Information evaluation method and system, electronic equipment and computer program product

Abstract

The invention is suitable for the field of data processing, and provides an information evaluation method and system, electronic equipment and a computer program product, and the method comprises the steps: calculating a plurality of operation index values based on obtained multi-source operation data of a target service; determining a current target operation stage from a plurality of operation stages according to the plurality of operation index values; different operation stages correspond to different weight coefficient sets, and each weight coefficient set comprises a plurality of weight coefficients; obtaining a target weight coefficient set which corresponds to the target operation stage and comprises a plurality of target weight coefficients; and performing weighted calculation based on the plurality of target weight coefficients and the plurality of operation index values, and determining operation effect evaluation information of the target business. According to the scheme, the evaluation credibility of the information of the business operation effect can be improved.

Description

Technical Field

[0001] This application belongs to the field of data processing, and in particular relates to an information evaluation method, system, electronic device, and computer program product. Background Technology

[0002] In various business operations (such as e-commerce, retail, services, and manufacturing), evaluating operational effectiveness is a core element for optimizing resource allocation, improving service quality, and ensuring economic benefits. Existing methods for evaluating operational effectiveness rely on manual experience, resulting in poor reliability. Summary of the Invention

[0003] This application provides an information evaluation method, system, electronic device, and computer program product to solve the problem of poor reliability in the existing technology where the evaluation of business operation results is carried out manually based on experience.

[0004] The first aspect of this application provides an information evaluation method, including: Based on the multi-source operational data of the target business obtained, calculate multiple operational indicator values; Based on multiple operational indicator values, the current target operational stage is determined from multiple operational stages; different operational stages correspond to different sets of weight coefficients, and each set of weight coefficients contains multiple weight coefficients; Obtain the target weight coefficient set, which contains multiple target weight coefficients, corresponding to the target operation stage; The operational effectiveness evaluation information of the target business is determined by weighting multiple target weight coefficients and multiple operational indicator values.

[0005] A second aspect of this application provides an information evaluation system, including: The calculation module is used to calculate multiple operational indicator values ​​based on the multi-source operational data of the acquired target business. The first determining module is used to determine the current target operation stage from multiple operation stages based on multiple operation indicator values; different operation stages correspond to different sets of weight coefficients, and each set of weight coefficients contains multiple weight coefficients; The acquisition module is used to acquire a set of target weight coefficients, which includes multiple target weight coefficients, corresponding to the target operation stage; The second determining module is used to perform weighted calculations based on multiple target weight coefficients and multiple operational indicator values ​​to determine the operational performance evaluation information of the target business.

[0006] A third aspect of this application provides an electronic device including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the steps of the method described in the first aspect.

[0007] A fourth aspect of this application provides a computer program product comprising a computer program that, when executed by a processor, implements the steps of the method described in the first aspect.

[0008] A fifth aspect of this application provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the steps of the method described in the first aspect.

[0009] As can be seen from the above, this application calculates multiple operational indicator values ​​based on multi-source operational data of the target business, effectively integrating fragmented data. Based on these operational indicator values, it dynamically determines the current target operational stage and obtains a set of target weight coefficients that are compatible with the target operational stage. Then, it performs weighted calculations based on multiple target weight coefficients and multiple operational indicator values ​​in the target weight coefficient set to determine the operational effectiveness evaluation information of the target business, thereby achieving objective and real-time effectiveness evaluation and improving the credibility of the evaluation information on the operational effectiveness of the business. Attached Figure Description

[0010] To more clearly illustrate the technical solutions in the embodiments of this application, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0011] Figure 1 This is a flowchart of an information evaluation method provided in an embodiment of this application; Figure 2 This is a flowchart illustrating the process of solving for an initial set of weight coefficients, as provided in an embodiment of this application. Figure 3 This is a structural diagram of an information evaluation system provided in an embodiment of this application; Figure 4 This is a structural diagram of an electronic device provided in an embodiment of this application. Detailed Implementation

[0012] In the following description, specific details such as particular system architectures and techniques are set forth for illustrative purposes and not for limitation, in order to provide a thorough understanding of the embodiments of this application. However, those skilled in the art will understand that this application may also be implemented in other embodiments without these specific details. In other instances, detailed descriptions of well-known systems, apparatuses, circuits, and methods have been omitted so as not to obscure the description of this application with unnecessary detail.

[0013] It should be understood that, when used in this specification and the appended claims, the term "comprising" indicates the presence of the described features, integrals, steps, operations, elements and / or components, but does not exclude the presence or addition of one or more other features, integrals, steps, operations, elements, components and / or a collection thereof.

[0014] It should also be understood that the terminology used in this specification is for the purpose of describing particular embodiments only and is not intended to limit the scope of the application. As used in this specification and the appended claims, the singular forms “a,” “an,” and “the” are intended to include the plural forms unless the context clearly indicates otherwise.

[0015] It should also be further understood that the term “and / or” as used in this application specification and the appended claims means any combination of one or more of the associated listed items and all possible combinations, and includes such combinations.

[0016] As used in this specification and the appended claims, the term "if" may be interpreted, depending on the context, as "when," "once," "in response to determination," or "in response to detection." Similarly, the phrase "if determined" or "if [the described condition or event] is detected" may be interpreted, depending on the context, as "once determined," "in response to determination," "once [the described condition or event] is detected," or "in response to detection of [the described condition or event]."

[0017] In specific implementations, the terminals described in the embodiments of this application include, but are not limited to, other portable devices such as mobile phones, laptop computers, or tablet computers with touch-sensitive surfaces (e.g., touchscreen displays and / or touchpads). It should also be understood that in some embodiments, the device is not a portable communication device, but a desktop computer with touch-sensitive surfaces (e.g., touchscreen displays and / or touchpads).

[0018] The following discussion describes terminals that include displays and touch-sensitive surfaces. However, it should be understood that terminals may include one or more other physical user interface devices such as physical keyboards, mice, and / or joysticks.

[0019] The terminal supports a variety of applications, such as one or more of the following: drawing applications, presentation applications, word processing applications, website creation applications, disc burning applications, spreadsheet applications, game applications, telephone applications, video conferencing applications, email applications, instant messaging applications, exercise support applications, photo management applications, digital camera applications, digital camcorder applications, web browsing applications, digital music player applications, and / or digital video player applications.

[0020] Various applications that can run on a terminal can use at least one common physical user interface device, such as a touch-sensitive surface. One or more functions of the touch-sensitive surface and the corresponding information displayed on the terminal can be adjusted and / or changed between and / or within applications. In this way, the terminal's common physical architecture (e.g., the touch-sensitive surface) can support various applications with user interfaces that are intuitive and transparent to the user.

[0021] It should be understood that the sequence number of each step in this embodiment does not imply the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of this application embodiment.

[0022] To illustrate the technical solution described in this application, specific embodiments are provided below.

[0023] See Figure 1 , Figure 1 This is a flowchart of an information evaluation method provided in an embodiment of this application. For example... Figure 1 As shown, an information evaluation method includes the following steps: Step 101: Calculate multiple operational indicator values ​​based on the multi-source operational data of the target business obtained.

[0024] The target business refers to a specific commercial project or service whose operational effectiveness is to be evaluated, such as a drinking water project in a certain area or a subscription service for a software product.

[0025] Multi-source operational data refers to operational data from different channels and of different types, typically including: customer consumption data, such as transaction records, recharge records, and package purchase records; operational cost data, such as construction costs, maintenance fees, and marketing and promotion costs; and marketing and feedback data, such as promotional activity participation records, user questionnaire texts, and customer service dialogue logs. Multi-source operational data includes numerical data (such as maintenance fees) and non-numerical data (such as user questionnaire texts).

[0026] In some embodiments, multi-source operational data is obtained through data interfaces, database extraction, or log collection tools.

[0027] Operational metrics are quantitative results calculated based on multi-source operational data and used to characterize the operational status of a specific aspect of a target business.

[0028] Data is collected from dispersed data sources and processed to form quantifiable operational metrics.

[0029] In some embodiments, the step of calculating multiple operational indicator values ​​based on the acquired multi-source operational data of the target business includes: normalizing the numerical data in the multi-source operational data; and calculating multiple operational indicator values ​​based on the normalized numerical data according to a predefined indicator calculation formula.

[0030] To eliminate the impact of dimensional differences between multi-source operational data on subsequent information evaluation, numerical data (such as amounts and frequency) in the multi-source operational data are normalized. For example, the min-max normalization method is used to map the numerical data to the [0, 1] interval, with the specific formula as follows: ,in, The data is in the original numerical format. and These are the minimum and maximum values ​​corresponding to the numerical data. This is the normalized numerical data.

[0031] After normalization, the values ​​of each operational indicator are calculated according to predefined indicator calculation formulas. Examples of these predefined formulas include: Ground promotion conversion rate = Number of new users / Number of users reached through ground promotion; Package subscription rate = Number of users who subscribed to a package / Total number of users; Activity participation rate = Number of users who participated in the activity / Number of users reached through the activity; Customer acquisition cost per customer = Total ground promotion cost / Number of new users; Cost recovery period = Total investment / (Revenue - Operating costs - Maintenance costs); Package profit margin = (Package revenue - Cost of corresponding services for the package) / Average monthly revenue of the package; Monthly repurchase rate = Number of users who recharged for two consecutive months or more / Total number of users; Annual repurchase rate = Number of users who recharged more than twice in a year / Total number of users; Package renewal rate = Number of users who renewed their packages upon expiration / Total number of users whose packages expired; Package utilization rate = Used resources within the user's package / Available resources within the package.

[0032] By using normalization and other processing methods, multi-source operational data is standardized, providing a unified and standardized input for subsequent evaluations and solving the problems of difficult integration and low analysis efficiency caused by data fragmentation in traditional evaluations.

[0033] In some embodiments, non-numerical data in multi-source operational data is structured to facilitate subsequent operational decisions based on the structured non-numerical data.

[0034] In some embodiments, natural language processing (NLP) technology is used to analyze non-numerical data and extract keywords to generate quantitative labels. For example, customer feedback such as "the package is expensive and I can't use it all" can be converted into quantitative labels such as "package capacity mismatch" or "price sensitive".

[0035] Step 102: Determine the current target operation stage from multiple operation stages based on multiple operation indicator values; different operation stages correspond to different sets of weight coefficients, and each set of weight coefficients contains multiple weight coefficients.

[0036] The operational phase refers to a pre-defined period with different operational focuses, based on business development patterns and strategic goals.

[0037] In some embodiments, common operational phases include, but are not limited to: a promotion phase focused on expanding user base, a growth phase focused on improving user activity and retention, and a maturity phase focused on maximizing user value and profit.

[0038] Different operational phases correspond to different core objectives (e.g., the promotion phase focuses on customer acquisition efficiency, while the maturity phase focuses on repeat purchases and profits), and exhibit differentiated phase characteristics (e.g., the range of indicator data, growth trends, etc.). To accurately measure the achievement of the core objectives of each phase, a dedicated set of weighting coefficients needs to be configured for each operational phase. Each set of weighting coefficients contains multiple weighting coefficients to quantify the relative importance of its corresponding operational indicator within the evaluation system of its respective operational phase.

[0039] By analyzing the numerical characteristics of multiple operational metrics, the current operational stage of the target business can be determined.

[0040] In this application, the division of operational phases is not based on linear time, but rather on a dynamic response and matching of the business status represented by operational metrics, achieving a precise alignment with the actual business cycle. The operational phase of the target business is dynamically determined based on these real-time operational metrics, facilitating the subsequent selection of appropriate evaluation standards.

[0041] In some embodiments, determining the current target operation stage from multiple operation stages based on multiple operation indicator values ​​includes: comparing the multiple operation indicator values ​​with the stage determination indicators of each operation stage; and determining the operation stage with the highest compliance as the target operation stage based on the comparison results.

[0042] The target business has multiple operational indicators, and the weight coefficients in the weight coefficient set correspond one-to-one with the multiple operational indicators. The weight coefficients are used to characterize the importance of the corresponding operational indicator in the corresponding operational stage.

[0043] In some embodiments, operational metrics can be configured as a multi-level structure. The multi-level structure defines the subordinate and aggregation relationships between lower-level and higher-level metrics. For example, a first-level metric may contain at least one second-level metric, and a second-level metric may contain at least one third-level metric. The evaluation results of lower-level metrics are used to aggregate and generate the evaluation results of their respective higher-level metrics. As shown in Table 1 below, Table 1 is a schematic table of multi-level operational metrics provided in an embodiment of this application, showing a three-level metric system.

[0044] Table 1. Schematic diagram of multi-level operational indicators

[0045] In some embodiments, the weighting coefficients of operational metrics are associated with the operational phase. In different operational phases, the weighting coefficients of the same operational metric can be configured with different values ​​to achieve dynamic adaptation between the evaluation strategy and the core objectives of each phase.

[0046] Each operational phase has its core objectives, and the corresponding target values ​​for that phase can be used as phase-determining indicators (such as ground promotion conversion rate > 20%, monthly repurchase rate > 30%, etc.). The phase-determining indicators consist of multiple indicator values ​​and serve as entry conditions for the phase, used to distinguish different operational phases, that is, to determine which operational phase the target business currently belongs to.

[0047] In some embodiments, the stage determination indicators and weighting coefficients for different operating stages are shown in Table 2 below. Table 2 is a parameter illustration table of various operating indicators for different operating stages provided in the embodiments of this application.

[0048] Table 2. Parameter illustration of various operational indicators at different operational stages.

[0049] Table 2 shows example operational phases such as the first operational phase, the second operational phase, and the third operational phase. It also shows the phase determination indicators and weight coefficients of some operational indicators of the target business (such as the ground promotion conversion rate and customer acquisition cost per customer shown in the table) in these example operational phases.

[0050] The first stage (such as the new customer acquisition stage or the promotion stage) is characterized by indicators such as whether the user conversion rate of on-the-ground promotion activities meets the target and whether the cost per customer acquisition is within the budget. The second stage (such as the cost recovery stage or the development stage) is characterized by indicators such as whether the package profit margin meets the target and whether the cost recovery period meets expectations. The third stage (such as the maturity stage or the stability stage) is characterized by indicators such as whether the monthly repurchase rate is stable and whether the package renewal rate reaches the company's benchmark value. These stage indicators can be quantified as shown in Table 2.

[0051] In some embodiments, the stage determination indicator for each operational stage is a combination of indicator threshold ranges (for example, the stage determination indicator for the promotion stage can be set to user growth rate > 15% and customer acquisition cost < 50 yuan).

[0052] The calculated operational metric values ​​are compared with the stage-determining indicators for each operational phase. This comparison can be based on rule matching or simple similarity calculations (such as Euclidean distance). Based on the comparison results, the operational phase with the highest degree of conformity is determined as the current target operational phase for the target business.

[0053] In some embodiments, multiple operational indicator values ​​are used as a feature vector, and similarity matching is performed with the feature vector composed of predefined stage determination indicators corresponding to each operational stage to achieve comparison.

[0054] In some embodiments, a machine learning model (such as a stage classifier trained based on the K-means clustering algorithm) can be used to automatically determine the operational stage of the target business. This involves inputting the current operational metric values ​​into the model to obtain the target operational stage information output by the model.

[0055] By dynamically identifying operational stages, it overcomes the shortcomings of traditional assessments, which have fixed assessment indicators and cannot adapt to the core objectives of different business development stages, making the assessment more flexible and targeted.

[0056] In some embodiments, a set of weight coefficients adapted to each operation stage needs to be matched in advance. Therefore, before step 103, that is, before obtaining the target weight coefficient set containing multiple target weight coefficients corresponding to the target operation stage, the method further includes: calculating multiple initial weight coefficients corresponding to each operation stage using the analytic hierarchy process; and optimizing and adjusting the multiple initial weight coefficients corresponding to each operation stage based on historical operation data to obtain the set of weight coefficients containing multiple weight coefficients.

[0057] In some embodiments, the Analytic Hierarchy Process (AHP) is used to calculate the initial weight coefficients corresponding to each operational indicator in each operational phase.

[0058] The 1-9 scale method of the hierarchical analysis method is used to quantify the relative importance of every two operational indicators at the same level in each operational stage, where 1 indicates equal importance and 9 indicates extreme importance.

[0059] For example, a scaling score of 5 for package subscription rate relative to activity participation rate indicates that package subscription rate is significantly more important than activity participation rate. A scaling score of 5 for on-the-ground promotion conversion rate relative to activity participation rate also indicates that on-the-ground promotion conversion rate is significantly more important than activity participation rate. A scaling score of 2 for on-the-ground promotion conversion rate relative to package subscription rate indicates that on-the-ground promotion conversion rate is slightly more important than package subscription rate. These scaling scores demonstrate that in the current operational evaluation system, package subscription rate and on-the-ground promotion conversion rate are given extremely high strategic priority, far exceeding activity participation rate, while the advantage of on-the-ground promotion conversion rate over package subscription rate appears relatively weak.

[0060] In some embodiments, the independent judgments of multiple senior operations experts are integrated to determine the scaling scores of operations metrics, thereby forming a high-confidence judgment matrix and ensuring that the scaling scores are consistent with the actual business situation.

[0061] In some embodiments, the initial weight coefficients of operational indicators must be tested for consistency using the Analytic Hierarchy Process (AHP) before optimization and adjustment to ensure their logical rationality.

[0062] In some embodiments, a judgment matrix corresponding to multiple operational indicators at the same level is constructed based on the scaling scores among multiple operational indicators at the same level. As shown in Table 3 below, Table 3 is a schematic table of a judgment matrix provided in an embodiment of this application.

[0063] Table 3. Schematic diagram of the judgment matrix

[0064] The values ​​in Table 3 represent the importance of the corresponding row's operational metrics relative to the corresponding column's operational metrics. For example, a value of 5 in the second column of row 4 indicates that the operational metric in row 4 (ground promotion conversion rate) is 5 in importance relative to the operational metric in column 2 (activity participation rate). An importance score of 5 means that the ground promotion conversion rate is rated 5 relative to the activity participation rate, and correspondingly, the activity participation rate is 0.2 in importance relative to the ground promotion conversion rate.

[0065] In some embodiments, the initial weighting coefficients of each level of operational indicators are further solved using the sum-product method, such as... Figure 2 As shown, Figure 2 This is a flowchart illustrating the solution process for an initial set of weight coefficients provided in an embodiment of this application. The specific solution process is as follows: Step 201: Normalize the judgment matrix of each level of operation indicator by column to obtain the normalized judgment matrix.

[0066] Divide each element of each column of the judgment matrix by the sum of the elements in that column, so that the sum of each column becomes 1, thus eliminating the dimensions and making the data in different columns comparable.

[0067] , , .

[0068] in, To determine the matrix, It is to determine the elements in the matrix. Representing the The operational metric relative to the first The importance of each operational metric; This is the normalized judgment matrix, also known as the normalized matrix, where the sum of the elements in each column is 1. To determine the elements in the normalized judgment matrix B after column normalization, let represent the original elements. The proportion of the total in its column; This refers to the matrix order, which represents the number of factors (operational metrics) at the corresponding level. Indicates a line, Indicates a column, , , It is a positive integer.

[0069] Step 202: Integrate the normalized judgment matrix into an eigenvector.

[0070] Normalize the judgment matrix Add all the elements in each row of the array to get a sum. The column vector in row 1 and column 1 is the eigenvector, represented as follows: The eigenvectors initially reflect the relative importance of each element. , elements in .

[0071] Step 203: Perform vector normalization on the feature vectors to obtain normalized feature vectors.

[0072] Divide the element of each row in the feature vector by the sum of the elements of all rows to obtain the normalized feature element (weight coefficient) of the corresponding row. This operation ensures that the sum of the weight coefficients is 1.

[0073] Normalized feature elements Normalized eigenvectors are approximate eigenvectors. .

[0074] Step 204: Calculate the maximum eigenvalue based on the judgment matrix and the normalized eigenvector.

[0075] Based on formula Calculate the largest eigenvalue This is to facilitate consistency checks.

[0076] Step 205: Perform a consistency check based on the largest eigenvalue, and determine the normalized eigenvectors that pass the check as the initial set of weight coefficients.

[0077] Based on formula Calculate the Consistency Index (CI).

[0078] The order is obtained by querying the Random Index (RI) table. The corresponding RI value.

[0079] Based on formula Calculate the Consistency Ratio (CR).

[0080] If CR < 0.1, the consistency test is passed, and the corresponding normalized eigenvector can be used as the initial set of weight coefficients. The initial set of weight coefficients is determined, which includes An initial weight coefficient is set. If the test fails, the corresponding judgment matrix is ​​fed back to the configuration interface for calibration until it meets the consistency requirements.

[0081] In some embodiments, the order n of the judgment matrix is ​​3, and the elements, namely the operational indicators, are the activity participation rate, package application rate, and ground promotion conversion rate. After the above steps, the feature vector, weight coefficient, maximum eigenvalue, and CI value are calculated sequentially. As shown in Table 4 below, Table 4 is a schematic table of process parameters for solving the initial weight coefficients provided by an embodiment of this application.

[0082] Table 4. Schematic diagram of process parameters for solving the initial weight coefficients.

[0083] The RI value is 0.52, and the corresponding CR value is 0.052, which is less than 0.1. Therefore, the consistency test is passed, and the subsequent evaluation can be carried out using the weighting coefficients of the activity participation rate (9.035%), the package application rate (35.372%), and the on-the-ground promotion conversion rate (55.593%).

[0084] In some embodiments, machine learning algorithms, such as random forest regression and gradient descent, are used to optimize and adjust the initial weight coefficients, so that the optimized and adjusted weight coefficients dynamically adapt to the actual business status, ensuring the objectivity and accuracy of the evaluation information and improving the credibility of the evaluation information.

[0085] In some embodiments, training is performed using historical operational data, namely historical operational indicator values ​​and historical operational performance evaluation information, and the initial weight coefficients are continuously adjusted so that the operational performance evaluation information determined based on the optimized and adjusted weight coefficients and historical operational data closely matches the historical operational performance evaluation information, thereby maximizing the fit to the actual business performance and ultimately obtaining a more accurate set of weight coefficients for final use.

[0086] In some embodiments, historical operational performance evaluation information is a comprehensive historical operational performance score. Cross-validation is used to ensure that the matching degree between the trained score and the comprehensive historical operational performance score reaches a set threshold, such as exceeding 90%, thereby improving the reliability of the comprehensive operational performance score calculated by the trained weight coefficients in practical applications. If the score matching degree does not reach the set threshold, the weight coefficients are adjusted backtrackingly until the matching degree requirement is met.

[0087] By combining hierarchical analysis with machine learning to generate weight coefficients, the method incorporates the experience of domain experts and utilizes historical data for objective optimization, ensuring the scientific nature and accuracy of weight setting. This provides a reliable basis for quantitative evaluation and enhances the credibility of operational performance assessment.

[0088] In some embodiments, the change range of at least one set operational indicator value among a plurality of operational indicator values ​​is monitored in real time; when the change range of at least one set operational indicator value meets the update trigger condition, the set of weight coefficients is updated.

[0089] To respond to market changes, the system monitors the changes in set operational metrics, i.e., key performance indicators, in real time. When the change in at least one set operational metric meets the preset update trigger condition (such as a drop of more than 15% in ground promotion conversion rate for two consecutive weeks), the set of weight coefficients is automatically updated. For example, the analytic hierarchy process and weight coefficient optimization adjustment process are re-executed to ensure that the weight coefficients always effectively respond to actual business changes.

[0090] By dynamically updating, we can ensure that the operational effectiveness of target businesses can be quantitatively evaluated and responded to in real time based on weighted coefficients, thus solving the problem of lagging decision-making in traditional methods.

[0091] Step 103: Obtain the target weight coefficient set corresponding to the target operation stage, which includes multiple target weight coefficients.

[0092] Based on the identified target operational stage label, the corresponding target weight coefficient set is retrieved and extracted from a pre-configured weight configuration library. This set is an ordered data group containing multiple target weight coefficients, where each weight coefficient is uniquely bound to a specific operational indicator, providing a basis for subsequent weighted calculations.

[0093] Step 104: Perform a weighted calculation based on multiple target weight coefficients and multiple operational indicator values ​​to determine the operational performance evaluation information of the target business.

[0094] Operational performance evaluation information is the final output evaluation result, which can be a report containing a comprehensive score, rating, ranking, and / or multi-dimensional scores.

[0095] By aggregating operational indicator values ​​using weighting coefficients, highly reliable operational performance evaluation information is ultimately generated.

[0096] In some embodiments, determining the operational performance evaluation information of the target business by weighted calculation based on multiple target weight coefficients and multiple operational indicator values ​​includes: calculating the operational indicator score and comprehensive operational performance score of each operational indicator of the target business level by level according to multiple target weight coefficients and multiple operational indicator values; and determining the operational indicator score, the comprehensive operational performance score, and the operational ranking corresponding to the comprehensive operational performance score as the operational performance evaluation information.

[0097] In some embodiments, operational performance evaluation information is determined through step-by-step calculation.

[0098] In some embodiments, the operational indicator scores of the lower-level indicators are first calculated. Then, the overall operational performance score is calculated by aggregating the scores upwards. For example, the score of a higher-level indicator can be the sum of the scores of all its lower-level indicators. Finally, the operational indicator scores at all levels, the overall operational performance score, and the operational ranking in a designated region based on the overall operational performance score are collectively determined as the operational performance evaluation information.

[0099] In some embodiments, the operational indicators include primary operational indicators, secondary operational indicators, and tertiary operational indicators, each of the tertiary operational indicators corresponding to an operational indicator value. The target weight coefficient set includes weight coefficients corresponding to each level of the operational indicators. The step of calculating the operational indicator score and comprehensive operational performance score of each operational indicator of the target business level by level based on multiple target weight coefficients and multiple operational indicator values ​​includes: calculating the operational indicator score of the tertiary operational indicator based on the operational indicator value and tertiary weight coefficient corresponding to each tertiary operational indicator; summing the operational indicator scores of all tertiary operational indicators included in each secondary operational indicator to obtain the operational indicator score of the secondary operational indicator; calculating the operational indicator score of the primary operational indicator based on the operational indicator scores and tertiary weight coefficients of all secondary operational indicators corresponding to each primary operational indicator; and calculating the comprehensive operational performance score of the target business based on the operational indicator scores and tertiary weight coefficients of all primary operational indicators.

[0100] The calculation proceeds from bottom to top: The operational indicator score for each level 3 operational indicator is calculated based on its corresponding operational indicator value and weighting coefficient (level 3 weighting coefficient). The scores of all level 3 operational indicators belonging to the same level 2 operational indicator are summed to obtain the level 2 operational indicator score. The operational indicator score for each level 1 operational indicator is calculated based on its corresponding level 2 operational indicator scores and weighting coefficient (level 2 weighting coefficient). Finally, the overall operational performance score is calculated based on the level 1 operational indicator scores and weighting coefficient (level 1 weighting coefficient).

[0101] In some embodiments, taking the indicator system in Table 1 as an example, the corresponding comprehensive score of operational performance is calculated. This comprehensive score refers to the overall performance of the target business (such as the direct drinking water project) in the three core dimensions of marketing conversion, cost-effectiveness, and customer retention. It is a quantitative assessment of whether the target business has achieved its phased operational goals.

[0102] In some embodiments, the dimensions for measuring various operational metrics differ, such as a 20% conversion rate for on-the-ground promotion activities or a customer acquisition cost of 100 yuan per customer. A score of 0-100 aligns with conventional assessment criteria (e.g., 60 points is acceptable, 80 points is excellent). To facilitate quantification, a 100-point scoring system is set for the metrics, mapping various operational metrics to a consistent evaluation system for easier understanding by operations personnel.

[0103] In some embodiments, the percentage range is defined as follows: 0-59 points, unqualified, meaning that the core indicator has not reached 60% of the stage target; 60-79 points, qualified, meaning that the core indicator has reached 60%-80% of the stage target; 80-100 points, excellent, meaning that the core indicator has reached more than 80% of the stage target.

[0104] In some embodiments, the operational indicator score for a third-level operational indicator is calculated as follows: (Operational indicator value / Stage target value) × 100 × Weighting coefficient. The stage target value can be the stage-specific indicator for that third-level operational indicator in the target operational stage. Taking the ground promotion conversion rate as an example, its stage target value is 20%, the operational indicator value is 15%, and the weighting coefficient is 0.3. Therefore, the operational indicator score for the ground promotion conversion rate is calculated as (15% / 20%) × 100 × 0.3 = 22.5 points. This score can be compared with the 30 points corresponding to a weighting coefficient of 0.3.

[0105] In some embodiments, operational performance evaluation information is output and visualized. This evaluation information can be output according to a set schedule, such as every Friday or Monday.

[0106] In some embodiments, the output operational performance evaluation information may also include operational indicator values ​​(such as conversion rate and cost) and package profitability evaluation information determined based on package renewal rate, package utilization rate and package revenue, to assist operations personnel in making resource investment decisions.

[0107] In some embodiments, standardized non-numerical data is output to provide support for pricing and event planning decisions.

[0108] In some embodiments, operational performance evaluation information may include operational strategy recommendations, such as reducing the frequency of on-the-ground promotions in areas with high customer acquisition costs and switching to social media marketing, and adding complimentary benefits to packages with low renewal rates.

[0109] This application outputs diverse assessment information and directly transforms the assessment results into actionable guidelines, providing direct and reliable data support for precise resource allocation and strategy optimization.

[0110] In this embodiment, multiple operational indicator values ​​are calculated based on multi-source operational data of the target business, effectively integrating fragmented data. The current target operational stage is dynamically determined based on these operational indicator values, and a set of target weight coefficients adapted to the target operational stage is obtained. Then, multiple target weight coefficients and multiple operational indicator values ​​in the target weight coefficient set are weighted and calculated to determine the operational effect evaluation information of the target business, thereby achieving objective and real-time effect evaluation and improving the credibility of the evaluation information of the operational effect of the business.

[0111] See Figure 3, Figure 3 This is a structural diagram of an information evaluation system provided in an embodiment of this application. For ease of explanation, only the parts related to the embodiment of this application are shown.

[0112] The information evaluation system 300 includes: a calculation module 301, a first determination module 302, an acquisition module 303, and a second determination module 304.

[0113] The calculation module 301 is used to calculate multiple operational indicator values ​​based on the multi-source operational data of the acquired target business.

[0114] The first determining module 302 is used to determine the current target operation stage from multiple operation stages based on multiple operation indicator values; different operation stages correspond to different sets of weight coefficients, and each set of weight coefficients contains multiple weight coefficients.

[0115] The acquisition module 303 is used to acquire the target weight coefficient set corresponding to the target operation stage, which includes multiple target weight coefficients.

[0116] The second determining module 304 is used to perform weighted calculations based on multiple target weight coefficients and multiple operational indicator values ​​to determine the operational performance evaluation information of the target business.

[0117] In some embodiments, the computing module is specifically used for: The numerical data in the multi-source operational data are normalized. Based on the normalized numerical data, multiple operational indicator values ​​are calculated according to predefined indicator calculation formulas.

[0118] In some embodiments, the first determining module is specifically used for: The values ​​of multiple operational indicators are compared with the stage determination indicators of each operational stage; Based on the comparison results, the operational stage with the highest degree of conformity is determined as the target operational stage.

[0119] In some embodiments, the system further includes a weighting coefficient determination module, configured to: The Analytic Hierarchy Process (AHP) is used to calculate multiple initial weight coefficients corresponding to each operational stage. Based on historical operational data, the initial weight coefficients corresponding to each operational stage are optimized and adjusted to obtain a set of weight coefficients containing the multiple weight coefficients.

[0120] In some embodiments, the weighting coefficient determination module is further configured to: Real-time monitoring of the change range of at least one set operational indicator value among multiple operational indicator values; The set of weight coefficients is updated when the change in at least one of the set operational indicator values ​​meets the update trigger condition.

[0121] In some embodiments, the second determining module is specifically used for: Based on multiple target weight coefficients and multiple operational indicator values, the operational indicator scores and comprehensive operational performance scores of each operational indicator of the target business are calculated step by step. The operational indicator scores, the comprehensive operational performance scores, and the operational rankings corresponding to the comprehensive operational performance scores are determined as the operational performance evaluation information.

[0122] In some embodiments, the operational indicators include primary operational indicators, secondary operational indicators, and tertiary operational indicators, each of the tertiary operational indicators corresponding to an operational indicator value, and the target weight coefficient set includes the weight coefficients corresponding to each level of the operational indicators. The second determining module is further configured to: The operational indicator score of each of the three-level operational indicators is calculated based on the operational indicator value and the three-level weight coefficient. The operational indicator scores of all the tertiary operational indicators included in each secondary operational indicator are summed to obtain the operational indicator score of the secondary operational indicator. The operational indicator score of the primary operational indicator is calculated based on the operational indicator scores and secondary weight coefficients of all the secondary operational indicators corresponding to each primary operational indicator. The overall operational performance score of the target business is calculated based on the operational indicator scores and primary weighting coefficients of all the primary operational indicators.

[0123] The information evaluation system provided in this application embodiment can implement all the processes of the above-described information evaluation method embodiments and achieve the same technical effect. To avoid repetition, it will not be described again here.

[0124] Figure 4 This is a structural diagram of an electronic device provided in an embodiment of this application. As shown in the figure, the electronic device 4 of this embodiment includes: at least one processor 40 ( Figure 4 (Only one is shown in the diagram), memory 41, and computer program 42 stored in said memory 41 and executable on said at least one processor 40, which, when executed, implements the steps in any of the above method embodiments.

[0125] The electronic device 4 can be a desktop computer, laptop, handheld computer, or cloud server, etc. The electronic device 4 may include, but is not limited to, a processor 40 and a memory 41. Those skilled in the art will understand that... Figure 4 This is merely an example of electronic device 4 and does not constitute a limitation on electronic device 4. It may include more or fewer components than shown, or combine certain components, or different components. For example, the electronic device may also include input / output devices, network access devices, buses, etc.

[0126] The processor 40 can be a Central Processing Unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor can be a microprocessor or any conventional processor.

[0127] The memory 41 can be an internal storage unit of the electronic device 4, such as a hard disk or memory. The memory 41 can also be an external storage device of the electronic device 4, such as a plug-in hard disk, Smart Media Card (SMC), Secure Digital (SD) card, or Flash Card. Furthermore, the memory 41 can include both internal and external storage units of the electronic device 4. The memory 41 is used to store the computer program and other programs and data required by the electronic device. The memory 41 can also be used to temporarily store data that has been output or will be output.

[0128] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the above-described division of functional units and modules is merely an example. In practical applications, the above functions can be assigned to different functional units and modules as needed, that is, the internal structure of the system can be divided into different functional units or modules to complete all or part of the functions described above. The functional units and modules in the embodiments 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. The integrated unit can be implemented in hardware or as a software functional unit. Furthermore, the specific names of the functional units and modules are only for easy differentiation and are not intended to limit the scope of protection of this application. The specific working process of the units and modules in the above system can be referred to the corresponding process in the foregoing method embodiments, and will not be repeated here.

[0129] In the above embodiments, the descriptions of each embodiment have different focuses. For parts that are not described in detail or recorded in a certain embodiment, please refer to the relevant descriptions of other embodiments.

[0130] Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0131] In the embodiments provided in this application, it should be understood that the disclosed systems / electronic devices and methods can be implemented in other ways. For example, the system / electronic device embodiments described above are merely illustrative. For instance, the division of modules or units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the mutual coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection of systems or units may be electrical, mechanical, or other forms.

[0132] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0133] Furthermore, the functional units in the various embodiments of this application 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. The integrated unit can be implemented in hardware or as a software functional unit.

[0134] If the integrated module / unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, all or part of the processes in the methods of the above embodiments can also be implemented by a computer program instructing related hardware. The computer program can be stored in a computer-readable storage medium, and when executed by a processor, it can implement the steps of the various method embodiments described above. The computer program includes computer program code, which can be in the form of source code, object code, executable files, or certain intermediate forms. The computer-readable medium can include: any entity or device capable of carrying the computer program code, recording media, USB flash drives, portable hard drives, magnetic disks, optical disks, computer memory, read-only memory (ROM), random access memory (RAM), electrical carrier signals, telecommunication signals, and software distribution media, etc. It should be noted that the content included in the computer-readable medium can be appropriately added or removed according to the requirements of legislation and patent practice in the jurisdiction. For example, in some jurisdictions, according to legislation and patent practice, computer-readable media do not include electrical carrier signals and telecommunication signals.

[0135] The processes in the above-described embodiments can be implemented by a computer program product. When the computer program product is run on an electronic device, the electronic device executes the steps in the above-described method embodiments.

[0136] The above-described embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit them. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of this application, and should all be included within the protection scope of this application.

Claims

1. An information evaluation method, characterized in that, include: Based on the multi-source operational data of the target business obtained, calculate multiple operational indicator values; Based on multiple operational indicator values, the current target operational stage is determined from multiple operational stages; different operational stages correspond to different sets of weight coefficients, and each set of weight coefficients contains multiple weight coefficients; Obtain the target weight coefficient set, which contains multiple target weight coefficients, corresponding to the target operation stage; The operational effectiveness evaluation information of the target business is determined by weighting multiple target weight coefficients and multiple operational indicator values.

2. The method according to claim 1, characterized in that, The calculation of multiple operational indicator values ​​based on the acquired multi-source operational data of the target business includes: The numerical data in the multi-source operational data are normalized. Based on the normalized numerical data, multiple operational indicator values ​​are calculated according to predefined indicator calculation formulas.

3. The method according to claim 1, characterized in that, The step of determining the current target operational stage from multiple operational stages based on multiple operational indicator values ​​includes: The values ​​of multiple operational indicators are compared with the stage determination indicators of each operational stage; Based on the comparison results, the operational stage with the highest degree of conformity is determined as the target operational stage.

4. The method according to claim 1, characterized in that, Before obtaining the target weight coefficient set containing multiple target weight coefficients corresponding to the target operation stage, the method further includes: The Analytic Hierarchy Process (AHP) is used to calculate multiple initial weight coefficients corresponding to each operational stage. Based on historical operational data, the initial weight coefficients corresponding to each operational stage are optimized and adjusted to obtain a set of weight coefficients containing the multiple weight coefficients.

5. The method according to claim 4, characterized in that, The method further includes: Real-time monitoring of the change range of at least one set operational indicator value among multiple operational indicator values; The set of weight coefficients is updated when the change in at least one of the set operational indicator values ​​meets the update trigger condition.

6. The method as described in claim 1, characterized in that, The step of determining the operational performance evaluation information of the target business by weighting multiple target weight coefficients and multiple operational indicator values ​​includes: Based on multiple target weight coefficients and multiple operational indicator values, the operational indicator scores and comprehensive operational performance scores of each operational indicator of the target business are calculated step by step. The operational indicator scores, the comprehensive operational performance scores, and the operational rankings corresponding to the comprehensive operational performance scores are determined as the operational performance evaluation information.

7. The method as described in claim 6, characterized in that, The operational indicators include primary operational indicators, secondary operational indicators, and tertiary operational indicators. Each tertiary operational indicator corresponds to an operational indicator value. The target weight coefficient set includes weight coefficients corresponding to each level of the operational indicators. The step of calculating the operational indicator score and comprehensive operational performance score of each operational indicator of the target business level by level based on multiple target weight coefficients and multiple operational indicator values ​​includes: The operational indicator score of each of the three-level operational indicators is calculated based on the operational indicator value and the three-level weight coefficient. The operational indicator scores of all the tertiary operational indicators included in each secondary operational indicator are summed to obtain the operational indicator score of the secondary operational indicator. The operational indicator score of the primary operational indicator is calculated based on the operational indicator scores and secondary weight coefficients of all the secondary operational indicators corresponding to each primary operational indicator. The overall operational performance score of the target business is calculated based on the operational indicator scores and primary weighting coefficients of all the primary operational indicators.

8. An information evaluation system, characterized in that, include: The calculation module is used to calculate multiple operational indicator values ​​based on the multi-source operational data of the acquired target business. The first determining module is used to determine the current target operation stage from multiple operation stages based on multiple operation indicator values; different operation stages correspond to different sets of weight coefficients, and each set of weight coefficients contains multiple weight coefficients; The acquisition module is used to acquire a set of target weight coefficients, which includes multiple target weight coefficients, corresponding to the target operation stage; The second determining module is used to perform weighted calculations based on multiple target weight coefficients and multiple operational indicator values ​​to determine the operational performance evaluation information of the target business.

9. An electronic device, characterized in that, The electronic device includes a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the computer program, the electronic device performs the method as described in any one of claims 1 to 7.

10. A computer program product, characterized in that, Includes a computer program, which, when run, causes the method as described in any one of claims 1 to 7 to be performed.

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