What do you think about data analysis for small and medium sized enterprises?

1) Aggregate data.

In the system, enterprise personnel can retrieve the data in any module to generate the report data they need, for example: if you want to view the data statistics of the current year's product profit, you can generate a summary report of the module and filter it by time, type and other conditions, then the system will automatically generate the required report data according to the conditions, which can greatly save a lot of time for enterprise personnel to sort out the data, and effectively improve work efficiency.

RushCRM management system can help enterprises make personalized and refined reports according to the different statistical and summarized data needs of different personnel, and can also export the summarized data to generate Excel**, which is convenient to operate and improve user experience.

2) Sales funnel chart.

In order to improve the sales use report function, RushCRM can better display and clearly understand the data report, which can be converted into the form of charts according to the custom generated report, and provides a sales funnel chart for the sales staff of the enterprise, so that the sales staff can easily and quickly automatically generate a sales overview report of their own through the sales funnel chart, which is conducive to the enterprise sales staff to intuitively understand the customer situation of the year, and also facilitate the sales to better conduct year-end data analysis. It can improve the efficiency of sales work and improve and optimize the sales management of enterprises.

3) Multi-functional display charts.

In addition to the sales funnel chart, in order to improve the personnel of other departments of the enterprise to make the report more vivid and vivid, so that the chart function becomes more perfect, the vertical bar chart, horizontal bar chart, pie chart, line chart can be generated. In addition, users can display charts on the home page, and can intuitively view the statistical data of the report, so that when the user wants to view the detailed data, they can directly click on the corresponding chart on the home page to enter the report page for viewing, which can help enterprises find problems in time, find enterprise winning points, improve enterprise win rates, and reduce enterprise costs.

RushCRM customer management system takes customer data as the core, providing enterprises with scientific management methods, as well as automatic management modes for enterprises, customers, sales, etc. And according to the needs of the enterprise, it supports mobile terminal and PC terminal, so as to meet the needs of enterprise personnel to view the system anytime and anywhere, realize efficient automatic and intelligent management, win more market share for enterprises in the new year, and lay a solid foundation for the subsequent development of enterprises.

The era of big data has come, data analysis is becoming more and more important to the development of an enterprise, I think there are still certain defects in the data analysis of small and medium-sized enterprises, unlike the data analysis of large enterprises is very comprehensive and specific, these are incomparable to the data analysis of small and medium-sized enterprises.

I'm not very optimistic about the data analysis of some small and medium-sized enterprises, because the data they analyze is not as detailed as the analysis of large enterprises, so I generally choose large enterprises.

I think that if you want to do better, then every company is from small and medium-sized enterprises, and do better, so you must be careful.

As a relatively objective object of analysis, data is generally very important, and if there is a lack of data, it is difficult to make a comprehensive evaluation and analysis of small and medium-sized enterprises. But it can be analyzed by some other information.

The data analysis of small and medium-sized enterprises does not need to do the analysis of every detail, but only needs to analyze the approximate data, because of the limited human and financial resources, and the management is limited.

The data analysis of small and medium-sized enterprises should also be done by a special person, and it should be done in detail, and then put it on the table, I think that such a thing, whether it is a large enterprise or a small enterprise, should be done clearly.

For small and medium-sized enterprise data analysis, I think this is still necessary and can help the development of many people. It's a nice thing.

Data analysis of small enterprises is also very necessary, it is impossible to say that his enterprise is small, and the data analysis is unreasonable, and it still needs to be careful.

First, clarify what kind of data we need, whether it's people-centric or product-centric. After clarifying this point, it is perfect to collect data in the business process, even if it is not currently useful, and save it.

The effective use of data has become the primary concern of each company, and they use the integration of the company's diverse data to help enterprises achieve project promotion and business development.

Now big data is used at every turn, and small data is also very useful when it is used well, and I hate gimmicks the most.

Much needed. Data analysis refers to the use of appropriate statistical analysis methods to analyze the large amount of data collected from macro macro balance, summarize and understand and digest them, in order to maximize the development of data functions and play the role of data.

Data analysis is the process of studying and summarizing data in detail in order to extract useful information and form conclusions.

The more small and medium-sized enterprises need to develop rapidly, the more inseparable they are from data analysis.

Data, also known as observations, is the result of experiments, measurements, observations, surveys, etc.

The data processed in data analysis is divided into qualitative data and quantitative data.

The Internet has given rise to the IT industry term big data, which refers to a collection of data that cannot be captured, managed, and processed by conventional software tools within a certain time frame, and is a massive, high-growth and diversified information asset that requires new processing models to have stronger decision-making, insight and process optimization capabilities.

As the information department of an enterprise, the financial department and the marketing and production management department need to provide accurate and comprehensive data and big data to the decision-makers of the enterprise. The decision-makers of the enterprise must learn to analyze the data, find out the achievements of good measures and find out the problems in the production and operation of the enterprise; And according to the data of the enterprise and the data of the enterprise in the same industry in the province and even the whole country, comparative analysis; In order to understand the level of enterprise development, find the crux of the problem, and summarize the laws and trends of industry development; In order to formulate and adjust the enterprise policy and system, in order to adjust the development strategy of the enterprise, and update the development concept of the enterprise; Determine the medium and long-term development plan of the enterprise and lay the foundation; In order to ensure the healthy development of the enterprise.

90% of market decisions and business decisions are determined through data analysis research. Speaking with data and attaching importance to quantitative analysis has gradually become a key consideration in the process of scientific research, business management, and decision-making. More and more people are realizing the importance of data analytics for economic development.

Data analysis serves three purposes:

1.It is the improvement and optimization of the business, including the improvement aspects of the enterprise user experience, and the allocation of company resources.

2.It is the process of helping businesses discover opportunities, mainly using data to find blind spots in people's thinking, and then discovering new business opportunities.

3.It is the process of creating new business value, mainly forming a new business model on the basis of data value, and directly converting data value into a money model or closer to money.