Various marketing methods have long been dazzling, but the essence is to study customers (consumers), research the needs and needs of customers, and make products ｏｒ services targeted. The era of big data has given it a new term: precision marketing. The first areas where big data is applied are mostly for the customer-facing industry. The first application scenarios are mostly precision marketing.

“Wine is good, and the alley is deep.” Information about products ｏｒ services should be delivered to customers before they can lead to transactions. It is generally believed that it is up to advertising to convey product ｏｒ service information to customers. Advertising has existed in the past, and the "three bowls are not on the job" wine cellar is advertising. In the era of no Internet, we are familiar with TV commercials, radio advertisements, print print advertisements, outdoor billboards, etc., of course, including sipping and selling. But the past advertisements are thousands of people and do not distinguish between audiences. Later, the merchants have collected CRM information from customers, and after customer classification, they can better serve different customer groups. The Internet + Big Data era has given CRM new opportunities for development. Managing customers is no longer a simple digital statistic and no personal (ｏｒ simple clustering) direct mail ｏｒ fixed investment. As merchants know more about customers and understand more deeply, they have the opportunity to provide customers with personalized marketing solutions to further improve the customer experience and become personalized marketing ｏｒ precision marketing. In the era of big data, many of the past impossibility has become possible, and marketing activities have also won new development opportunities.

Different times, the form of business management will change, but the essence is two things: open source, throttling. Open source is to open up new customers and discover new business opportunities; throttling is to reduce internal operating costs and improve resource utilization efficiency. To achieve this requires data-driven decision making. In the past, people also collected and applied many strong related data related to business activities in long-term business activities, and also formed the criteria for selecting customers. In view of the technical bottleneck at that time, the cost of data collection and data analysis for large samples was too high to be widely used. In the era of big data, people have the possibility of collecting data and storing data cheaply. Cheap computing resources make data analysis possible.

Behind the big data precision marketing is to use multi-dimensional data to observe customers, describe customers, that is, for customer portraits. It is no exaggeration to say that relying on big data can make marketers know customers better than in the past and understand customers' needs better than customers themselves. Marketers don't want to know who the customer is, where they are, what the consumption habits are, what they need, when they need it, and how to pass them to them more effectively. The answer can be found through data collection and data analysis. Accurate marketing can not only help businesses open source -- discover potential customers, but also help merchants cut costs -- to identify potential risks. When we learn more about our customers, we know which customers may be at risk.

If you ask each operator whether they will use their experience to market, most of the answers are yes. But if you ask the operators whether they will use the data for marketing, I am afraid the answer is very varied. It is generally believed that the application of data for marketing is a big company's business, and it has no connection with small companies. In fact, as big as multinational companies, as small as street vendors, using data for marketing, they will receive unexpected results. Don't believe it? Street vendors pay attention to the weather forecast (wind, rain, ｏｒ exposure) to know what business opportunities there are tomorrow, and then know how to stock up. It is recommended that people in small and medium-sized companies should not reject the idea of precision marketing, and may wish to learn the methods of precision marketing. Even if the operator has a wealth of experience, it will be helpful to digitize the experience to operate.

The book "Subversion Marketing" is to teach readers how to use big data to do marketing. The book is rich in cases and the language is readable. It is worth reading about all the friends of big data marketing.

I agree with many points in the book: "Big data redefines the rules of industrial competition, not the size of the data, not the statistical technology, nor the powerful computing power, but the ability to interpret the core data." Today, many people are entangled in the definition of big data, we really should pay more attention to the core value understanding and application of data. The question asked in the book is also very important. The operators usually have a lot of problems, but when they ask the question, there may be deviations, which leads to "a thousand miles of lost." Asking questions about the ability to improve involves thoughts and methods that need to be improved during exercise. Verifying that the question is right is exactly where the data analyst can contribute.

The book also raises two questions that deserve more in-depth thinking:

It is not enough to just find out the consumption habits of different customer groups and remind customers to spend at the right time. For example, a consumer's normal rational consumption for one month is at the level of two thousand yuan, and is generally consumed in two stores, A and B. The A store uses the concept of precision marketing to allow consumers to spend both of these two thousand dollars in the A store. With the B store's later, the consumer may return to the B store to spend two thousand dollars. Today, when the demand for excess supply is insufficient, the distribution ｏｒ migration of existing consumption among different businesses cannot bring about an increase in the total amount of social consumption. A higher level of application for big data marketing is to know in advance the needs of customers that have not been met ｏｒ even discovered. The value mining of big data has the opportunity to connect merchants (including manufacturers) with customers, so that merchants can provide more products ｏｒ services that meet the individual needs of customers, so that customers' willingness to consume will increase. This is a new challenge for data value mining workers.

The more data, the better? Many big data companies are keen to use crawlers to "crawl" various data online. However, the same data set has different value density in different application scenarios. The specific application scenario is not the more data dimensions, the better. It is necessary to collect data and use data around the application target. Raising the dimension to collect more data must help to describe things in more detail, but undoubtedly increases the complexity of processing data. Every advancement in technology has brought new imagination to human beings. It is inevitable that desires will be inflated and confident, and the cognition of the world will be upgraded, even unrestrained. Later, it was discovered that the use of resources for the promotion of the dimension, the wisdom can not keep up, the unconstrained upgrade is the complexity of the solution, calm down will restart the thinking of dimensionality. Perhaps human cognition and wisdom are alternately moving forward in dimensioning, dimension reduction, re-elevation, and then dimension reduction. The book's dimensionality thinking, if necessary, return to the element of thinking to give people a revelation.

The tools of the big data era are of course important, and the way of thinking is more important.