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How big data drives refined operations
How big data drives refined operations

With the rapid development of the Internet, the transmission of information is becoming increasingly convenient and fast, and the demand is becoming more and more prominent, looking at the entire Internet field, big data has been regarded as a major disruptive technological revolution following the cloud computing, the Internet of Things, the big data market is a gold mine to be mined, and its value is self-evident. Enterprise operation is very important for enterprises, because a good operation system will allow enterprises to easily cope with various situations in the market promotion. When we enter the DT data era, enterprises in the operation of the corresponding also changed, from the initial rough operation gradually transitioned to refined operation.

Big Data, for the first time in history, can be said to be the users of all walks of life, program providers, service providers, operators, and the entire ecosystem of upstream vendors, into a large environment, whether it's the enterprise market or consumer market, or the government **** services, are or will be inextricably linked with Big Data.

1. Why enterprises need to do fine-tuned operations

With the development of big data, enterprises are also paying more attention to the development and application of data, so as to obtain more market opportunities. On the one hand, big data can significantly improve the accuracy and timeliness of enterprise data; in addition, it can also reduce the transaction friction cost of enterprises; more critically, big data can help enterprises analyze a large amount of data to further explore market segmentation opportunities, and ultimately shorten the time of enterprise product research and development, enhance the innovation of the enterprise in the business model, products and services, and significantly improve the level of business decision-making, which reduces the risk of enterprise operation. Reduce the risk of business operation. Big Data is a new perspective on reality, changing not only marketing and manufacturing, but also business models. Data itself is a source of value, which means new business opportunities. No industry is immune to big data, and adapting to it is the only way to survive this change.

For enterprises, the benefits of creating a fine-tuned operation lies in the ability to track and portrait the characteristics and profiles of target user groups or individuals, helping enterprises analyze the characteristics and habits of users in a certain period of time content, and finally allowing enterprises to form a kind of exclusive services based on the characteristics of the user and create.

It is precisely for this reason that enterprise operations in the DT digital era, the need to carry out refined operations in order to better from the management, marketing to enhance the user's service experience, and at the same time according to the differentiation of services to make the operation more refined.

As far as the Chinese market is concerned, after several years of accumulation, generally, most medium and large enterprises and institutions have already established a relatively complete CRM, ERP, OA and other basic information systems. The unified characteristics of these systems are: through the operation of business personnel or users, and ultimately add, modify, delete and other operations on the database. The above systems can be uniformly called

OLTP (Online TransactionProcess, online transaction processing), refers to the system has been running for a period of time, is bound to help enterprises and institutions to collect a large amount of historical data.

But, in the database scattered, independent existence of a large number of data for the actual analysts, just some can not read the sky book. What analysts need is information, abstract information that they can look at, understand, and benefit from; after all, cash, a professional data analyst, is in short supply. This leads to the content and form of enterprise operations is difficult to pull new users, while at the same time can not activate the old users, which leads to the enterprise in the digital era must make changes in operations in order to seize the user. Therefore, the enterprise operation towards refinement is the inevitable trend.

2. The value of big data for fine-tuned operations

In fact, the value of big data for fine-tuned operations is manifested in three important dimensions:

Helping enterprises understand from which channels users come in;

What these users are concerned about;

Whether these users are newly concerned or old users.

Through the analysis of these three dimensions, it allows enterprises to decide their own placement strategy and direction, which is entirely the value that big data brings to the refined operation.

In analyzing the channels from which users come in, it can help enterprises discover the source of more traffic and the channels in which they need to strengthen the placement, such as whether users are from microblogging, WeChat, forums, or portals, which can help enterprises continuously adjust their marketing placement and discover which channel has more potential and value to attract users, and if it is not tapped into, they can continue to dig deeper.

In terms of sharing what users pay attention to, big data analysis through users' clicks on products, discussions on topics, and forwarding of content can help companies effectively find users' favorite points of interest and the direction of accepting content, which facilitates companies to make timely adjustments to operational content and forms.

Finally, through the analysis of new and old user observation, it allows enterprises to grasp the life cycle of users when doing precise operation, know when to market content to what kind of users, as well as help enterprises find ways to activate old users.

3. How big data drives refined operations

The construction of an accurate data system is a long way to go. Only with an accurate data system, the analysis results obtained by using reasonable and scientific data analysis means can provide valuable references for marketing and operation strategies.

The construction of an accurate data system is not an overnight task, and it needs to be regarded as a long-term task on the basis of fully realizing the great and far-reaching value and significance of data analysis for the future development of enterprises. Through all kinds of operational means and the close cooperation of a number of related departments, to the accurate data system construction into the daily work.

The ways of obtaining data are various, but summarized as follows:

1. Collection and collation of public information

For example, the data of the statistics bureau, the company's own annual report, the research reports of other market institutions, or based on the collation of public information, which is usually true, but the work is an accumulation of work over a long period of time. But the work is a cumulative work, need to be persistent to collect and accumulate.

2. Activity

The most accurate form of data acquisition, in the Internet era, is the best expression of "activity or policy + Internet" means the combination of forms. With a clear theme of the form of activities, set the corresponding reasonable and necessary "threshold" form, so that the participants in the activities, fill in the necessary corresponding data we need.

3. Questionnaire research

Sometimes for a certain purpose will collect very special data, research questionnaires, although the form of traditional, but has its irreplaceable role in significance. Reasonable form of questionnaire research, often will play the expected unimaginable effect.

4. Technology acquisition

Information acquisition technology, information acquisition system based on the network information mining engine to build, it can be in the shortest possible time, to help you to the latest information from different Internet sites to collect down. Information acquisition technology is the use of computer software technology, for customized target data sources, real-time information acquisition, extraction, mining, processing, unstructured information from a large number of web pages to save to the structured database, so as to provide data input for a variety of information service systems throughout the process. The data collected by this technology is cluttered with information and requires customized data cleaning and screening work.

5. Purchased database

There are many productized databases on the market, this is generally in the name of the company to buy the entrance, not only consulting firms there are many institutions of higher learning and research institutions will also be purchased, this type of data is usually the majority of industry representative data, and the data is generally unable to meet "timeliness "

There are a lot of invalid data in the cut.

6. Consultation with industry experts

Of course it is paid, this is more common in some corporate strategy implementation projects. Some industry experts will specialize in collecting and selling data.

Massive data is a gold mine and silver mine, but massive data is not gold and silver treasure. The acquisition of accurate data is a process of removing the rough and saving the fine, in the face of the vast amount of structural and non-structural data, the traditional form of processing has paled in comparison to the need for more specialized technical means, more in-depth data construction thinking, and put the accumulation of data into the daily work.

4. Summary

For enterprises, the benefits of creating a fine-tuned operation lies in the ability to track and image the characteristics and portraits of the target user groups or individuals, helping enterprises analyze the characteristics and habits of users in a certain time period of the content, and finally allowing the enterprise to form a kind of exclusive services based on the characteristics of the user and the creation of the service. Borrowing big data will make the refined operation of the enterprise more effective and targeted, refined data operation, closer to the enterprise from the user's nearest that pass, borrowing big data to do the precise analysis of the user can reduce marketing a lot of unnecessary behavior, and then enhance the efficiency and increase the conversion rate.