智能呼叫中心不止是呼叫,还有智能语音质检

摘要:人工智能技术对于话务质检,可以说是给话务质检带来质的变化。具体的运作逻辑如下:我们通过ASR技术实现话务服务的全量录音转文本,转换成文本后依据大数据进行关键核心词匹配,最后完成全通话服务量文本的关键字标红和统计

智能呼叫中心不止是呼叫,还有智能语音质检

呼叫中心从最初的单纯解决客户咨询、投诉问题人工热线外呼,到预览式外呼,再到电话销售、金融贷款、催收的预测式外呼和自动外呼(这也是现在让很多人觉得困扰的电话骚扰)。其实你可以发现一直是技术在推动着呼叫中心业务场景的变化,反过来客户业务的痛点也促进技术的发展迭代。

那么,作为大热的人工智能技术,与呼叫中心相关的人工智能技术有哪些?人工智能究竟在呼叫中心行业是如何落地,又有什么具体的场景?那么我们就来剖析一下。

首先,我们要有一个普遍的认知,当前阶段下,研究和应用的比较成熟并且和呼叫中心有关系的人工智能技术包含哪些,目前主要包括的有:语音识别、自然语言处理、图像识别等。

有了这个基础,我们来看看人工智能技术在呼叫中心行业的一些具体运用场景。

第一个,智能识别和智能知识库

以前的人,包括现在的大部分人,可能都体验过这样一个流程,你去某银行热线咨询一个问题,你首先听到的是语言的选择(中文还是英文等)然后是业务选择(储蓄卡业务还是信用卡业务等),可能下一层是业务操作(查询还是申办),很多人其实在还未完成全部选择就已经很不耐烦,会直接切换到人工。

其实这种行为是违背企业设置智能识别业务以减少人工服务量的初衷的。那么,有什么能解决这个问题吗?是的,你可能通过智能IVR和智能知识库结合,很好的解决这个问题。

具体的逻辑如下:你拨通某银行的热线,在进入服务层级之前,我们的智能IVR可以直接进行业务需求引导(比如:你需要办理什么业务?)。这个时候,你需要的是直接说出你的需求(比如:我想要申请信用卡、我想改密码等)。

这个时候,我们的智能IVR能通过语音识别和自然语言处理,快速并且高效的理解你的需求,并通过银行业务系统的智能知识库,进行关键词检索,锁定该业务的答案,并且通过TTS、系统录音或者最原始的短信将当前业务的答案发送或者触达给你。

你会发现你节省了大量的时间,客户满意度一下提升,同时银行业也省去大量的人工,运营更加高效。

但是智能知识库和传统知识库并不尽相同,智能知识库拥有更强大的算法能力,并且能够根据设定的规则,进行阶段性重点关键问题的智能排序,和报表生成,有助于企业实时关注客户痛点和关注点的变化,并采取针对性的措施。

第二个,智能全量质检

在呼叫中心运营中各项数据都非常重要,如:接通率、通话时长、投诉、客户满意度等。这些数据直接对应的是客服人员或者电销人员的业务素质。而不同人员之间的业务素质差距,不是完全靠培训能就能全部解决的。

这时候,就需要我们能够进行大量监控和反馈,但之前很多的监控和质检都通过人工抽检的方式,不仅耗时而且耗精力,并且只能提完成30%左右的话务质检,着实有些差强人意。

而现在,新的技术为这个问题的解决带来了曙光。人工智能技术对于话务质检,可以说是给话务质检带来质的变化。具体的运作逻辑如下:我们通过ASR技术实现话务服务的全量录音转文本,转换成文本后依据大数据进行关键核心词匹配,最后完成全通话服务量文本的关键字标红和统计,这样就能清楚的知道整个运营现场的话务服务质量统计和趋势,同样也试用于单个业务员所有话务服务质量分析。

通过人工智能的实时质检,不仅节省了人工质检的时间,还能很好的统计和分析,客户的具体需求和投诉点,并总结出相关规律,协助业务的开展和投诉的解决。

举个例子,呼叫中心接到了大量的用户投诉,如果需要人工确切的进行话务质检,需要好几天的整理和分析才能明确客户投诉的缘由和方向。而通过人工质检,不仅能100%对话务进行质检,还能抓取关键字,形成定向的投诉整理,从而调整产品投放。

对此,我们可以看到人工智能对于呼叫中心的业务提升非常大,很多沉重、繁琐的工作都能通过人工智能去完成,这是传统行业需要作出的改变,也是新型技术带来的挑战。其实企业生存,也和学习一样,在时代的潮流里逆水行舟,不进则退。

Call centers range from manual hotline calls to preview calls to predictive calls and automatic calls to telephone sales, financial loans, collection calls (which are now a problem for many people). In fact, you can see that technology has been driving changes in the call center business scenario, in turn, customer business pain points also promote technology development iteration.

Then, what are AI technologies related to call centers, as artificial intelligence technology with great heat? How does AI fall into the call center industry and what specific scenarios are there? Then we'll analyze it.

First of all, we need to have a general understanding of the current stage, research and application of more mature and call center-related artificial intelligence technology which includes: speech recognition, natural language processing, image recognition and so on.

With this in mind, let's take a look at some of the specific scenarios of AI technology in the call center industry.

First, intelligent recognition and intelligent knowledge base.

Previous people, including most people today, may have experienced a process in which you go to a bank hotline to ask a question. You first hear the choice of language (Chinese or English, etc.) and then the choice of business (savings card business or credit card business, etc.) and maybe the next layer is the operation (inquiry). Or bid, many people in fact have not yet completed all the choices have been very impatient, will switch directly to the manual.

In fact, this behavior is contrary to the original intention of setting up intelligent identification business to reduce the amount of manual services. So, what can be done to solve this problem? Yes, you can solve this problem well by combining intelligent IVR and intelligent knowledge base.

The specific logic is as follows: you dial a bank hotline, before entering the service level, our intelligent IVR can directly guide business needs (such as: What business do you need to deal with?). At this point, what you need is to say what you want (for example, I want to apply for a credit card, I want to change my password, etc.).

At this point, our Intelligent IVR can quickly and efficiently understand your needs through voice recognition and natural language processing, and through the Intelligent Knowledge Base of the banking system, carry out keyword retrieval, lock in the business answer, and through TTS, system recording or the most primitive SMS will answer the current business answer. Send or touch to you.

You'll find that you've saved a lot of time, improved customer satisfaction, and the banking industry has saved a lot of labor and operated more efficiently.

But intelligent knowledge base is not the same as traditional knowledge base. Intelligent knowledge base has more powerful algorithm ability, and can sort the key issues intelligently according to the set rules, and generate report forms. It is helpful for enterprises to pay attention to the changes of customer pain and concerns in real time and take corresponding measures. Shi.

Second, intelligent full quality inspection.

In the operation of call center, all kinds of data are very important, such as connection rate, call time, complaints, customer satisfaction and so on. These data correspond directly to the professional quality of customer service personnel or electric sales personnel. The difference of professional quality between different personnel is not entirely solved by training.

At this time, we need to be able to carry out a lot of monitoring and feedback, but before a lot of monitoring and quality inspection through manual sampling, not only time-consuming and energy-consuming, but also can only mention the completion of about 30% of the traffic quality inspection, which is somewhat unsatisfactory.

Now, new technology has brought dawn to the solution of this problem. Artificial intelligence technology for telephone quality inspection, it can be said to bring qualitative changes to the telephone quality inspection. Specific operation logic is as follows: we use ASR technology to achieve full-volume voice service transcription text, translated into text based on large data keyword matching, and finally complete the full-volume voice service text keyword red and statistics, so that we can clearly know the entire operation site traffic service quality statistics. And trend is also applied to all service quality analysis of a single salesperson.

Through the real-time quality inspection of artificial intelligence, not only saves the time of manual quality inspection, but also good statistics and analysis, customer's specific needs and complaint points, and summarizes the relevant laws, to help business development and complaint settlement.

For example, the call center receives a large number of complaints from users, and it takes several days of collation and analysis to clarify the cause and direction of customer complaints if the exact manual quality check is needed. And through manual quality inspection, not only can 100% of the business for quality inspection, but also grasp the keywords, forming a directional complaint collation, thus adjusting the product delivery.

In this regard, we can see that artificial intelligence for call center business promotion is very big, a lot of heavy, cumbersome work can be done through artificial intelligence, which is the traditional industry needs to make changes, but also the challenges of new technologies. In fact, the survival of enterprises, like learning, is going against the current in the trend of the times.

相关标签

智能客服质检,呼叫中心,呼叫中心质检

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