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Companies that endeavor to provide outstanding customer service need professional response management to ensure that customers get the right answer to their inquiry quickly. Numerous companies have already recognized that good customer service is a relevant competitive advantage, especially in increasingly saturated markets. Response management plays a key role in this context. Inquiries should be answered reliably, quickly, in a friendly manner and with the correct content, as this ensures a high level of customer satisfaction and loyalty, in addition to a high recommendation rate. Response management can therefore make a decisive contribution to a company’s business success. In the following, we explain the most important aspects of the topic and discuss what companies should pay attention to when selecting a response management software solution.

1. Summary

  • Definition of response management: In response management, service inquiries are structured and processed in transparent fashion according to defined service levels and other KPIs.
  • KPIs in response management: The most important quantitative metrics are the average response time and the average ticket costs, while the most important qualitative metrics are the first fix rate and customer satisfaction (including recommendation rate).
  • Response management systems:  Bei den Systemen unterscheidet man zwischen CRM-Systemen mit Response-Management-Funktionalität und spezialisierten Lösungen. Ideal sind aufgrund des deutlich größeren Funktionsumfanges spezialisierte Lösungen mit offenen Schnittstellen. 
  • ERMS, multichannel and omni-channel systems: Email response management systems (ERMS) only process email requests. With multi-channel systems, multiple communication channels can be handled via one software platform. Omni-channel systems handle all text-based service channels offered, including telephone.
  • Automated response management: The degree of automation possible in response management depends on the precise identification of the inquiry topic.
  • Artificial intelligence in response management: Artificial intelligence offers significant opportunities to automate response management. When it comes to precise topic recognition, the best results are achieved by vector-based algorithms combined with statistical methods.
  • Criteria for good response management: Thanks to high response quality and speed on all service channels, good response management ensures high customer satisfaction and customer loyalty.

2. Definition: What is response management?

Response management is a discipline within customer service. In principle, it entails the processing of large volumes of incoming customer inquiries in a structured and comprehensible manner, many times within a specific, typically predetermined period of time, by the customer service department (call center/contact center) or a contracted service provider.
It is important to prioritize the inquiries for communication channels and/or content and to route them to the available customer service agents in such a way that these defined service levels are met and customers receive the correct answer quickly and in a case-resolving manner. The process should be documented (customer contact history) so that when the customer makes a new inquiry, other service agents can see exactly what information the customer received last.
In the case of B2C companies with a large customer base, as well as for many B2B companies, a normal office mail program is insufficient to answer inquiries reliably and promptly. In particular when processing service requests from other text-based service channels (social media, chat, etc.) via multiple customer service agents, companies need a specialized response management system that routes requests to service staff according to certain criteria and that above all ensures that no inquiry is lost.

3. What are the relevant KPIs in response management?

Zu den wichtigsten Kennzahlen im schriftlichen Response-Management zählen

  • Response time
  • Ticket costs
  • First Fix Rate / First Resolution Rate
  • Customer satisfaction (with Net Promotor Score)


A distinction is made between quantitative and qualitative Key Performance Indicators (KPIs). One of the most important quantitative KPIs is the average response time. This defines how long customers or sales prospects have to wait for a response from the company. In the case of service providers in the contact center environment, it often also defines the “service level”, i.e. how quickly a service provider must answer inquiries on certain channels. Response time requirements, which are either set as internal goals or are a part of the contract when awarding work to a customer service provider, differ significantly according to the communication channel. They factor in customers’ expectations that chat and Messenger messages be answered immediately, for example, while inquiries via social media should be answered within an hour and, for email inquiries, ideally within 24 hours. Typically, for telephone service there is a default “80/20” service level, i.e. that 80% of calls be answered within 20 seconds. An overview of what is currently considered the “market standard” is available here, for example.

Another KPI is average ticket costs. represent another quantitative KPI. Every inquiry in the contact center is counted as a “ticket”. At a minimum, the average costs should include personnel and IT infrastructure costs (including telephone and internet). Full-cost calculations are also used to calculate ticket costs especially when it comes to a comparison with external service providers. If some inquiries can be answered at least partially in automated fashion, this usually lowers average ticket costs since fewer staff are required to process them.

One of the most important qualitative KPIs is the first fix rate or first resolution rate. This indicates the proportion of inquiries that were able to be definitively answered the first time the customer made contact. An answer should not only be quick, but also be correct and have readily comprehensible content so that the customer does not need to re-contact staff in order to resolve his or her concern. A low first fix rate means a high proportion of multiple contacts, which has a negative impact on customer satisfaction as well as on the total cost of the service.

Customer satisfaction is also one of the most important KPIs in customer service. Often, customer satisfaction is automatically surveyed following contact with customer service – be it directly following a chat by using an on-screen form, or by sending an email that requests a rating. In many cases, the recommendation rate is a sub-component of the customer satisfaction measurement. The Net Promotor Score indicates the number of customers who would recommend the respective company. Customer satisfaction has a significant impact on customer loyalty, i.e. whether the customer repeatedly purchases from the same company or will continue to maintain his or her contractual relationship. Customers, however, who migrate or terminate their contract in order to switch to a competitor (churn rate) can be an indicator of both product quality and service quality. Consequently, all KPIs should only be viewed and analyzed in context and over time.

In addition to the KPIs mentioned, there are a number of other Key Performance Indicators that can be used for contact center control and response management controlling. A selection can be found here, for example.

4. What response management systems are available?

Response management systems are available as part of a CRM solution or as a specialized response management software solution. In the case of specialized solutions, a distinction is made between proprietary (self-contained) systems and those that have interfaces to other important company applications such as CRM or ERP systems in order to ensure data exchange. The solutions are either classically licensed and installed on site at the company (on-premise) or offered as a SaaS solution (Software as a Service).
In order to ensure optimal customer experience, companies should choose specialized response management software that is integrated into the company’s IT infrastructure via interfaces. Such enterprise solutions offer a very extensive range of services tailored to the needs of customer service centers. They can extract data from other company systems and thus give the service employee a 360° view of the customer and provide content from knowledge management systems, document the customer contact history in parallel in the CRM system if desired, or can perform downstream tasks such as initiate a shipment. Consequently, in the event of renewed inquiries, service employees can trace the customer contact history or the current status of an inquiry at any time.

5. Email response management versus multi-channel and omni-channel response management

The first response management solutions that came onto the market were, in line with the state of the art at the time, pure email response management systems (ERMS, which is often used as an abbreviation for email response management service). Most of the response management software solutions available on the market today are multi-channel capable, i.e. they can be used to process inquiries from several communication channels – including primarily social media. The term omni-channel solution is used when all communication channels used for customer service can be managed – from telephone to chat and email to various social media channels and messenger services.
Multi-channel or omni-channel response management places increased demands on the routing and prioritization of inquiries. Each channel has its own specific requirements regarding response speed, which service managers must take into account. An inquiry in live chat should be answered within a minute. Twitter and social networks such as Facebook require a maximum response time of one hour. For an email, the customer expects a competent answer within 24 hours, and for a letter it can take three to four days. Advanced systems therefore offer numerous options, for example, according to service employee availability, according to the input channel, telephone, email, chat, various social media channels etc., according to the language or level of competence of the service employees, as well as based on content-related criteria if the associated response management solution features content analysis of the incoming inquiries. In addition, multi-channel and omni-channel systems allow the communication channel to be changed within one processing operation, for example to protect sensitive personal data on openly accessible social media platforms or to ensure legal certainty. Systems such as ReplyOne, for example, are able to take an email inquiry and instantly generate a letter for the necessary postal confirmation of an order.

6. How can response management be automated?

Today, virtually all of the specialized response management solutions available on the market can at least rudimentarily understand the content of incoming inquiries. The systems differ in the type and quality of analysis.
The aim of such content analysis is, on the one hand, to quickly route the inquiry to the right employee and possibly pre-provide text modules for answers, and, on the other hand, to answer as many standard inquiries as possible in automated manner in order to relieve service employees of routine tasks and reduce costs.
The possible degree of automation in response management depends crucially on the precise identification of the subject of the inquiry. Many systems are still predominantly keyword-based. The risk here is that the topic will not be recognized correctly and that customers will either automatically receive the wrong answer or that service staff will have to search for the correct answer manually. Modern systems such as ReplyOne, on the other hand, use the latest AI technology with sophisticated semantic analyses and statistical methods to capture the content of a query very precisely and with a match accuracy of over 90 percent.


But when automating response management, considerations in the area of customer experience management also play a role. Companies that attach particular importance to highly personal, individualized customer service and excellent customer experience can use partially automated response management, in which each response proposed by the response management software is rechecked by a service employee.

7. What can artificial intelligence do in response management?

Artificial intelligence offers great potential for response management automation. Consulting companies such as Lünendonk and Bearing Point also reach this conclusion in their studies. Nevertheless, the topic is surrounded by numerous myths, as summarized e.g. by Frauenhofer IAO in a blog post. The first misconception is that all systems that provide automatic responses are based on artificial intelligence. This is incorrect. There are numerous response management systems that provide automated answers based on a keyword but which do not really understand the inquiry. They are not based on artificial intelligence, but rather rely on developers to program them in advance with keywords or sentences and the appropriate answers. If the keyword or a certain programmed wording is missing in the inquiry, it will not be understood correctly, and the customer will receive no answer or the wrong answer. The second misconception is that AI-based response management systems learn from every inquiry and become a champion service provider virtually on their own. This is also wrong. What distinguishes human learning, namely the “understanding” of a context and the subsequent application in an abstractly similar situation, i.e. transfer, does not take place in machine learning. The technology hasn’t come that far.

To be able to be used in response management, AI must first be specifically trained to recognize certain recurring service topics by “tagging” highly suitable answers previously developed and content-checked by service experts. For these vector-based AI algorithms, a significantly smaller number of datasets or sample inquiries is sufficient for the learning phase in order to achieve very good results. Thus, the AI is not given an unstructured heap of big data in which it is supposed to recognize patterns, but rather is provided with clear guidelines regarding which answer or which answer category is actually the right one. The best results for precise topic recognition are achieved by vector-based algorithms that are combined with statistical methods – a technology that is also at work in ReplyOne.

The key to highly successful response management automation with the best customer experience, however, is an intelligent combination of man, machine and well-thought-out service processes, so that service employees are relieved of routine tasks and can deal with complex inquiries.

8. Conclusion: What comprises good response management?

The goal of good response management should be to retain customers over the long term through a high level of satisfaction with the relevant service. Customer satisfaction is increasingly viewed as the overarching quality criterion for customer service and is systematically gauged in the context of benchmark studies such as customer monitor. As part of customer experience management, contact centers should ensure high response speed and quality on all service channels. At the same time, the service process should be recorded and processed in the system completely independently of the selected communication channel.

Response management systems should be networked with other important company systems in order to enable a 360° view of the customer. When automating response management, potential effects on the customer experience should be considered in advance and factored in. A high degree of automation that doesn’t sacrifice customer experience is only possible when the subject of an inquiry is precisely identified.


Case example

If you would like to learn how contact centers use a modern response management solution such as ReplyOne in daily operations, be sure to read one of our user reports.

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