In the coming years, with the in-depth development of the Internet, social networks, and mobile technologies, Big Data will continue to grow at a high speed and enter the period of deep cultivation and landing. In the post-big data era, how to use data analysis technology to quickly acquire real business insights will become the key to business success. As a very important part of big data, “customer voice big data†is related to customer needs. Effective analysis of “customer voice big data†can help companies to see the customer’s real needs, and then take corrective action to optimize business processes and improve customers. Satisfaction, improve business capabilities. "Client voice big data" is not just from social media. In fact, for most companies, most of the customers’ voices are hidden in customer calls, e-mails, networks, and surveys. "Customer voice big data" therefore also has the characteristics of mass, channel diversity. In addition, the survey found that more than 90% of "customer voice big data" is unstructured, including customer voice, text, web pages, images, video and multimedia, all kinds of information can not be marked with numbers and symbols. How to tap the voice of customers from these complex, intricate and disorderly unstructured data has become the biggest challenge for many companies to analyze the voice of customers. Capgemini's research work, The Deciding Factor: Big Data & Decision Making1, shows that 40% of senior corporate respondents stated that it is difficult to use and analyze non- Structured data. Transform unstructured data into structured data Converting unstructured data into structured data requires the use of advanced data analysis tools. Verint's customer voice analysis solution can structure massive amounts of voice and text data through business classification and service grooming, find the focus of customers, find common problems of customers, and the causes and focus of customer complaints. Verint's customer voice analysis solution has three main components. The first major component is the speech analysis engine. Speech analysis engine is different from ordinary speech recognition. It is built on the basis of mass recording recognition. It seeks the commonality between businesses to find the most concerned or core issues in the process of interaction between companies and customers, and then helps enterprises These issues are to be further analyzed and processed to gain insight into the real demands of customers. Followed by the text analysis engine. The text analysis engine can automatically identify the natural language generated by various customer contact points such as e-commerce, e-mail, Weibo, and Wechat, deeply dig and analyze the customer sentiments contained in the text information, and analyze the customer sentiment through the form of reports. The results are presented to business decision makers. Finally, it is customer feedback analysis. Through enterprise-level customer feedback analysis, scattered and messy customer feedback information from different channels can be integrated into a unified report for use by enterprises. Establish a collaborative and unified "customer voice big data" analysis platform Massive and diversified “customer aspirations big data†has made it difficult for companies to conduct unified analysis of customer feedback information from different channels and disorganized. On the other hand, due to the different channels of access to customer information accessed by various departments of the company, the tools for mining customer information used are also varied. As a result, the voices of customers obtained by various departments of the company are also very different, and it is difficult for enterprises to distinguish their work priorities. Take corresponding actions, which in turn lead to the company being harassed by "unrelated listening." Capgemini's report shows that 56% of respondents surveyed believe that "isolated islands" is the biggest obstacle to making effective decisions using big data. Therefore, the establishment of a collaborative and unified "customer voice big data" analysis platform will help enterprises to gain a comprehensive insight into the customer's true "voice" and appeal, and truly provide useful information for business decision-making. At the technical level, companies can apply solutions that provide unified analysis capabilities. Verint's Operations Management Optimization Suite can collaboratively process data from different sources into a unified analysis platform that presents all the analysis results on a unified interface. Enterprises can see from this unified interface where the focus of complaints from the voice analysis customer complaints comes from text analysis where the hot spots of the current media are, where the most mentioned concerns are, and the preferences of the customers. At the same time, companies need to optimize organizational structure to solve the problem of each department's own governance in the analysis of customer voice data. At present, although there is still some distance from the actual landing of big data, voice analysis, text analysis, and other “client voice†analysis technologies are not new technologies at home, and they have been successfully implemented in companies in various industries such as telecommunications, finance, and insurance. . In the era of big data, it is a challenge but an opportunity for companies to obtain comprehensive, real “customer voice†insight from massive unstructured data. The use of effective customer voice analysis technology will help companies improve their performance, enhance their competitiveness and achieve intelligent enterprise management. Disclaimer: All the works that indicate the source of this site are copyrighted or have the right to use the works legally owned by this site, welcome to reprint and indicate the source. All non-Bennet works are from the Internet, and the purpose of the reprint is to convey more information. 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Read and understand the "customer voice" in the era of big data