Small and micro financial marketing data analysis and effect statistics method and device and computer equipment

Abstract

The embodiment of the invention discloses a small and micro financial marketing data analysis and effect statistics method and device and computer equipment. The method comprises the following steps: in an activity planning stage, positioning a target customer group; setting a message transmission mechanism; capturing an interaction behavior of the target customer group according to the message passing mechanism to obtain initial data; performing effect statistics and deep analysis on the initial data to obtain an analysis result; and continuously optimizing resource allocation according to the analysis result. By implementing the method provided by the embodiment of the invention, the problem of effect statistics caused by customer group diversity due to business diversity in marketing activities of the small and micro financial industry and association relationship complexity can be effectively solved.

Description

Technical Field

[0001] The present invention relates to a data analysis method, and more specifically to a method, device and computer equipment for analyzing and statistically analyzing small and micro-finance marketing data. Background Art

[0002] In the microfinance industry, evaluating the effectiveness of marketing activities and tracking customer behavior face many complex challenges. Traditional methods usually rely on static data collection and analysis, but in multi-channel and complex customer relationship networks, this approach often cannot accurately track customers' specific behaviors and reactions in real time. Therefore, banks and financial institutions face the dual pressure of real-time and accuracy when evaluating the effectiveness of marketing activities.

[0003] The data fragmentation and information island problems in the microfinance industry have further complicated this challenge. The data sources from multiple channels and the data isolation between different systems limit the construction of a comprehensive customer portrait, thus affecting the precision of marketing activities and the accuracy of effect evaluation. In addition, existing systems often lack intelligent data processing mechanisms and cannot effectively identify potential connections between customer data, which also limits the refinement of marketing strategies and decision support.

[0004] Therefore, it is necessary to design a new method to effectively solve the problem of customer diversity caused by business diversity in the marketing activities of the microfinance industry, combined with the difficulty of effectiveness statistics caused by the complexity of the relationship. Summary of the invention

[0005] The purpose of the present invention is to overcome the defects of the prior art and provide a method, device and computer equipment for analyzing microfinance marketing data and statistical results.

[0006] To achieve the above-mentioned purpose, the present invention adopts the following technical scheme: a method for analyzing marketing data and statistically analyzing the effectiveness of microfinance, including:

[0007] During the event planning stage, identify the target audience;

[0008] Set up a messaging mechanism;

[0009] Capturing the interactive behavior of the target customer group according to the message delivery mechanism to obtain initial data;

[0010] Performing effectiveness statistics and in-depth analysis on the initial data to obtain analysis results;

[0011] Resource allocation is continuously optimized based on the analysis results.

[0012] The further technical solution is: in the activity planning stage, the target customer group is positioned, including:

[0013] During the event planning stage, we consider macro trends, industry trends, customer value, behavioral patterns, and social network dimensions, conduct graph clustering algorithm analysis on the set customer base, and find similar customers under weighted characteristics to obtain the target customer base.

[0014] A further technical solution is: the message delivery mechanism includes embedding an identification ID in a variety of marketing information delivery channels.

[0015] A further technical solution is: capturing the interactive behavior of the target customer group according to the message transmission mechanism to obtain initial data includes:

[0016] By deploying monitoring points in the financial product or service process, using tracking technology to capture the interactive behavior of the target customer group to obtain initial data;

[0017] The initial data includes data corresponding to user operation details including clicks, browsing and form filling.

[0018] The further technical solution is: by deploying monitoring points in the financial product or service process, using the embedding technology to capture the interactive behavior of the target customer group to obtain initial data, including:

[0019] Generate an identification ID for each marketing campaign;

[0020] Sending marketing information containing identification ID to the target customer group through various channels;

[0021] By deploying monitoring points in the financial product or service process, the interactive behavior of the target customer group is captured using tracking technology to obtain initial data.

[0022] A further technical solution is: performing effectiveness statistics and in-depth analysis on the initial data to obtain analysis results, including:

[0023] The initial data is associated with the identification ID, and the initial data is mapped to the original marketing campaign list through the identification ID to obtain the analysis result.

[0024] A further technical solution is: the continuously optimizing resource allocation according to the analysis result comprises:

[0025] Continuously adjust marketing strategies based on the analysis results combined with A / B testing to optimize resource allocation.

[0026] The present invention also provides a microfinance marketing data analysis device, comprising:

[0027] Positioning unit, used to locate target customers during the activity planning stage;

[0028] A mechanism setting unit, used to set a message delivery mechanism;

[0029] A capturing unit, used to capture the interaction behavior of the target customer group according to the message transmission mechanism to obtain initial data;

[0030] An analysis unit, used to perform effectiveness statistics and in-depth analysis on the initial data to obtain analysis results;

[0031] The optimization unit is used to continuously optimize resource allocation according to the analysis result.

[0032] The present invention further provides a computer device, which includes a memory and a processor. The memory stores a computer program, and the processor implements the above method when executing the computer program.

[0033] The present invention also provides a storage medium, wherein the storage medium stores a computer program, and the computer program implements the above method when executed by a processor.

[0034] The beneficial effects of the present invention compared with the prior art are: the present invention realizes precise marketing and continuous resource optimization through the process of target customer positioning, message delivery setting and data-driven optimization, and effectively solves the problem of customer diversity caused by business diversity in the marketing activities of the small and micro financial industry, and the problem of effectiveness statistics caused by the complexity of the association relationship.

[0035] The present invention is further described below in conjunction with the accompanying drawings and specific embodiments. BRIEF DESCRIPTION OF THE DRAWINGS

[0036] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other accompanying drawings can be obtained based on these accompanying drawings without paying any creative work.

[0037] Figure 1 A schematic diagram of an application scenario of the microfinance marketing data analysis and effectiveness statistics method provided by an embodiment of the present invention;

[0038] Figure 2 A flowchart of a method for analyzing microfinance marketing data and calculating effectiveness provided by an embodiment of the present invention;

[0039] Figure 3 A schematic block diagram of a microfinance marketing data analysis device provided by an embodiment of the present invention;

[0040] Figure 4 A schematic block diagram of a computer device provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0041] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0042] It should be understood that when used in this specification and the appended claims, the terms "include" and "comprises" indicate the presence of described features, integers, steps, operations, elements and / or components, but do not exclude the presence or addition of one or more other features, integers, steps, operations, elements, components and / or combinations thereof.

[0043] It should also be understood that the terms used in this specification of the present invention are only for the purpose of describing specific embodiments and are not intended to limit the present invention. As used in the specification of the present invention and the appended claims, unless the context clearly indicates otherwise, the singular forms "a", "an" and "the" are intended to include plural forms.

[0044] It should be further understood that the term "and / or" used in the present description and the appended claims refers to any and all possible combinations of one or more of the associated listed items, and includes these combinations.

[0045] See also Figure 1 and Figure 2 , Figure 1 A schematic diagram of an application scenario of the microfinance marketing data analysis and effectiveness statistics method provided in an embodiment of the present invention. Figure 2 A schematic flow chart of a method for analyzing marketing data and performing statistical results of microfinance provided in an embodiment of the present invention. The method for analyzing marketing data and performing statistical results of microfinance is applied to a server. The server interacts with the terminal to perform data exchange, deeply transforms the information transmission mode in the channel contact stage, and on this basis, strengthens the accuracy and completeness of data association in the statistical results link. The microfinance industry needs to collect and analyze a large amount of data through a digital platform to provide valuable insights into customer behavior and improve the effectiveness of marketing activities. Digital transformation can not only improve operational efficiency, but also enhance customer acquisition and retention capabilities; the application of big data and predictive analysis technology in the microfinance industry can help the microfinance industry identify customer behavior patterns and trends, optimize marketing strategies, and improve the effectiveness of customer relationship management. The application of these technologies can significantly improve the accuracy of marketing activity effectiveness evaluation and strategy optimization. Effectively solve the problem of customer diversity caused by business diversity in the marketing activities of the microfinance industry, combined with the problem of statistical results caused by the complexity of the association relationship.

[0046] Figure 2 1 is a flow chart of a method for analyzing microfinance marketing data and calculating effectiveness provided by an embodiment of the present invention. Figure 2 As shown, the method includes the following steps S110 to S150.

[0047] S110. During the event planning stage, identify the target customer group.

[0048] In this embodiment, the target customer group refers to the marketing object.

[0049] Specifically, during the activity planning stage, we consider the macro trend, industry trend, customer value, behavior pattern and social network dimension, conduct graph clustering algorithm analysis on the set customer group, find similar customers under weighted characteristics, and obtain the target customer group. To achieve accurate positioning. This analysis not only covers the direct associates of small and micro enterprises as the marketing subject, such as the legal person, shareholders, actual controllers and senior managers of the enterprise, but also goes deep into the second-degree associates who have close social ties with these direct associates, including their family members and relatives, as well as other non-associated persons such as financial personnel and cashiers who may indirectly contact marketing information due to job relationships or data errors.

[0050] This method aims to accurately locate the target customer group by comprehensively considering multiple dimensions such as macro trends, industry trends, customer value, behavioral patterns, and social networks. To achieve this goal, a graph clustering algorithm is used to construct an undirected graph G = (V, E). V is a node set and E is an edge set.

[0051] The node set V is divided into four subsets:

[0052] V1 is a node set for small and micro enterprises, including bill associates and transaction associates directly associated with the enterprise.

[0053] V2 is a set of directly associated person nodes, such as the legal person, shareholders, senior management, etc. of the enterprise.

[0054] V3 is the set of nodes of second-degree related persons, i.e., family members and relatives who have close social ties with the directly related person V2.

[0055] V4 is a set of other non-directly related nodes, such as financial personnel, cashiers, etc., who may be exposed to marketing information through their positions or data.

[0056] In graph G, each edge e ij The weight w of ∈E ij Defined according to the node type connected, as follows:

[0057] That is, if the edge connects the nodes in V1 and V2, the weight is w1; if the edge connects the nodes in V1 and V3, the weight is w2; if the edge connects two nodes in V1, the weight is w3; if the edge connects the nodes in V1 and V4, the weight is w4; these weights are set according to the strength of the relationship, w1>w2>w3>w4. This is intended to reflect the differences in the strength of the relationship between small and micro enterprises and various types of related persons.

[0058] Through graph clustering algorithm analysis, the connections and influences between different customer groups can be more accurately identified and understood. This helps locate potential customer groups and formulate personalized marketing strategies based on their relationship networks, thereby improving the effectiveness and response rate of marketing activities. Not only can directly related legal persons, shareholders, etc. be analyzed, but also their family members, relatives, and other people who are indirectly exposed to marketing information. This comprehensive perspective helps to better understand the customer's social network and decision-making path, so as to more effectively carry out market positioning and promotion activities. By clarifying the weight differences between different relationship types, enterprises can optimize resource allocation, focus their energy and resources on the customer groups that have the greatest impact on marketing, and improve resource utilization efficiency and return on investment.

[0059] In summary, customer analysis through graph clustering algorithms can not only help companies understand and utilize customer relationship networks more accurately, but also improve the accuracy and efficiency of marketing, thereby enhancing the company's competitiveness and market share.

[0060] S120: Set a message delivery mechanism.

[0061] In this embodiment, the message delivery mechanism includes embedding identification IDs in various marketing information delivery channels.

[0062] The message delivery mechanism is designed to solve the data tracking problem caused by a complex network of associated people. The mechanism embeds a unique identification ID in the marketing information sent through multiple channels (such as SMS, App Push notifications, corporate WeChat, outbound calls, etc.). It not only includes detailed information on the marketing activities (such as activity number, name, type, start and end dates, scenarios, target products, and versions), but also integrates the attribute information of the marketing list (including customer number, type, stratification, industry attributes, relevance, associated roles, operating regions, transaction frequency, response tendency points, channel preferences, and the latest interaction date). This ensures that every message sent can be effectively traced. In this way, no matter how the information is finally implemented through directly related corporate contacts or indirectly related individuals, such as family members, financial personnel, etc., it can ensure the accurate transmission of information and subsequent accurate statistics, greatly improving the feasibility of evaluating the effectiveness of marketing activities and optimizing strategies;

[0063] This message transmission mechanism constructs a potential node set V5: marketing-touching relationships based on the original small and micro enterprise relationship map. While enriching the small and micro enterprise relationship map, it also improves and connects the characteristic information of related marketing. Its relationship with small and micro enterprise V1 is between w2, w3, and w4.

[0064] Each message carries a unique ID, ensuring that the marketing information sent can be effectively traced. Whether the information is sent through directly related corporate contacts or indirectly related individuals (such as family members, financial personnel, etc.), it can ensure accurate transmission and subsequent tracking of the information. This effectively solves the data tracking problem under a complex network of related persons and ensures the accuracy of information transmission and execution of marketing activities.

[0065] By integrating detailed information about marketing activities with customer attributes, the mechanism not only promotes business implementation, but also greatly improves the feasibility of evaluating the effectiveness of marketing activities and optimizing strategies. Enterprises can accurately formulate personalized marketing strategies based on customer response tendencies, transaction frequency, channel preferences and other attribute information to increase the success rate and return on investment of marketing activities.

[0066] By building the potential node set V5 (marketing reach relationship) based on the original small and micro enterprise relationship map, the mechanism not only enriches the relationship map of small and micro enterprises, but also opens up the characteristic information of related marketing. This enrichment and improvement enables enterprises to understand and utilize the customer relationship network more comprehensively, thereby more accurately positioning the market and identifying target customer groups.

[0067] In short, this messaging mechanism not only improves the efficiency and accuracy of marketing campaign execution, but also brings more data insights and strategic optimization opportunities to companies, helping to enhance their position and influence in market competition.

[0068] S130: Capture the interactive behavior of the target customer group according to the message transmission mechanism to obtain initial data.

[0069] In this embodiment, monitoring points are deployed in the financial product or service process, and the interactive behavior of the target customer group is captured using tracking technology to obtain initial data; wherein the initial data includes data corresponding to user operation details including clicks, browsing, and form filling.

[0070] Specifically, by setting monitoring points in the financial product or service process, that is, using tracking technology, users' interactive behaviors can be recorded and analyzed in real time. Whether it is a directly related user or a second- or indirect user who receives a message with a unique ID and enters the product page, the system will automatically trigger the preset tracking point and record the user's clicks, browsing, form filling and other operation details.

[0071] This rich behavioral data is then used to deeply analyze the user's behavior patterns and paths. By analyzing this data, marketing strategies can be optimized to ensure that all potential business conversions are effectively captured and associated. This method greatly improves the accuracy of marketing campaign effectiveness evaluation and strategy iteration, enabling companies to understand user needs and behaviors more accurately, thereby effectively improving market competitiveness.

[0072] In one embodiment, the above-mentioned step S130 may include steps S131 - S133 .

[0073] S131. Generate an identification ID for each marketing activity;

[0074] S132, sending the marketing information containing the identification ID to the target customer group through various channels;

[0075] S133. By deploying monitoring points in the financial product or service process, the interactive behavior of the target customer group is captured using the embedding technology to obtain initial data.

[0076] In this embodiment, a unique activity ID is generated for each marketing campaign. This ensures that each marketing campaign has a unique identifier for subsequent tracking and analysis; marketing information containing the activity ID is sent to target customers through various channels (such as SMS, App push, etc.). This precise way of sending information can ensure that target customers receive customized marketing content and improve the efficiency of information dissemination; after receiving the information, customers may interact with it directly or forward it to others. This behavior expands the scope of influence of marketing activities and increases the coverage of potential customers; whether it is a direct customer or an indirect recipient, when they click on the link to enter the product or service page, the activity ID will be passed to the page. This step ensures the association between the user and the activity ID, laying the foundation for subsequent behavior capture; deploying point technology on the product / service page to accurately capture various interactive behaviors of users (such as browsing, clicking, filling out forms, etc.). These data provide detailed user behavior information for subsequent analysis.

[0077] S140: Perform effectiveness statistics and in-depth analysis on the initial data to obtain analysis results.

[0078] In this embodiment, based on the improved statistical method, the limitations of the traditional OneId system are broken through, and a relatively complete marketing map of small and micro enterprises is built through the identification ID embedded in the marketing information push. When the target customer group receives the message containing these identification IDs and further interacts with the product, the system uses the embedding technology to accurately capture the user's operation behavior and closely associates these behavior data with the target customer group information of the marketing activity.

[0079] The analysis results refer to the results of the analysis, such as the effectiveness of the marketing strategy.

[0080] In this embodiment, the initial data is associated with the identification ID, and the initial data is mapped to the original marketing activity list through the identification ID to obtain the analysis result.

[0081] Specifically, the system associates the captured user behavior data with the incoming activity ID. Through this association, the impact of a specific marketing activity on user behavior can be accurately tracked and the actual effect of the activity can be analyzed.

[0082] Using the activity ID, the captured user behavior data is mapped back to the original marketing activity list to achieve association with the target customer group information. This association allows for a more accurate assessment of the impact and effectiveness of marketing activities on specific customer groups.

[0083] By associating the data in the above steps, the system can track the impact of each marketing campaign on a specific customer group, including direct target customers and indirect contacts. This data-driven analysis can help companies more accurately evaluate and optimize marketing strategies and improve overall marketing effectiveness and ROI (return on investment).

[0084] In summary, this marketing method based on identification ID and tracking technology not only enriches the company's marketing relationship map, but also significantly improves the accuracy and depth of marketing campaign effectiveness evaluation. By accurately tracking user behavior and real-time correlation of behavioral data, companies can more accurately understand user needs and behavior patterns, thereby optimizing marketing activities and improving market competitiveness.

[0085] S150. Continuously optimize resource allocation according to the analysis result.

[0086] In this embodiment, the marketing strategy is continuously adjusted according to the analysis results in combination with A / B testing to optimize resource allocation.

[0087] Specifically, through real-time data analysis, marketing teams can instantly identify fluctuations in the effectiveness of marketing campaigns. This agile feedback mechanism allows the team to quickly adjust strategies to optimize campaign results and maximize conversion rates. Information mismatch or loss problems that may exist in traditional methods are effectively solved, ensuring that decisions are based on the most accurate data.

[0088] Combined with A / B testing, the team can compare the effects of different strategies in the experiment, thereby continuously optimizing the marketing strategy. This method not only improves the efficiency of activity execution, but also greatly reduces decision-making risks, ensuring that every strategy adjustment is based on reliable data and experimental evidence.

[0089] The unique ID embedded in the marketing information enables the team to fully map the user's business and product conversion process. In addition to direct conversion, it can also track the behavior of first- and second-degree related users, and even the impact of indirect related users. This comprehensive performance analysis capability provides companies with deeper insights and helps accurately analyze user behavior patterns and decision paths.

[0090] Through accurate performance statistics, operations teams and decision makers can effectively analyze the ROI (return on investment) of each marketing campaign. This data-driven decision-making makes resource allocation more efficient, ensuring that the cost-effectiveness of marketing activities is maximized while maximizing market competitiveness.

[0091] Through dynamic optimization of marketing strategies, enterprises can more accurately meet customer needs and improve customer satisfaction. At the same time, optimized marketing activities and resource allocation strategies can also stand out in the fiercely competitive microfinance industry and enhance brand influence and market position.

[0092] In summary, this marketing optimization method that comprehensively utilizes real-time data analysis, A / B testing, and unique identification ID not only improves the decision-making ability and execution efficiency of the operation team, but also significantly enhances the competitiveness and sustainable development capabilities of enterprises in the highly competitive market environment.

[0093] The application of the method of this embodiment in the microfinance industry has indeed effectively solved many challenges, especially the difficulties in performance statistics caused by business diversity, customer diversity, and complex relationships.

[0094] The microfinance industry covers a wide range of businesses and has a diverse customer base, so marketing activities often need to face customer groups with different characteristics and needs. Traditional methods are difficult to accurately grasp the preferences and behavior patterns of each customer group, resulting in poor marketing results. The method of this embodiment can more accurately identify the characteristics and reactions of different groups through refined data management and tracking, thereby adjusting marketing strategies in a targeted manner.

[0095] In the microfinance industry, the customer relationship network is complex, and one activity may affect multiple customers or related businesses. Traditional statistical methods are difficult to accurately capture such multiple impacts and related effects, so the true effectiveness of activities is often underestimated or misjudged. The method of this embodiment uses a unique ID and real-time data analysis to track and quantify the performance of each customer and its related businesses, effectively solving this statistical problem and improving the reliability and practicality of the quantitative analysis of activity effects.

[0096] The method of this embodiment realizes the refined management and tracking of the whole chain data from activity planning to business implementation. Through the accurate recording and analysis of the data of each link, the marketing strategy can be adjusted and optimized in real time to ensure that the execution of the strategy is consistent with the expected effect. This refined management and tracking greatly improves the accuracy and efficiency of decision-making, and supports the implementation of intelligent marketing practices and accurate decision-making in the microfinance industry.

[0097] The method of this embodiment significantly improves the intelligent marketing practice and accurate decision-making capabilities in the microfinance industry. Through data-driven strategy adjustment and optimization, enterprises can better understand and meet customer needs, improve market response speed and competitiveness, and bring continuous positive impacts to business growth and customer satisfaction.

[0098] In short, this marketing optimization method that comprehensively utilizes refined data management, real-time analysis, and unique identification ID has brought a new marketing management model to the microfinance industry, effectively responded to the complex and changing market environment within the industry, and promoted the sustainable development and success of enterprises in the fierce competition.

[0099] The above-mentioned microfinance marketing data analysis and effectiveness statistics method achieves precise marketing and continuous resource optimization through target customer positioning, message delivery setting and data-driven optimization process, and effectively solves the customer diversity caused by business diversity in the microfinance industry's marketing activities, combined with the effectiveness statistics problem caused by the complexity of the relationship.

[0100] Figure 3 is a schematic block diagram of a microfinance marketing data analysis device 300 provided in an embodiment of the present invention. Figure 3 As shown, corresponding to the above microfinance marketing data analysis and effectiveness statistics method, the present invention also provides a microfinance marketing data analysis device 300. The microfinance marketing data analysis device 300 includes a unit for executing the above microfinance marketing data analysis and effectiveness statistics method, and the device can be configured in a server. Figure 3 The microfinance marketing data analysis device 300 includes a positioning unit 301, a mechanism setting unit 302, a capture unit 303, an analysis unit 304 and an optimization unit 305.

[0101] The positioning unit 301 is used to locate the target customer group during the activity planning stage; the mechanism setting unit 302 is used to set the message transmission mechanism; the capture unit 303 is used to capture the interactive behavior of the target customer group according to the message transmission mechanism to obtain initial data; the analysis unit 304 is used to perform effectiveness statistics and in-depth analysis on the initial data to obtain analysis results; the optimization unit 305 is used to continuously optimize resource allocation according to the analysis results.

[0102] In one embodiment, the positioning unit 301 is used to consider macro trends, industry trends, customer value, behavior patterns and social network dimensions during the activity planning stage, perform graph clustering algorithm analysis on the set customer group, and find similar customers under weighted characteristics to obtain the target customer group.

[0103] In one embodiment, the capturing unit 303 is used to capture the interaction behavior of the target customer group by deploying monitoring points in the financial product or service process and using the embedding technology to obtain initial data;

[0104] The initial data includes data corresponding to user operation details including clicks, browsing and form filling.

[0105] In one embodiment, the capturing unit 303 includes:

[0106] The ID generation subunit is used to generate an identification ID for each marketing activity; the sending subunit is used to send the marketing information containing the identification ID to the target customer group through various channels; the tracking point capture subunit is used to deploy monitoring points in the financial product or service process and use tracking point technology to capture the interactive behavior of the target customer group to obtain initial data.

[0107] In one embodiment, the analysis unit 304 is used to associate the initial data with the identification ID, and map the initial data to the original marketing activity list through the identification ID to obtain the analysis result.

[0108] In one embodiment, the optimization unit 305 is used to continuously adjust the marketing strategy according to the analysis result in combination with A / B testing to optimize resource allocation.

[0109] It should be noted that technicians in the relevant field can clearly understand that the specific implementation process of the above-mentioned microfinance marketing data analysis device 300 and each unit can refer to the corresponding description in the aforementioned method embodiment, and for the convenience and brevity of description, it will not be repeated here.

[0110] The microfinance marketing data analysis device 300 can be implemented in the form of a computer program. Figure 4 Runs on the computer device shown.

[0111] See also Figure 4 , Figure 4 5 is a schematic block diagram of a computer device provided in an embodiment of the present application. The computer device 500 may be a server, wherein the server may be an independent server or a server cluster composed of multiple servers.

[0112] See also Figure 4The computer device 500 includes a processor 502 , a memory and a network interface 505 connected via a system bus 501 , wherein the memory may include a non-volatile storage medium 503 and an internal memory 504 .

[0113] The non-volatile storage medium 503 can store an operating system 5031 and a computer program 5032. The computer program 5032 includes program instructions, and when the program instructions are executed, the processor 502 can execute a microfinance marketing data analysis and effectiveness statistics method.

[0114] The processor 502 is used to provide computing and control capabilities to support the operation of the entire computer device 500 .

[0115] The internal memory 504 provides an environment for the operation of the computer program 5032 in the non-volatile storage medium 503. When the computer program 5032 is executed by the processor 502, the processor 502 can execute a microfinance marketing data analysis and effectiveness statistics method.

[0116] The network interface 505 is used to communicate with other devices over the network. Figure 4 The structure shown in the figure is merely a block diagram of a portion of the structure related to the solution of the present application, and does not constitute a limitation on the computer device 500 to which the solution of the present application is applied. The specific computer device 500 may include more or fewer components than those shown in the figure, or combine certain components, or have a different arrangement of components.

[0117] The processor 502 is used to run the computer program 5032 stored in the memory to implement the following steps:

[0118] During the activity planning stage, the target customer group is identified; a message delivery mechanism is set up; the interactive behavior of the target customer group is captured according to the message delivery mechanism to obtain initial data; effectiveness statistics and in-depth analysis of the initial data are performed to obtain analysis results; and resource allocation is continuously optimized according to the analysis results.

[0119] The message delivery mechanism includes embedding identification IDs in a variety of marketing information delivery channels.

[0120] In one embodiment, when implementing the step of locating the target customer group in the activity planning stage, the processor 502 specifically implements the following steps:

[0121] During the event planning stage, we consider macro trends, industry trends, customer value, behavioral patterns, and social network dimensions, conduct graph clustering algorithm analysis on the set customer base, and find similar customers under weighted characteristics to obtain the target customer base.

[0122] In one embodiment, when the processor 502 implements the step of capturing the interaction behavior of the target customer group according to the message transmission mechanism to obtain initial data, the processor 502 specifically implements the following steps:

[0123] By deploying monitoring points in the financial product or service process, using tracking technology to capture the interactive behavior of the target customer group to obtain initial data;

[0124] The initial data includes data corresponding to user operation details including clicks, browsing and form filling.

[0125] In one embodiment, when the processor 502 implements the step of deploying monitoring points in the financial product or service process and using the tracking technology to capture the interactive behavior of the target customer group to obtain initial data, the processor 502 specifically implements the following steps:

[0126] Generate an identification ID for each marketing campaign; send marketing information containing the identification ID to the target customer group through various channels; deploy monitoring points in the financial product or service process and use point-of-sale technology to capture the interactive behavior of the target customer group to obtain initial data.

[0127] In one embodiment, when the processor 502 implements the step of performing effectiveness statistics and in-depth analysis on the initial data to obtain the analysis result, the processor 502 specifically implements the following steps:

[0128] The initial data is associated with the identification ID, and the initial data is mapped to the original marketing campaign list through the identification ID to obtain the analysis result.

[0129] In one embodiment, when the processor 502 implements the step of continuously optimizing resource allocation according to the analysis result, the processor 502 specifically implements the following steps:

[0130] Continuously adjust marketing strategies based on the analysis results combined with A / B testing to optimize resource allocation.

[0131] It should be understood that in the embodiment of the present application, the processor 502 may be a central processing unit (CPU), and the processor 502 may also be other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. Among them, the general-purpose processor may be a microprocessor or the processor may also be any conventional processor, etc.

[0132] It can be understood by those skilled in the art that all or part of the processes in the method for implementing the above embodiment can be completed by instructing the relevant hardware through a computer program. The computer program includes program instructions, and the computer program can be stored in a storage medium, which is a computer-readable storage medium. The program instructions are executed by at least one processor in the computer system to implement the process steps of the embodiment of the above method.

[0133] Therefore, the present invention also provides a storage medium. The storage medium may be a computer-readable storage medium. The storage medium stores a computer program, wherein when the computer program is executed by a processor, the processor executes the following steps:

[0134] During the activity planning stage, the target customer group is identified; a message delivery mechanism is set up; the interactive behavior of the target customer group is captured according to the message delivery mechanism to obtain initial data; effectiveness statistics and in-depth analysis of the initial data are performed to obtain analysis results; and resource allocation is continuously optimized according to the analysis results.

[0135] The message delivery mechanism includes embedding identification IDs in a variety of marketing information delivery channels.

[0136] In one embodiment, when the processor executes the computer program to implement the step of locating the target customer group in the activity planning stage, the processor specifically implements the following steps:

[0137] During the event planning stage, we consider macro trends, industry trends, customer value, behavioral patterns, and social network dimensions, conduct graph clustering algorithm analysis on the set customer base, and find similar customers under weighted characteristics to obtain the target customer base.

[0138] In one embodiment, when the processor executes the computer program to implement the step of capturing the interactive behavior of the target customer group according to the message transmission mechanism to obtain initial data, the processor specifically implements the following steps:

[0139] By deploying monitoring points in the financial product or service process, using tracking technology to capture the interactive behavior of the target customer group to obtain initial data;

[0140] The initial data includes data corresponding to user operation details including clicks, browsing and form filling.

[0141] In one embodiment, when the processor executes the computer program to implement the step of deploying monitoring points in the financial product or service process and using the embedding technology to capture the interactive behavior of the target customer group to obtain initial data, the processor specifically implements the following steps:

[0142] Generate an identification ID for each marketing campaign; send marketing information containing the identification ID to the target customer group through various channels; deploy monitoring points in the financial product or service process and use point-of-sale technology to capture the interactive behavior of the target customer group to obtain initial data.

[0143] In one embodiment, when the processor executes the computer program to implement the step of performing effectiveness statistics and in-depth analysis on the initial data to obtain the analysis result, the processor specifically implements the following steps:

[0144] The initial data is associated with the identification ID, and the initial data is mapped to the original marketing campaign list through the identification ID to obtain the analysis result.

[0145] In one embodiment, when the processor executes the computer program to implement the step of continuously optimizing resource allocation according to the analysis result, the processor specifically implements the following steps:

[0146] Continuously adjust marketing strategies based on the analysis results combined with A / B testing to optimize resource allocation.

[0147] The storage medium may be a USB flash drive, a mobile hard disk, a read-only memory (ROM), a magnetic disk, or an optical disk, etc., which are computer-readable storage media that can store program codes.

[0148] Those of ordinary skill in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, computer software, or a combination of the two. In order to clearly illustrate the interchangeability of hardware and software, the composition and steps of each example have been generally described in terms of function in the above description. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of the present invention.

[0149] In the several embodiments provided by the present invention, it should be understood that the disclosed devices and methods can be implemented in other ways. For example, the device embodiments described above are only schematic. For example, the division of each unit is only a logical function division, and there may be other division methods in actual implementation. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed.

[0150] The steps in the method of the embodiment of the present invention can be adjusted in order, combined and deleted according to actual needs. The units in the device of the embodiment of the present invention can be combined, divided and deleted according to actual needs. In addition, the functional units in the various embodiments of the present invention can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit.

[0151] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a storage medium. Based on this understanding, the technical solution of the present invention is essentially or the part that contributes to the prior art, or all or part of the technical solution can be embodied in the form of a software product, and the computer software product is stored in a storage medium, including a number of instructions for a computer device (which can be a personal computer, terminal, or network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present invention.

[0152] The above is only a specific embodiment of the present invention, but the protection scope of the present invention is not limited thereto. Any technician familiar with the technical field can easily think of various equivalent modifications or replacements within the technical scope disclosed by the present invention, and these modifications or replacements should be included in the protection scope of the present invention. Therefore, the protection scope of the present invention shall be based on the protection scope of the claims.

Claims

1. A method for analyzing small and micro financial marketing data and statistical results, characterized in that: include: During the event planning stage, identify the target audience; Set up a messaging mechanism; Capturing the interactive behavior of the target customer group according to the message delivery mechanism to obtain initial data; Performing effectiveness statistics and in-depth analysis on the initial data to obtain analysis results; Resource allocation is continuously optimized based on the analysis results.

2. The microfinance marketing data analysis and effectiveness statistics method according to claim 1 is characterized in that: In the event planning stage, the target audience is identified, including: During the event planning stage, we consider macro trends, industry trends, customer value, behavioral patterns, and social network dimensions, conduct graph clustering algorithm analysis on the set customer base, and find similar customers under weighted characteristics to obtain the target customer base.

3. The microfinance marketing data analysis and effectiveness statistics method according to claim 1 is characterized in that: The messaging mechanism includes embedding an identification ID in various marketing information delivery channels.

4. The microfinance marketing data analysis and effectiveness statistics method according to claim 3 is characterized in that: The capturing of the interaction behavior of the target customer group according to the message transmission mechanism to obtain initial data includes: By deploying monitoring points in the financial product or service process, using tracking technology to capture the interactive behavior of the target customer group to obtain initial data; The initial data includes data corresponding to user operation details including clicks, browsing and form filling.

5. The microfinance marketing data analysis and effectiveness statistics method according to claim 4 is characterized in that: The monitoring points are deployed in the financial product or service process, and the target customer group's interactive behavior is captured by using the embedding technology to obtain initial data, including: Generate an identification ID for each marketing campaign; Sending marketing information containing identification ID to the target customer group through various channels; By deploying monitoring points in the financial product or service process, the interactive behavior of the target customer group is captured using tracking technology to obtain initial data.

6. The microfinance marketing data analysis and effectiveness statistics method according to claim 1 is characterized in that: The performing of effectiveness statistics and in-depth analysis on the initial data to obtain analysis results includes: The initial data is associated with the identification ID, and the initial data is mapped to the original marketing campaign list through the identification ID to obtain the analysis result.

7. The microfinance marketing data analysis and effectiveness statistics method according to claim 1 is characterized in that: The continuously optimizing resource allocation according to the analysis result includes: Continuously adjust marketing strategies based on the analysis results combined with A / B testing to optimize resource allocation.

8. A microfinance marketing data analysis device, characterized in that: include: Positioning unit, used to locate target customers during the event planning stage; A mechanism setting unit, used to set a message delivery mechanism; A capturing unit, used for capturing the interaction behavior of the target customer group according to the message transmission mechanism to obtain initial data; An analysis unit, used to perform effectiveness statistics and in-depth analysis on the initial data to obtain analysis results; The optimization unit is used to continuously optimize resource allocation according to the analysis result.

9. A computer device, characterized in that: The computer device comprises a memory and a processor, the memory stores a computer program, and the processor implements the method according to any one of claims 1 to 7 when executing the computer program.

10. A storage medium, characterized in that: The storage medium stores a computer program, and when the computer program is executed by a processor, the method according to any one of claims 1 to 7 is implemented.

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