Construction scheme of consumer financial marketing system

Abstract

The invention relates to a construction scheme of a consumer financial marketing system. The construction scheme comprises the following steps: constructing a user full-life-cycle digital marketing system; constructing a customer data platform to integrate customer data; a data-driven closed-loop marketing whole process is realized; a marketing automation technology is applied; and an end-to-end marketing integration capability is constructed. According to the method, the reach rate is improved, and by constructing a user full-life-cycle digital marketing system, precise marketing and personalized services can be realized, so that the reach rate of marketing activities is remarkably improved.

Description

Technical Field

[0001] The present invention belongs to the technical field, and particularly relates to a construction plan for a consumer finance marketing system. Background Art

[0002] In the current consumer finance market, marketing activities face many challenges. One of the most prominent problems is the low reach rate. This means that marketing information often fails to effectively reach the target customer group, resulting in a waste of marketing resources and the loss of potential customers. At the same time, the insufficient reach quality is also a serious problem. The transmission of marketing information often lacks pertinence and attraction, making it difficult to stimulate customer response and participation. In addition, the unclear customer stratification makes the marketing strategy unable to be accurately positioned, resulting in the lack of personalization in marketing activities and the inability to meet the specific needs of different customer groups. The core of these problems lies in the unclear understanding of the customer situation. Enterprises often lack an in-depth understanding of customer behavior, preferences, and needs, which makes it difficult for marketing activities to achieve the expected results. Summary of the Invention

[0003] (1) Invention Objectives

[0004] In order to overcome the above deficiencies, the objective of the present invention is to provide a construction plan for a consumer finance marketing system to solve the above technical problems.

[0005] (2) Technical Solutions

[0006] To achieve the above objective, the technical solutions provided by this application are as follows:

[0007] A construction plan for a consumer finance marketing system includes the following steps:

[0008] Build a digital marketing system for the entire user life cycle;

[0009] Build a customer data platform to integrate customer data;

[0010] Implement a data-driven closed-loop marketing full process;

[0011] Apply marketing automation technology;

[0012] Build end-to-end marketing integration capabilities.

[0013] Preferably, the digital marketing system for the entire user life cycle includes obtaining data on potential populations, attracting customers, activating new users to become borrowing users, improving user experience, dividing the value of active users, cross-selling, secondary marketing, enhancing user viscosity for active users turning into inactive users, early warning systems, and awakening dormant users.

[0014] Preferably, the customer data platform includes a customer one ID system, tag management, user portrait analysis, data source access, portrait construction, behavior path tracking, offline / real-time data fusion processing and calculation, and API / H5 form service output.

[0015] Preferably, the data-driven closed-loop marketing full process includes data integration and tag system construction, marketing model and strategy development, marketing activity design and execution, and marketing effect analysis and optimization.

[0016] Preferably, the marketing automation technology includes data access and processing, marketing content management, marketing touch plan formulation, marketing automation execution, and marketing result analysis.

[0017] Preferably, the end-to-end marketing integration ability includes a unified control platform and a real-time push and feedback system.

[0018] Preferably, the customer diversion algorithm and formula of the MA strategy center include a credit score calculation formula and a customer value calculation formula.

[0019] Preferably, the credit score = ∑(variable i * weight i), where variable i represents various factors affecting customer credit, and weight i represents the importance of these factors in the credit score.

[0020] Preferably, LTV = average customer transaction amount * customer repurchase rate * customer life cycle length, where LTV represents the life cycle value of the customer.

[0021] Beneficial effects:

[0022] 1. Improve the reach rate: By constructing a digital marketing system for the entire user life cycle, the present invention can achieve precise marketing and personalized services, thus significantly improving the reach rate of marketing activities.

[0023] 2. Improve the reach quality: Using an intelligent marketing system, the present invention can ensure the relevance and attractiveness of marketing information, thus improving the reach quality.

[0024] 3. Clarify customer stratification: By integrating multiple data through the customer data platform to form a customer tag system, the present invention can achieve the clarification of customer stratification and provide support for precise marketing.

[0025] 4. Enhance customer understanding: By deeply analyzing and mining user portraits, the present invention enables enterprises to clearly understand customer situations, including needs and preferences.

[0026] 5. Improve user acquisition efficiency: By optimizing marketing strategies and channel selection, the present invention can reduce customer acquisition costs while improving user acquisition efficiency. Specific embodiments

[0027] To make the objectives, technical solutions and advantages of the present invention clearer and more understandable, the present invention will be further described in detail below in conjunction with specific embodiments. It should be understood that these descriptions are merely exemplary and are not intended to limit the scope of the present invention. In addition, in the following descriptions, the descriptions of well-known structures and technologies are omitted to avoid unnecessarily confusing the concepts of the present invention.

[0028] A construction plan for a consumer finance marketing system includes the following steps:

[0029] Construct a digital marketing system for the entire user life cycle;

[0030] Construct a customer data platform to integrate customer data;

[0031] Implement a closed-loop marketing full process driven by data;

[0032] Apply marketing automation technology;

[0033] Construct end-to-end marketing integration capabilities.

[0034] Preferably, the digital marketing system for the entire user life cycle includes obtaining data on potential populations, attracting customers through drainage, activating new users as borrowing users, improving user experience, dividing the value of active users, cross-selling, secondary marketing, improving user stickiness of active-to-inactive users, early warning systems, and awakening sleeping users.

[0035] In today's consumer finance market, effective user marketing is not only crucial for attracting new customers, but also an effective means to enhance user value and extend the user life cycle. To build an efficient, accurate and sustainable marketing system, we propose a digital marketing system based on the entire user life cycle. This system, through a data-driven approach, covers the entire process from user acquisition, activation, conversion, retention to awakening, realizes precision marketing and personalized services, and maximizes user value.

[0036] We first form user portraits by collecting user data from multiple online and offline channels, including social media, search engines, advertising click records, etc. Then, we use advertising creativity and media channels for precise placement to attract the attention of potential users. For new users, we activate them as borrowing users through means such as first-time borrowing discounts and fast approval processes, and optimize the registration process and improve the borrowing experience to ensure that new users feel convenient and trusted during use.

[0037] For active users, we classify their value based on data such as the amount and frequency of borrowing and repayment status, and provide cross-selling opportunities for other financial products to high-value users. At the same time, we use data on users' online channel behavior characteristics and usage habits for personalized product recommendations and marketing. For users who have changed from active to inactive, we promote user activity and loyalty by regularly pushing preferential information and product update notifications, and establish a user inactivity warning system to detect and take measures to prevent user churn in a timely manner.

[0038] For dormant users, we provide reactivation incentives by sending wake-up emails, text messages, phone calls, etc., and analyze the reasons and characteristics of user return to optimize the wake-up strategy. In addition, we extract key performance indicators from user behavior data, such as user activity, conversion rate, retention rate, etc., calculate the return on investment of marketing activities, evaluate the marketing effect, and optimize the marketing strategy. We also identify the characteristics of different user groups through user portrait analysis, formulate targeted marketing strategies, evaluate the effectiveness of different marketing channels, and select the most suitable marketing channel for delivery.

[0039] It is expected that by building this digital marketing system for the entire user lifecycle, we can improve user acquisition efficiency, reduce customer acquisition costs, increase user conversion and retention rates, extend the user lifecycle, increase user value, and enhance the overall revenue of the consumer finance business. The implementation of this system will bring significant competitive advantages to the enterprise, achieve the optimization of marketing activities and business growth.

[0040] Preferably, the customer data platform includes a customer oneID system, tag management, user portrait analysis, data source access, portrait construction, behavior path tracking, offline / real-time data fusion processing and calculation, and service output in the form of API / H5.

[0041] In today's consumer finance market, competition is intensifying. For enterprises to stand out in the market, accurate user portraits and efficient data utilization have become the key to winning market share. For this reason, we propose a construction plan based on CDP, aiming to integrate and analyze customer data from different channels and systems to form a unified customer view and provide strong data support for the enterprise's marketing decisions.

[0042] As a customer omnichannel data empowerment middle platform for business growth, CDP helps enterprises achieve data-driven business growth by providing complete customer basic data services and tag operation and analysis tools. It outputs services in the form of API or H5, enabling enterprises to obtain the required data and analysis results on demand, and thus flexibly integrate into the enterprise's business system and decision-making process.

[0043] One of the core functions of CDP is the customer oneD system, which is the basis for data integration. It supports multi-ID-mapping technology, which can break data silos and integrate customer data from different systems and channels into a unified customer view. In addition, CDP also supports combined configuration based on attributes, behavioral events / behavior sequences, allowing companies to flexibly build customer tags and portraits. The tag management function supports companies to classify, manage and maintain tags to ensure the accuracy and timeliness of tags. Companies can independently complete tag configuration according to business needs and achieve accurate user portrait analysis. At the same time, CDP also supports operations such as cleaning and unification of tags to ensure data quality.

[0044] User portrait analysis is another core function of CDP. It supports enterprises to build a global user portrait based on rich data sources and a complete analysis system. Enterprises can gain insights into user needs and preferences by analyzing behavioral characteristics such as user attributes and transaction records, and provide data support for precision marketing. CDP supports access to multiple data sources, including but not limited to social media, e-commerce platforms, offline stores, etc., and cleans and unifies attribute field data to ensure data accuracy and consistency. Based on the cleaned data, CDP can build a complete user attribute / transaction indicator library for user portrait construction and analysis. In addition, CDP also supports tracking the life cycle behavior path of a single user and recording the time series of user behavior events. These data can be used to analyze user behavior characteristics and explore potential needs and purchase intentions. CDP supports offline / real-time data fusion processing and calculation to meet the different needs of enterprises for data timeliness. Whether it is real-time data analysis or historical data mining, CDP can provide accurate data support.

[0045] In terms of application scenarios, CDP can support enterprises to accurately build marketing population packages for business decision-making or operation and delivery. Through in-depth analysis and mining of user portraits, enterprises can accurately locate target customer groups and improve the efficiency and effectiveness of marketing activities. CDP also provides comprehensive customer operation application tools to support enterprises to manage customers in a refined manner. Through data analysis and mining, enterprises can discover customers' potential needs and preferences and provide customers with personalized services and experiences. In addition, CDP supports the analysis and mining of massive data, providing enterprises with in-depth data insights. Through in-depth analysis and mining of data, enterprises can discover market trends and opportunities, providing strong data support for their strategic decisions.

[0046] Preferably, the entire data-driven closed-loop marketing process includes data integration and label system construction, marketing model and strategy development, marketing campaign design and execution, and marketing effect analysis and optimization.

[0047] In the field of consumer finance, the success of marketing activities often depends on the accurate understanding and timely response to customer needs. To achieve this goal, it is particularly important to build a data-driven closed-loop marketing system. This chapter will introduce in detail how to integrate diverse data through a customer data platform, form a customer tagging system, and develop marketing models and strategies, ultimately realizing the entire process of data-driven closed-loop marketing.

[0048] A customer data platform is a system that integrates multiple data sources and has powerful integration capabilities. Through normalization and integration technologies, it integrates data from multiple channels such as the enterprise's own, partners', and third parties, forming a complete customer profile. This platform not only supports real-time data updates and dynamic optimization but also provides comprehensive, diverse, and real-time support for marketing decisions.

[0049] In terms of data integration, the customer data platform can integrate data from first-party enterprise-owned, second-party enterprise advertising partners, and third-party independent data providers. These data include user attributes, such as gender, age, income, occupation, transaction information, customer service information, registration information, APP access records, website access records, membership benefit usage, coupon usage, etc. Based on the integrated data, the customer data platform can form a rich customer tagging system, including new customer tags, customer value tags, old customer tags, customer risk tags, interest tags, life cycle stage tags, intent tags, etc., enabling enterprises to understand customers' characteristics and needs more deeply and providing strong support for precision marketing.

[0050] By leveraging the data integration and tagging system of the customer data platform, enterprises can develop marketing models suitable for their own business needs. These models can be built based on multi-dimensional data such as customer attributes, behaviors, and transactions, and are used to predict key indicators such as customer purchase intent and conversion rate. Based on the results of the marketing models, enterprises can formulate targeted marketing strategies, including target customer group screening, marketing activity management, personalized recommendations, marketing risk control strategies, etc. Through accurate target customer positioning and personalized marketing strategies, enterprises can improve the efficiency and effectiveness of marketing activities.

[0051] In terms of marketing activity design and execution, under the guidance of marketing strategies, enterprises can design marketing activities that meet customer needs, such as promotional offers, new product launches, membership privileges, etc. When designing activities, enterprises need to fully consider customers' interests, needs, and behavioral characteristics to ensure the attractiveness and participation of the activities. During the activity execution stage, enterprises need to utilize the marketing automation function of the customer data platform to achieve user reach across touchpoints and media. Through means such as A / B testing, personalized interactions, and dynamic optimization of interactive materials, enterprises can continuously optimize the activity effects and improve customer participation and satisfaction.

[0052] After the marketing campaign ends, the enterprise needs to conduct a comprehensive, diverse, and real-time analysis of the campaign effects, including the calculation and comparison of indicators such as conversion rate, ROI, and customer satisfaction. Through data analysis, the enterprise can understand the success or failure of the campaign and discover potential problems and improvement directions. Based on the results of the marketing effect analysis, the enterprise needs to continuously optimize data, tags, and models. By adjusting marketing strategies, optimizing campaign designs, and improving customer experiences, etc., the enterprise can continuously enhance the marketing effects and achieve a closed-loop marketing full process driven by data.

[0053] Preferably, the marketing automation technology includes data access and processing, marketing content management, marketing touch plan formulation, marketing automation execution, and marketing result analysis.

[0054] The MA marketing automation platform is a comprehensive system that integrates functions such as data access, processing, application, and output. Through the connection with the CDP customer data platform, the platform realizes real-time update and dynamic optimization of user data, providing all-round and intelligent marketing support for marketers. The MA platform has functions such as intelligent decision support, marketing content management, and marketing touch plan formulation, making marketing campaigns more accurate and efficient.

[0055] In terms of data access and processing, the MA platform supports the access of multiple data sources, including user behavior data, business order data, dialogue interaction data, etc. These data go through steps such as aggregation, cleaning, and conversion to form a structured and standardized data format, providing a basis for subsequent marketing analysis. The marketing content management function allows the platform to support the creation, editing, and management of various content forms such as articles, product introductions, audio and video, and regular Q&A. At the same time, the platform also has a content recommendation algorithm that can intelligently recommend suitable marketing content according to user interests and behavior characteristics.

[0056] The MA platform also supports the formulation of multiple marketing touch plans, including call strategies, script strategies, multi-round dialogue strategies, etc. These plans can be customized according to factors such as user attributes, behavior characteristics, and purchase intentions to achieve precise marketing. The marketing automation execution function of the platform can automatically execute marketing actions such as making calls, sending text messages, and pushing messages according to the pre-determined marketing touch plans, and supports real-time monitoring of the execution of marketing tasks to ensure the smooth execution of tasks.

[0057] The marketing result analysis function enables the MA platform to conduct real-time evaluation and analysis of the execution effects of marketing tasks. By analyzing indicators such as conversion rate, ROI, and customer satisfaction, marketers can understand the success or failure of marketing campaigns and discover potential problems and improvement directions.

[0058] The MA platform adopts a customer diversion algorithm, including diversion based on credit scores, diversion based on customer value, and diversion based on customer activity. By collecting data such as the customer's credit history, income level, debt situation, and multi-borrowing behavior, and using a credit scoring model to calculate the customer's credit score, customers are divided into different risk levels, and corresponding loan approval strategies, interest rates, and amounts are formulated. At the same time, by calculating the customer's lifetime value (LTV), customers are divided into different value levels, providing better services and discounts for high-value customers, and taking more stringent risk control measures for low-value customers. In addition, by analyzing data such as the customer's transaction behavior, usage frequency, and recent transaction time, customers are divided into different levels according to their activity, and corresponding interaction and marketing strategies are adopted for customers at different levels.

[0059] The close integration of the MA marketing automation platform and the CDP customer data platform constitutes the core of the consumer finance marketing system. The CDP platform is responsible for the integration and management of user data, providing real-time and accurate data support for the MA platform, while the MA platform uses this data to formulate and execute personalized marketing strategies, achieve precise marketing, and feedback the marketing results to the CDP platform for further optimizing user tags and portraits and improving data quality.

[0060] The application scenarios of the MA marketing automation platform include new user activation, repeat purchase by old users, and user retention. For new users, the MA platform can formulate personalized activation strategies, such as sending welcome text messages and pushing preferential activities, to improve the activity and retention rate of new users. For old users, the MA platform can formulate targeted repeat purchase strategies, such as sending promotional information and recommending relevant products, based on their historical purchase records and interest preferences, to promote repeat purchases by old users. For lost users, the MA platform can formulate retention strategies, such as sending retention text messages and providing coupons, by analyzing the reasons for their loss and interest preferences, to reduce the user loss rate.

[0061] Preferably, the end-to-end marketing integration ability includes a unified control platform and a real-time push and feedback system.

[0062] When building an efficient marketing system, the design of the system framework and functions is crucial. As the core of the entire marketing system, the unified control platform is responsible for coordinating and managing the data flow and interaction among various components. It provides data access functions, supporting data access from multiple data sources, including internal system data and third-party data, to ensure the comprehensiveness and accuracy of data. Data processing functions include data cleaning, transformation, aggregation, etc., to ensure data quality and consistency. The user profiling function constructs user profiles based on user data, covering basic information, behavioral characteristics, interest preferences, etc., providing a basis for precision marketing. The data analysis and reporting function provides rich data analysis tools and reporting functions, supporting real-time monitoring and evaluation of marketing effectiveness.

[0063] The marketing automation module is a key component for achieving end-to-end marketing integration, supporting strategy and interaction functions, allowing marketers to formulate marketing strategies based on user profiles and data analysis results, and realizing real-time interaction with users through the MOT engine. The reach content management function provides management of reach content such as SMS and PUSH, supporting customized content push to improve user engagement. The activity & rights management function supports the creation, configuration, and management of activities, including activity page configuration, coupon management, etc., to ensure the smooth progress of marketing activities. The full-process data analysis function conducts full-process data analysis of marketing activities, including indicators such as user engagement, conversion rate, ROI, etc., providing data support for optimizing marketing strategies.

[0064] The real-time push and feedback system is responsible for pushing marketing content to users in real time and collecting user feedback data. This system features real-time capabilities, supporting real-time push of marketing content to ensure that users can receive relevant information in a timely manner. The personalized feature, based on user profiles and marketing strategies, enables personalized content push to improve user satisfaction. The feedback collection function collects user feedback data, including click-through rate, conversion rate, etc., providing data support for optimizing marketing strategies.

[0065] To achieve end-to-end marketing integration, advanced data fusion and processing technologies need to be adopted. ID-Mapping technology correlates and integrates user data from different data sources to form a unified user view. The tag processing engine processes and transforms user data to generate a rich user tag system. The event processing engine captures and processes user behaviors in real time to generate event data, providing support for user profiling and behavior analysis.

[0066] User profiling construction technology is the basis for achieving precision marketing. By integrating multi-dimensional data such as user basic information, behavioral characteristics, and interest preferences, a comprehensive and accurate user profile is constructed. At the same time, technologies such as machine learning are used to continuously optimize and update the user profile to ensure the timeliness and accuracy of the profile.

[0067] Real-time data analysis and decision-making technologies are the key to achieving real-time push and feedback collection, including real-time data stream processing technologies and online learning algorithms. Real-time data stream processing technologies process and analyze user data in real time, providing data support for real-time push. Online learning algorithms continuously optimize and adjust marketing strategies to improve marketing effectiveness. The implementation of these technologies provides the marketing system with powerful data support and decision-making capabilities, ensuring the efficient execution and continuous optimization of marketing activities.

[0068] By building an integrated marketing system based on the integration of a CDP-based customer data platform and an MA marketing automation platform, the system achieves comprehensive data integration and in-depth analysis, providing a series of significant benefits for enterprises. First of all, it enhances the comprehensiveness and accuracy of data. Through the integration of multiple data sources, a complete customer profile is formed, providing a solid data foundation for precision marketing. Secondly, the system supports the timely adjustment and optimization of marketing activities by updating and dynamically optimizing user data in real time, improving the response speed and adaptability of marketing activities.

[0069] In addition, the system enhances the personalization and relevance of marketing content through intelligent decision-making support and marketing content management, increasing user engagement and satisfaction. At the same time, by formulating and automatically executing marketing touch plans, the system improves the efficiency and effectiveness of marketing activities and reduces labor costs. The real-time push and feedback system further ensures the timeliness and personalization of marketing content, while the user feedback data collected provides a basis for the continuous optimization of marketing strategies.

[0070] The application of key technologies, such as ID-Mapping, label processing engines, event processing engines, and real-time data analysis, enables the system to quickly respond to market changes and achieve end-to-end marketing integration. The use of user profile construction technologies improves the accuracy of marketing, while real-time data analysis and decision-making technologies ensure the real-time adjustment and optimization of marketing activities.

[0071] Overall, the system significantly improves marketing efficiency and effectiveness, reduces marketing costs, enhances the market competitiveness of enterprises, and ultimately promotes business growth by enhancing data integration capabilities, optimizing marketing strategies, increasing user engagement and satisfaction, and achieving automation and real-time optimization of marketing activities.

[0072] It should be noted that, in this document, relational terms such as first and second are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any actual relationship or order between these entities or operations. Moreover, the term "comprising", "including" or any other variant thereof is intended to cover non-exclusive inclusion, so that a process, method, article or device comprising a series of elements not only includes those elements, but also includes other elements not expressly listed, or also includes elements inherent to such process, method, article or device. Without further limitation, an element defined by the statement "comprising one..." does not exclude the presence of additional identical elements in the process, method, article or device comprising the said element.

[0073] The above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it; although the present invention has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that they can still modify the technical solutions recorded in the foregoing embodiments, or perform equivalent replacements for some of the technical features; and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A solution for constructing a consumer finance marketing system, characterized in that: The following steps are involved: Build a digital marketing system for the entire user life cycle; Build a customer data platform to integrate customer data; Realize the entire process of data-driven closed-loop marketing; Apply marketing automation technology; Build end-to-end marketing integration capabilities.

2. According to the construction scheme of a consumer finance marketing system according to claim 1, it is characterized in that: The digital marketing system for the entire user life cycle includes data acquisition of potential groups, traffic generation and customer acquisition, activation of new users and borrowing users, user experience improvement, value segmentation of active users, cross-selling, secondary marketing, improvement of user stickiness by converting active users to silent users, early warning system, and awakening of dormant users.

3. According to the construction scheme of a consumer finance marketing system according to claim 1, it is characterized in that: The customer data platform includes customer oneD system, tag management, user portrait analysis, data source access, portrait construction, behavior path tracking, offline / real-time data fusion processing and calculation, and API / H5 service output.

4. According to claim 1, the solution for constructing a consumer finance marketing system is characterized in that: The entire process of data-driven closed-loop marketing includes data integration and label system construction, marketing model and strategy development, marketing campaign design and execution, and marketing effect analysis and optimization.

5. According to claim 1, the solution for constructing a consumer finance marketing system is characterized in that: Marketing automation technology includes data access and processing, marketing content management, marketing reach plan formulation, marketing automation execution, and marketing results analysis.

6. According to claim 1, the solution for constructing a consumer finance marketing system is characterized in that: End-to-end marketing integration capabilities include a unified management and control platform and a real-time push and feedback system.

7. According to claim 1, the solution for constructing a consumer finance marketing system is characterized in that: MA Strategy Center’s customer diversion algorithms and formulas, including credit score calculation formulas and customer value calculation formulas.

8. The solution for constructing a consumer finance marketing system according to claim 7, characterized in that: Credit score = ∑(variable i*weight i), where variable i represents the various factors that affect customer credit, and weight i represents the importance of these factors in the credit score.

9. The solution for constructing a consumer finance marketing system according to claim 7, characterized in that: LTV = average customer transaction amount * customer repurchase rate * customer life cycle length, where LTV represents the customer's lifetime value.