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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 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.
The main KPIs to consider in Response Management are:
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.
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.
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.
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.
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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