Shulou(Shulou.com)11/24 Report--

The heat of AIGC continues, and the landing is more and more widespread. One phenomenon is that artificial customer service is disappearing, and users are receiving more and more AI calls. Although there are some complaints that "AI after-sales customer service still can not solve the problem" and "artificial customer service can not be found", the intelligence level of AI is constantly improving, the cost reduction and efficiency improvement effect brought to enterprises will continue to appear, and the market scale of AI customer service is still expanding. According to the 2023 China Intelligent customer Service Market report recently released by Sullivan, a well-known international market research institute, the size of China's intelligent customer service market reached 66. 5% in 2022. 800 million yuan, and the market is expected to grow to 181. 5% by 2027. 300 million yuan, with a compound growth rate of more than 20% within five years. The scope of application of AIGC will continue to expand, and how to make good use of AI in various scenarios of communication between enterprises and users is gradually becoming a must-answer.

Customer service is one of the epitome, as a highly standardized type of work, it is also very easy to be replaced by AI first. Now some consumers think that AI customer service is not easy to use. First, because the authority has not been adjusted in place, some AI customer service can only answer questions, repeat apologies, can not solve the problem, make reasonable compensation and so on. One of the reasons why Haidilao service is good is that it is authorized for waiters, and the front-line waiters have the right to give consumers a discount. Second, AI's understanding of vertical scenarios is not deep enough, and AI, which can already talk normally in the general field, is almost hot in the professional field. Third, AI needs to get through various systems to access orders, goods, logistics and other information, while understanding users' natural voice and related specific information for many times smoothly, the requirements are very high.

This requires science and technology enterprises in various industries to use massive vertical data and train them on the basis of the general large model to improve the industry large model. Take multipoint DMALL, which serves the digital intelligence transformation of brick-and-mortar retailers, as an example, the digital retail SaaS is the largest retail cloud solution service provider in Asia, serving six countries and regions. In the past few years, in extensive cooperation with brick-and-mortar retailers, Multipoint DMALL can use a large number of people, goods, and market data to train AI in the retail vertical industry, providing a complete set of software and hardware such as intelligent marketing, intelligent selection, automatic ordering, intelligent scale, end-to-end retail scene and omni-channel digital intelligence. Today, in the era of AIGC, Multipoint DMALL still maintains the leading practice in the retail vertical industry, and has cooperated with first-class large model companies at home and abroad to develop products and services suitable for retail scenarios.

AI customer service should reduce costs and improve experience at the same time.

In terms of customer service, we have chosen the function of "AI customer service quality inspection" as a starting point, and have landed in the actual business of partners. The direct customer of multipoint service is the B-end retailer. Domestic physical retailers have been caught in fierce competition in the stock market, which not only helps retailers to reduce costs and improve efficiency, but also helps them to improve the experience of C-end consumers. Multi-point use of large language model to detect customer service recording, identify customer service quality and customer feedback, to achieve customer service work order voice full AI quality inspection, reduce labor costs and improve the service level of retailers.

Through a large number of "professional data" training, AI customer service can improve user satisfaction through automatic response and personalized service. Especially in the after-sales service, it is necessary to analyze the user's voice, tone and emotion in order to better understand the user's needs and problems; by analyzing the user's historical data and behavior and obtaining the corresponding authority, can we solve the problem more pertinently? On the basis of 7-hour 24-hour "work", we should also "learn" to give way to human customer service at an appropriate time, so as not to let the stock of users be lost because "manual customer service can not be found".

Another exploration direction is the collection of user feedback, in addition to the direct feedback of the phone, user evaluation and voice scattered in various channels, active questionnaires of merchants, etc., AI can better analyze and generate reports, so as to help enterprises better understand the needs of users. While serving physical retail, the integration of online and offline customer service is also a proposition, including the customer needs handled by manual services in Shang Chao, the extensive use of intelligent IoT settings, in which valuable data are worth being included in the system. AI provides a way to deal with these data in a low-cost and efficient way.

AIGC brings the Evolution of Smart Marketing

In user communication, AIGC can undoubtedly play a great role in marketing scenarios to automate and personalize marketing at a lower cost. We know that copywriting, pictures and videos can be generated quickly with AI. On this basis, multi-point has also developed AI smart marketing suitable for physical retail. In the process of changing from offline to online and offline omni-channel marketing, there is not only the demand for cost reduction, but also the gap of talents.

In interaction and marketing, "one picture is worth a thousand words", with emotional voice can also move people, live broadcast has reflected this incisively and vividly. AIGC can produce high-quality and rich content at low cost, so that Shang Chao can show more goods and activities with videos and pictures.

Takeout platform, short video, live broadcast. Various channels are competing for offline customers, and brick-and-mortar retailers are also actively moving into various platforms, but there is a lack of talents who are good at operating these channels. And AI smart marketing can generate different styles of material to adapt to different channels.

In particular, private domain traffic operation is the key to the current development of physical retail enterprises. The use of AIGC technology can more intelligently reach offline users, transform it into private domain traffic, operate continuously and efficiently, and spread the net into accurate recommendations, truly showing personalized content with thousands of people and thousands of faces, and displaying it in appropriate time and communication scenarios, so as to enhance user experience, reduce costs and increase sales opportunities.

B-end user communication reshaping

For retailers, C-end consumers are users, while for SaaS, which is a multi-point service retailer, B-end customers are its direct users. AIGC also has a lot of opportunities to give full play to its talents in customer communication on the B side. SaaS enterprises can not only use AI to generate code to reduce core R & D costs, but also have a lot of room for cost reduction in customer communication services such as marketing, customer service, training, etc., and finally enable customers to get quality services at a lower price. For example, the AI knowledge base allows shop assistants to directly use natural voice to ask how to use this function if they encounter problems when using a multipoint system. For example, customized sales plan, AIGC can complete from the basic clue recording, analysis, follow-up, to sales tutoring, and then to the output of the final sales strategy, according to customer needs to generate personalized solution PPT.

AIGC can efficiently process a large amount of data, and with this data, enterprises can formulate more effective business strategies. Data insight and operational strategies used to be analyzed and made by industry experts, but now strategic insights can be made through large models. Multipoint is still doing some things, such as implementing the conversion between natural language and data reports. The supermarket owner can ask the system directly: how was yesterday's gross margin? How does it compare with last year and the year before last? What's the difference? What do you do after that?

For B-end customers, the use efficiency is always a big problem in the process of digital transformation and replacement of the system. This new way of communication based on AIGC can make it more intuitive and efficient to obtain the required information, reduce the worry of transformation, and make the system really "easy to use and good to use".

AIGC is data-driven, reshaping user communication, and the confusion between human customer service and AI customer service may soon occur, and there will be more efficient communication between companies and users. However, how to communicate with users moderately may test the wisdom of enterprises.

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