Insight into customer needs from big data

In Hangzhou, I met a fortune teller. Because I often meet him, I gradually get to know him. Once, I asked him seriously, is fortune telling really credible? He told me very seriously that fortune telling is actually a statistic and a summary of many lives in the past. If it is not accurate, it can only be said that the level is not up to home.

In fact, people make various predictions based on the statistical analysis of the data that happened in the past, including investment analysis, ball game result prediction and even Oscar award prediction, and predict a trend. However, in the past, due to the limitations of technology and hardware, it was difficult for us to save a large amount of data, so the data that could be analyzed was always limited. However, with the development of science and technology, especially the birth of a series of technology companies such as IBM, Microsoft and Google,

There is no doubt that big data has become the hottest business vocabulary. Searching for "big data" on Google can get 65.2 million results. In enterprises, we also find that more and more companies are beginning to pay attention to big data, but the real situation is that few companies can extract valuable information from data, and even fewer make decisions based on data. The reason behind this is that in most companies, the investment in data analysis is random and temporary, and there is no reasonable planning and strategy.

All along, enterprises have emphasized "customer-centered" and customer demand-centered. It's easy to know, but it's hard to really do it. In fact, the bankruptcy of many enterprises can finally be attributed to staying away from customers. In the past, we learned about customer needs through pre-market research, communication with customers and questionnaire survey. Today, more and more enterprises are using big data to gain insight and analyze the actual needs of customers. Research shows that it is more accurate and targeted.

Kraft Australia, the world's second largest food company, crawled and analyzed 654.38 billion social network posts and 500,000 forum discussions through big data analysis tools, and found that the focus of discussion on Virgil sauce was not the taste and packaging, but the various ways to eat it except toast. Finally, the investigators analyzed three issues that consumers care about: health, vegetarianism and food safety, and found that folic acid is particularly important for pregnant women. Therefore, Kraft conducted marketing based on this information, opened up the pregnant women's market, and the sales of Virgil sauce increased greatly, creating a historical record of this product.

Enterprises want to highlight their competitiveness in the fierce competitive environment, accurately capture customer needs to individuals, and provide customized services according to individual needs. Big data provides insight and action for this personalized service.

For a long time, China Unicom can only roughly calculate the monthly customer churn rate, and can't judge which customer groups will lose the most users, so it is difficult to lock in the needs of specific user groups to strengthen services. In theory, mobile phone users will have signs before returning the lease, and if they can catch the clues, they will have the opportunity to retain the guests. For example, if a mobile phone user's usage habit is mainly short messages, and the amount of short messages sent decreases within three months, he may fall into the arms of his opponent. If he can find out that he is using the "billing scheme based on each SMS", the marketing staff can promptly and accurately suggest him to switch to the preferential scheme of monthly SMS or free online SMS, which may attract customers to stay. By analyzing the real-time call records of a large number of customers, the predicted churn rate of China Unicom has increased by more than 5 times, the renewal rate of its Chongqing branch has greatly increased, and the number of 2G and 3G network users has increased by 6 times.

Similarly, many companies have used big data to open up new market maps and found new blue oceans, such as Alibaba. Alibaba is using big data to transform from an e-commerce company to a financial company, a data service company and a platform company. Alibaba's transformation will have a great impact on financial industry, logistics industry, e-commerce, manufacturing industry and retail industry. In fact, the rules of the game in these industries have changed because of the entry of Alibaba. Alibaba has made full use of big data and established a leading position in the industry.