I always feel that big data applications are not satisfactory, especially for users in traditional industries. Compared with native Internet companies, companies in traditional industries have been greatly impacted and squeezed. One of the reasons is data-based applications.
The Internet can improve and adjust services for registered users based on their access behavior. But for users in traditional industries, they do not have the Internet capabilities of cloud-native applications. In this case, how should users in traditional industries accelerate their pursuit?
It is said that traditional industries have a large amount of data. indeed so. Banks have depositor data, civil aviation has user flight records, and telecommunications has mobile phone user data ... These data are the wealth of companies in these industries, but they are also the privacy of users. When it comes to big data, we have not seen more. Business model innovation.
Compared with traditional industries and Internet companies, the gap lies in the Internet. One is the Internet + transformation, and the other is the Internet. The gap is obvious.
Speaking of the traditional enterprise Internet + transformation, Analysys CPO Zhu Jiang divided it into 4 phases in an interview: the first phase, marketing Internet, similar advertising on the Internet; the second phase, channel Internet , Using the Internet as a channel to sell products; the third stage, the Internet of products, has its own products and services on the Internet, and can support users in digital form; the fourth stage, operating the Internet.
Today, more industry users are still in the process of transition from the second to the third stage.
Only when the third stage is achieved can big data business innovation really be on track.
For the traditional industry, Analysys released the ARGO growth model for smart user operations and the Analysy Ark product suite. Among them, the ARGO model created conversion from Acquisition, Retention, and Growth to create value, and combed the intelligent operation based on OpenTech's big data and open technology applications.
Only when you truly have your own Internet-based product platform, can you really build a bridge between enterprises and consumers. This is different from traditional industry companies that open online stores on e-commerce platforms such as Taobao, Tmall, and Jingdong. Or, the user's access data belongs to e-commerce and does not belong to industry companies, so it is impossible to talk about business innovation based on big data.
Only with its own Internet-based product platform, big data-based business innovation can open its doors.
Only in this way can the ARGO model and the Easy View Ark be used.
Simply put, ARGO is a methodology. From reaching users: such as guided registration, event attraction, SMS verification, email verification, third-party account quick login, APP message notification, new user coupons, account information / preferences, novice task reminders, core function reminders ... ; To user behavior analysis, demographics / device information clustering, etc., to channel new capabilities, conversion quality, abnormal traffic investigation, etc., and how to introduce products, how to guide user conversion, etc. Process to provide guidance for smart user operations.
Compared with ARGO, Analysys Ark provides software tools required for big data operations, including a series of suites such as intelligent analysis, intelligent operations, user portraits, etc., ranging from buried point solutions, buried point management, and fine user grouping; to multi-channel A series of operations including reach, localized deployment, free design of operation plan, and real-time kanban.
These tool platforms are completely based on open platforms and can be seamlessly integrated with open source platforms.
In a word, for enterprise users in traditional industries, big data business innovation can be described as everything and only owes Dongfeng!
Dongfeng needs users to build their own Internet platform of products as soon as possible, otherwise, their voices are not good, and no matter how good the drama is, they can't get out!
Traditional industry users' big data application "card" is stuck here!