Digital transformation has become a strategic demand for the development of various industries. The blueprint of "Digital China" was determined in the "Tenth Five-Year Plan", which also provided guidance for the direction of the industry's scientific and technological capacity building. Eight core industries, such as retail and finance, took the lead in further promoting the internalization of scientific and technological capabilities and leading China enterprises to carry out digital transformation. For example, retail digitalization is upgrading from the era of 1.0 with channel construction and business digitalization as the core to the era of 2.0 with digital business operation and overall efficiency improvement as the core. According to the Tenth Five-Year Plan for Science and Technology Development of Securities and Futures Industry issued by CSRC, financial institutions have defined the guiding ideology, working principles and key directions of digital transformation of securities companies. All these have prompted China enterprises to re-examine their overall business strategy, and a user-centered omni-channel closed-loop marketing platform is particularly important. Relying on the technical and digital capabilities accumulated by the core team for ten years, Digital Potential Technology focuses on the digital upgrade scenarios of consumer retail and retail finance, and proposes a marketing cloud product scheme with user life cycle management as the core. Combining with customer data, customer insight and customer journey modules, it uses digital tools to carry out marketing work, reach new users, retain old users and use existing users to drive increments, so as to realize the good operation of user ecology, better achieve customer refined business objectives and realize MAU, GMV and GMM. What is 0 1 digital marketing cloud and what pain points does it solve for enterprises? Digital marketing cloud is a product aggregation scheme based on enterprise digital brain in marketing operation scenario. It helps enterprises to establish a data asset platform through the user operation index system, and then integrates online and offline business data with knowledge map and machine computing to build a 360-degree user portrait, and outputs customer insight analysis and marketing strategies in combination with "people and goods yard" data, and finally realizes multi-business growth scenarios such as customer acquisition, recommendation, marketing, drainage, asset retention and promotion. In fact, since the era of enterprise digital transformation 1.0, various data service providers have been exploring and formulating the product architecture of digital operation, but the exploration process is not smooth sailing and faces the threshold of technology and knowledge reserve. First of all, in data development and integration, how to obtain the first-hand business data of the whole platform of the enterprise and choose the third-party platform data that conforms to the development of the industry for structural development. Furthermore, under the data integration mode, all enterprises have spent several years to complete IT informatization, but due to the weak correlation between the data of various business counterparts, it is easy to fall into the dilemma of data islands and connecting the complete data of a single user in series. At the same time, in the process of data capitalization, the data caliber of different departments is different, which makes it difficult to distinguish objectivity from authenticity. There is no unified index system in the data center, and the data is not available. Finally, in the decision-making stage, due to the long data output process and the lack of tags and algorithm modules, it is easy to have problems such as lagging output of analysis results or low efficiency of strategy iteration. Based on the above difficulties, the digital transformation of enterprises is not easy, and it is often difficult to effectively understand user needs, make marketing decisions, accurately implement intelligent operations, evaluate the effectiveness of marketing strategies, and upgrade. What are the core functions of digital potential marketing cloud products and how are they different from traditional operating products? In view of the above pain points, digital potential marketing cloud products include customer data platform, customer insight platform and customer journey platform. Customer data (CD-CustomerData) is the basis of product components, and its main purpose is to democratize data, manage and precipitate the tag data assets of enterprise customers, accurately locate the target population in customer operation, customer analysis and other scenarios, and make the data available for operation. The strategic system constructed by operation has data basis. CI-CustomerInsight conducts all-round insight analysis of customized people through various analysis models, which is the data basis for all aspects of interaction between enterprises and customers. CI-Customer Insight can be used for crowd selection and customer portraits, and comprehensively enhance the richness of behavioral portraits such as user activity, retention and repurchase through big data capabilities. CJ-CustomerJourney plays an important role in strategy formulation and optimization, and carries out refined operation on the user journey through automatic, intelligent and templated operation strategies to enhance the user value. Upgrading the traditional "carpet bombing" marketing method to an intelligent marketing product with omni-channel integration, complete closed-loop decision-making and automatic iteration has four core advantages: omni-channel and full-link, personalized operation, simple configuration and closed-loop operation. Omni-channel: the online and offline integration strategy system is perfect; Personalized operation: "Thousands of people N policy" can enhance the value of old customers and individual customers. The configuration method is simple: quickly build all kinds of complex scenario applications, open the box and run in closed loop: in addition to rich and intelligent strategy templates, there are built-in pre-diagnosis and post-analysis templates related to specific scenarios, which makes strategy iteration more efficient. What are the application scenarios of digital potential marketing cloud products and how to realize them? Based on the core functions and advantages of the marketing cloud, the main application scenarios are data capitalization, personalized customer marketing and intelligent strategy execution. For example, enterprise operators can build customer portraits and groups with the help of marketing cloud products, or they can independently and quickly create an operation activity for customers to achieve the target conversion rate of monitoring the operation plan. At the same time, the marketing cloud pays attention to the life cycle management of users, which can help enterprises to continuously tap customer value, attract new customers and retain and cultivate old customers, continuously improve customer satisfaction and realize innovation, and improve the retention and repurchase rate of existing customers. The methodology of the application scenario solution is as follows: firstly, the internal and external data are capitalized through four steps: data integration, data development, data governance and data service, and then a unified index system is established according to industry know-how to construct and group label portraits; Secondly, using GASO model combined with AI algorithm, through the concept of operation plan, the strategies of different business teams are classified, designed and managed to support scenarios such as high-potential customer mining, product reinvestment, loss warning and loss recall. , and continue to track core business indicators, combined with pre-diagnosis analysis kanban to complete strategy formulation and management; Third, combine multi-channel online extension with offline account manager-integration strategy implementation; Finally, visually monitor the status and progress of the current strategy, and evaluate, improve and optimize it by combining internal behavior, business data and external industry index data, so as to complete closed-loop operation. Finally, the result data of this strategy is fed back to the next strategy goal to realize machine learning and automatic iteration of operation strategy. Conclusion Digital environment is driving profound changes, whether it is human thinking mode, organizational incentive mode, or enterprise strategy, marketing and operation. China enterprises are gradually transitioning to a brand-new development stage of "open platforms and interoperability, and global traffic * * * builds value * * *". Although there are many branches in the digital transformation of enterprises, the construction of marketing cloud has become the first choice for the digital transformation of most enterprises. By storing and analyzing internal and external data, as well as rich industry knowledge and advanced algorithm addition, we believe that digital marketing cloud products can help financial, retail and other enterprises accelerate digital upgrading and achieve new growth with a more efficient business model.