CN-122022905-A - Intelligent retail user insight data acquisition and processing method and system

CN122022905ACN 122022905 ACN122022905 ACN 122022905ACN-122022905-A

Abstract

The application discloses an intelligent retail user insight data acquisition processing method and system. The method comprises the steps of firstly designing a questionnaire containing multi-dimension indexes in a management platform, putting the questionnaire to a terminal user in a network or off-line mode, receiving answer data returned by the terminal user, carrying out integrity check and duplication removal processing on the answer data to obtain an original user data set, then executing preprocessing operation to generate a standardized user data set, carrying out grouping and statistical calculation on the standardized user data set according to a preset classification rule to obtain user behavior indexes and ranking results, finally synchronizing the user behavior indexes and the ranking results, and automatically generating a readability report in the form of a chart, characters and a table to complete acquisition and processing of user insight data.

Inventors

CHEN HAN
HUANG AIHUA
YIN JUEHUI

Assignees

上海趣致网络科技有限公司

Dates

Publication Date: 20260512
Application Date: 20260203

Claims (10)

1. An intelligent retail user insight data acquisition processing method, which is characterized by comprising the following steps: designing a questionnaire containing multi-dimension indexes in a management platform, and throwing the questionnaire to a terminal user in a network or off-line mode; Receiving answer data returned by a terminal user, and carrying out integrity check and duplication removal processing on the answer data to obtain an original user data set; Performing preprocessing operation on the original user data set to generate a standardized user data set, wherein the preprocessing operation at least comprises data cleaning, complement, splitting and merging operations; Grouping and counting the standardized user data sets according to a preset classification rule to obtain user behavior indexes and ranking results; And synchronizing the user behavior indexes and the ranking results, automatically generating a readability report in the form of a chart, characters and a table, and completing acquisition and processing of user insight data.
2. The method for collecting and processing intelligent retail user insight data according to claim 1, wherein a questionnaire containing multi-dimension indexes is designed in a management platform, and the questionnaire is put into an end user in a network or offline mode, and the method specifically comprises the steps of: In a questionnaire design module of the management platform, a questionnaire template is created according to business requirements, the questionnaire template comprises a plurality of questions, and each question corresponds to one or more user behavior indexes; Setting answer options for each question, and allocating a unique coding identifier for each answer option, wherein the coding identifier is used for index mapping in subsequent data processing; and storing the questionnaire template as a file in a preset format, and sending the file to the terminal user in a network or offline mode through a questionnaire delivery module.
3. The method for collecting and processing the insight data of the smart retail user according to claim 1, wherein receiving answer data returned by the terminal user specifically comprises: Receiving answer data returned by a terminal user through an API interface corresponding to questionnaire delivery, wherein the answer data is packaged in a JSON format and comprises a user identifier, a question identifier, an answer identifier and an answer time stamp; temporarily storing the received answer data in a memory queue, and simultaneously recording a data receiving time stamp for checking the integrity and timeliness of the subsequent data; And carrying out preliminary analysis on answer data temporarily stored in the memory queue, and extracting a user identifier, a question identifier and an answer identifier for subsequent integrity check and duplicate removal processing.
4. The smart retail user insight data collection processing method of claim 1, wherein performing preprocessing operations on the raw user data sets generates standardized user data sets, comprising: performing data cleaning on the original user data set to remove invalid data and abnormal values, wherein the invalid data comprises null values, repeated values and data which do not accord with a preset format; Performing complementation operation on the cleaned data, calling a third party data service to complete the missing user characteristic data, and performing consistency check on the completed data and the original data; Splitting the data after completion into a plurality of independent fields for subsequent analysis and processing; And merging the split data, merging a plurality of pieces of related data of the same user into a complete user record, and generating a unique identifier for subsequent statistical calculation by the merged data.
5. The method for collecting and processing the insight data of the smart retail user according to claim 1, wherein the grouping and statistical calculation are performed on the standardized user data set according to a preset classification rule to obtain the user behavior index and the ranking result, specifically comprising: Dividing a standardized user data set into a plurality of sub-data sets according to a preset classification rule, wherein each sub-data set corresponds to a set user group or behavior mode, and the preset classification rule at least comprises time, region and user characteristics; carrying out statistical calculation on each sub-data set, calculating statistics of the user behavior indexes, and calculating ranking results of the user behavior indexes according to the statistics, wherein the statistics at least comprise mean, median and standard deviation; For complex behavior pattern analysis, sub-data sets are further grouped by adopting a clustering algorithm, and potential patterns of user behaviors are found through the clustering analysis.
6. The method for collecting and processing the intelligent retail user insight data according to claim 1, wherein the user behavior indexes and the ranking results are synchronized, and the readability report is automatically generated in the form of a chart, a text and a table, and the method specifically comprises the following steps: synchronizing the calculated user behavior indexes and ranking results, and filling data into corresponding charts, characters and tables according to a preset template format; Performing online editing, and enabling a user to customize a report template through a drag control and a modification style to generate a user insight report meeting requirements; The edited report is exported to PDF or Excel format, supporting online preview and downloading, and simultaneously the report is stored in a system database for subsequent query and analysis.
7. The smart retail user insight data collection processing method of claim 1, further comprising: Managing and maintaining the generated user insight report, and supporting operations of re-editing, deleting and exporting the report; For the finished investigation task, the management platform supports to re-activate the questionnaire, modify the question or answer setting, re-execute the data acquisition and processing flow, and generate an updated user insight report; The system further provides a log recording function, records user operation, a data processing process and a system running state, and is convenient for problem investigation and system optimization.
8. An intelligent retail consumer insight data acquisition processing system, the system comprising: the management platform is used for designing a questionnaire containing multidimensional indexes and throwing the questionnaire to a terminal user in a network or off-line mode; The receiving module is used for receiving answer data returned by the terminal user, and carrying out integrity check and duplicate removal processing on the answer data to obtain an original user data set; the processing module is used for executing preprocessing operation on the original user data set to generate a standardized user data set, wherein the preprocessing operation at least comprises data cleaning, complement, splitting and merging operations; The classification module is used for grouping and counting the standardized user data sets according to a preset classification rule to obtain user behavior indexes and ranking results; And the reporting module is used for synchronizing the user behavior indexes and the ranking results, automatically generating a readability report in the form of a chart, a text and a table, and completing acquisition and processing of user insight data.
9. An electronic device comprising a memory and a processor, the memory storing a computer program that when executed by the processor implements the smart retail user insight data collection processing method of any of claims 1 to 7.
10. A computer readable storage medium, having stored thereon a computer program which when executed by a processor implements the smart retail user insight data collection processing method of any of claims 1 to 7.

Description

Intelligent retail user insight data acquisition and processing method and system Technical Field The application relates to the technical field of computer technology and intelligent retail technology, in particular to an intelligent retail user insight data acquisition and processing method and system. Background In the field of smart retail, user insight is key to promoting sales strategies, product customization, and service experience. At present, a set of mature questionnaire issuing, recycling and data processing systems have been developed in the intelligent retail machine industry, such as a unified monopoly supervision platform for tobacco as described in publication CN119721583a, and resource optimization configuration and risk control are realized by constructing an internal supervision architecture and monitoring and analyzing relevant data of tobacco sales in real time, while in a financial scene, publication CN107977864A proposes a client insight method based on a data analysis model, so as to improve the intellectualization and efficiency of the insight process. However, the prior art has limitations in terms of multi-dimensional user insight in the field of smart retail. Traditional data acquisition and processing modes are often focused on a single field, such as tobacco sales or financial services, lack of multi-dimensional data fusion capability across industries, and are difficult to provide comprehensive user behavior analysis. In addition, the real-time performance and flexibility of the data are limited, so that the market change is difficult to respond immediately, and the strategy suggestion of dynamic adjustment is provided. Disclosure of Invention Based on the above, the embodiment of the application provides a method and a system for acquiring and processing intelligent retail user insight data, which aim to realize multidimensional analysis of user behaviors and real-time report generation by integrating multi-source data, thereby enhancing market insight and strategy flexibility of intelligent retail. In a first aspect, a method for collecting and processing insight data of an intelligent retail user is provided, the method comprising: designing a questionnaire containing multi-dimension indexes in a management platform, and throwing the questionnaire to a terminal user in a network or off-line mode; Receiving answer data returned by a terminal user, and carrying out integrity check and duplication removal processing on the answer data to obtain an original user data set; Performing preprocessing operation on the original user data set to generate a standardized user data set, wherein the preprocessing operation at least comprises data cleaning, complement, splitting and merging operations; Grouping and counting the standardized user data sets according to a preset classification rule to obtain user behavior indexes and ranking results; And synchronizing the user behavior indexes and the ranking results, automatically generating a readability report in the form of a chart, characters and a table, and completing acquisition and processing of user insight data. Optionally, designing a questionnaire containing multi-dimension indexes in a management platform, and throwing the questionnaire to a terminal user in a network or offline mode, which specifically comprises: In a questionnaire design module of the management platform, a questionnaire template is created according to business requirements, the questionnaire template comprises a plurality of questions, and each question corresponds to one or more user behavior indexes; Setting answer options for each question, and allocating a unique coding identifier for each answer option, wherein the coding identifier is used for index mapping in subsequent data processing; and storing the questionnaire template as a file in a preset format, and sending the file to the terminal user in a network or offline mode through a questionnaire delivery module. Optionally, receiving answer data returned by the terminal user specifically includes: Receiving answer data returned by a terminal user through an API interface corresponding to questionnaire delivery, wherein the answer data is packaged in a JSON format and comprises a user identifier, a question identifier, an answer identifier and an answer time stamp; temporarily storing the received answer data in a memory queue, and simultaneously recording a data receiving time stamp for checking the integrity and timeliness of the subsequent data; And carrying out preliminary analysis on answer data temporarily stored in the memory queue, and extracting a user identifier, a question identifier and an answer identifier for subsequent integrity check and duplicate removal processing. Optionally, performing a preprocessing operation on the original user data set generates a normalized user data set, specifically including: performing data cleaning on the original user data set to remove invalid data