Top 5 Gartner customer service technologies in 202

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Gartner 2020 customer service technology five trends recently, Gartner released the five trends driving Gartner 2020 customer service and support technology maturity curve. The following is a free translation of the content in Chinese. At the same time of translation, chatopera slightly modified the original content. Chatopera's view does not represent the original author's view

customer service supervisors can use Gartner technology maturity curve to evaluate the maturity and deployment risk of customer service technologies and products

in order to create a leading customer service experience, today's enterprises need to use various technical means. However, each technology needs careful consideration and evaluation in order to improve the user experience as a whole and obtain considerable returns

the Gartner 2020 customer service and support technology maturity curve report describes 33 technologies, and gives the evaluation conclusions of each technology: how advanced the technology is, how much it is hyped and exaggerated, and what kind of return it can get by choosing to apply them

gartner technology maturity curve

gartner technology maturity curve method helps to understand how a technology or application evolves over time, thus providing a reliable source of business intelligence analysis to guide the application of these technologies in the context of specific business objectives

each technology maturity curve divides the technology life cycle into five key stages

innovation trigger/technology embryonic stage: potential technological breakthroughs are about to begin. Early proof of concept reports and media attention caused extensive publicity. Generally, there is no available product, and the commercial feasibility has not been proved

peak of inflated expectations/expectation inflation period: early publicity has produced many successful cases - usually accompanied by many failures. Some companies will take action, but most will not

try of disillusionment/bottom period of Foam Burst: with the failure of experiment and implementation, people's interest gradually weakened. Technology creators are abandoned or fail. Investment will continue only if the surviving providers improve their products to the satisfaction of early adopters

slope of illumination/steady climb recovery period: more examples about how the technology benefits enterprises began to be concretized and gained wider understanding. Technology providers launch second and third generation products. More enterprise investment experiments; Conservative companies remain cautious

platform of productivity/production maturity: mainstream adoption began to surge. The criteria for evaluating the viability of suppliers are more explicit. The broad market applicability and relevance of the technology have clearly paid off

in chatopera's view, Gartner's report conclusion is based on the use and results of various technologies by existing enterprises. This year's results represent the results of last year, so the results of the report year have not been reflected in the report. In fact, for an enterprise that wants to take the lead in customer service and break the unfavorable situation in the competition, it should start from whether the functions of different product providers meet their own needs. The Gartner report can be used as a side reference, but not as a direct reference. Enterprises should make decisions and control risks according to their own conditions and the latest products and technologies in the market. In addition, when enterprises enter the market at the mature stage of technology, it is difficult to enjoy the technology dividend. Often, there is no other choice, and the surrounding competitors have to adopt it. In fact, it is quite different from the situation in which the leading enterprises in the field take the lead to try and get the most return. It is either a leading enterprise or a rising star who wants to catch up with and surpass. Technologies with certain risks should be deployed as soon as possible. At least 1% of the annual operating income of the enterprise shall be used to try new technologies

five key technologies focused in the field of customer service

the priority of customer service experience provided by organizations or enterprises has been changed by covid-19 COVID-19. Drew Kraus, an analyst at Gartner vice president, said that one performance is that this year's maturity curve shows that customer service executives are more concerned about selecting a wide range of technical means to create a complete and well integrated customer service system. In this way, the enterprise customer service experience is consistent, spend less manpower, and obtain a more intelligent and personalized customer service experience. In addition, enterprises can better analyze returns. Guide enterprises to ensure that the customer service system is in line with expectations

for those enterprises that want to make ambitious strategies in customer service, Gartner has identified five key technologies for these enterprises to try, which have been clearly identified in Gartner 2020 customer service and support technology maturity curve. These options should become the most noteworthy options for enterprise account executives: customer interaction center, customer service analysis, customer voice, Chat robot and virtual customer assistant

figure 1 Gartner hype cycle for customer service and support technologies, 2020

the above figure is a technical summary of Gartner based on the data obtained in August 2020. Different colors and shapes represent Gartner's prediction that it will take several years for this technology to enter the rightmost region: the production mature region. According to the example, the years of entering the mature production area are as follows:

less than 2 years

rpa, consumer messaging applications, customer engagement center, work from home agent technology

2 ~ 5 years

workforce engagement management solutions, customer journey analytics, IOT for customer service, augmented reality for customer support, 360 degree view, customer service analytics, In-App Mobile Customer Service, Video Calling for Customer Service, Voice-of-Customer Solutions, Chatbots, Recorded Video Customer Service, Speech Analytics for Customer Service, Knowledge Management for Customer Service, Visual Customer Assistants, Field Service Workforce Optimization, Proactive Communications Applications and Services, Contact center as a service

5 ~ 10 years

muleexperience, blockchain for customer service, emotion AI, field service dragons, customer psychology, digital experience platforms, customer engagement hub, conversational user interfaces, natural language processing (NLP)

*work from home agent technology and home office technology have entered a mature stage. Bold bold is the most concerned customer service technology in 2020

customer engagement hub

customer engagement hub (CEH) is an architectural concept that integrates multiple systems to help customers have the best interactive experience. The customer interaction center uses artificial, artificial intelligence, sensors and other methods to complete cross interaction channels. It starts to communicate with customers actively or passively, giving customers personalized and context related service experience. For example, it reaches all departments and synchronizes information about marketing, sales or customer service processes

the isolated island of operation and technology is still a difficult problem that large enterprises must face. Kraus said that, however, the rapid rise of attention to the customer interaction center will integrate more personalized, consistent and consistent experiences into the customer service process. Both the business department and the IT Department of the enterprise agree with this view

customer service analysis

customer service analysis optimizes customer service experience by comprehensively analyzing customer service data, such as using desktop software, text and voice for interactive analysis, using user page Jump to analyze user stories, and using user behavior prediction that can absorb fruit and vegetable juice. Customer service analysis collects real-time data and historical data, provides friendly man-machine interface for customer service, and provides more business intelligence and decision support

deploying customer service analysis software is conducive to discovering potential relationships. These findings can optimize enterprise operations and consultants' suggestions. But customer service analysis also has a big challenge. Enterprises must deploy such a system before they can get a return

voice of customer

voice of customer (VOC) solutions connect traditional data collection, storage and analysis technologies to act on indirect or direct customer feedback, thus breaking multiple technology silos. By unifying the information sources fed back by different customers, enterprises will find more sophisticated business intelligence and guide enterprises to be more confident and accurate in making decisions. These decisions affect individual consumers and the overall architecture, such as what to dial in the call center, the adjustment of a business process, and so on

the purpose of comprehensive analysis is to ensure that the right decisions are made to the right employees and are immediate. These business intelligence data help enterprises manage brand image, understand user intentions and strategies to upgrade customer interaction experience

chat robot

chat robot realizes human-computer dialogue interaction through app, instant messaging service platform, social networking or chat solutions. There are many forms of chat robots, from simple marketing robots in the form of decision trees to robot platforms that use various cutting-edge technologies to achieve more functions. Robot customer service, which has appeared before, has become an important response means for many companies during the covid-19 COVID-19. Robot customer service plays an important role in enterprise operation. This will accelerate the development of chat robot technology

chat robots will step into the customer service position of enterprises in 2020, which is in line with the needs of enterprises in both open source and cost saving. Chatopera has also clearly felt this trend in the operation of chat robot platform. Even if the data analysis from March to may 2020 is 10 times higher than that from January to February 2020. The deployment and launch of chat robots will be faster than ever in 2020

virtual customer assistant

virtual Customer Assistant (VCA) is an application that helps enterprises release messages to consumers or issue behavior operations from the perspective of consumers. Its purpose is to make the interaction between enterprises and consumers more frequent and convenient. Virtual customer assistants are very different from chat robots. Virtual customer assistants need more infrastructure investment, memory, and a closer relationship with consumers

although the virtual customer assistant has more functional requirements, its technical implementation is basically the same as the chat robot technology. The two have a great intersection, such as natural language processing, speech recognition, information retrieval, in-depth learning, cluster analysis, etc. in chatopera's view, the virtual customer assistant should be based on the chat robot and integrated with more enterprise business units

the virtual customer assistant extends the customer interaction objectives of the enterprise to a larger scale, breaking through the scope that was not covered before, especially from the perspective of the contact center. For example, the use of voice based virtual customer assistants in newsstands or machine announcers can not only reduce the pressure of typing, but also help non-traditional potential customers to stimulate their interest in enterprise products

reference article

application effect analysis of customer service robot

5 trends drive the Gartner hype cycle for customer service and support technologies, 2020

gartner technology maturity curve methodology

bots gain im uses air preservation attributes to protect heavy objects

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