In recent years, operator big data has developed rapidly in the market, and companies from all walks of life are using operator big data to obtain more accurate and effective corporate information and customer resources. For example, when an enterprise is in the process of precision marketing, it can quickly obtain a more accurate customer list based on clues and conditions, unlike the traditional method of "finding a needle in a haystack", which takes a long time and cannot guarantee quality. The same goes for salespeople looking for customers. They can rely on the development of big data to find high-quality customer resources without worrying about where the customers are.
As early as 2019, China Telecom first proposed the concept of "operator big data". At that time, China Telecom developed a modeling platform to provide outbound call seats to users. , Too few are true, and soon died, and then China Unicom made a move to create the "operator big data 2.0" version, which is the prototype of the operator big data we are using today.
Carrier big data, also known as triple network big data
Based on the huge user pools and powerful user data systems of China Mobile, China Unicom, and China Telecom, through the establishment of data models, user data analysis and user data mining are performed on corresponding platforms and tags, and the captured users Data, through the establishment of a complete user portrait, and finally according to the different customer acquisition needs of the industry, accurate industry labels are attached to the user data to achieve accurate customer acquisition.
So how can enterprises use operator big data to acquire customers?
Relying on the network traffic collection and analysis capabilities of big data, it can build a communication link between operators and customers. In the data age, any enterprise that takes traffic as a breakthrough cannot do without the corresponding Data services and platform assistance can accurately and effectively mine users through the accumulation of traffic after big data transformation.
Wide range of data sources: The carrier industry has a large number of customers, involving massive data such as user call records, SMS records, and Internet access records. These data are valuable resources for big data analysis and mining.
High data quality: The data involved in the carrier industry is generally authenticated with real names and has high reliability, which can provide effective data support for accurate customer acquisition.
Diverse customer acquisition channels: Operators have rich customer contact channels, including phone calls, text messages, APPs, etc., which can provide multiple channel options for big data marketing.
The special feature of the big data customer acquisition model is its unique capture method, which breaks through the traditional traffic capture method, makes advertising more accurate and effective, and further reduces the overall customer acquisition cost, thereby bringing brand and enterprise Higher return on investment.
Now there are many industries and enterprises that can use big data from operators to acquire customers, such as: education industry (degree improvement, secondary construction, self-examination, etc.), investment promotion industry (food franchise, mechanical equipment franchise, dry cleaner franchise, beauty salon franchise, etc.) etc.), the automobile industry (special vehicles, new cars, second-hand cars, etc.), the corporate service industry (corporate finance and taxation, etc.), the legal consulting industry (lawyers, policy protection, etc.), the financial industry (credit, loan assistance, etc.), Real estate industry (commercial real estate, new houses, second-hand houses, etc.)...
Reasonable use of traffic means and choosing a better, more advanced, and more scientific marketing model is of great help to companies in breaking through the traffic dilemma. The operator's big data model is undoubtedly an excellent choice, providing new ideas, new methods, and new breakthroughs for many companies that are following suit.