Response Management

Companies that endeavor to provide outstanding customer service need professional Response Management to ensure that customers get the right answer to their enquiry quickly. Many companies rightly recognise that good customer service is a significant competitive advantage, especially in increasingly saturated markets. Response Management plays a vital role in this context. Enquiries should be quickly answered, in a friendly and professional manner and most importantly, with the correct content to ensure higher levels of customer satisfaction, loyalty, and recommendations. Response Management is therefore a key contributor to a company’s business success. In the following section, 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: A system whereby, service enquiries are structured and processed in a transparent manner, 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: With regard to these systems, a distinction is made between CRM systems with response management functionality and specialized solutions. Due to the significantly larger range of functionality, specialized solutions with open interfaces are ideal.
ERMS, multi-channel 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 also handle all service channels offered, including telephone but also allow any number of these to be combined seamlessly during the entire customer service journey.
Automated Response Management: The degree of automation possible in Response Management depends on the precise identification of the enquiry topic.
Artificial intelligence in Response Management: AI offers significant opportunitiy to automate Response Management. When it comes to precise topic recognition, the best results are achieved by vector-based AI algorithms combined with statistical methods.
Benefits of good Response Management: By delivering high response quality and speed on all service channels, good Response Management ensures high levels of customer satisfaction and loyalty.

2. Definition: What is Response Management?

Response Management is an integral part of customer service. . It entails the processing of large volumes of incoming customer enquiries 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 by a contracted service provider.

It is important to prioritize the enquiries by communication channel as well as content and to route them to the available customer service agents in such a way that defined service levels are met and customers receive the correct answer quickly leading to effective case resolution. The process must be documented (customer contact history) such that when the customer makes a new enquiry, other service agents can see exactly what has been done before and what information the customer previously requested and received, in order to eliminate any annoying repetition of requests.

More often than not, providing good customer service, via a traditional e-mail program is insufficient to answer enquiries reliably and promptly. In particular when processing service requests from multiple service channels (e.g. social media, chat, etc.) via multiple customer service agents, companies need a Dedicated Response Management system that can quickly and accurately route requests to service staff according to certain criteria andabove all, ensures that no enquiry is lost.

3. What are the relevant KPIs in Response Management?

The main KPIs to consider in Response Management are:

Response time
Ticket costs
First Fix Rate / First Resolution Rate
Customer satisfaction (with Net Promoter 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 existing or prospective customers 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 enquiries 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 such that chat and Messenger messages be answered immediately, while enquiries via social media should be answered within an hour and, via email, ideally within 24 hours. Typically, for a telephone service there is a generally-expected“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 quantitative KPI is average ticket cost. Every enquiry in the contact center is considered a “ticket”. At a minimum, the average cost should include personnel and IT infrastructure costs (including telephone and internet). The full-cost calculations should be used to calculate ticket cost especially when it comes to a comparison with external service providers. If some enquiries can be answered at least partially in an automated fashion, this usually lowers the average ticket cost, since fewer staff are required to process them.

One of the most important qualitative KPIs is the first fix rate (aka first resolution rate). This indicates the proportion of enquiries that were able to be definitively answered the first time the customer made contact. An answer should not only be quick, but also needs to be correct and deliver relevant content so that the customer does not need to re-contact staff in order to resolve their enquiry. A low first fix rate means a high proportion of multiple contacts, which has a negative impact on customer satisfaction as well as increasing the total cost of the service.

Customer Satisfaction is also one of the most important KPIs in customer service. Often, customer satisfaction is automatically sought following contact with the customer service department – be it directly following a chat by using an on-screen form, or by sending an email requesting a rating. Often, a recommendation rate is also collected as a sub-component of the customer satisfaction measurement. This so-called “Net Promoter Score” (NPS) is a measure which indicates the proportion of customers who would recommend the company to others. Customer satisfaction has a direct impact on Brand Loyalty, (i.e. whether the customer repeatedly purchases from the same company or will continue to maintain his or her contractual relationship). The number of Customers, , that switch to a competitor (churn rate) is a good indicator of both product capability and service quality.

In addition to the ones mentioned above, there are a number of other Key Performance Indicators which can be used for measuring contact center and response management system effectiveness. A selection can be found here, for example.

4. What Response Management systems are available?

Response Management systems can be part of a CRM solution or a dedicated software solution. In the case of dedicated solutions, a distinction is made between proprietary (self-contained) systems and those which have data exchange interfaces to other important company applications such as CRM or ERP systems. The solutions can also be traditionally-licensed and installed on-site at the company (on-premise) or offered as a SaaS solution (Software as a Service) in the cloud.

To ensure optimal customer experience, it is recommended that companies choose dedicated Response Management software which is integrated with the company’s IT infrastructure via open interfaces. Such enterprise solutions offer a very flexible range of services, tailored to the needs of customer service centers. For example, they can extract data from other company systems and give the service employee a 360° view of the customer. This can include providing content from knowledge management systems, documenting the customer contact history in parallel within the CRM system and performing downstream tasks such as initiating a shipment. Consequently, in the event of follow-up enquiries, service employees can track the customer contact history and current status of an enquiry at any point in time.

5. Email Response Management versus multi-channel and omni-channel Response Management

Early Response Management solutions were, limited to email messaging (often referred to as ERMS). Conversely, most modern Response Management solutions are multi-channel (and some also omni-channel) capable, i.e. they can be used to process enquiries from several communication channels – including social media. The term omni-channel is used when multi-channel communications are combined, seamlessly during a customer’s entire contact thread with the Company – from telephone to chat and email to various social media channels and messenger services.

Multi-channel and in particular omni-channel Response Management places increased demands on the routing and prioritization of enquiries. Each channel has its own specific requirements regarding response speed, that service managers must take into account. For example; An enquiry in live chat should be answered within a minute, Twitter and other social networks such as Facebook require a maximum response time of an hour, whilst withemail, the customer normally expects a competent answer within 24 hours, ascompared to letters which can take three to four days. Advanced systems also offer other options, for example,routing of an enquiry according to service employee availability, according to the initial communication channel, the language or level of competence of the service employees, as well as based on content-related criteria, but only if the associated Response Management solution has the ability to conduct content analysis of the incoming enquiries. In addition, multi-channel and omni-channel systems must 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 compliance. For example, systems such as ReplyOne are able to take an email inquiry and instantly generate a letter for the required postal confirmation of an order.

6. How can Response Management be automated?

Today, virtually all of the dedicated Response Management solutions available on the market offer a rudimentary understanding of the content of incoming enquiries. What differentiates such systems is the type and resulting accuracy of such analysis.

The aim of this content analysis is two-fold; on the one hand, to quickly route the enquiry to the right employee, possibly provide a pre-populated text module as an answer template, and, on the other hand, to answer as many basic enquiries as possible in an automated manner, to relieve service employees of routine tasks and reduce overall costs.

Crucially, the degree of automation in Response Management depends on the precise identification of the subject of the enquiry. 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 manually search for the correct answer. Conversely, more advanced systems such as ReplyOne, use the latest AI technology, with sophisticated semantic analysis and statistical methods, to capture the content of a query very precisely delivering a resultant accuracy of over 90 percent.

However, it is also extremely important to consider the customer experience when automating response management, Companies that attach particular importance to highly personal, individualized customer service can utilise partially-automated response management, in which each response proposed by the Response Management software is reviewed, approved and delivered by a service employee.

7. What can Artificial Intelligence do in Response Management?

Artificial Intelligence (AI) offers great potential for the automation of Response Management. Whilst consulting companies such as Lünendonk and Bearing Point agree with this assertion in their studies. the topic is surrounded by several myths. The first misconception is that all systems which provide automated responses are based on AI. This is incorrect. There are numerous response management systems which provide automated answers based only on simple keyword identification and without a true understanding of the enquiry. So rather than artificial intelligence, they rely on developers hard-coding them in advance with keywords (or sentences) and matching answers. If the keyword, or a certain programmed wording is missing in the enquiry, it will not be understood correctly, and the customer will either receive no answer or worse still, the wrong answer. The second misconception is that AI-based Response Management systems “learn” from every enquiry and become an “expert” service provider, virtually on their own!. This is also misleading. 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 just hasn’t come that far!

To be useful in Response Management, AI must first be specifically-“trained” to recognize certain recurring service topics by “tagging” highly relevant answers, previously selected and content-checked by service experts. For these vector-based AI algorithms, a significantly smaller number of datasets or sample enquiries is sufficient for the learning phase in order to achieve satisfactory results. Thus, the AI is not simply given an unstructured “pile” of big data in which it is supposed to recognize patterns, but rather it 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 which are combined with statistical methods – one solution that utilizes such an approach is 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 focus on the more complex enquiries.

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 integrated 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 enquiry 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 case studies.

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