion of dissatisfied, happy, confident customers, etc.


The logging rate correlates the number of contacts with the number of interactions entered in the ticketing or CRM tools. It measures the traceability of customer requests. To guarantee the customer insight and make the contact more personalised, as much information as possible must be traced, stored, qualified and entered. The logging rate ensures that this good practice is implemented within the customer service.


The quality of work life of the employees is a new indicator stemming from the observation that a good customer experience starts with a good adviser experience. It is often measured using forms of internal surveys conducted once or twice a year. These forms include a question similar to that used to calculate the CSAT. This innovating KPI was developed from the concept of “symmetry of attentions”.  This concept is based on the principle that happy employees make happy customers and that it is easier to achieve excellence in customer relations by first achieving excellence in managerial relations.


From all these indicators, each company must find those matching its own situation and meeting its ambitions. We must keep in mind that the indicators must allow companies to build relevant and achievable objectives and measure the impact of the actions set up to reach them. What counts is not their number but their relevance and operability.
To obtain a vision representative of a service, the “produced quality” and “perceived quality” indicators must be mixed. The first determine the status at time 0 and the second the status expected by the customer. The trend of the two indicators reflects the progress of the objective and its impact on the customer.


In addition, an indicator must be analysed in a particular context, never isolated from it.
We will take the example of a contact centre whose email processing delay is 6 working days and whose quality perceived by the customer is unsatisfactory. What factor(s) can be used to change the quality perceived by the customer? Just shorter delays? Or is the quality of the answer given taken into account in the context of this contact centre? Do customers merely expect to receive a confirmation email indicating how long it will take to solve the problem?


Once the indicators have been defined for an activity, this does not mean that they are fixed. Even if their interest lies in the fact that the progress can be monitored in the long term, companies must not hesitate to stop using obsolete indicators or reduce their production frequency and set up indicators matching the changes observed in the contact centres. The start of this century saw the emergence of new communication channels and changing exchange mechanisms. This change will be confirmed in the coming years.

According to Gartner, in 2020, 85 % of interactions between a customer and a company will occur without human intervention and 25 % of contact centres will have a bot or virtual adviser solution.
At the same time, the various surveys indicate that customers place increasing importance on the quality of the customer service and personalisation of the exchanges. The results of the 2017 observatory of customer services published by BVA indicate that the communication channels preferred by French people are face to face (20 %) and telephone (20 %), i.e. a human interaction, compared with 1 % of the respondents for chatbots. The 2018 KPMG survey on Customer Experience Excellence emphasises personalisation as being the most important of the 6 customer experience pillars in loyalty and promotion.


Current customer expectations are as follows:

  • Handling of their requests without having to follow up the customer service,
  • Rather than fast processing, relevant processing and ongoing communication,
  • A consistent, complete answer concerning their request and the information requested to process it,
  • Personalised, non-standardised exchanges.

The challenge of KPIs in customer relations is therefore to use the right indicators to reach a balance between the efficiency and speed of a standardised answer and the relevance and quality of a personalised answer.



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