Various marketing methods have been dazzling for a long time, but their essence is to study customers (consumers), what customers want and need, so that products or services can be targeted. The era of big data has given it a new term: precision marketing. The first application fields of big data are mostly customer facing industries, and the first application scenarios are also precision marketing.
"Good wine is also afraid of deep alley". Only when the product or service information is delivered to the customer can the transaction be facilitated. It is generally believed that the communication of product or service information to customers depends on advertising. Advertising has existed since ancient times, and the liquor front of "three bowls are not enough" is advertising. In the era without the Internet, we are familiar with TV advertisements, radio advertisements, print advertisements, outdoor billboards, and of course, shouting and selling. However, in the past, advertisements were one-sided and did not distinguish between audiences. Later, when merchants collected customer information, they had CRM. After customer classification, they could better serve different customer groups. The era of Internet+big data gives CRM a new development opportunity, and customer management is no longer simple digital statistics or personalized (or simple clustering) direct mail and fixed investment. As businesses know more about customers, they have the opportunity to provide personalized marketing programs for customers, further improve customer experience, and become personalized marketing or precision marketing. In the era of big data, many impossibilities in the past have become possible, and marketing activities have also won new development opportunities.
In different times, the form of commercial operation will change, but the essence is two things: open source and cost saving. Open source is to open up new customers and find new business opportunities; Throttling is to reduce internal operating costs and improve resource utilization efficiency. To achieve all of this, data based decisions are needed. In the past, people also collected and used many strong relevant data related to business activities in long-term business activities, and 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 popularized in a wider range. In the era of big data, people have the possibility to collect and store data cheaply. Cheap computing resources make data analysis possible.
Behind the big data precision marketing is the use of multi-dimensional data to observe customers, describe customers, that is, to paint customers. It is not too much to say that "relying on big data can enable marketers to understand customers better than in the past, and understand customers' needs better than customers themselves". Marketing personnel all want to know who the customer is, where they are, what their consumption habits are, what they need, when they need it, and how to transmit information to them more effectively. The answer can be found through data collection and data analysis. Precision marketing can not only help businesses open source -- find potential customers, but also help businesses cut costs -- find potential risks. When we know more about customers, we will know which customers may have risks in operation.
If asked whether each operator will use their experience in marketing, most of the answers are yes. But if you ask the operators whether they will use data for marketing, I'm afraid the answers are various. It is generally believed that the application of data for marketing is the business of large companies, not small companies. In fact, from multinational companies to street vendors, using data for marketing will receive unexpected results. Don't believe it? The street vendors will know what business opportunities are available tomorrow and how to stock up after watching the weather forecast (wind, rain, or exposure). It is suggested that people in small and medium-sized companies should not reject the concept of precision marketing, but learn the thinking method of precision marketing. Even if the operator has rich experience, it will be very helpful for the operation to digitize the experience.
The book Subversion Marketing is to teach readers how to use big data for marketing. The book is rich in cases and readable in language. It is worth reading for friends from all walks of life who care about big data marketing.
I agree with many points in the book: "Big data redefines the rules of industrial competition, not the size of data, not statistical technology, nor strong computing power, but the ability to interpret core data". Today, when many people are obsessed with the definition of big data, we really should pay more attention to the understanding and application of the core values of data. The "ask the right question" in the book is also very important. There must be a lot of problems for operators at ordinary times, but there may be deviations when they ask about the truth, which leads to "a thousand li is lost if one is lost". The improvement of the ability to ask the right questions involves the way of thinking, which needs to be improved in practice. Verifying whether the question is asked correctly is exactly where data analysts can contribute.
This book also raises two questions that deserve further consideration:
It is not enough to just find out the consumption habits of different customer groups and remind customers to consume in a timely manner. For example, a consumer's normal and rational consumption in a month is at the level of 2000 yuan, which is generally consumed in stores A and B. Store A uses the concept of precision marketing to make consumers spend the two thousand yuan on Store A. With Store B coming from behind, consumers may return to Store B to spend the two thousand yuan again. In today's era of oversupply and insufficient demand, the distribution or migration of existing consumption among different businesses cannot bring about an increase in the total social consumption. A higher level application of 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 businesses (including manufacturers) and customers, so that businesses can provide more products or services that meet customers' personalized needs, and customers' consumption willingness can be improved. This is a new challenge for data value mining workers.
Is the more data really the better? Many big data companies are keen on "crawling" various data on the Internet with crawler software. However, the value density of the same data set is different in different application scenarios. For specific application scenarios, the more data dimensions are not the better. You must collect and use data around application goals. Raising dimensions to collect more data must help describe things in more detail, but it undoubtedly increases the complexity of processing data. Every technological progress has brought new imagination space to human beings. It is inevitable that desire will expand and self-confidence will be full, and the cognition of the world will also increase, even without control. Later, it was found that the dimension upgrading brought about the occupation of resources, and the wisdom could not keep up with it. The uncontrolled dimension upgrading led to the complexity of the solution. When calm down, it would restart the thinking of dimension reduction. Perhaps human cognition and wisdom are moving forward alternately in the process of dimension raising, dimension lowering, dimension raising and dimension lowering. The dimensionality reduction thinking of this book, when necessary, gives people enlightenment by returning to the original thinking.
In the age of big data, tools and means are certainly important, and the thinking method is more important.
