The rapid growth of big data and the development of related technologies are bringing new business opportunities. How will big data change people's lives? How will it change the business of the enterprise? Victor Schoenberg pointed out in "Big Data Age: Great Changes in Life, Work and Thinking" that the biggest change in the era of big data is to give up the desire for causality and pay attention to relevance instead. In other words, you just need to know what it is, not why.
According to the prediction of relevant institutions, in 20 15 years, more than 90% business executives will regard information as strategic assets, but less than 10% business executives will fully realize the economic value of this information. Because of this, in reality, many consumers will have the feeling that I am a real name, but the merchants don't know me yet.
With the diversification of users' needs, enterprises had to swallow their pride before, because they didn't know the source of customers' needs. However, in the era of big data, enterprises have more opportunities to understand customers, and may even know their own needs better than customers themselves. Therefore, with the support of huge data, the personalized service in the past has a better extension and greater value.
Huge data also contains gold.
For ordinary people, big data seems far away, but its power is ubiquitous: credit card companies can track customer information, quickly find changes in funds, and issue early warnings to cardholders; Telecom companies track customers' travel trends and push relevant tourism or business information by region; Airline service companies send flight delay information in time ... these are inextricably linked with big data.
Statistics show that the amount of data accumulated in the world in the past two years has exceeded the sum of all previous histories, and it is still growing at an annual rate of 40%. In other words, the global data volume can double every two years. What is the value in the huge data? What is the significance of its existence? It depends on how the enterprise uses it.
The data contains a lot of information, and the most commercial value is the information related to consumers. If we can collect accurate consumer information, we can customize more personalized services for them and let us know them better than consumers themselves. Of course, not all consumer data is regarded as a treasure. Name, gender, age and even income are outdated information. Saying that they are outdated does not mean that they are worthless, but that such basic information is easy to obtain.
Information is fluid and changeable. Only by obtaining dynamic information can enterprises have the most commercial value. Dynamic information can help enterprises understand customers' consumption habits, such as whether they like online shopping or shopping, whether they like shopping during the day or at night, what is the difference between their consumption concepts and when they will make irrational decisions.
Personalized service, new wine in old bottles
Standardized service has made many well-known enterprises, whether it is catering, hotels or tourism, we can list many well-known brands. The so-called standardized service means that the services enjoyed by consumers are limited and standardized, and there is no difference in the actual experience of different consumers. Standardization has greatly reduced the management costs of procurement, manpower and services. However, with more and more products and services and more choices for consumers, businesses that always follow standardized services will find that their customers are gradually losing.
Why did the customer leave? Who did they choose?
The biggest drawback of standardized services is that enterprises treat all customers as one customer. When customers find that other services can meet their needs, it is easy for them to move on. In contrast, the management cost of personalized service is higher, which depends on the degree of personalization. Take Xiabu Xiabu as an example, it has a high standard service process, but at the same time it provides two different experiences for customers according to different consumption needs. One is a small hot pot of desktop dining system, which is suitable for fast food consumption of 2~3 people, and the other is a big hot pot of about 4 people, which is suitable for multi-person dinner, which is also the embodiment of personalized service. However, this degree of personalization is very narrow, and it is still based on reducing management costs and enriching its service types. In order to realize personalized service for thousands of people, enterprises must rely on huge data support and effective management.
Of course, thousands of personalized services can play a role in all walks of life, but it is still the industries and products related to network digitalization that can make full use of the value of data. The biggest advantage is that enterprises can obtain users' online records in real time through technical support and provide customized services in time. In the middle of July 20 13, the iqiyi PC client was completely revised. The biggest feature of the new version is that it relies on data analysis to provide users with comprehensive personalized video content recommendation on the home page. In other words, different users' PC clients will display different homepage contents, and they are all interested.
20 1 1 On September 27th, Haier and Tmall launched customized TV activities online. Customers can choose the attributes such as size, border, definition, energy consumption, color and interface before TV production, and then the manufacturer will organize the production and send it to customers' homes. This personalized service is so popular that 1 0,000 customized TVs were robbed in two days. Similar customized services have also appeared in industries such as air conditioning and clothing, and have also been welcomed by customers.
These examples have shown the dawn of the future business-by meeting individual needs, customers can get more satisfactory products and services, thus shortening the cycle of design, production, transportation and sales and improving the efficiency of business operations.
Why is personalized service difficult to land?
According to statistics, 95% of enterprises don't use their data, and 39% of marketers think they can't correctly predict customers' needs through data. Such a large amount of data is vacant, and a considerable proportion of data is always wasted, so it is not that personalized services are difficult to land, but that the data is not fully and effectively used at all. At the same time, limited by the current technical level, it is difficult to convert data into services. It's like you have a beautiful jade, but you don't have the exquisite manual skills to carve it into a priceless work of art.
The white paper "Analysis: Application of Big Data in the Real World" released on March 20 13 provided five key suggestions for the application of big data, including "taking customers as the center" and making an early "big data strategic plan"; Formulate a comprehensive and complete enterprise "big data blueprint"; Starting from the existing data, set and complete short-term and phased "big data strategic goals"; According to business priorities, gradually establish an analysis system and gradually improve the "big data analysis ability"; Customize measurable indicators to analyze "Big Data ROI".
This conclusion comes from the big data research conducted by IBM and Oxford University. The project surveyed 1 144 business people and IT professionals from 26 industries in 95 countries around the world, and interviewed more than 20 scholars, business experts and corporate executives.
Ideal personalized service
In order to provide users with ideal personalized services, enterprises must master two points: first, how to fully understand users' personalities through data; The second is to reasonably control and design the personalization of services.
Understanding users' personality is to provide users with the products and services they want. First of all, enterprises need to find the most valuable data in a huge database; Secondly, users with the same data performance are divided into one category, and targeted services are designed according to the data performance of users. Here, whether the enterprise's service can be in place depends on whether the core data is grasped. However, one question we have to think about is: If there are too many service items classified by data analysis, will it lead to an increase in management costs and a decrease in service efficiency?
Personalized decentralization units can be large or small, as large as a customer group with the same needs, and as small as each user is a personalized demand unit. However, too scattered personalized service will increase the service cost and management complexity of enterprises, so it is necessary to control and design personalized service reasonably. Consider whether all the data provided should be turned into services. Is the increased cost in direct proportion to the actual income? What's the point if the growth of service cost can't get a better return?
In short, the biggest difficulty for enterprises to realize personalized service is the reliability of key data and the controllability of management costs. Specifically, the starting point of personalized service design is the analysis of key data. If the data screening analysis is wrong, the result can be imagined. Personalized services are accompanied by various costs, such as data management. To some extent, personalized service can only be based on consumer groups, not every consumer, and at the same time, the actual cost input and income return of enterprises must be considered.
Four steps of personalized service landing
1, extracting massive basic data. Owning big data is like owning a gold mine. The gold content of this gold mine directly affects how much gold can be extracted. Similarly, the quality of big data directly determines how much data can be used by enterprises in the future.
2. Mining useful core data. Extracting useful data from basic data for sorting and matching is data mining. Data mining needs professional data companies to operate, and it is difficult for ordinary enterprises to have such professional ability. So, are companies willing to open their core data? Can you afford to hire a professional company? These all need to be weighed.
3. Respond to marketing data. After the data results are used for marketing, enterprises should respond. After data mining, it can be applied to a certain market segment, and enterprises should formulate targeted marketing strategies.
4. Maintain member service data. The implementation of marketing plan and follow-up service will further test the management and adaptability of enterprises.