CN115168379A - E-commerce operation log management and control method - Google Patents

Abstract

The application relates to the technical field of internet commerce, in particular to an e-commerce operation log control method, which comprises the following steps: acquiring current data of a target to be analyzed; acquiring historical data of the target to be analyzed; dividing the current data into a plurality of operation data according to a preset division rule; comparing each operation data with the corresponding historical data to obtain difference data; marking each difference data in the historical data according to a marking rule to form updated data; and updating the operation log of the target to be analyzed according to the updating data. The e-commerce operation log management and control method can reduce the recording and management workload of the operation log and effectively improve the operation management efficiency.

Description

E-commerce operation log management and control method

Technical Field

The application relates to the technical field of internet commerce, in particular to an e-commerce operation log management and control method.

Background

With the development of internet technology, internet e-commerce, which is simply referred to as internet e-commerce, is more and more widely applied, and audience groups are more and more. The internet e-commerce refers to a business operation mode in which a buyer and a seller perform various business activities between any places where networks can be connected under an internet open network environment, and the exchange of production data between two or more traders and the derived trading process, financial activity and related comprehensive service activity are realized.

For e-commerce merchants, the operation work such as operation, management and maintenance needs to be performed on stores so as to ensure that consumers can complete commodity purchase in the stores, and the operation policy can be adjusted according to the sales condition and the market need, and the operation work needs to be recorded correspondingly so as to form an operation log.

However, the operation logs are recorded manually at present, and due to high repeatability and large workload of operation work, the content of daily adjustment needed by operators is large, manual log recording takes a long time, and the operation logs are difficult to view and manage by managers due to different recording modes of each person.

Therefore, it is an urgent need for technical personnel to provide a method for managing and controlling an e-commerce operation log, which can reduce the workload of recording and managing the operation log and effectively improve the operation management efficiency.

Disclosure of Invention

In order to reduce the recording and management workload of the operation log and effectively improve the operation management efficiency, the application provides an e-commerce operation log management and control method.

The application provides an e-commerce operation log control method, which comprises the following steps:

acquiring current data of a target to be analyzed;

acquiring historical data of the target to be analyzed;

dividing the current data into a plurality of operation data according to a preset division rule;

comparing each operation data with the corresponding historical data to obtain difference data;

marking each difference data in the historical data according to a marking rule to form updated data;

and updating the operation log of the target to be analyzed according to the updating data.

According to the technical scheme, the preset division rule is adopted, the difference data obtained after the current data and the historical data of the target to be analyzed are divided are marked according to the marking rule, the updating data used for updating the operation log of the target to be analyzed is formed, the automatic updating and the marking of the corresponding content are achieved, the recording and management workload of the operation log can be reduced, and the operation management efficiency is effectively improved.

Optionally, the comparing each operation data with the corresponding historical data to obtain difference data includes:

selecting one of the operation data as current comparison data;

acquiring category information of the current comparison data;

acquiring the historical data corresponding to the type information as current historical data;

comparing the current comparison data with the current historical data, and taking the difference between the current comparison data and the current historical data as difference subdata corresponding to the current category information;

selecting another operation data as the current comparison data to circulate the steps until a preset comparison requirement is met;

and integrating the difference sub-data to generate the difference data.

According to the technical scheme, the category information is adopted to compare the operation data with the corresponding current historical data, the difference between the operation data and the corresponding current historical data is used as the difference subdata, each difference subdata is obtained in a circulating mode and is integrated to generate the difference data, the difference data comprises the category information, and the difference data forms the operation log, so that the data corresponding to the category in the category information in the operation log can be inquired according to the category information, the on-demand inquiry is achieved, and the management efficiency of the operation log is improved.

Optionally, the comparing each operation data with the corresponding historical data to obtain difference data includes:

acquiring a data blank line in each operation data;

replacing the data blank row with a placeholder to form the processed operation data;

and comparing each processed operation data with the corresponding historical data to obtain the difference data.

Through the technical scheme, the empty data rows are replaced by the placeholders, and the problem that the differential data acquisition is wrong or fails due to the fact that the empty data rows are difficult to perform effective data comparison is solved.

Optionally, the marking, according to a marking rule, each of the difference data in the historical data to form update data includes:

judging the difference type of each difference data;

if the difference type is a new type, marking corresponding difference data in the historical data by adopting a first mark to form first updating data;

if the difference type is a deletion type, marking corresponding difference data in the historical data by adopting a second mark to form second updating data;

if the difference type is a change type, marking the corresponding content before change in the difference data by using the second mark in the historical data, and marking the corresponding content after change in the difference data by using the first mark in the historical data to form third updated data;

and integrating the first updating data, the second updating data and the third updating data to form the updating data.

According to the technical scheme, the different types are marked by different marks according to the difference types of the difference data to form corresponding updated data, and then the updated data are integrated to form the updated data, so that the effect of accurately and visually comparing the front and back changes of the target to be analyzed is achieved.

Optionally, after the dividing the current data into a plurality of operation data according to the preset dividing rule, the method further includes:

acquiring supplementary recording data;

dividing the additional recording data into a plurality of additional recording subdata according to the preset division rule;

and combining each additional entry sub-data with the corresponding operation data so as to form each updated operation data.

According to the technical scheme, the acquired additional recording data are divided according to the preset division rule and then combined with the corresponding operation data, so that the manual entry or the import of other records can be supported besides the automatic generation of the operation logs, and the generation mode of the operation logs of various types is supported.

Optionally, before the obtaining the current data of the target to be analyzed, the method further includes:

acquiring an interactive instruction;

acquiring a target type to be analyzed according to the interactive instruction;

and filtering all analysis targets according to the target types to form the target to be analyzed.

According to the technical scheme, the target type to be analyzed is obtained from the interactive instruction, so that the required target to be analyzed is obtained from all the analysis targets, and the target corresponding to the operation log can be generated as required.

Optionally, after the updating the operation log of the target to be analyzed according to the update data, the method further includes:

acquiring the current display resolution;

acquiring a preset display specification of the operation log;

processing a loading window of the operation log according to the ratio of the preset display specification to the current display resolution;

and loading and displaying the operation log in the processed loading window.

According to the technical scheme, the loading window of the operation log is processed according to the proportion of the preset display specification and the current display resolution, so that the content is ensured to be displayed in the visible area all the time.

Optionally, after the updating the operation log of the target to be analyzed according to the update data, the method further includes:

acquiring a preset attention label;

acquiring an attention category to be displayed according to the attention label;

and filtering all the operation logs according to the attention categories to form operation log display contents.

According to the technical scheme, the preset attention label is adopted, and the final display content is the operation log content corresponding to the attention category according to the attention category, namely the effect of display on demand is achieved.

Optionally, after the updating the operation log of the target to be analyzed according to the update data, the method further includes:

acquiring all dimension types contained in the operation log;

acquiring a current dimension statistical rule;

according to the dimension statistical rule, the operation logs are subjected to distinguishing statistics according to the dimension types;

and generating dimension statistical data corresponding to each dimension type based on each operation log after the distinguishing statistics.

According to the technical scheme, the operation logs are distinguished and counted according to the dimension counting rule, so that dimension counting data corresponding to each dimension type are generated, and the operation logs are counted according to different dimensions.

Optionally, the acquiring the historical data of the target to be analyzed includes:

acquiring current time;

acquiring a time difference value between the current time and the last acquired current time;

judging whether the time difference value is larger than a preset period or not;

if the time difference is larger than or equal to the preset period, copying corresponding data of the target to be analyzed before the current time as the historical data;

and if the time difference value is smaller than the preset period, returning to obtain the current time again and repeating the steps.

According to the technical scheme, the mode of the preset period is adopted, the time difference value of the current time obtained in the last two times is compared with the preset period, and the corresponding data before the current time is determined to be copied as the historical data based on the comparison result, so that the effect of periodically obtaining the historical data is achieved, and the historical data is copied original data and cannot influence the original data.

To sum up, this application marks through adopting and predetermine the partition rule, the difference data after current data after will waiting to analyze the target partition is compared with historical data, according to the mark rule, forms the update data who is used for renewing the operation log of waiting to analyze the target, reaches automatic update and marks corresponding content to the realization can reduce the record of operation log and the work load of management, effectively promotes operation management efficiency's effect, solves the work repeatability height of traditional log record mode, work load is big problem.

Drawings

Fig. 1 is a schematic flowchart of one implementation manner of an e-commerce operation log management and control method according to an embodiment of the present application;

fig. 2 is a schematic flowchart of one implementation manner of the e-commerce operation log management and control method according to the embodiment of the present application;

fig. 3 is a schematic flowchart of one implementation manner of an e-commerce operation log management and control method according to an embodiment of the present application;

fig. 4 is a schematic flowchart of one implementation manner of an e-commerce operation log management and control method according to an embodiment of the present application;

fig. 5 is a schematic flowchart of one implementation manner of an e-commerce operation log management and control method according to an embodiment of the present application;

fig. 6 is a schematic flowchart of one implementation manner of an e-commerce operation log management and control method according to an embodiment of the present application;

fig. 7 is a schematic flowchart of one implementation manner of an e-commerce operation log management and control method according to an embodiment of the present application;

fig. 8 is a flowchart illustrating a flow of one implementation manner of the e-commerce operation log management and control method according to the embodiment of the present application;

fig. 9 is a schematic flowchart of one implementation manner of an e-commerce operation log management and control method according to an embodiment of the present application;

fig. 10 is a flowchart illustrating one implementation manner of an e-commerce operation log management and control method according to an embodiment of the present application.

Detailed Description

In order to make those skilled in the art better understand the technical solutions in the present application, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are only a part of the embodiments of the present application, and not all the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present application.

The embodiment of the application provides an e-commerce operation log management and control method, as shown in fig. 1, the method comprises the following steps:

s01, acquiring current data of a target to be analyzed;

s02, acquiring historical data of a target to be analyzed;

s03, dividing the current data into a plurality of operation data according to a preset division rule;

s04, comparing each operation data with corresponding historical data to obtain difference data;

s05, marking each difference data in the historical data according to a marking rule to form updated data;

and S06, updating the operation log of the target to be analyzed according to the updating data.

In this embodiment, the target to be analyzed refers to an analysis target corresponding to an operation log to be generated or updated, and may be one or more shops, one or more commodities, or the whole e-commerce platform.

The current data in step S01 is data of a target to be analyzed corresponding to current time, and the current time may be display time of a current system acquired by the system, or may be a time node in which time determined by an instruction is used as a current operation object.

The historical data in step S02 is data in which the target to be analyzed is different from the current time compared to the current time, and the selection node of the historical data is also different according to the specific type of the current time. If the current time is the current time acquired by the system, the selection node of the historical data is the data of any node before the display time of the current system; if the current time is the time determined by the instruction, the selected node of the history data is data of any node before or after the determined time.

The preset partition rule in step S03 may be a time-sharing node according to the current time, or may be an occupied space according to the current data, or may be a shop or a commodity in the target to be analyzed, to sum up, the partition rule is not necessarily only for information included in the current data, but also may be information included in the current time or the target to be analyzed, and this embodiment is not limited specifically.

Step S04, comparing each of the divided operation data with corresponding historical data, where the correspondence refers to comparing each of the operation data with the same historical data of the shop or the commodity according to a preset division rule corresponding to each of the operation data, for example, the preset division rule is according to the shop or the commodity in the target to be analyzed, and obtaining a difference between the operation data and the historical data based on a data difference algorithm or other comparison algorithms to obtain difference data.

The marking rule in step S05 may be similar to a preset dividing rule, for example, if the dividing rule is based on a store or a commodity in the target to be analyzed and includes multiple stores or commodities, the marking rule may mark the difference data according to a single store or a single commodity; for another example, if the partition rule is a time-sharing node according to the current time and includes a plurality of time-sharing nodes, the marking rule may mark the difference data according to each time-sharing node.

The operation log for updating the target to be analyzed in step S06 may be the operation log already existing before the target to be analyzed, or the target to be analyzed that has not generated the operation log before, and a brand new operation log is generated at this time as the update of the log content. That is, the updating here does not limit the operation log existing in the past in the narrow sense of updating, but also includes updating the log type of the object to be analyzed in the broad sense, so that the log type is updated to the log type also including the operation log, and the updated content here is added to the original log, and the category is the operation log.

In practical application, the e-commerce operation log management and control method generates or updates the operation log, and is suitable for various application scenarios.

For example, real-time monitoring of daily operational actions and data changes in a store, including: the marketing optimization, the sales state, the advertisement adjustment, the commodity ranking and the comment and the like are timely, accurate and comprehensive, and the operation is helped to quickly master the sales dynamics.

For example, the logs are recorded in batches in the corresponding log module, and the operation logs can be recorded quickly in time when a plurality of pages such as home sales dynamics, commodity management, commodity performance and the like are subjected to operation analysis, so that a habit of recording in real time is developed.

For example, the operation log is checked in combination with the sales data, the operation is assisted to carry out operation backtracking, the whole operation thinking is formed, the most effective and most suitable legal strategies are summarized, the operation manager can be assisted to guide the sales actions of the operators, and the operation management efficiency is effectively improved.

According to the e-commerce operation log control method provided by the embodiment, the preset division rule is adopted, the difference data obtained after the current data and the historical data of the target to be analyzed are divided are compared, the marking is carried out according to the marking rule, the updating data used for updating the operation log of the target to be analyzed is formed, the automatic updating and the marking of the corresponding content are achieved, the recording and management workload of the operation log can be reduced, the operation management efficiency is effectively improved, and the problems that the work repeatability is high and the workload is large in the traditional log recording mode are solved.

In one implementation manner of this embodiment, as shown in fig. 2, the step S04 of comparing each operation data with corresponding history data, and acquiring difference data includes:

s11, selecting one of the operation data as current comparison data;

s12, acquiring category information of current comparison data;

s13, acquiring historical data corresponding to the type information as current historical data;

s14, comparing the current comparison data with the current historical data, and taking the difference between the current comparison data and the current historical data as difference subdata corresponding to the current category information;

s15, selecting another operation data as the current comparison data to circulate the steps until the preset comparison requirement is met;

and S16, integrating the difference subdata to generate difference data.

In practical applications, since the current data is divided into a plurality of operation data according to the preset division rule in step S03, one of the operation data is selected as the current comparison data in step S11 and the category information thereof is obtained in step S12, where the category information may correspond to the preset division rule, for example, the division rule is according to a store or a commodity in the target to be analyzed and includes a plurality of stores or commodities, and the category information is the category information of the corresponding store or commodity. Of course, such category information may not correspond to the preset partition rule, for example, the type of change of the numerical value is increased, decreased or unchanged, and the specific manner is not described herein again.

Step S13 obtains current historical data corresponding to the type information of the operation data, compares the current historical data with the current comparison data in step S14, and uses the difference between the current historical data and the current comparison data as the difference subdata corresponding to the category information, and step S15 repeats the above steps for another operation data which is not used as the current comparison data until the preset comparison requirement is met.

It should be noted that the preset comparison requirement may be set or selected according to actual needs, for example, all the operation data are compared completely, or only certain type information is compared, or the comparison is not performed after a predetermined number is reached, and the specific selection and the corresponding steps are not described in detail herein.

In addition, how to judge whether each operation data is used as the current comparison data may also be performed in different ways, in this embodiment, the relevant flag of the operation data that has been used as the current comparison data is assigned to 1, and the relevant flag of the operation data that has not been used as the current comparison data is assigned to 0. Of course, other approaches are possible and will not be described again here.

And after the preset comparison requirement is met, ending the loop and entering step S16, and integrating the obtained difference subdata to generate the required difference data.

It should be understood that specific types and sources of various data may be selected from various types and quantities according to needs, in this embodiment, an interface or a report in the ERP system synchronous e-commerce platform system or e-commerce API may be used to capture or obtain various types of data from the interface or the report, or other data in the ERP system may be combined.

For example, the synchronous commodity report captures the commodity state, the distribution channel and the original price; a synchronous commodity price interface captures a distribution channel, a discount price and an original price; the synchronous commodity feature interface captures commodity features, commodity descriptions and keywords; the synchronous commodity attribute interface captures commodity pictures, commodity titles, variants and commodity ranks; a synchronous review interface, namely a shop feedback interface, captures newly added shop feedback numbers, shop feedback poor evaluation information and commodity grading information; a synchronous feedback interface, namely a product comment interface, captures the number of newly added product comments, product comment deletion and poor product comment information; the seller operates ERP to adjust key information; manual entry by the seller, etc.

According to the technical scheme, the category information is adopted to compare the operation data with the corresponding current historical data, the difference between the operation data and the corresponding current historical data is used as the difference subdata, each difference subdata is obtained in a circulating mode and is integrated to generate the difference data, the difference data comprises the category information, and the difference data forms the operation log, so that the data corresponding to the category in the category information in the operation log can be inquired according to the category information, the on-demand inquiry is achieved, and the management efficiency of the operation log is improved.

In one implementation manner of this embodiment, as shown in fig. 3, the step S04 of comparing each operation data with the corresponding historical data, and acquiring difference data includes:

s21, acquiring data blank rows in each operation data;

s22, replacing the data blank line with a placeholder to form processed operation data;

and S23, comparing each processed operation data with corresponding historical data to obtain difference data.

In practical use, different comparison modes can be selected when the operation data and the corresponding historical data are compared, for example, in this embodiment, character comparison is adopted, that is, the operation data and the historical data are compared on each character, a comparison result is formed according to a difference on the character, and then the difference data is formed by combining with a preset processing rule of the comparison result.

In the specific comparison by using character comparison, when the operation data has multiple lines of data, which may include a data blank line and cannot be effectively compared with the historical data, corresponding processing needs to be performed on the data blank line, in this embodiment, a manner of acquiring the data blank line in step S21 first and then replacing the data blank line with a placeholder in step S22 is adopted, so that each operation data is processed to form the processed operation data obtained in step S22, and then step S23 is performed to acquire difference data.

It should be noted that the data blank line in the history data may also be acquired separately or simultaneously, and the data blank line is also replaced by a placeholder to perform similar processing, and the time node of the processing may also be selected according to actual needs. In this embodiment, after the data blank line of the history data is acquired, corresponding processing is performed in the background, and specific steps are not described again here.

Through the technical scheme, the blank data rows are replaced by the placeholders, and the problem that the difference data acquisition is wrong or fails due to the fact that the blank data rows are difficult to carry out effective data comparison is solved.

In one implementation manner of this embodiment, as shown in fig. 4, the step S05 of marking each difference data in the history data according to the marking rule to form the update data includes:

s31, judging the difference type of each difference data;

s32, if the difference type is the newly added type, marking corresponding difference data in the historical data by adopting a first mark to form first updating data;

s33, if the difference type is a deletion type, marking corresponding difference data by adopting a second mark in the historical data to form second updating data;

s34, if the difference type is the change type, marking the content before change in the corresponding difference data by adopting a second mark in the historical data, and marking the content after change in the corresponding difference data by adopting a first mark in the historical data to form third updated data;

and S35, integrating the first updating data, the second updating data and the third updating data to form updating data.

In practical application, various labeling types may be adopted, or different difference types may be set, where the difference types in this embodiment are three difference types of adding, deleting, and changing content, and the first mark is a green mark, and the second mark is a red-underlined mark.

Therefore, according to the above setting, it is first determined in step S31 whether the specific difference data of each difference data is of any of the three difference types of the new content, the deleted content and the modified content, and the following labeling step is selected according to actual situations, which includes the following three cases corresponding to step S32 to step S34, respectively:

if the difference type is the newly added type, marking corresponding difference data by adopting a first mark, namely a green mark, in the historical data to form first updating data;

if the difference type is a deletion type, marking corresponding difference data by adopting a second mark, namely a red marking line mark, in the historical data to form second updating data;

and if the difference type is the change type, marking the content before change in the corresponding difference data by adopting a second mark, namely a red marking line mark, in the historical data, and marking the content after change in the corresponding difference data by adopting a first mark, namely a green mark, in the historical data to form third updating data.

In addition, other auxiliary marks may also be combined, for example, in a mark corresponding to the modification type, besides the aforementioned mark, an arrow may also be used as an auxiliary mark to point to the corresponding content before and/or after the modification.

According to the technical scheme, the different types are marked by different marks according to the difference types of the difference data to form corresponding update data, and then the update data are integrated to form the update data, so that the effect of accurately and visually comparing the front and back changes of the target to be analyzed is achieved.

In one implementation manner of this embodiment, as shown in fig. 5, after the step S03 of dividing the current data into a plurality of pieces of operation data according to the preset dividing rule, the method further includes:

s41, acquiring additional recording data;

s42, dividing the additional recording data into a plurality of additional recording subdata according to a preset division rule;

and S43, combining each additional entry subdata with the corresponding operation data so as to form each updated operation data.

In actual use, the operation log can select or display various changes of the analysis target as needed, so that the operation log also has diversified functions, and can play a role in reference to management and sales of stores or merchants. When the operation log is displayed or counted, some data which cannot be directly compared, for example, other data different from the current data type is not included, and the data are not included in the historical data, but the data can be reflected from the side or prove the reason of the commodity sales change, such as the change trend of local recent fixed population and floating population, and the data can be used as supplementary data to be combined with the operation data to form each updated operation data.

Of course, the acquisition mode of the additional data may be direct manual entry, or entry by a custom log type, or splitting and importing the form data, or directly inserting the database format data into the database or the data table of the operation data according to the matching rule, and may also adopt a mode that the log content supports rich text format entry and supports uploading picture record, which is not described herein again.

According to the technical scheme, the acquired additional recording data are divided according to the preset division rule and then combined with the corresponding operation data, so that the manual entry or the import of other records can be supported besides the automatic generation of the operation logs, and the generation mode of the operation logs of various types is supported.

In one implementation manner in this embodiment, as shown in fig. 6, before the step S01, that is, before acquiring the current data of the target to be analyzed, the method further includes:

s51, acquiring an interactive instruction;

s52, acquiring a target type to be analyzed according to the interactive instruction;

and S53, filtering all analysis targets according to the target types to form the target to be analyzed.

In practical applications, in order to achieve different analysis purposes through the operation log, the target to be analyzed corresponding to the operation log itself may also be selected in advance, in this embodiment, a human-computer interaction manner is adopted in step S51 to obtain an interaction instruction including a target type, and step S52 obtains the target type therein, so that all the analysis targets are filtered in step S53 to obtain the target to be analyzed according with the target type. For example, if the required operation log only includes commodity a, the target type in the interactive instruction is commodity a, and the specific setting is not described here again.

According to the technical scheme, the target type to be analyzed is obtained from the interactive instruction, so that the required target to be analyzed is obtained from all the analysis targets, and the target corresponding to the operation log can be generated as required.

In one implementation manner in this embodiment, as shown in fig. 7, after the step S06, that is, according to the update data, updating the operation log of the target to be analyzed, the method further includes:

s61, acquiring the current display resolution;

s62, acquiring a preset display specification of the operation log;

s63, processing a loading window of the operation log according to the proportion of the preset display specification and the current display resolution;

and S64, loading and displaying the operation log in the processed loading window.

In practical application, because the display resolution of the terminal equipment is different, in order to achieve an effective display effect, the user experience is improved. When the operation log is generated and sent to the terminal device, the current display resolution of the terminal device needs to be acquired first, and the operation log is displayed after the loading window is correspondingly processed by combining the ratio of the current display resolution to the preset display specification of the operation log.

For example, if the current resolution of the terminal is 1920 and the preset display specification of the operation log is 800, the ratio between the two is 1920/800, and at this time, two modes can be selected for processing.

The first is to obtain a specific value 2.4 of the ratio of the two, and then to enlarge the display of the operation log by 2.4 times in the loading window, and the second is to pre-store the processing modes of each display resolution because the display resolution of the existing terminal is limited, that is, the 1920/800 ratio is directly matched with the pre-stored ratio display table, and after the corresponding processing mode is obtained, the display of the loading window or the operation log is processed, and the specific selection and processing steps are not described herein again.

It should be noted that other performance optimizations may also be performed on the window display, for example, a virtual scrolling technique is used for the display list to prevent multiple pages from being stuck at one time when the elements are loaded, and for example, a floating window singleton mode is adopted, only one floating window is generated globally, and the floating window data is switched by moving to the content area, so as to ensure smooth pages.

According to the technical scheme, the loading window of the operation log is processed according to the proportion of the preset display specification and the current display resolution, so that the content is ensured to be displayed in the visible area all the time.

In one implementation manner in this embodiment, as shown in fig. 8, after updating the operation log of the target to be analyzed according to the update data in step S06, the method further includes:

s71, acquiring a preset attention label;

s72, obtaining the attention type to be displayed according to the attention label;

and S73, filtering all the operation logs according to the attention categories to form operation log display contents.

In an actual application, after the operation log is generated, the required display content may also be selected as needed, in this embodiment, a manner of setting an attention tag in advance is adopted, the attention tag includes an attention category that is a category corresponding to the required display content, and the operation log that has been updated and formed is filtered according to the attention category, so that only the relevant content corresponding to the attention category is displayed, and the effect of displaying as needed is achieved.

For example, the preset attention tag is an a tag, and the corresponding attention categories in the a tag are the monthly average sales volume of the product X, the product Y and the store Z, so that only the relevant contents matched with the monthly average sales volume of the product X, the product Y and the store Z in the operation log can be displayed through the a tag during displaying.

According to the technical scheme, the preset attention label is adopted, and the final display content is the operation log content corresponding to the attention category according to the attention category, namely the effect of display on demand is achieved.

In one implementation manner in this embodiment, as shown in fig. 9, after the step S06, updating the operation log of the target to be analyzed according to the update data, the method further includes:

s81, acquiring all dimension types contained in the operation log;

s82, acquiring a current dimension statistical rule;

s83, distinguishing and counting the operation logs according to dimension types according to dimension counting rules;

and S84, generating dimension statistical data corresponding to each dimension type based on the operation logs subjected to the distinguishing statistics.

In actual application, statistics can be performed according to different dimensions according to needs, that is, the operation logs are subjected to distinguishing statistics according to the dimension types and the dimension statistical rules, so that dimension statistical data corresponding to each dimension type are generated.

In this embodiment, the MSKU dimension is counted according to the shop differentiation, the AISN dimension is counted according to the country differentiation, and the parent ASIN dimension is counted according to the country differentiation, where the operation logs recorded by the ASIN and the parent ASIN dimension synchronously record the operation logs of MSKU belonging to the site of the country.

According to the technical scheme, the operation logs are distinguished and counted according to the dimension counting rule, so that dimension counting data corresponding to each dimension type are generated, and the operation logs are counted according to different dimensions.

In one implementation manner of this embodiment, as shown in fig. 10, the step S02 of acquiring the historical data of the target to be analyzed includes:

s91, acquiring current time;

s92, acquiring a time difference value between the current time and the last acquired current time;

s93, judging whether the time difference is greater than a preset period or not;

s94, if the time difference is larger than or equal to the preset period, copying corresponding data of the target to be analyzed before the current time as historical data;

and S95, if the time difference is smaller than the preset period, returning to obtain the current time again and repeating the steps.

In practical application, in order to avoid data congestion or excessive resource occupation which may be caused by frequent acquisition of historical data, an on-demand acquisition mode may be adopted.

Of course, the time length or the time frequency of the preset period can be selected according to actual needs, and in this embodiment, a plurality of timing tasks are adopted to synchronize corresponding information hourly, so that the change of the key information of the commodity is effectively acquired.

According to the technical scheme, a preset period mode is adopted, the time difference value of the current time obtained in the last two times is compared with the preset period, corresponding data before the current time is determined to be copied as historical data based on the comparison result, and therefore the effect of periodically obtaining the historical data is achieved, the historical data is copied original data, and the original data cannot be affected.

It is further noted that, herein, relational terms such as first and second, and the like may be used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Also, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrases "comprising a," "8230," "8230," or "comprising" does not exclude the presence of additional like elements in a process, method, article, or apparatus that comprises the element.

It should be understood that, although the steps in the flowcharts of the figures are shown in order as indicated by the arrows, the steps are not necessarily performed in order as indicated by the arrows. The steps are not performed in the exact order shown and may be performed in other orders unless explicitly stated herein. Moreover, at least a portion of the steps in the flow chart of the figure may include multiple sub-steps or multiple stages, which are not necessarily performed at the same time, but may be performed at different times, which are not necessarily performed in sequence, but may be performed alternately or alternately with other steps or at least a portion of the sub-steps or stages of other steps.

The previous description of the disclosed embodiments is provided to enable any person skilled in the art to make or use the present application. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the generic principles defined herein may be applied to other embodiments without departing from the spirit or scope of the application. Thus, the present application is not intended to be limited to the embodiments shown herein but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.

Claims (10)

1. A method for managing and controlling an e-commerce operation log is characterized by comprising the following steps:

acquiring current data of a target to be analyzed;

acquiring historical data of the target to be analyzed;

dividing the current data into a plurality of operation data according to a preset division rule;

comparing each operation data with the corresponding historical data to obtain difference data;

according to a marking rule, marking each difference data in the historical data to form updated data;

and updating the operation log of the target to be analyzed according to the updating data.

2. The e-commerce operation log control method of claim 1, wherein the comparing each operation data with the corresponding historical data to obtain difference data comprises:

selecting one of the operation data as current comparison data;

acquiring category information of the current comparison data;

acquiring the historical data corresponding to the type information as current historical data;

comparing the current comparison data with the current historical data, and taking the difference between the current comparison data and the current historical data as difference subdata corresponding to the current category information;

selecting another operation data as the current comparison data to circulate the steps until a preset comparison requirement is met;

and integrating the difference sub-data to generate the difference data.

3. The e-commerce operation log control method of claim 2, wherein the comparing each operation data with the corresponding historical data to obtain difference data comprises:

acquiring a data blank line in each operation data;

replacing the data empty line with a placeholder to form the processed operation data;

and comparing each processed operation data with the corresponding historical data to obtain the difference data.

4. The e-commerce operation log management and control method according to claim 1, wherein the marking each difference data in the history data according to a marking rule to form update data comprises:

judging the difference type of each difference data;

if the difference type is a new type, marking corresponding difference data in the historical data by adopting a first mark to form first updating data;

if the difference type is a deletion type, marking corresponding difference data in the historical data by adopting a second mark to form second updating data;

if the difference type is a change type, marking the corresponding content before change in the difference data by using the second mark in the historical data, and marking the corresponding content after change in the difference data by using the first mark in the historical data to form third updated data;

and integrating the first updating data, the second updating data and the third updating data to form the updating data.

5. The e-commerce operation log management and control method according to claim 1, wherein after the dividing the current data into a plurality of operation data according to a preset dividing rule, the method further comprises:

acquiring additional recording data;

dividing the additional recording data into a plurality of additional recording subdata according to the preset division rule;

and combining each additional entry sub-data with the corresponding operation data so as to form each updated operation data.

6. The e-commerce operation log management and control method according to claim 1, further comprising, before the obtaining current data of a target to be analyzed:

acquiring an interactive instruction;

acquiring a target type to be analyzed according to the interactive instruction;

and filtering all analysis targets according to the target types to form the target to be analyzed.

7. The e-commerce operation log management and control method according to claim 1, wherein after the updating of the operation log of the target to be analyzed according to the update data, the method further comprises:

acquiring the current display resolution;

acquiring a preset display specification of the operation log;

processing a loading window of the operation log according to the proportion of the preset display specification and the current display resolution;

and loading and displaying the operation log in the processed loading window.

8. The e-commerce operation log management and control method according to claim 1, further comprising, after the updating the operation log of the target to be analyzed according to the update data:

acquiring a preset attention label;

acquiring an attention category to be displayed according to the attention label;

and filtering all the operation logs according to the attention categories to form operation log display contents.

9. The e-commerce operation log management and control method according to claim 1, further comprising, after the updating the operation log of the target to be analyzed according to the update data:

acquiring all dimension types contained in the operation log;

acquiring a current dimension statistical rule;

according to the dimension statistical rule, the operation logs are subjected to distinguishing statistics according to the dimension types;

and generating dimension statistical data corresponding to each dimension type based on each operation log after distinguishing statistics.

10. The e-commerce operation log management and control method according to claim 1, wherein the obtaining of the historical data of the target to be analyzed includes:

acquiring current time;

acquiring a time difference value between the current time and the last acquired current time;

judging whether the time difference is greater than a preset period or not;

if the time difference is larger than or equal to the preset period, copying corresponding data of the target to be analyzed before the current time as the historical data;

and if the time difference is smaller than the preset period, returning to obtain the current time again and repeating the steps.

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