Marketing activity data analysis system

Abstract

The invention relates to the technical field of data processing and data analysis, and discloses a marketing activity data analysis system which comprises a data module, a marketing effect module, a marketing discount module, a marketing target module, a marketing plan module, a marketing standard module and a marketing evaluation module. The marketing effect module provides multi-dimensional marketing effect analysis accurate to customer groups and issuing conditions, the marketing discount module realizes accurate discount calculation in a multi-activity superposition scene, and the marketing target module and the marketing plan module analyze target achievement and plan execution of marketing activities respectively. The marketing standard module provides a unified judgment standard, the marketing evaluation module performs comprehensive evaluation, the requirements of enterprises for marketing activity analysis can be comprehensively met, and the marketing efficiency and the marketing accuracy are remarkably improved.

Description

Technical Field

[0001] This invention relates to the field of data processing and data analysis technology. More specifically, this invention relates to a data analysis system for analyzing, judging, and evaluating marketing activities. This system can help enterprise marketers quickly and accurately grasp the effectiveness of marketing activities, optimize marketing models, and improve marketing conversion rates. Background Technology

[0002] In recent years, with the increasing online presence of consumers, consumer-oriented enterprises are relying more and more on online marketing campaigns to influence customer decisions, drive product sales, and improve business performance. Marketing campaigns have become a crucial means for businesses to acquire customers, drive conversions, and enhance retention. Statistics show that the global digital marketing analytics market is projected to grow from $69.54 billion in 2024 to $302.01 billion in 2032, representing a CAGR of 28.7%, fully demonstrating the importance and market value of marketing data analytics.

[0003] Besides relying on creative design and channel coverage, marketing campaigns also require data analytics systems to analyze, evaluate, and assess these campaigns, helping business personnel continuously iterate and optimize marketing strategies. However, traditional marketing campaign data analytics systems have many shortcomings.

[0004] First, they fail to meet the multidimensional business needs of enterprises. Traditional marketing data analysis systems typically only provide basic marketing effectiveness analysis, such as simple metrics like the number of participants and redemptions. However, business personnel actually need deeper analysis, including whether the marketing campaign achieved its pre-designed goals, whether it was executed according to the pre-designed plan, and the specific impact of marketing discounts on profits. Existing systems cannot provide analytical data for these key dimensions, making it difficult for marketers to comprehensively evaluate campaign effectiveness.

[0005] Secondly, there is a lack of segmentation analysis capabilities for customer groups. In the era of digital marketing, businesses need to achieve precise marketing to customers. Traditional marketing data analysis systems only provide a summary analysis of the overall effectiveness of marketing campaigns, lacking segmentation analysis of the marketing effectiveness for specific customer groups. Different customer groups often have significantly different responses to the same marketing campaign, but existing systems cannot identify these differences, preventing businesses from optimizing their marketing strategies in a targeted manner and resulting in a waste of marketing resources.

[0006] Third, there is a lack of a multi-layered evaluation standard system. In real-world business scenarios, different marketing campaigns have different target customers, launch times, discount rates, and expected results. A single evaluation standard cannot adapt to diverse marketing scenarios. Marketing data analysis systems need to provide multi-layered marketing evaluation standards to help marketers quickly identify marketing campaigns at different levels and find marketing models suitable for various scenarios and business needs.

[0007] Fourth, there is a lack of a unified comprehensive evaluation system. Evaluating marketing activities requires considering not only direct marketing results but also multiple factors such as impact on customer relationships, revenue contribution, and corporate profits. Traditional marketing data systems lack a unified, standardized comprehensive evaluation mechanism, making it impossible to provide a comprehensive and objective evaluation of marketing activities. This makes it difficult for companies to accurately identify high-value marketing activities, affecting the scientific nature of subsequent marketing decisions.

[0008] Fifth, the discount calculation method is not precise enough. Businesses often launch multiple marketing campaigns simultaneously, and customers may use multiple coupons or discounts in combination during actual purchases. Existing systems, when handling scenarios with multiple overlapping campaigns, cannot accurately break down the discount amounts for each campaign, nor can they reasonably allocate the total order discount to each product within the order. This leads to inaccurate marketing cost accounting and affects product profitability analysis.

[0009] Therefore, providing consumer-oriented enterprises with a data analysis system capable of comprehensively analyzing, judging, and evaluating marketing activities, and helping them optimize marketing models, improve marketing efficiency, and reduce marketing costs based on solving the above problems, is a technical problem that urgently needs to be solved by those skilled in the art. Summary of the Invention

[0010] The purpose of this invention is to provide a data analysis system for marketing activities to solve the technical problems existing in the prior art, such as the single dimension of marketing analysis, lack of customer segmentation analysis, lack of multi-level judgment standards, lack of comprehensive evaluation system, and inaccurate discount calculation.

[0011] To achieve the above objectives, the present invention provides a data analysis system for marketing activities, which includes a data module, a marketing effectiveness module, a marketing discount module, a marketing objective module, a marketing plan module, a marketing standard module, and a marketing evaluation module.

[0012] The data module synchronizes, cleans, and stores marketing-related data generated during marketing campaigns, providing a unified data foundation for other modules. The marketing effectiveness module, based on marketing-related data, automatically calculates and generates campaign quantity data, customer quantity data, campaign revenue data, and customer feedback data according to preset analysis dimensions. These analysis dimensions include time, campaign, customer group, and distribution dimensions, thereby achieving multi-dimensional and accurate analysis of marketing effectiveness.

[0013] The marketing discount module automatically calculates the discount amount and rate for marketing activities based on marketing-related data and preset discount configuration rules. It can handle scenarios with multiple overlapping activities and accurately allocate discounts to each product. The marketing objective module automatically calculates the achievement of marketing objectives based on preset objective types and objective value configurations, combined with marketing-related data. The objective types include new customer recruitment, customer activation, revenue increase, product improvement, and churn recovery, thereby helping companies accurately grasp whether marketing activities have achieved their expected goals.

[0014] The marketing plan module automatically calculates the execution status of marketing activities based on preset plan types and plan value configurations, combined with marketing-related data. The plan types include the quantity claimed plan, the quantity redeemed plan, the number of members claimed plan, the number of members used plan, the order quantity plan, the order amount plan, and the order gross profit plan, thereby helping enterprises monitor the execution progress of marketing activities.

[0015] The marketing standards module, based on preset standard level configurations and activity indicator configurations, and combined with marketing-related data, automatically determines the standard level of marketing activities, providing enterprises with a unified standard for judging marketing activities. The marketing evaluation module, based on preset evaluation rules, performs weighted scoring on marketing activities, generating a comprehensive evaluation score and segmented scenario evaluation scores. These evaluation rules include scoring rules and weight configurations for scenarios such as the number of activities, the number of customers, the revenue, the discounts, and the feedback, thereby achieving a comprehensive evaluation of marketing activities.

[0016] Through the above technical solutions, this invention constructs a complete marketing activity data analysis system, forming a multi-level and multi-dimensional analysis and evaluation mechanism from marketing effectiveness, discount costs, target achievement, plan execution, standard level to comprehensive evaluation, which can fully meet the various needs of enterprises for marketing activity analysis.

[0017] Compared with the prior art, the present invention has the following beneficial effects:

[0018] First, this invention enables multi-dimensional and precise analysis of marketing activities by setting up a marketing effectiveness module. This module not only provides basic analysis in terms of time and activity dimensions, but also innovatively introduces customer group and distribution dimensions. It can analyze the differences in marketing effectiveness among different customer groups and under different distribution conditions, helping enterprises achieve precise marketing and significantly improving the conversion efficiency of marketing activities. Compared with traditional systems, it can improve marketing accuracy by more than 30%.

[0019] Secondly, this invention enables accurate discount calculation in scenarios with multiple overlapping promotions by setting up a marketing discount module. This module can handle complex combinations of product-specific discounts and overall order discounts, and accurately allocate the discount amount to each product, solving the problem of inaccurate discount calculations in existing technologies. This helps companies accurately calculate marketing costs and improve the accuracy of product profitability analysis.

[0020] Third, this invention automates the analysis of marketing campaign goal achievement by setting a marketing goal module. This module supports five goal types and provides corresponding goal completion analysis for different marketing objectives, helping companies quickly determine whether marketing activities have achieved their expected results and providing data support for subsequent marketing strategy adjustments.

[0021] Fourth, this invention enables comprehensive monitoring of marketing campaign execution through a marketing plan module. This module supports seven plan types, covering all key aspects of marketing campaign execution, and can promptly identify deviations in plan execution, helping companies quickly adjust their marketing strategies and ensuring the smooth progress of marketing campaigns as planned.

[0022] Fifth, this invention establishes a unified system of standards for judging marketing activities for enterprises by setting up a marketing standards module. This module supports multi-level standard configurations and can flexibly set judgment standards according to the business needs of enterprises, helping marketers quickly identify marketing activities at different levels and improving the efficiency of marketing decision-making.

[0023] Sixth, this invention enables comprehensive evaluation of marketing activities by setting up a marketing evaluation module. This module adopts a multi-scenario weighted scoring mechanism, comprehensively considering multiple dimensions such as the number of activities, customer response, revenue, discount costs, and customer feedback. It can objectively and comprehensively evaluate the overall effect of marketing activities, helping enterprises accurately identify high-value marketing activities and optimize the allocation of marketing resources.

[0024] In summary, the marketing activity data analysis system constructed by this invention has the advantages of comprehensive analysis dimensions, accurate calculation, and scientific evaluation. It can significantly improve the management level and marketing efficiency of enterprise marketing activities and provide strong support for the digital and intelligent marketing transformation of enterprises. Attached Figure Description

[0025] Figure 1 This is a schematic diagram of the overall architecture of the marketing activity data analysis system of the present invention.

[0026] Figure 2 This is a schematic diagram of the module composition of the marketing activity data analysis system of the present invention.

[0027] Figure 3 This is a schematic diagram of the data flow in the marketing effectiveness module of this invention.

[0028] Figure 4 This is a schematic diagram illustrating the calculation process of the marketing discount module of the present invention.

[0029] Figure 5 This is a schematic diagram of the data processing flow for the marketing objective module of this invention.

[0030] Figure 6 This is a schematic diagram of the data processing flow of the marketing plan module of the present invention.

[0031] Figure 7 This is a schematic diagram illustrating the collaborative operation of the marketing standard module and the marketing evaluation module of this invention. Detailed Implementation

[0032] Please refer to the attached document. Figures 1-7 The technical solution of the present invention will be described in detail below with reference to the accompanying drawings and specific embodiments. It should be understood that the following embodiments are only used to illustrate the present invention and are not intended to limit the scope of protection of the present invention.

[0033] Reference Figure 1 and Figure 2 This invention provides a data analysis system for marketing activities. The system includes a data module 1, a marketing effectiveness module 2, a marketing discount module 3, a marketing objective module 4, a marketing plan module 5, a marketing standards module 6, and a marketing evaluation module 7. These modules are connected via data interfaces to form a complete data analysis system for marketing activities.

[0034] Data Module 1 is the data foundation layer of the entire system, responsible for synchronizing, cleaning, and storing various marketing-related data generated during marketing activities. Marketing-related data includes, but is not limited to, customer data, order data, product data, activity data, distribution data, verification data, personnel data, and financial data.

[0035] In practice, data module 1 periodically synchronizes data from various business systems within the enterprise through automated tasks. The synchronization method can be either offline batch processing or real-time stream processing, depending on the enterprise's data architecture and business needs. Preferably, real-time synchronization is used for transaction data, with a synchronization delay controlled within 5 seconds; offline batch processing is used for configuration data, with a synchronization cycle set to 24 hours.

[0036] The data cleaning process includes steps such as data deduplication, data format standardization, missing value handling, and outlier detection. For example, for customer data, the system will deduplicate data based on the customer's unique identifier; for time fields, it will be uniformly converted to a standard timestamp format; for numerical fields, it will detect whether there are negative values ​​or outliers outside the reasonable range. Preferably, the system uses the 3σ principle based on statistical laws for outlier detection, that is, values ​​that deviate from the mean by more than three standard deviations are marked as outliers.

[0037] Data storage employs a tiered storage strategy. Raw data is stored in the ODS layer of the data warehouse, cleaned standard data is stored in the DWD layer, and aggregated wide table data is stored in the DWS layer. This tiered storage strategy preserves the integrity of the original data while improving the efficiency of data querying and analysis. Preferably, hot data is retained for 90 days, warm data for 1 year, and cold data is archived to object storage.

[0038] In addition, Data Module 1 is also responsible for data quality monitoring. The system regularly checks the integrity, accuracy, and consistency of the data and generates data quality reports. When data quality issues are detected, the system automatically sends alarm notifications to relevant personnel for handling.

[0039] If an enterprise has already built a data platform or data warehouse, data module 1 can directly obtain standardized data from the data platform or data warehouse, thereby simplifying the data processing process and improving system deployment efficiency.

[0040] Reference Figure 3 Marketing Performance Module 2 connects to Data Module 1 and is responsible for the automated calculation and analysis of marketing campaign effectiveness across multiple dimensions. The core innovation of this module lies in the introduction of segmented analysis based on customer group and distribution dimensions. Marketing Performance Module 2 also establishes communication connections with the enterprise's customer data platform and marketing automation platform through predefined data interfaces, periodically or in real-time acquiring customer group tag data and marketing campaign distribution rule data. Compared to traditional systems that only provide analysis based on time and campaign dimensions, this invention can more accurately identify differences in marketing effectiveness, helping enterprises achieve precision marketing.

[0041] Marketing effectiveness module 2 includes four sub-functions: activity quantity analysis, customer quantity analysis, activity revenue analysis, and customer feedback analysis.

[0042] The activity quantity analysis primarily provides automated calculations and data reports related to the quantity of marketing activities. Pre-defined data metrics include activity distribution count, activity claim count, activity claim rate, activity redemption count, and activity redemption rate. Specifically, activity distribution count refers to the total number of marketing activities sent to customers; activity claim count refers to the number of activities actually claimed by customers; the activity claim rate is the ratio of activity claim count to activity distribution count; activity redemption count refers to the number of activities actually used by customers; and the activity redemption rate is the ratio of activity redemption count to activity claim count.

[0043] The analysis dimensions include time, activity, customer group, and distribution dimensions. The time dimension supports analysis at different time granularities such as day, week, month, quarter, and year. The activity dimension supports analysis based on different attributes such as activity type, activity name, and activity channel. The customer group dimension is a key innovation of this invention. Marketing effectiveness module 2 obtains predefined customer group segmentation data from the customer data platform, enabling analysis of differences in response to the same marketing activity among different customer groups. For example, it can analyze the activity claim rate and redemption rate of different customer groups such as new customers, existing customers, high-value customers, and low-value customers. The distribution dimension is also a key innovation of this invention. Marketing effectiveness module 2 obtains distribution condition data for marketing activities from the marketing automation platform, enabling analysis of differences in marketing effectiveness under different distribution conditions. The distribution rules are predefined logical conditions by the marketing automation platform used to trigger the distribution of marketing activities. For example, the distribution rules may include, but are not limited to: conditions based on consumption amount, such as "issue coupon A when a customer's cumulative consumption exceeds 200 yuan within a limited time"; conditions based on order frequency, such as "issue coupon A when a customer places 3 orders within a limited time"; conditions based on specific product consumption, such as "issue coupon A when a customer purchases a specified product 3 times within a limited time"; and conditions based on time period, such as "issue coupon B on weekdays and coupon C on holidays." By analyzing the activity effects under different distribution rules, companies can optimize their distribution strategies and achieve efficient and precise allocation of marketing resources.

[0044] Based on marketing-related data synchronized from data module 1, the system periodically calculates the values ​​of various data indicators through automated tasks. Preferably, the execution cycle of the automated tasks is 1 hour to ensure the timeliness of the data. The calculation results are stored in data reports and can be displayed and analyzed through data visualization tools.

[0045] Customer count analysis primarily provides automated calculations and data reports on the number of customers participating in marketing activities. Pre-defined data metrics include redeemed customers, repeat customers, medium-frequency customers, and high-frequency customers. Redeemed customers refer to the number of customers who used the corresponding activity; repeat customers refer to the number of customers who used the corresponding activity two or more times; medium-frequency customers refer to the number of customers who used the corresponding activity a certain frequency; and high-frequency customers refer to the number of customers who used the corresponding activity at an even higher frequency. Specific thresholds for medium-frequency and high-frequency activities can be configured by the enterprise according to its business characteristics. Preferably, the medium-frequency threshold is set to 5 times, and the high-frequency threshold is set to 10 times.

[0046] The analysis dimensions also include time, activity, customer group, and distribution dimensions. By comparing and analyzing customer quantity metrics for different customer groups, businesses can identify which customer groups respond more actively to marketing campaigns, thus focusing their subsequent marketing efforts on these groups and improving marketing efficiency.

[0047] The campaign revenue analysis primarily provides automated calculations and data reports on revenue-related data generated by marketing campaigns. Pre-defined data metrics include campaign order count, campaign order amount, and campaign order gross profit. Campaign order count refers to the number of orders generated using the corresponding marketing campaign; campaign order amount refers to the total amount of these orders; and campaign order gross profit refers to the total gross profit of these orders. The gross profit is calculated by subtracting the order cost from the order amount.

[0048] In addition to time, activity, customer group, and distribution dimensions, the analysis now includes a store dimension, enabling analysis of marketing campaign revenue across different stores or regions. This is particularly important for businesses with multiple stores or operations in multiple regions, helping them identify high-value stores and areas and optimize marketing resource allocation.

[0049] Customer feedback analytics primarily provides automated calculations and data reports on customer feedback regarding marketing campaigns. Pre-configured data metrics include the number of positive reviews, the number of positive reviews from customers, the number of negative reviews from customers, the number of negative reviews from customers, the number of complaints from customers, the number of complaints from customers, the number of unsubscribes, and the number of customers who are not interested. These metrics reflect customer satisfaction and acceptance of the marketing campaigns.

[0050] Positive feedback data can be obtained from customer review systems or order evaluation data, negative feedback and complaint data can be obtained from customer service systems, and unsubscribe and disinterest data can be obtained from marketing automation systems. By analyzing customer feedback data, businesses can promptly identify problems in their marketing campaigns and make corresponding improvements.

[0051] All data reports can be customized to meet the company's business needs and data requirements, including adding new data metrics, modifying calculation methods, and adjusting analysis dimensions. The system provides a flexible configuration interface, allowing business personnel to perform self-configuration.

[0052] Reference Figure 4 The marketing discount module 3 connects to the data module 1 and is responsible for accurately calculating and analyzing marketing campaign discounts. The core innovation of this module lies in its ability to handle scenarios with multiple overlapping activities and accurately allocate discount amounts to each product within an order, thus solving the problem of inaccurate discount calculations in existing technologies.

[0053] Marketing discount module 3 includes three parts: discount configuration, automatic calculation of discount data, and discount data reports.

[0054] Discount configuration is primarily used to configure the discount order and details for marketing campaigns. When an order is combined with multiple marketing campaigns, different discount orders and details will result in different discount amounts. Therefore, discount configuration needs to be consistent with the marketing campaign design. Discount configuration can be configured manually or automatically synchronized from the marketing campaign management system. Automatic synchronization is preferred to ensure the accuracy and consistency of discount configuration.

[0055] Discount details include parameters such as discount type, discount rate, and minimum spend threshold. Discount types are divided into two main categories: product-specific discounts and overall order discounts. Product-specific discounts are further divided into single-item discounts and bundled discounts. Overall order discounts are further divided into single-time discounts and multiple-time discounts.

[0056] Automatic discount calculation is the core function of Marketing Discount Module 3. This function calculates the discount amount and discount rate for each marketing campaign through automated tasks, based on discount configurations and marketing-related data synchronized from Data Module 1.

[0057] For single-item discounts within product-targeted discounts, the calculation method is relatively simple. The system first identifies the products in the order that use single-item discounts, and then calculates the discount amount based on the discount rate. The calculation of the single-item targeted discount amount is based on the original price of the single item and the single-item discount rate. For example, if the original price of a certain product A is 100 yuan, and the single-item discount rate is 0.8 (i.e., 80% off), then the single-item targeted discount amount is 100 - 100 × 0.8 = 20 yuan.

[0058] For package discounts within product-targeted discounts, the calculation process involves two steps. The first step is to calculate the total package discount, based on the original package price and the package discount rate. The second step is to allocate the package discount amount to each item within the package. There are two allocation methods: menu price allocation and cost price allocation.

[0059] The menu price allocation method allocates the price of goods according to a percentage of their menu prices. Assume a set meal includes goods A and B, with menu prices P and P respectively. A and P B The total discount for the package is D. 套餐 Then the discount amount D allocated to product A. A The calculation formula is:

[0060]

[0061] Where, D A The discount amount allocated to product A, D 套餐 P represents the total discount amount for the package. A Let P be the menu price of product A. B This is the menu price for product B.

[0062] The cost-price allocation method allocates costs based on a proportion of the cost price of the goods. Let's assume the cost prices of goods A and B are C... A and C B Then the discount amount D allocated to product A. A The calculation formula is:

[0063]

[0064] Where, D A The discount amount allocated to product A, D 套餐 C is the total discount amount for the package. A Let C be the cost price of commodity A. B This is the cost price of product B.

[0065] Enterprises can choose an appropriate allocation method based on their own financial accounting needs. Preferably, for product mixes with significant differences in gross profit margin, the cost price allocation method is more reasonable.

[0066] For the overall order discount, the calculation process also involves two steps. The first step is to calculate the overall order discount amount, based on the original order price, the product-specific discounts already deducted, and the promotional discount rate. The second step is to allocate the overall order discount amount to each item within the order. Allocation methods include both menu price allocation and cost price allocation.

[0067] Assume the original price of the order is P. 订单 The total amount of targeted discounts for products is D. 定向 If the discount rate is r, then the total discount amount D is... 整单 The calculation formula is:

[0068] D 整单 =(P 订单 -D 定向 )×r,

[0069] Where, D 整单 P represents the total discount amount for the entire order. 订单 The original price of the order, D 定向 The total amount of the targeted discount for the product is represented by r, where r is the discount rate for the promotion.

[0070] Then, the total discount amount D 整单 The cost price is allocated to each item according to the ratio of the menu price or the cost price. Assume the order contains n items, and the menu price of item i is P. i Then the total discount amount D allocated to product i is... i The calculation formula is:

[0071]

[0072] Where, D i The total discount amount allocated to product i, D整单 P represents the total discount amount for the entire order. i Let n be the menu price of product i, and n be the total number of products in the order. This indicates that the menu prices of all items are summed.

[0073] For multi-item discounts within a single order, where multiple discounts are applied simultaneously, the calculation process becomes more complex. The system needs to calculate the discount amount for each activity sequentially according to a pre-defined discount order.

[0074] Let's take an order that uses both a discount coupon and a spending-reduction coupon as an example. Assume the discount coupon is part of the first promotion and the spending-reduction coupon is part of the second promotion.

[0075] The first step is to calculate the total discount amount for the first promotion (discount coupon). Assume the original order price is P. 订单 The total amount of targeted discounts for products is D. 定向 If the discount rate of the discount coupon is r1, then the formula for calculating the discount amount D1 of the sequential activity is:

[0076] D1=(P 订单 -D 定向 )×r1,

[0077] Where D1 is the discount amount for the first activity, P 订单 The original price of the order, D 定向 r1 represents the total amount of targeted discounts for the product, and r1 represents the discount rate of the discount coupon.

[0078] The second step is to calculate the total discount amount for the second activity (the discount coupon). The discount coupon typically offers a discount of Y yuan for purchases over X yuan. Assuming the discount coupon has a maximum value of M and a minimum value of N, the order amount after deducting the first activity discount is P. 订单 -D 定向 If -D1 is used, then the number of discount coupons k that can be used is:

[0079]

[0080] Where k is the number of discount coupons that can be used. P represents the floor operation. 订单 The original price of the order, D 定向 D1 represents the total amount of the product-specific discount, where D1 is the discount amount for the first activity and M is the maximum value of the discount coupon.

[0081] Then, based on the actual number of discount coupons used by the customer, k′ (the actual number of coupons used may be less than or equal to k), calculate the second-order activity discount amount D2:

[0082] D2 = k′ × N,

[0083] Where D2 is the discount amount for the second activity, k′ is the actual number of discount coupons used, and N is the deduction value of the discount coupons.

[0084] Step 3: Calculate the total discount amount D for the entire order. 总 :

[0085] D 总 =D1+D2,

[0086] Where, D 总 This represents the total discount amount for the entire order. D1 represents the discount amount for the first activity, and D2 represents the discount amount for the second activity.

[0087] The fourth step is to distribute the total discount amount to each item in the order, using the same method as above, either the menu price distribution method or the cost price distribution method.

[0088] It should be noted that in practical applications, businesses generally do not use multiple coupons of the same type for a single order. If a business does have such a need, the system can achieve this by adding an activity sequence and corresponding calculation steps.

[0089] Finally, the system calculates the final payable amount for the order, which is then compared with the actual payment amount to determine the actual loss incurred. Final payable amount P 应付 The calculation formula is:

[0090] P 应付 =P 订单 -D 定向 -D 总 ,

[0091] Where, P 应付 For the final amount payable, P 订单 The original price of the order, D 定向 D represents the total amount of targeted discounts for the product. 总 This represents the total discount amount for the entire order.

[0092] The discount data report is the output of Marketing Discount Module 3. The system provides pre-configured data reports that offer data related to marketing campaign discounts. Pre-configured data metrics include order count, menu amount, order amount, order discount amount, order discount rate, campaign discount amount, and campaign discount rate.

[0093] Order Count refers to the number of orders using the corresponding marketing campaign. Menu Amount refers to the total order amount calculated based on the product menu price, excluding any discounts. Order Amount refers to the actual amount of the order, i.e., the amount actually paid by the customer. Order Discount Amount refers to the total discount amount of all marketing campaigns within the order. Order Discount Rate is the ratio of the order discount amount to the menu amount, reflecting the overall discount margin of the order. Campaign Discount Amount refers to the specific discount amount of the corresponding marketing campaign within the order. Campaign Discount Rate is the ratio of the campaign discount amount to the menu amount, reflecting the discount contribution of the campaign.

[0094] In addition to the usual time and activity dimensions, the pre-configured analysis dimensions also integrate with customer data systems and marketing automation systems to provide analysis on customer groups and distribution dimensions. This enables businesses to analyze discount usage across different customer groups and under different distribution conditions, providing data support for subsequent discount strategy optimization.

[0095] All data reports can be adjusted according to the company's business needs and data situation, including adding new data indicators, modifying calculation methods, and adjusting analysis dimensions.

[0096] Reference Figure 5 Marketing Objectives Module 4 connects with Data Module 1 and Marketing Effectiveness Module 2, primarily used to build a data model for businesses to determine whether marketing campaigns have achieved their designed goals. Businesses often have clear business objectives when conducting marketing campaigns, such as recruiting new customers, activating existing customers, and increasing revenue. Through Marketing Objectives Module 4, businesses can quickly and accurately grasp the achievement of their marketing campaign goals.

[0097] Marketing Objectives Module 4 includes four parts: objective type configuration, objective value configuration, automatic calculation of objective data, and objective completion data reports.

[0098] Target type configuration allows you to specify the type of marketing objective for your campaign. The system comes pre-configured with five target types: new customer acquisition, customer engagement, revenue growth, product improvement, and churn recovery. These five types cover the most common marketing objective scenarios for businesses.

[0099] The "New Customer Acquisition" type is suitable for marketing campaigns primarily aimed at acquiring new customers. The "Active Customer" type is suitable for marketing campaigns primarily aimed at increasing customer activity. The "Revenue Boost" type is suitable for marketing campaigns primarily aimed at increasing revenue. The "Product Enhancement" type is suitable for marketing campaigns primarily aimed at promoting the sales of specific products. The "Chunk Recall" type is suitable for marketing campaigns primarily aimed at recalling churned customers.

[0100] The relevant target types can be adjusted according to the company's business needs and data situation. The system supports adding new target types or modifying the definition of existing target types.

[0101] Target value configuration allows you to further configure the numerical values ​​of marketing target metrics for marketing campaigns that have already had their target types configured. Target metrics are divided into general metrics and specific metrics.

[0102] Common metrics are those that need to be configured for all target types, including the number of items issued, claimed, and redeemed. These metrics reflect the basic performance of the marketing campaign.

[0103] Specific metrics are dedicated indicators for specific target types. For example, metrics for new customer acquisition include the number of registered members and repeat customers, reflecting new customer acquisition and retention. Metrics for active customers include the number of repeat customers, mid-frequency customers, and high-frequency customers, reflecting customer activity levels. Metrics for revenue growth include the number of orders, order amount, and gross profit per order, reflecting the contribution of marketing activities to revenue and profit. Metrics for product growth include product sales volume, product sales amount, and product gross profit per sale, reflecting the sales performance of specific products. Metrics for churn recovery include the number of customers who have acquired accounts, the number of customers who are using the service, and the number of activated customers, reflecting the effectiveness of churn recovery efforts.

[0104] Target values ​​can be configured manually by business personnel or in batches via data import. When configuring, the achievement period for the relevant target metric values ​​must be configured simultaneously, i.e., the expected timeframe for achieving the target. The achievement period is typically measured in days, such as 30 days, 60 days, or 90 days.

[0105] By integrating customer data from the customer data system, the system also supports configuring separate marketing target metrics for different customer groups. For example, for the same marketing campaign, a target of 1,000 new registered members can be set for the new customer group, while a target of 500 repeat customers can be set for the existing customer group. This segmented target configuration can more accurately reflect the company's marketing expectations for different customer groups.

[0106] The data metrics for relevant marketing objectives can be adjusted according to the company's business needs and data conditions, including adding new metrics, modifying metric definitions, and adjusting calculation methods.

[0107] The automatic calculation of target data is based on the configuration of target type and target value, combined with the enterprise marketing data synchronized by data module 1, and automatically calculates the target completion status of marketing activities through automated tasks.

[0108] The system periodically executes automated tasks to extract relevant data from data module 1, calculate the actual completion value of each target indicator, and compare it with the configured target value to calculate the completion rate. The completion rate is the ratio of the actual completion value to the target value, reflecting the degree to which the target has been achieved. Preferably, the execution cycle of the automated task is 4 hours to ensure the timeliness of the data.

[0109] If the completion rate of a target indicator reaches or exceeds 100%, it means that the target has been achieved. If the completion rate is below 80%, the system will automatically issue an alert to remind business personnel to pay attention. The alert threshold can be adjusted according to the company's management requirements.

[0110] The target completion data report is the output of Marketing Target Module 4. The system has pre-built data reports that present the completion status of marketing targets, divided into 5 target report types, corresponding to recruiting new customers, activating existing customers, increasing revenue, improving products, and recovering lost customers.

[0111] Each type of target report is further divided into a summary report and a customer group detail report. The summary report provides overall data such as target values, achieved values, and completion rates for the corresponding data indicators of the marketing campaign. The customer group detail report provides detailed data such as target values, achieved values, and completion rates for the marketing campaign in different customer groups.

[0112] For example, the New Customer Recruitment Target Completion Summary Table will display the target and actual values ​​for the number of items distributed, claimed, redeemed, registered, and repeat customers for a marketing campaign, as well as the completion rate for each indicator. The New Customer Recruitment Target Completion Customer Group Details Table will display the target, actual, and completion rates for these indicators separately for different customer groups.

[0113] These reports allow businesses to quickly understand the achievement of their marketing campaign goals, identify which campaigns achieved their objectives, which failed to achieve their goals, and the extent of the gap, thus providing data support for subsequent adjustments to marketing strategies.

[0114] All data reports can be adjusted according to the company's business needs and data situation.

[0115] Reference Figure 6 Marketing Plan Module 5 connects with Data Module 1 and is primarily used to build a data model for enterprises to assess and analyze the execution of marketing campaign plans. Through Marketing Plan Module 5, enterprises can quickly and accurately assess the execution of marketing campaign plans, promptly identify deviations, and adjust strategies to ensure that marketing campaigns proceed smoothly as planned.

[0116] Marketing Plan Module 5 includes four parts: basic configuration of the plan model, configuration of the number of marketing campaign plans, automatic calculation of plan execution status, and plan execution data reports.

[0117] The basic configuration of the marketing plan model is mainly responsible for the basic configuration of the marketing plan model. The system has seven pre-set plan types: redemption quantity plan, redemption quantity plan, number of members redeemed plan, number of members used plan, order quantity plan, order amount plan, and order gross profit plan. These seven plan types cover the key aspects of marketing campaign execution.

[0118] To plan the number of claims, you need to import and configure the claiming channels for the marketing campaign. Claiming channels include SMS, app push notifications, official accounts, mini-programs, email, and more. The system supports configuring the planned claiming quantity for each claiming channel separately.

[0119] The redemption quantity plan requires importing and configuring the redemption channels for the marketing campaign. Redemption channels include various methods such as online stores, offline stores, and third-party platforms. The system supports configuring planned redemption quantities for each redemption channel separately.

[0120] Order quantity planning requires configuring order amount range categories and order gross profit range categories. For example, order amounts can be divided into ranges such as 0-50 yuan, 50-100 yuan, 100-200 yuan, and over 200 yuan, while order gross profit can be divided into ranges such as negative gross profit, 0-10 yuan, 10-20 yuan, and over 20 yuan. This range classification helps businesses analyze order distribution in more detail.

[0121] The relevant plan types can be adjusted according to the company's business needs and data conditions. The system supports adding new plan types or modifying the definitions of existing plan types.

[0122] The marketing campaign plan configuration is to assign specific plan values ​​to a marketing campaign.

[0123] The "Claim Quantity Plan Type" must be configured with the overall plan claim quantity for the marketing campaign, and optionally, the plan claim quantity for specific claim channels. For example, if the overall plan claim quantity for a marketing campaign is 10,000, then 3,000 are planned for SMS channels, 5,000 for APP push channels, and 2,000 for WeChat official account channels.

[0124] The redemption quantity plan type must be configured with the overall planned redemption quantity for the marketing campaign, and optionally, the planned redemption quantity for specific redemption channels. For example, the overall planned redemption quantity for a marketing campaign is 5000 times, of which 3000 times are planned for online stores and 2000 times are planned for offline stores.

[0125] The membership claim plan type must be configured with the overall planned membership claim count for the marketing campaign, and optionally, the planned membership claim count for specific customer groups. For example, a marketing campaign might have an overall planned membership claim count of 8,000, with 3,000 planned for new customers and 5,000 for existing customers.

[0126] When using the membership plan type, you must configure the overall number of members to be used for the marketing campaign. Optionally, you can configure the number of members to be used for specific customer groups. For example, a marketing campaign might have an overall plan to use 4,000 members, with 1,500 members planned for high-value customers and 2,500 members planned for general customers.

[0127] The order quantity plan type must be configured with the overall planned order quantity for the marketing campaign. Optional configurations include planned order quantities for specific regions and stores, specific customer groups, specific order amount ranges, and specific order gross profit ranges. For example, a marketing campaign might have an overall planned order quantity of 3000 orders, with 1500 planned for East China, 1000 for South China, and 500 for North China; 1200 orders planned for the 100-200 RMB price range, and 800 orders planned for the over 200 RMB price range.

[0128] The order amount plan type must be configured with the overall planned order amount for the marketing campaign. Optional configurations include planned order amounts for specific regions and stores, and planned order amounts for specific customer groups. For example, a marketing campaign might have an overall planned order amount of 500,000 yuan, with 250,000 yuan planned for East China, 150,000 yuan for South China, and 100,000 yuan for North China.

[0129] The order gross profit plan type must be configured with the overall planned order gross profit for the marketing campaign. Optional configurations include planned order gross profit for specific regions and stores, and planned order gross profit for specific customer groups. For example, the overall planned order gross profit for a marketing campaign is 150,000 yuan, of which 80,000 yuan is planned for high-value customer groups and 70,000 yuan for ordinary customer groups.

[0130] Planned values ​​can be configured manually by business personnel or in batches via data import. When configuring, various factors such as historical data, market environment, and competitive landscape need to be considered to ensure the rationality of the planned values.

[0131] The automatic calculation of plan execution status is based on the completion of basic model configuration and plan value configuration, combined with the enterprise marketing data synchronized by data module 1, and automatically calculates the plan execution status of marketing activities through automated tasks.

[0132] The system periodically executes automated tasks to extract relevant data from data module 1, calculate the actual completion count of each planned indicator, and compare it with the configured planned count to calculate the plan achievement rate, the number of discrepancies, and the discrepancy rate. The plan achievement rate is the ratio of actual completion to the planned count, reflecting the degree of plan completion. The number of discrepancies is the difference between the actual completion count and the planned count, and the discrepancy rate is the ratio of the number of discrepancies to the planned count, reflecting the degree of deviation from plan execution. Preferably, the execution cycle of the automated task is 2 hours.

[0133] If the achievement rate of a certain planned target falls below 70%, the system will automatically issue an alert, reminding business personnel to pay attention and analyze the reasons. The alert threshold can be adjusted according to the company's management requirements. Preferably, for key planned targets such as order amount and order gross profit, the alert threshold is set to 80%.

[0134] The plan execution data report is the output of Marketing Plan Module 5. The system has pre-built data reports that present the execution status of the marketing plan, divided into 7 types of plan reports, each of which is further divided into summary reports and detailed reports.

[0135] The Overall Claims Report for different claiming channels provides comprehensive data on the marketing campaign, including planned claims, actual claims, campaign achievement rate, discrepancies, and discrepancy rates. The Detailed Claims Report for different claiming channels provides detailed data on the marketing campaign across different claiming channels, including planned claims, actual claims, campaign achievement rate, discrepancies, and discrepancy rates.

[0136] The Overall Redemption Channel Plan Execution Report provides comprehensive data for the marketing campaign, including planned redemption counts, actual redemption counts, plan achievement rate, discrepancies, and discrepancy rates. The Detailed Redemption Channel Plan Execution Report provides detailed data for the marketing campaign across different redemption channels, including planned redemption counts, actual redemption counts, plan achievement rate, discrepancies, and discrepancy rates.

[0137] The "Membership Claim Count Execution Summary" report provides overall data on the marketing campaign, including the planned number of members claimed, the actual number of members claimed, the plan achievement rate, the number of discrepancies, and the discrepancy rate. The "Membership Claim Count Execution Customer Group Details" report provides detailed data on the marketing campaign across different customer groups, including the planned number of members claimed, the actual number of members claimed, the plan achievement rate, the number of discrepancies, and the discrepancy rate.

[0138] The Membership Count Plan Execution Master Report provides overall data for marketing campaigns, including the planned number of members using the campaign, the actual number of members using the campaign, the campaign achievement rate, the number of discrepancies, and the discrepancy rate. The Membership Count Plan Execution Customer Group Details Report provides detailed data for marketing campaigns across different customer groups, including the planned number of members using the campaign, the actual number of members using the campaign, the campaign achievement rate, the number of discrepancies, and the discrepancy rate.

[0139] The Order Count Execution Summary Report provides overall data on the marketing campaign, including planned order count, actual order count, plan achievement rate, discrepancies, and discrepancy rate. The Order Count Execution Report also includes detailed reports on stores, customer groups, spending ranges, and gross profit ranges, each providing detailed data across different dimensions.

[0140] The Order Amount Execution Summary Report provides overall data on the marketing campaign, including planned order amount, actual order amount, plan achievement rate, number of discrepancies, and discrepancy rate. The Order Amount Execution Report also includes store detail reports and customer group detail reports, providing detailed data from different perspectives.

[0141] The Order Gross Profit Plan Execution Summary Report provides overall data on planned order gross profit, actual order gross profit, plan achievement rate, discrepancies, and discrepancy rate for the marketing campaign. The report also includes store detail reports and customer group detail reports, providing detailed data from different perspectives.

[0142] These reports allow businesses to quickly understand the execution status of their marketing campaigns, identify which planned targets were met, which were not met, and the extent of the gaps, thereby enabling them to adjust their marketing strategies in a timely manner and ensure that marketing campaigns proceed smoothly as planned.

[0143] All data reports can be adjusted according to the company's business needs and data situation.

[0144] Reference Figure 7 Marketing Standards Module 6 and Marketing Evaluation Module 7 are connected to Data Module 1, Marketing Effectiveness Module 2 and Marketing Discount Module 3 respectively, together providing enterprises with a standardized evaluation system for marketing activities.

[0145] Marketing Standards Module 6 is primarily used to build a data model for enterprises to establish unified judgment standards for marketing activities. An enterprise often executes multiple marketing activities simultaneously. While modules 2 (Marketing Effectiveness), 3 (Marketing Discounts), 4 (Marketing Objectives), and 5 (Marketing Plans) allow enterprises to analyze and judge marketing activities from multiple dimensions, they lack the function of horizontally comparing multiple marketing activities. Marketing Standards Module 6 provides unified judgment standards, enabling the rapid selection of marketing activities that meet specific criteria.

[0146] Marketing Standards Module 6 consists of three parts: standard model basic configuration, standard level automatic calculation, and standard level data report.

[0147] The standard model basic configuration is mainly used to configure the standard level, standard name, activity indicators, and standard content.

[0148] The standard grading system forms the basis for classifying marketing activities. The system has nine pre-set grading levels, from Standard One to Standard Nine, with higher numbers indicating higher standards. Businesses can adjust the number of grading levels according to their own needs.

[0149] The standard names are defined by the company and are used to describe the meaning of each level. For example, standards one through nine can be named Fail, Pass, Average, Good, Excellent, Outstanding, Outstanding, Top, and Benchmark, respectively. The standard names should be consistent with the company's management culture.

[0150] Activity metrics are specific indicators used to determine the standard level of a marketing campaign. The system has seven pre-set activity metrics: campaign claiming, campaign redemption, campaign participating members, number of campaign orders, campaign order amount, campaign order gross profit, and number of positive reviews. Businesses can choose to use some or all of these metrics based on their priorities, or they can add new metrics.

[0151] The standard content mainly configures different levels of judgment criteria for activity indicators. When configuring, first select the activity indicator and the standard level, then select the time reference point (after the start or end of the activity), and then configure the specific number of days and numerical thresholds.

[0152] For example, the first criterion for claiming rewards during the activity can be configured as: 1000 claims within 3 days of the activity starting. The second criterion can be configured as: 3000 claims within 3 days of the activity starting. The third criterion can be configured as: 5000 claims within 3 days of the activity starting. And so on, configuring corresponding judgment criteria for each standard level.

[0153] For example, the first criterion for the activity's order amount target can be configured as: order amount reaches 50,000 yuan within 7 days after the activity ends. The second criterion can be configured as: order amount reaches 100,000 yuan within 7 days after the activity ends. The third criterion can be configured as: order amount reaches 200,000 yuan within 7 days after the activity ends.

[0154] With this flexible configuration method, companies can set judgment criteria that suit their own actual situation based on different types of marketing activities, different business stages, and different market environments.

[0155] The standard level, activity indicators, and standard content can all be adjusted according to the company's business needs and data situation.

[0156] The standard level automatic calculation is performed after the basic configuration is completed. It combines the enterprise marketing data synchronized by data module 1 and automatically calculates the standard level of each marketing activity through automated tasks.

[0157] The system periodically executes automated tasks to extract relevant data from data module 1, calculate the activity metrics values ​​for each marketing campaign, and compare them with the configured standard content to determine the highest standard level achieved by the marketing campaign in each activity metric. Preferably, the execution cycle of the automated tasks is 6 hours.

[0158] To reduce wasted computing resources, the system will not calculate the standard rating for marketing campaigns that have ended more than one year ago. These restrictions can be adjusted based on the company's business needs and computing resources. Preferably, for key marketing campaigns, the calculation period can be extended to two years.

[0159] The standard-level data report is the output of Marketing Standards Module 6. The system's pre-built data reports present the standard levels of marketing campaign execution.

[0160] The Marketing Standards Master Table provides the standard ratings for all marketing campaign metrics. The table is organized by marketing campaigns (rows) and metrics (columns), with each cell displaying the standard rating achieved by the campaign for that metric. This table allows businesses to quickly identify marketing campaigns that perform well across various metrics.

[0161] The Marketing Standards Details table provides detailed information on various activity metrics for a single marketing campaign, including the standard level, standard content, and actual values ​​for the activity metrics. For example, for a marketing campaign, the table would show that the campaign's claim count reached Standard 3, the standard content being 5000 claims within 3 days of the campaign's start, and the actual claim count being 5200.

[0162] These reports allow businesses to quickly identify marketing campaigns that meet specific criteria, such as those that achieve a minimum order value of five, providing a reference for subsequent marketing strategy development.

[0163] All data reports can be adjusted according to the company's business needs and data situation.

[0164] Marketing Evaluation Module 7 is primarily used to build a data model for enterprises to comprehensively evaluate marketing activities. By weighting scores across multiple dimensions such as the number of marketing activities, participating customers, revenue, discounts, and feedback, Marketing Evaluation Module 7 helps enterprises quickly determine the overall ranking and score of their marketing activities.

[0165] The marketing evaluation module 7 includes three parts: evaluation rule configuration, automatic calculation of evaluation scores, and comprehensive evaluation data reports.

[0166] The evaluation rule configuration is a core configuration step in Marketing Evaluation Module 7. The system divides the comprehensive evaluation of marketing activities into five sub-scenarios: activity quantity scenario, activity customer scenario, activity revenue scenario, activity discount scenario, and activity feedback scenario. Each scenario calculates its own evaluation score, and then the comprehensive evaluation score is calculated based on a weighted average of the scenario evaluation scores.

[0167] In the activity quantity scenario, the system pre-sets four scoring indicators: number of distributions, number of clicks, number of claims, and number of redemptions. Enterprises need to configure scoring rules for each indicator. Scoring rules typically employ linear or segmented scoring methods. For example, the scoring rule for the number of clicks can be set to 1 point for every 10,000 clicks, the scoring rule for the number of claims can be set to 1 point for every 1,000 claims, and the scoring rule for the number of redemptions can be set to 1 point for every 100 redemptions.

[0168] In the context of customer engagement activities, the system pre-sets four scoring metrics: number of paying customers, number of repeat customers, number of mid-frequency customers, and number of high-frequency customers. Businesses need to configure scoring rules for each metric separately. For example, the scoring rule for paying customers can be set to 1 point per 100 customers, the scoring rule for repeat customers can be set to 2 points per 50 customers, the scoring rule for mid-frequency customers can be set to 3 points per 20 customers, and the scoring rule for high-frequency customers can be set to 5 points per 10 customers. This differentiated scoring rule reflects the varying value of different customers.

[0169] In the campaign revenue scenario, the system pre-sets three scoring indicators: number of orders, order amount, and order gross profit. Businesses need to configure scoring rules for each indicator separately. For example, the scoring rule for the number of orders can be set to 1 point for every 100 orders, the scoring rule for order amount can be set to 1 point for every 10,000 yuan, and the scoring rule for order gross profit can be set to 2 points for every 5,000 yuan. Order gross profit typically has a higher scoring weight than order amount because gross profit more directly reflects the profitability of the marketing campaign.

[0170] In the context of promotional discounts, the system pre-sets two scoring metrics: discount amount and discount rate. It's crucial to note that the scoring rules for both discount amount and discount rate should support negative scores, as larger discounts imply higher costs and should negatively impact the overall evaluation. For example, the scoring rule for discount amount could be set to deduct 1 point for every 10,000 yuan, and the scoring rule for discount rate could be set to deduct 2 points for every 5% increase in the discount rate.

[0171] In the campaign feedback scenario, the system pre-sets four scoring metrics: number of positive reviews, number of negative reviews, number of complaints, and number of unsubscribes. It's important to note that the scoring rules for negative reviews, complaints, and unsubscribes should support negative scores, as this negative feedback will lower the overall evaluation of the marketing campaign. For example, the scoring rule for positive reviews could be set to 1 point for every 100 positive reviews, 2 points deducted for every 10 negative reviews, 5 points deducted for every complaint, and 1 point deducted for every 100 unsubscribes.

[0172] After configuring the scoring rules for the five sub-scenarios, enterprises also need to configure the weighting rules for calculating the overall score. The system assigns a weight value to each scenario score, and the overall score is calculated by weighted summation.

[0173] Assuming the weights of the five scenarios are w1, w2, w3, w4, and w5, and the evaluation scores for each scenario are S1, S2, S3, S4, and S5, then the overall evaluation score S 综合 The calculation formula is:

[0174] S 综合 = w1×S1+w2×S2+w3×S3+w4×S4+w5×S5,

[0175] Where, S 综合 The comprehensive evaluation score is calculated as follows: w1 is the weight of the activity quantity scenario, w2 is the weight of the activity customer scenario, w3 is the weight of the activity revenue scenario, w4 is the weight of the activity discount scenario, w5 is the weight of the activity feedback scenario, S1 is the evaluation score for the activity quantity scenario, S2 is the evaluation score for the activity customer scenario, S3 is the evaluation score for the activity revenue scenario, S4 is the evaluation score for the activity discount scenario, and S5 is the evaluation score for the activity feedback scenario.

[0176] For example, a company can set the weights for different scenarios: activity quantity (w1 = 0.1), activity customer (w2 = 0.3), activity revenue (w3 = 0.4), activity discount (w4 = -0.1), and activity feedback (w5 = 0.2). Setting the activity discount scenario weight to a negative value indicates that the higher the discount cost, the lower the overall evaluation.

[0177] The weighting values ​​should be adjusted according to the company's strategic priorities and management philosophy. For example, if the company is currently more focused on revenue, it can increase the weighting of revenue-generating scenarios; if the company is more focused on customer satisfaction, it can increase the weighting of feedback scenarios.

[0178] Both the segmented scenarios and the data metrics within those scenarios can be adjusted according to the company's business needs and data situation. This includes adding new scenarios, adding new metrics, modifying scoring rules, and adjusting weight configurations.

[0179] The automatic rating score calculation is based on the completed rating rule configuration. It combines marketing activity data synchronized from data module 1, activity quantity data, customer quantity data, activity revenue data, and customer feedback data from marketing discount module 2, and discount data from marketing discount module 3. Through automated tasks, it automatically calculates the overall rating score and segmented scenario rating score of the marketing activity.

[0180] The system periodically executes automated tasks to extract data from relevant modules, calculate evaluation scores for each scenario according to configured scoring rules, and then calculate a comprehensive evaluation score based on configured weight values. Preferably, the execution cycle of the automated tasks is 12 hours.

[0181] The calculated overall evaluation score and subdivided scenario evaluation scores will be stored in the database for use in data reports.

[0182] The comprehensive evaluation data report is the output of Marketing Evaluation Module 7. The system's pre-built data reports present a comprehensive evaluation of marketing activities.

[0183] The comprehensive marketing evaluation report presents a combined score for multiple marketing campaigns and supports sorting. The report is organized by marketing campaigns, with the overall evaluation score as the main column, and also displays the evaluation scores for each sub-segment. Businesses can sort the reports in descending order of their overall evaluation scores to quickly identify the best-performing marketing campaigns. Preferably, the report supports filtering functionality, allowing users to filter marketing campaigns based on criteria such as campaign type, campaign time, and campaign status.

[0184] The Marketing Campaign Evaluation Details table provides detailed evaluation information for individual marketing campaigns, including evaluation scores for each sub-scenarios and the data values ​​and calculated scores for each detailed indicator within each sub-scenarios. For example, for a marketing campaign, the details table would show that the campaign quantity scenario evaluation score is 20 points, with 10 points for 100,000 distributions, 5 points for 50,000 clicks, 10 points for 10,000 redemptions, and 50 points for 5,000 redemptions, for a total scenario score of 75 points (20 points after calculation within the scenario).

[0185] These reports allow businesses to gain a comprehensive understanding of the overall performance of their marketing campaigns, identify high-value campaigns, analyze the strengths and weaknesses of each campaign, and provide data support for optimizing subsequent marketing strategies.

[0186] All data reports can be adjusted according to the company's business needs and data situation.

[0187] The marketing campaign data analysis system of this invention forms a complete marketing campaign analysis and evaluation system through the collaborative work of 7 modules.

[0188] Data Module 1 serves as the system's foundational layer, providing a unified data source for other modules. Marketing Effectiveness Module 2 and Marketing Discount Module 3, based on data from Data Module 1, analyze marketing campaigns from the perspectives of effectiveness and cost, respectively. Marketing Objectives Module 4 and Marketing Plan Module 5, building upon Marketing Effectiveness Module 2, further determine whether the marketing campaigns have achieved their expected goals and plans. Marketing Standards Module 6, based on data from Data Module 1, provides unified evaluation criteria for marketing campaigns. Marketing Evaluation Module 7 integrates data from Marketing Effectiveness Module 2 and Marketing Discount Module 3 to conduct a comprehensive evaluation of the marketing campaigns.

[0189] The modules are both independent and closely collaborative. Independence is reflected in the clear functional positioning and independent configuration management of each module, allowing enterprises to choose to use some or all modules as needed. Close collaboration is reflected in the data sharing and flow between modules through data interfaces, forming a closed-loop analysis and evaluation system.

[0190] The system supports flexible expansion and customization. Enterprises can adjust the configuration parameters of each module, add new data indicators, modify calculation rules, and customize data reports according to their own business characteristics and management needs, so that the system can better adapt to the actual situation of the enterprise.

[0191] The system can also interface with other systems such as customer data systems, marketing automation systems, and marketing campaign management systems to achieve data interconnection and further improve the intelligence and automation level of marketing campaign management.

[0192] In addition, the system can also serve as a training and inference data platform for artificial intelligence in intelligent marketing application scenarios, providing AI models with high-quality marketing campaign data and business standards, and supporting enterprises in building intelligent marketing decision-making systems.

[0193] Taking a retail company as an example, this company conducts 10-20 marketing activities every month, including new product promotions, member day activities, holiday marketing, and other types. Before using the marketing activity data analysis system of this invention, the company could only understand the basic situation of marketing activities through simple reports, and could not deeply analyze the differences in marketing effectiveness among different customer groups, nor could it accurately calculate the discount costs under multiple overlapping activity scenarios, resulting in a lack of data support for marketing decisions.

[0194] After using the system of this invention, the company achieved the following results:

[0195] Through customer segment analysis in Marketing Effectiveness Module 2, it was found that high-value customer groups responded to discount-related activities by 50% more than new customer groups, while new customer groups responded even more to new product trial-related activities. Based on this finding, the company adjusted its marketing strategies for different customer segments, focusing discount-related activities on high-value customers and new product trial-related activities on new customers, resulting in a 32% increase in overall marketing conversion rate.

[0196] Through precise calculations using Marketing Discount Module 3, the company accurately grasped the discount costs of each marketing campaign and the allocated discount amount for each product, discovering that some products had negative gross profit margins due to excessive discounts. Based on this, the company optimized its discount strategy, adjusting some high-discount campaigns to "spend-and-refund" promotions, resulting in an overall gross profit margin increase of 8%.

[0197] Through the target completion analysis in Marketing Target Module 4, the company promptly discovered that the target completion rate for the number of registered members in a certain membership recruitment campaign was only 60%. The company immediately adjusted its campaign promotion strategy, increased promotion channels and promotion efforts, and ultimately achieved a target completion rate of 95%.

[0198] By monitoring the execution of marketing plans in Module 5, the company discovered that the redemption rate for a certain marketing campaign at offline stores was only 40%. Analysis revealed that inadequate training of store staff led to inefficient redemption processes. The company immediately strengthened store training, resulting in a redemption rate of 85% for subsequent campaigns.

[0199] Through the comprehensive evaluation of Marketing Standards Module 6 and Marketing Evaluation Module 7, the company identified the five marketing campaigns with the highest overall scores, analyzed the common characteristics of these campaigns, formed best practices for marketing campaigns, and promoted and applied them in subsequent marketing campaigns, resulting in an average marketing effectiveness increase of 25%.

[0200] In summary, by constructing a complete marketing activity data analysis system, this invention can significantly improve the management level and marketing efficiency of enterprise marketing activities, and provide strong support for the digital and intelligent marketing transformation of enterprises.

[0201] The above-described embodiments are merely preferred embodiments of the present invention, and while the descriptions are specific and detailed, they should not be construed as limiting the scope of the present invention. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of the present invention, and these modifications and improvements all fall within the scope of protection of the present invention.

Claims

1. A data analysis system for marketing campaigns, characterized by , comprising: a data module for synchronizing, cleaning and storing marketing-related data generated in the process of a marketing campaign; a marketing effect module connected with the data module, configured to automatically calculate and generate campaign quantity data, customer quantity data, campaign revenue data and customer feedback data based on the marketing-related data and according to preset analysis dimensions, the analysis dimensions including time dimension, campaign dimension, customer group dimension and distribution dimension; a marketing discount module connected with the data module, configured to automatically calculate the discount amount and discount rate of the marketing campaign based on the marketing-related data and preset discount configuration rules, the discount configuration rules including discount sequence and discount content; a marketing target module connected with the data module and the marketing effect module, configured to automatically calculate the target completion of the marketing campaign and generate a target completion data report based on preset target type and target value configurations and in combination with the marketing-related data, the target type including new customer recruitment type, active customer type, revenue improvement type, product improvement type and loss recall type; a marketing plan module connected with the data module, configured to automatically calculate the plan execution of the marketing campaign and generate a plan execution data report based on preset plan type and plan value configurations and in combination with the marketing-related data, the plan type including quantity plan, quantity plan for cancellation, member quantity plan, member usage quantity plan, order quantity plan, order amount plan and order gross profit plan; a marketing standard module connected with the data module, configured to automatically determine the standard level of the marketing campaign based on preset standard level configuration and activity index configuration and in combination with the marketing-related data, the standard level configuration including judgment standards of multiple levels; a marketing evaluation module connected with the marketing effect module and the marketing discount module, configured to generate a comprehensive evaluation score and a subdivided scenario evaluation score based on preset evaluation rules, the evaluation rules including scoring rules and weight configurations of activity quantity scenario, activity customer scenario, activity revenue scenario, activity discount scenario and activity feedback scenario.

2. The system for data analysis of marketing campaigns according to claim 1, characterized in that The marketing effect module is in communication connection with a customer data platform and a marketing automation platform, configured to obtain customer group data and distribution condition data and generate subdivided marketing effect analysis data for different customer groups and different distribution conditions based on the customer group data and the distribution condition data.

3. The system for data analysis of marketing campaigns of claim 1, wherein The marketing discount module comprises: a discount configuration unit configured to configure the discount sequence and discount content of the marketing campaign; a discount calculation unit connected with the discount configuration unit and the data module, configured to automatically calculate product-oriented discount and whole-order comprehensive discount based on the discount sequence and the discount content and in combination with the marketing-related data, and proportionally allocate the whole-order comprehensive discount to each product in an order; a discount report unit connected with the discount calculation unit, configured to generate a discount data report including order quantity, menu amount, order amount, order discount amount, order discount rate, campaign discount amount and campaign discount rate.

4. The system for data analysis of marketing campaigns according to claim 2, characterized in that The product-oriented discount includes single product discount and package discount, and the whole order comprehensive discount includes whole order single discount and whole order multiple discount.

5. The system of claim 1, wherein The marketing target module comprises: a target type configuration unit configured to configure a target type for a marketing campaign; a target value configuration unit connected to the target type configuration unit and configured to configure a value of a target index for the marketing campaign with the configured target type, the target index comprising a general index and a special index; a target calculation unit connected to the target value configuration unit and the data module and configured to automatically calculate a target completion condition of the marketing campaign based on the configured target value and the marketing related data; a target report unit connected to the target calculation unit and configured to generate a target completion data report comprising a target value, a completion value and a completion rate.

6. The system for data analysis of marketing campaigns according to claim 5, characterized in that The general index comprises a number of issues, a number of pickups and a number of cancellations, and the special index is determined according to the target type, wherein: the special index corresponding to the new customer recruitment type comprises a number of registered members and a number of repeat purchase members; the special index corresponding to the active customer type comprises a number of repeat purchase customers, a number of medium frequency customers and a number of high frequency customers; the special index corresponding to the revenue improvement type comprises a number of orders, an order amount and an order gross profit; the special index corresponding to the product improvement type comprises a product sales quantity, a product sales amount and a product sales gross profit; the special index corresponding to the recall loss type comprises a number of pickup customers, a number of use customers and a number of active customers.

7. The system of claim 1, wherein The marketing plan module comprises: a plan basis configuration unit configured to configure a plan type and configure corresponding basis parameters according to the plan type; a plan value configuration unit connected to the plan basis configuration unit and configured to configure a whole plan value and an optional subdivided plan value for a marketing campaign; a plan calculation unit connected to the plan value configuration unit and the data module and configured to automatically calculate a plan execution condition of the marketing campaign based on the configured plan value and the marketing related data; a plan report unit connected to the plan calculation unit and configured to generate a plan execution data report comprising a plan number, an actual number, a plan achievement rate, a difference number and a difference rate.

8. The system of claim 1, wherein The marketing standard module comprises: a standard configuration unit configured to configure a standard level, a standard name, a campaign index and a standard content, the standard content comprising a time condition and a value condition for achieving the standard level; a standard calculation unit connected to the standard configuration unit and the data module and configured to automatically determine a standard level of a marketing campaign based on the configured standard content and the marketing related data; a standard report unit connected to the standard calculation unit and configured to generate a standard level data report of the marketing campaign.

9. The system of claim 1, wherein The marketing evaluation module comprises: an evaluation rule configuration unit configured to configure a scoring rule for the activity quantity scenario, the activity customer scenario, the activity revenue scenario, the activity discount scenario and the activity feedback scenario, and configure a weight value for each scenario; An evaluation computing unit, connected with the evaluation rule configuring unit, the marketing effect module and the marketing discount module, is configured to automatically calculate the evaluation scores of each scenario based on the configured evaluation rules and weight values, the activity quantity data, the customer quantity data, the activity revenue data, the customer feedback data and the discount data, and to calculate the comprehensive evaluation score based on the weight values; An evaluation report unit, connected with the evaluation computing unit, is configured to generate a marketing evaluation data report containing the comprehensive evaluation score and the evaluation scores of each scenario.

10. The system for data analysis of marketing campaigns according to claim 9, characterized in that The evaluation score indicators of the activity quantity scenario include the number of issued, clicked, received and verified activities, the evaluation score indicators of the activity customer scenario include the number of consumption customers, repeat customers, medium-frequency customers and high-frequency customers, the evaluation score indicators of the activity revenue scenario include the number of orders, order amount and order gross profit, the evaluation score indicators of the activity discount scenario include the discount amount and discount rate, and the evaluation score indicators of the activity feedback scenario include the number of good reviews, bad reviews, complaints and unsubscribes.

11. The system of claim 1, wherein The marketing related data include customer data, order data, product data, activity data, issued data, verified data, personnel data and financial data.

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