The following paper on marketing I prepared for you, welcome to read for reference, and hope it will help you.

First, the evolution of the era of data analysis

(A) data 1.0 era

Data analysis appeared after the realization of new computing technology, and the era of analysis 1.0 is also called the era of business intelligence. Through the objective analysis and in-depth understanding of business phenomena, intuitive and outdated market research reports are prohibited in decision-making, helping managers to rationalize and maximize decision-making based on facts. For the first time, with the help of computer, the data of production, customer interaction and market are entered into the database for integrated analysis. However, due to the limitation of development, the use of data is more about preparing data, and little time is spent on analyzing data.

(b) Data 2.0 era

The 2.0 era began in 2005, which is different from the requirements of company analysis ability 1.0. Xinshida requires quantitative analysts to have superior data analysis ability. The data comes not only from inside the company, but also from outside the company, the Internet, sensors and various publicly released data. For example, LinkedIn makes full use of data analysis to seize opportunities and develop impressive data services.

(3) Data 3.0 era

Also known as the product era of rich data. The standard for analyzing the coming of the 3.0 era is that large companies from various industries have stepped in. Companies can analyze data well and guide appropriate business decisions. However, it must be admitted that with more and more data, the update speed is getting faster and faster, which brings both development opportunities and challenges. How to make use of this change in business is an urgent task.

Second, the essence of big data marketing

With the arrival of the era of customer-oriented logic and the emergence of multi-channel shopping methods such as Internet e-commerce, the roles and needs of customers have changed, and the world is being perceived, interconnected and intelligent. With the advent of the era of big data, personal behavior can not only be quantitatively collected and predicted, but also the personal views of customers are likely to change the operation of the business world and society. Therefore, an era of personalized customer-oriented business needs has arrived. Under the impact of big data, the enterprise transformation led by marketing has begun to take shape.

(1) In the era of big data, consumers become the masters of marketing.

The traditional marketing process is to collect information from the current market through market research to help enterprises develop, produce, market and promote. But today, with the prevalence of big data and social media, this marketing model is eclipsed. Nowadays, consumers have become the masters of marketing, and they will actively search for commodity information, shop around and strictly screen. They pay more attention to the experience value and situational value in the whole process of consumption from the previous value. Even the shaping of corporate brand image is no longer a single publicity of enterprises, and the word-of-mouth of virtual communities and shopping websites has begun to affect consumers' buying behavior. What's more, consumers' expression of personal needs through social media and other channels has become an important factor affecting product design, research and development, production and sales of enterprises.

(2) Accurate marketing of enterprises in the era of big data has become possible.

In the era of big data, the development of technology has greatly exceeded the imagination of enterprises. It has become possible to collect unstructured information. Big data can not only understand the possibility of market segmentation, but also be accurate to every customer through truly personalized insight. Through data mining and in-depth analysis, enterprises can grasp valuable information and help enterprises discover customers' thinking patterns and consumption behavior patterns. Especially today, customers have a unique consumption tendency in order to show their individuality. Compared with loyalty to a certain brand, customers are more loyal and position themselves. If an enterprise's brand can't maximize customer value, it is difficult to ensure customer continuity even if it patronizes again. Moreover, enterprises cannot expect to classify customers, because each customer's needs are different. Just like this, big data analysis can better grasp the consumer behavior and preferences of customers and make suggestions for the precise marketing of enterprises.

(3) Enterprise marketing concept in the era of big data-? Create value completely with customers as the center?

Traditional marketing and strategic point of view holds that mass production means standardized production mode, and there is no personalization at all. Customized production is personalized production, but it is only small-scale customization. After all, mass production and customization cannot be combined. But today, the marketing and sales of big data analysis have solved the contradiction between mass production and personalized needs of customers. Let large enterprises have one-to-one customer relationship management of traditional small convenience stores, and let large enterprises communicate with customers in real time with instant tools and personalized recommendations.

Third, the data-based case study of marketing-JD.COM

JD.COM is the largest self-operated e-commerce enterprise. Among them, JD.COM Mall covers clothing, cosmetics, daily necessities, fresh food, computer digital and other categories. In the whole mobile phone retail industry, JD.COM accounts for half of the market share in both sales volume and sales volume. The reason why it occupies such a favorable position is due to the application of big data, namely JD Phone's plan in JD.COM.

The JD Phone plan is based on JD. COM's big data and comprehensive service capabilities, integrate the high-quality resources of the industrial chain with users as the center, and cooperate with manufacturers to create the product and service experience that users expect. In the sales process, JD.COM developed a model called product portrait through the analysis of big data. This model integrates the information of consumers' shopping on JD.COM website, such as age, gender, preferences and other categories, and then makes an in-depth analysis. According to the analysis results, combined with different consumers, there are online programmatic buying, accurate click and other marketing methods, which effectively help JD.COM achieve accurate marketing push. Moreover, by analyzing the after-sales data of subsequent users' shopping, we can accurately analyze the shortcomings of goods or the direct needs of consumers. A characteristic of the data 3.0 era is that enterprises do not simply analyze data within the enterprise, but * * * enjoy the realized value * * *. Therefore, JD.COM uses these data to communicate with upstream suppliers on a regular basis, which indirectly promotes the communication between manufacturers and consumers, understands the market demand, and guides the next product market positioning. Generally speaking, this scheme is based on JD.COM's big data analysis. COM sales and after-sales links. On the one hand, guide their own precise marketing; On the other hand, it affects the product positioning and enterprise planning of suppliers, and ultimately provides consumers with personalized products that meet their needs.

Fourth, the strategic analysis of big data marketing

(A) data analysis should establish a people-oriented thinking.

? People-oriented? Reflected in two aspects. On the one hand, data analysis is customer-oriented, analyzing customers' needs, and using data analysis to guide the next product design, production and marketing. On the other hand, people-oriented is reflected in the confidentiality and reasonable application of user data. Effectively maintain privacy protection under the background of big data and Internet, and make information technology develop healthily.

(2) Correctly handle the contradiction between massive data and core data.

Big data has the characteristics of large amount of data, diverse types, low value density, high speed and high timeliness. Therefore, in the massive data, only the information that reflects consumer behavior and market demand is what enterprises need. Unnecessary data analysis will only affect enterprises to make correct decisions. In view of this, first of all, enterprises need to clarify the standards of core data; Secondly, enterprises should file the core data in time; Finally, there should be a professional data analysis team to analyze the data and draw scientific and reasonable results to guide practice.

(C) Integration of value chain * * * Enjoy data and realize value creation.