CN111859285B

CN111859285B - Method and device for supplementing sales missing data

Info

Publication number: CN111859285B
Application number: CN202010535676.6A
Authority: CN
Inventors: 王秋文; 李百川; 苏伟鹏
Original assignee: Youmi Technology Co ltd
Current assignee: Youmi Technology Co ltd
Priority date: 2020-06-12
Filing date: 2020-06-12
Publication date: 2023-06-27
Anticipated expiration: 2040-06-12
Also published as: CN111859285A

Abstract

The invention discloses a method and a device for supplementing sales missing data, comprising the following steps: acquiring sales data of a certain target commodity at each target moment of a certain target time period from the starting moment of the certain target time period at intervals of the target time period; judging whether empty data time when sales volume data is empty exists in all target time according to the acquired sales volume data of all target time; when judging that at least one empty data moment exists in all the target moments, supplementing sales volume data of each empty data moment; the sales volume data of each target moment is used for calculating sales contribution values brought by each commodity video in all commodity videos of the target commodity in the target time period. Therefore, the invention can supplement the missing sales volume data, is beneficial to acquiring more comprehensive sales volume data, and is further beneficial to accurately calculating the sales contribution value of each commodity-carrying video to the commodity.

Description

Method and device for supplementing sales missing data

Technical Field

The invention relates to the technical field of Internet, in particular to a method and a device for supplementing sales missing data.

Background

With the rapid development of the internet, internet users are increasing. In order to expand the audience range and influence of commodities, the marketing mode of commodities introduces video marketing based on internet besides traditional advertising marketing, for example: the advertiser can select a plurality of video bloggers to introduce and display commodities in a video recording or video live broadcasting mode, so that more people can be attracted to purchase the commodities, wherein videos which are released by the video bloggers and used for introducing and displaying the commodities can be also called as goods-carrying videos.

In practical application, for the same commodity, there are usually multiple video with goods distributed by multiple video bloggers, and the styles of the video with goods distributed by different video bloggers are various, and the sales contribution of the video with goods distributed by each video blogger is different. In order to gradually increase the cost performance of commodity video marketing, the commodity video with higher sales contribution to commodities needs to be determined from the commodity videos of the video bloggers, that is, the sales contribution value of each commodity video to commodities needs to be accurately determined. When calculating the sales contribution value of each video with goods to goods, corresponding sales data are required to be used, if the acquired sales data are missing, the sales contribution value of each video with goods to goods cannot be calculated or the calculated sales contribution value of each video with goods to goods is low in accuracy.

Disclosure of Invention

The invention aims to solve the technical problem of providing a method and a device for supplementing missing sales data, which can supplement the missing data, are beneficial to acquiring relatively comprehensive sales data, and are further beneficial to accurately calculating sales contribution values of each video with goods to goods.

In order to solve the technical problem, the first aspect of the present invention discloses a method for supplementing sales missing data, the method comprising:

acquiring sales data of a certain target commodity at each target moment of a certain target time period from the starting moment of the certain target time period at intervals of the target time period;

judging whether empty data time when sales volume data are empty exists in all the target time according to the acquired sales volume data of all the target time;

supplementing sales volume data of each empty data moment when judging that at least one empty data moment exists in all the target moments;

the sales volume data of each target moment is used for calculating sales contribution values of all the carried videos of the target commodity in the target time period, wherein the sales contribution values are brought by each carried video of the target commodity for the target commodity.

As an optional implementation manner, in the first aspect of the present invention, before the supplementing sales volume data at each empty data time, the method further includes:

determining all first-type null data time instants from all the null data time instants, wherein the first-type null data time instants are not adjacent to any null data time instant except the first-type null data time instant; or alternatively, the process may be performed,

determining all second-class null data moments from all the null data moments, wherein the second-class null data moments are adjacent to at least one null data moment except the second-class null data moment;

wherein said supplementing sales volume data for each of said null data moments comprises:

and supplementing sales data of each empty data moment according to a data supplementing mode matched with the category of each empty data moment.

In a first aspect of the present invention, the supplementing the sales data of each empty data time according to the data supplementing method matched with the category of each empty data time includes:

for any first type of null data time, sequentially acquiring first sales volume data of each of a first preset number of preceding non-null data time before the first type of null data time and second sales volume data of each of a second preset number of following non-null data time after the first type of null data time from all target time according to the sequence of short and long time lengths from the first type of null data time;

And supplementing sales volume data of the first type of null data moment according to the first sales volume data of each preceding non-null data moment and the second sales volume data of each following non-null data moment.

As an alternative embodiment, in the first aspect of the present invention, the first preset number is equal to 1, and the second preset number is equal to 1;

wherein the supplementing sales volume data of the first type of empty data time according to the first sales volume data of each preceding non-empty data time and the second sales volume data of each following non-empty data time comprises:

calculating the average value of the second sales volume data at the later non-empty data moment and the first sales volume data at the earlier non-empty data moment;

when the average value is an integer, supplementing sales volume data of the first type of empty data moment to the average value;

and when the average value is a non-integer, supplementing sales volume data of the first type of empty data time to be an upward rounding value or a downward rounding value of the average value.

Dividing all second-class empty data time instants into a plurality of time instant sets, wherein any two second-class empty data time instants included in the same time instant set are directly adjacent or indirectly adjacent through at least one second-class empty data time instant, and any two second-class empty data time instants in different time instant sets are not directly adjacent and are not indirectly adjacent through the second-class empty data time instant;

for any time set, determining a target number of sub-time periods included in the time set, a minimum second-class empty data time and a maximum second-class empty data time in the time set, and acquiring first sales volume data of a preceding non-empty data time closest to the minimum second-class empty data time and second sales volume data of a following non-empty data time closest to the maximum second-class empty data time from all the target times, wherein the target number is equal to the number of second-class empty data times included in the time set plus 1;

calculating a difference value between the second sales volume data and the first sales volume data, and supplementing sales volume data of each second class of empty data moment included in the moment set according to the second sales volume data, the first sales volume data, the target quantity and the difference value;

The sub-time period included in the time set is composed of a sub-time period formed by all directly adjacent two second-class empty data time instants in the time set, a sub-time period formed by the preceding non-empty data time instant and the minimum second-class empty data time instant, and a sub-time period formed by the following non-empty data time instant and the maximum second-class empty data time instant.

As an optional implementation manner, in the first aspect of the present invention, the supplementing sales volume data of each second type of empty data time included in the time set according to the second sales volume data, the first sales volume data, the target number, and the difference value includes:

determining sales volume increment of each sub-time period included in the time set according to the result of dividing the difference value by the target quantity;

and supplementing sales volume data of each second class of empty data moment included in the moment set according to the second sales volume data, the first sales volume data and sales volume increment of each sub-time period included in the moment set.

Dividing the determined mother time set into a front time set and a rear time set corresponding to the mother time set according to a dichotomy, calculating the sales volume increment of the front time set and the sales volume increment of the rear time set corresponding to the mother time set according to the sales volume increment of the mother time set and the allocation proportion corresponding to the mother time set, caching the sales volume increment of the sub-time set of which the number of sub-time periods included in the front time set and the rear time set corresponding to the mother time set meets the preset number condition, and judging whether the sub-time set of which the number of sub-time periods included in the front time set and the rear time set corresponding to the mother time set does not meet the preset number condition exists or not;

when the judgment result is negative, supplementing sales volume data of each second type of empty data moment included in the moment set according to the second sales volume data, the first sales volume data and the sales volume increment of all cached time sets, wherein the number of the time periods included in the second sales volume data meets the preset number condition;

when the judgment result is yes, determining a sub-time set, which is corresponding to the mother time set and is included in the back time set, of sub-time periods not meeting the preset number condition as a new mother time set, repeatedly executing the operation of dividing the determined mother time set into the front time set and the back time set corresponding to the mother time set according to a bisection method, calculating the sales volume increment of the front time set and the sales volume increment of the back time set corresponding to the mother time set according to the sales volume increment of the mother time set and the allocation proportion corresponding to the mother time set, caching the sales volume increment of the sub-time set, which is included in the front time set and the back time set corresponding to the mother time set, of the sub-time set, and judging whether the sub-time set, which is not meeting the preset number condition, exists in the front time set and the back time set corresponding to the mother time set;

The initial determined mother time set is the time set, and the sales volume increment of the time set is equal to the difference value.

performing data fitting operation on sales volume data of all non-empty data moments of all the target moments except all the empty data moments to obtain a sales volume curve corresponding to the target time period, wherein the sales volume curve is used for representing the corresponding relation between the moments and the sales volume data in the target time period;

substituting each empty data moment into the sales volume curve in turn to obtain sales volume data of each empty data moment.

The second aspect of the invention discloses a supplementing device for sales missing data, the device comprising:

the acquisition module is used for acquiring sales data of a certain target commodity at each target moment of a certain target interval duration from the starting moment of a certain target time period;

The judging module is used for judging whether empty data time when the sales volume data are empty exists in all the target time according to the acquired sales volume data of all the target time;

the supplementing module is used for supplementing sales data of each empty data moment when the judging module judges that at least one empty data moment exists in all the target moments;

As an alternative embodiment, in the second aspect of the present invention, the apparatus further includes:

a determining module, configured to determine all first type of null data time instants from all the null data time instants after the determining module determines that at least one null data time instant exists in all the target time instants, and before the supplementing module supplements sales data of each null data time instant, where the first type of null data time instants are not adjacent to any null data time instant except the first type of null data time instant; or determining all second-type null data moments from all the null data moments, wherein the second-type null data moments are adjacent to at least one null data moment except the second-type null data moment;

The specific way of supplementing sales data at each empty data moment by the supplementing module is as follows:

In a second aspect of the present invention, as an optional implementation manner, the supplementing module supplements sales data of each empty data moment according to a data supplementing manner matched with a category of each empty data moment, which is specifically:

As an alternative embodiment, in the second aspect of the present invention, the first preset number is equal to 1, and the second preset number is equal to 1;

the specific way of the supplementing module supplementing the sales volume data of the first type of empty data moment according to the first sales volume data of each preceding non-empty data moment and the second sales volume data of each following non-empty data moment is as follows:

As an optional implementation manner, in the second aspect of the present invention, the supplementing module supplements sales volume data of each second type of empty data time included in the time set according to the second sales volume data, the first sales volume data, the target number and the difference value in a specific manner:

the data fitting module is used for executing data fitting operation on sales volume data of all non-empty data moments except all empty data moments in all target moments after the judging module judges that at least one empty data moment exists in all target moments and before the supplementing module supplements sales volume data of each empty data moment, so as to obtain a sales volume curve corresponding to the target time period, wherein the sales volume curve is used for representing the correspondence between the moments and the sales volume data in the target time period;

In a third aspect, the invention discloses another sales volume missing data supplementing device, which comprises:

A memory storing executable program code;

a processor coupled to the memory;

the processor invokes the executable program code stored in the memory to perform some or all of the steps in the method for supplementing sales volume missing data disclosed in the first aspect of the present invention.

A fourth aspect of the invention discloses a computer storage medium storing computer instructions that, when invoked, are adapted to perform part or all of the steps of the method of supplementing sales volume missing data disclosed in the first aspect of the invention.

Compared with the prior art, the embodiment of the invention has the following beneficial effects:

in the embodiment of the invention, sales data of a certain target commodity at each target moment of time interval from the starting moment of a certain target time period are acquired; judging whether empty data time when sales volume data is empty exists in all target time according to the acquired sales volume data of all target time; when judging that at least one empty data moment exists in all the target moments, supplementing sales volume data of each empty data moment; the sales volume data of each target moment is used for calculating sales contribution values brought by each commodity video in all commodity videos of the target commodity in the target time period. Therefore, the invention can supplement the missing sales volume data, is beneficial to acquiring more comprehensive sales volume data, and is further beneficial to accurately calculating the sales contribution value of each video with goods to the goods.

Drawings

In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings required for the description of the embodiments will be briefly described below, and it is apparent that the drawings in the following description are only some embodiments of the present invention, and other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.

FIG. 1 is a schematic flow chart of a method for supplementing sales missing data according to an embodiment of the present invention;

FIG. 2 is a flow chart of another method for supplementing sales missing data according to an embodiment of the present invention;

FIG. 3 is a schematic structural diagram of a device for supplementing sales missing data according to an embodiment of the present invention;

FIG. 4 is a schematic diagram of another exemplary sales volume missing data supplementing device according to an embodiment of the present invention;

FIG. 5 is a schematic diagram of a device for supplementing sales missing data according to an embodiment of the present invention;

fig. 6 is a schematic structural diagram of a compensation device for sales missing data according to an embodiment of the present invention.

Detailed Description

In order that those skilled in the art will better understand the present invention, a technical solution in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in which it is apparent that the described embodiments are only some embodiments of the present invention, not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.

The terms first, second and the like in the description and in the claims and in the above-described figures are used for distinguishing between different objects and not necessarily for describing a sequential or chronological order. Furthermore, the terms "comprise" and "have," as well as any variations thereof, are intended to cover a non-exclusive inclusion. For example, a process, method, apparatus, article, or article that comprises a list of steps or elements is not limited to only those listed but may optionally include other steps or elements not listed or inherent to such process, method, article, or article.

Reference herein to "an embodiment" means that a particular feature, structure, or characteristic described in connection with the embodiment may be included in at least one embodiment of the invention. The appearances of such phrases in various places in the specification are not necessarily all referring to the same embodiment, nor are separate or alternative embodiments mutually exclusive of other embodiments. Those of skill in the art will explicitly and implicitly appreciate that the embodiments described herein may be combined with other embodiments.

The invention discloses a method and a device for supplementing missing sales volume data, which can supplement the missing sales volume data, are favorable for acquiring relatively comprehensive sales volume data, and are further favorable for accurately calculating sales contribution values of each video with goods to goods. The following will describe in detail.

Example 1

Referring to fig. 1, fig. 1 is a flow chart of a method for supplementing sales missing data according to an embodiment of the invention. The method described in fig. 1 may be applied to a data supplementing device, such as a server, and the embodiment of the invention is not limited. As shown in fig. 1, the supplementing method of the sales missing data may include the following operations:

101. the data supplementing device acquires sales data of a certain target commodity at each target time of every target interval duration from the starting time of a certain target time period.

The certain target time period is any time period selected by the related personnel, and the certain target commodity is any commodity selected by the related personnel. Alternatively, sales volume data for each target time may be obtained by web crawler technology.

102. The data supplementing device judges whether empty data time when the sales volume data is empty exists in all the target time according to the acquired sales volume data of all the target time.

In the embodiment of the present invention, when the determination result in step 102 is yes, step 103 is triggered and executed; when the result of the step 102 is no, the process may be ended, that is, the sales volume data of each target moment is comprehensively obtained through related technical means (such as web crawler technology), without performing data supplementation.

103. When it is judged that at least one empty data time exists among all the target times, the data supplementing means supplements sales volume data of each empty data time.

In the embodiment of the invention, the sales volume data of each target moment is used for calculating the sales contribution value of each video with goods for the target goods in all videos with goods of the target goods in the target time period.

In the embodiment of the present invention, taking the target time period of 09:00-09:10 and the target interval duration of 1min as an example for illustration, if sales volume data of target time 09:02, target time 09:04, target time 09:05, target time 09:06, target time 09:07, target time 09:08, and target time 09:09 are not obtained, these times are all referred to as empty data times, and when it is determined that at least one empty data time exists in all the target times, the data supplementing device needs to supplement corresponding sales volume data for these empty data times first, and then perform subsequent calculation operations.

Therefore, by implementing the method described by the embodiment of the invention, whether the target moment has empty data moment or not can be judged before the sales contribution value of each goods-carrying video for the target goods in the target time period is calculated, and if the empty data moment exists, the sales volume data of the empty data moment needs to be supplemented, so that the method is beneficial to acquiring more comprehensive sales volume data, and further is beneficial to accurately calculating the sales contribution value of each goods-carrying video for the goods.

In an alternative embodiment, after determining that at least one null data time exists among all the target time instants, and before the data supplementing device supplements sales volume data of each null data time instant, the method may further include the operations of:

the data supplementing device performs data fitting operation on sales volume data of all non-empty data moments of all target moments except all empty data moments, and obtains a sales volume curve corresponding to the target time period, wherein the sales volume curve is used for representing the corresponding relation between the moments and the sales volume data in the target time period.

Wherein in this alternative embodiment, the data supplementing means supplements sales data at each empty data time, may include:

the data supplementing device substitutes each empty data moment into the sales volume curve in turn to obtain sales volume data of each empty data moment.

Therefore, the alternative embodiment can also supplement sales volume data at each empty data moment in a curve fitting mode, and is beneficial to improving the matching degree of the supplemented sales volume data and the sales volume increasing trend.

In practical application, the sales contribution value brought by each of all the shipment videos of the target commodity in the target time period can be calculated by the shipment effect determining device, and the specific flow is as follows:

Acquiring target data corresponding to all the cargo video of the target commodity in the target time period by a cargo effect determining device;

calculating an allocation weight value of each cargo video according to the target data corresponding to each cargo video by the cargo effect determining device;

and calculating a sales contribution value of each video with goods for the target goods in the target time period according to the allocation weight value of each video with goods, the sum of the allocation weight values of all the videos with goods and the acquired sales data of the target goods at each target moment in the target time period by the goods effect determining device.

The target data corresponding to the video with goods comprise data which has an association relation with the sales volume of the target commodity in all data corresponding to the video with goods. Further, the target data corresponding to the video with goods comprise data which have an association relation with the sales amount of the target commodity and influence degree of the sales amount of the target commodity on the target commodity is larger than or equal to a preset degree threshold value, so that the accuracy and the efficiency of the allocation weight value of the video with goods calculated according to the target data of the video with goods can be improved.

Optionally, the target data corresponding to the video with goods may include at least one of vermicelli data of a video blogger of the video with goods, cumulative viewing amount of the video with goods in the target time period, and viewing amount peak value of the video with goods in the target time period.

Optionally, all the live video of the target commodity in the target time period includes all live video of the target commodity in the target time period and/or all the non-live video of the target commodity in the target time period.

Optionally, the vermicelli data of the video blogger with the goods video may include one or more combinations of the number of the vermicelli of the video blogger, the age of the vermicelli of the video blogger, the number of the vermicelli with different sexes in the vermicelli of the video blogger, the number of the vermicelli with different areas in the vermicelli of the video blogger, the number of the vermicelli with different social attributes in the vermicelli of the video blogger, and the social attributes may be one of middle school students, college students, social workers, retired people, and the like. Preferably, the fan data of the video bloggers with the goods video at least comprises the number of the fan of the video bloggers.

Optionally, calculating, by the cargo effect determining device, an allocation weight value of each cargo video according to the target data corresponding to each cargo video may include:

calculating the sum of all data in the target data corresponding to each video with the goods effect determining device to obtain a calculation result (also called as a bottom layer weight value) corresponding to each video with goods;

The method comprises the steps that a belt effect determining device executes conversion operation on a calculation result corresponding to each belt video according to a predetermined conversion formula to obtain a conversion result corresponding to each belt video;

determining a conversion result corresponding to each video with goods as an allocation weight value of the video with goods by a goods effect determining device; or determining a weight value correction parameter corresponding to each video with goods, and correcting a conversion result corresponding to the video with goods according to the weight value correction parameter corresponding to each video with goods to obtain an allocation weight value of the video with goods.

For example, assume that each video on-demand or video blogger of each video on-demand is numbered i, and the target data corresponding to the video on-demand i includes the number of vermicelli F _i Cumulative viewing quantity of Q _i Peak view M _i The calculation result corresponding to the video i with goods is: k (k) _i ＝F _i +Q _i +M _i 。

Still further, before the tape effect determining device calculates the sum of all data in the target data corresponding to each tape video to obtain the calculation result (also called as the bottom layer weight value) corresponding to each tape video, the tape effect determining device may further perform the following operations:

for any of the above-mentioned video-in-charge, the data which does not satisfy the calculation order of magnitude in the target data corresponding to the video-in-charge is subjected to data conversion by the effect determining device, so that the data which does not satisfy the calculation order of magnitude is converted into the data which satisfies the calculation order of magnitude.

Therefore, as the data in the target data corresponding to the cargo video are various, the data which does not meet the calculation order of magnitude in the target data is subjected to data conversion before the summation calculation so as to obtain the data which meets the calculation order of magnitude, and further the subsequent summation calculation is performed, so that the rationality and the accuracy of the calculated apportionment weight value can be improved.

Still further, determining, by the cargo effect determining device, a weight value correction parameter corresponding to each cargo video may include:

and determining a weight value correction parameter corresponding to each video with goods by the goods effect determining device according to at least one of the video type, the delivery channel and the interval duration from the initial release time to the starting time of the target time period.

Still further alternatively, the above conversion formula is:

wherein k is _i ' is the conversion result corresponding to the ith video with goods, k _i And (3) calculating a result corresponding to the ith video with goods, wherein i is a positive integer.

The conversion result corresponding to each video with goods is corrected according to the weight value correction parameter corresponding to each video with goods, and a calculation formula corresponding to the apportioned weight value of the video with goods is obtained as follows:

Wherein k is _i "is the assigned weight value, P, of the ith video with goods obtained by correcting the conversion result _i And correcting the parameters for the weight value corresponding to the ith video.

For example, when the weight value correction parameters are determined according to the delivery channel (i.e., delivery platform) of the video-in-charge, P _i An average 1 ten thousand fan journal price can be used as a weight value correction parameter for the ith video.

Therefore, when the weight value is calculated and apportioned, the vermicelli owned by the traffic star and the watching orders of magnitude are higher and far higher than those of other traffic hosts can be considered, so that conversion operation needs to be carried out on the calculation result corresponding to each cargo video through a conversion formula, and the method is in order to solve the problems of difference caused by extreme data, basically ineffective low-end traffic and low loyalty of the traffic star, compress obvious difference caused by data like vermicelli and the like, and is beneficial to improving the effect of middle waist. In addition, because the influence of some factors can cause the difference of the feelings of different audience groups on the target commodity, the influence weight (namely the weight value correction parameter) can be determined according to the influence factors, and then the conversion result is corrected or adjusted so as to improve the accuracy of the finally determined shared weight value of the video with goods.

Still further alternatively, the sales contribution value of each of the video-in-band for the target commodity in the target time period may be represented by a percentage, or may be represented by corresponding sales data, or may be represented by a sales contribution level, which is not limited by the embodiment of the present invention.

Still further alternatively, after calculating the sales contribution value for the target commodity for each of the video under load for the target time period by the effect determination means, the following operations may be further performed by the effect determination means:

the goods effect determining device sorts the calculated sales contribution value of each goods video for the target goods in the target time period, and sends the sorting result to the marketing thrower of the target goods; and/or the number of the groups of groups,

and screening a plurality of video with sales contribution values which are greater than or equal to preset sales contribution values according to the calculated sales contribution values of each video with goods for the target goods in the target time period by using the goods effect determining device, and counting one or more combinations of the types of video bloggers of the plurality of video with goods, the video styles of the plurality of video with goods, the video types of the plurality of video with goods, the delivery channels of the plurality of video with goods and the like.

Therefore, after the sales contribution value of each goods-carrying video for the target goods in the target time period is calculated, the sales contribution values are automatically ordered and sent to marketing players, so that the marketing players can know the effect of different goods-carrying videos for goods marketing in time; in addition, one or more of the types of video bloggers of the plurality of video with goods, the video styles of the plurality of video with goods, the video types of the plurality of video with goods, the delivery channels of the plurality of video with goods and the like can be counted, so that reasonable reference basis is provided for other marketing dispensers who want to market goods through the video with goods.

and judging whether a plurality of video with the same video blogger exist in the video with the goods effect determining device, and when the judgment result is yes, calculating the sum of sales contribution values of all the video with the same video blogger, which are brought by each video with the goods and are the target goods, in the target time period as the sales contribution value of the video blogger, which is brought by the video blogger to the target goods in the target time period.

Still further alternatively, after calculating sales contribution values for the target commodity brought by the video bloggers having the plurality of video bloggers with the same video bloggers with the target commodity in the target time period, the following operations may be further performed by the tape effect determining apparatus:

and calculating the ratio of the sales contribution value of the video blogger for the target commodity in the target time period to the number of the video bloggers released in all the video bloggers by using the video effect determining device, and taking the ratio as the average sales contribution value of the single video blogger for the target commodity in the target time period. Therefore, the sales contribution value of the video blogger for the target commodity in the target time period can be intelligently calculated, and further, the average sales contribution value of the single video with the commodity of the video blogger for the target commodity in the target time period can be intelligently calculated, so that an effective data basis is provided for searching a proper video blogger for commodity marketing.

Dividing all the video with goods into video groups corresponding to different video types according to the video types of all the video with goods by a goods effect determining device;

and for the video group corresponding to any video type, dividing all the video in the video group into a plurality of sub-video groups with different video styles according to the video styles by a video effect determining device, and calculating the average sales contribution value of each sub-video group for the target commodity in the target time period to obtain the average sales contribution value of the video with different video styles for the target commodity.

Wherein the average sales contribution value of each sub-commodity video set for the target commodity in the target time period is equal to the sum of sales contribution values of all commodity videos in the sub-commodity video set for the target commodity in the target time period divided by the number of all commodity videos in the sub-commodity video set.

It can be seen that the above-described cargo effect determining apparatus can accurately determine the contribution of each cargo video to the sales volume of the same commodity when a plurality of cargo video bands sell the same commodity, that is, accurately determine the cargo effect of each cargo video, which is beneficial to providing an accurate reference for selecting a proper cargo blog and/or video style of the cargo video.

Example two

Referring to fig. 2, fig. 2 is a flow chart of another method for supplementing sales missing data according to an embodiment of the invention. The method described in fig. 2 may be applied to a data supplementing device, such as a server, and the embodiment of the invention is not limited. As shown in fig. 2, the supplementing method of the sales missing data may include the following operations:

201. the data supplementing device acquires sales data of a certain target commodity at each target time of every target interval duration from the starting time of a certain target time period.

202. The data supplementing device judges whether empty data time when the sales volume data is empty exists in all the target time according to the acquired sales volume data of all the target time.

In the embodiment of the present invention, when the determination result in step 202 is yes, step 203 is triggered and executed; when the result of the determination in step 202 is no, the process may be ended, that is, the sales volume data of each target moment is comprehensively obtained through the related means (such as the web crawler technology), without performing data supplementation.

203. When it is judged that at least one empty data time exists in all target time, the data supplementing device determines all first-class empty data time from all empty data time or determines all second-class empty data time from all empty data time.

Wherein the first type of null data instant is not adjacent to any null data instant other than the first type of null data instant, and the second type of null data instant is adjacent to at least one null data instant other than the second type of null data instant.

Taking the target time period of 09:00-09:10 and the target interval duration of 1min as an example for illustration, if sales data of the target time period of 09:02, the target time period of 09:04, the target time period of 09:05, the target time period of 09:06, the target time period of 09:07, the target time period of 09:08 and the target time period of 09:09 are not acquired, all the time periods are referred to as null data time periods, wherein the target time period of 09:02 is not adjacent to any other null data time period, the first null data time period is classified, and the target time period of 09:04, the target time period of 09:05, the target time period of 09:06, the target time period of 09:07, the target time period of 09:08 and the target time period of 09:09 are adjacent to at least one null data time period, so that the first null data time period can be classified as the second null data time period.

204. The data supplementing device supplements sales data of each empty data moment according to a data supplementing mode matched with the category of each empty data moment.

The category of the null data time is used to specifically indicate whether the null data time belongs to the first category of null data time or the second category of null data time.

Therefore, the method described by the embodiment of the invention can supplement the missing sales volume data, is beneficial to acquiring more comprehensive sales volume data, and is further beneficial to accurately calculating the sales contribution value of each video with goods to the goods; in addition, after determining the category of each empty data time, sales data can be supplemented according to the data supplementing mode matched with the category.

In an alternative embodiment, the data supplementing device supplements sales data of each empty data moment according to a data supplementing mode matched with the category of each empty data moment, and the method may include:

For any first type of empty data time, the data supplementing device sequentially acquires first sales volume data of each preceding non-empty data time in a first preset number of preceding non-empty data time before the first type of empty data time and second sales volume data of each following non-empty data time in a second preset number of following non-empty data time after the first type of empty data time from all target time according to the sequence of short and long time length from the first type of empty data time;

the data supplementing means supplements sales data at the first kind of null data time based on first sales data at each preceding non-null data time and second sales data at each following non-null data time.

In this alternative embodiment, the first preset number may be equal to 1 and the second preset number may be equal to 1. The data supplementing device supplements sales data of the first kind of empty data moment according to first sales data of each preceding non-empty data moment and second sales data of each following non-empty data moment, and the data supplementing device can include:

the data supplementing device calculates the average value of the second sales volume data at the later non-empty data time and the first sales volume data at the earlier non-empty data time;

When the average value is an integer, the data supplementing device supplements sales data of the first type of empty data moment to the average value;

when the average value is a non-integer, the data supplementing device supplements sales data of the first type of empty data time as an upward rounding value or a downward rounding value of the average value.

After calculating the average value, the data supplementing device may directly supplement the sales data at the first type of empty data time to the average value, without determining whether the average value is an integer.

Therefore, when the sales volume data is supplemented for the first kind of empty data moment, the alternative embodiment can directly supplement the sales volume data for the first kind of empty data moment according to the average value of the sales volume data of the adjacent preceding non-empty data moment and the adjacent following non-empty data moment, so that the error is smaller, and the data supplementing speed is high.

In another alternative embodiment, the data supplementing device supplements sales data of each empty data moment according to a data supplementing mode matched with the category of each empty data moment, and the method may include:

the data supplementing device divides all second-class empty data time into a plurality of time sets, any two second-class empty data time points included in the same time set are directly adjacent or indirectly adjacent through at least one second-class empty data time point, and any two second-class empty data time points in different time sets are not directly adjacent and are not indirectly adjacent through the second-class empty data time points;

For any time set, the data supplementing device determines the target number of sub-time periods included in the time set, the minimum second-class empty data time and the maximum second-class empty data time in the time set, and acquires first sales volume data of the prior non-empty data time closest to the minimum second-class empty data time and second sales volume data of the subsequent non-empty data time closest to the maximum second-class empty data time from all target time, wherein the target number is equal to the number of the second-class empty data time included in the time set plus 1;

the data supplementing device calculates the difference value between the second sales volume data and the first sales volume data, and supplements the sales volume data of each second class empty data moment included in the moment set according to the second sales volume data, the first sales volume data, the target quantity and the difference value.

The sub-time period included in the time set consists of a sub-time period formed by all directly adjacent second-class empty data time instants in the time set, a sub-time period formed by a previous non-empty data time instant and a minimum second-class empty data time instant in the time set, and a sub-time period formed by a later non-empty data time instant and a maximum second-class empty data time instant in the time set.

It should be noted that indirect adjacency refers to indirect adjacency through one or more second type null data moments, and if any two second type null data moments are not indirectly adjacency, it means that the two second type null data moments cannot be indirectly adjacency through one or more second type null data moments. Taking the example of the target time period being 9:00-09:10 and the target interval duration being 1min as an illustration, if sales data of the target time points 09:02, 09:03, 09:05, 09:06, 09:07, 09:08 and 09:09 are not obtained, these time points are all referred to as null data time points and all belong to the second type of null data time points. And all the second type of null data time can be divided into two time sets, wherein the first time set comprises a target time 09:02 and a target time 09:03, the target time comprised by the first time set is directly adjacent, the second time set comprises a target time 09:05, a target time 09:06, a target time 09:07, a target time 09:08 and a target time 09:09, any two target times comprised by the second time set are directly adjacent or indirectly adjacent, and as the first time set and the second time set are separated by a non-null data time 09:04, any one target time in the first time set is not directly adjacent or indirectly adjacent to any one target time in the second time set.

In this alternative embodiment, as an alternative implementation manner, the data supplementing device supplements sales volume data of each second class of empty data time included in the time set according to the second sales volume data, the first sales volume data, the target number and the difference value, and may include:

determining the sales volume increment of each sub-time period included in the time set according to the result of dividing the difference value by the target quantity;

and supplementing sales volume data of each second class of empty data moment included in the moment set according to the sales volume increment of each sub-time period included in the second sales volume data, the first sales volume data and the moment set.

The sub-time periods included in each time set are sequentially composed of a preceding non-null data time moment closest to the minimum second-class null data time moment of the time set, each second-class null data time moment and a following non-null data time moment closest to the maximum second-class null data time moment of the time set, and each sub-time period has no intersection or overlapping of other times except for the coincidence of one time end point, and the time length of each sub-time period is equal to the target interval duration.

Specifically, the alternative embodiment first calculates a sales volume increment average value of each sub-time period in the time set, where the sales volume increment average value is equal to a difference between sales volume data at a second time point (i.e., a last non-empty data time point closest to a maximum second empty data time point of the time set) and sales volume data at a first time point (i.e., a previous non-empty data time point closest to the minimum second empty data time point of the time set) divided by a number of sub-time periods included in the time set. In practical application, because there is no less than one sales volume increment, the calculated sales volume increment average value needs to be estimated as an integer, that is, the sales volume increment average value of sub-time periods corresponding to each second type of empty data time instant except the maximum second type of empty data time instant (or the minimum second type of empty data time instant) in the time instant set is sequentially estimated as an integer in a rounding manner, then the sub-time periods formed by the maximum second type of empty data time instant (or the minimum second type of empty data time instant) and the second time instant (or the first time instant) in the time instant set bear errors so as to ensure that the sales volume increment and the difference value between the sales volume data of the second time instant and the sales volume data of the first time instant keep consistent, alternatively, the average value of sales volume increment of sub-time periods corresponding to each second type of empty data time except the maximum second type of empty data time (or the minimum second type of empty data time) in the time set can be estimated as an integer in turn according to a mode of cross rounding up and rounding down, and then errors are accepted by sub-time periods formed by the maximum second type of empty data time (or the minimum second type of empty data time) and the second time point (or the first time point) in the time set, so that the sales volume increment is kept consistent with the difference value between the sales volume data of the second time point and the sales volume data of the first time period.

For example, a certain target time period or a certain time set of the target time period of 02 month 01 of 2020 is taken as an example, wherein the starting time is 00:01, the ending time is 00:06, and the time interval duration is 1min, and the number obtained by the crawler technology is as follows:

{ time: 2020-02-01:01, sales: 1};

{ time: 2020-02-01:04, sales: 8};

{ time: 2020-02-01 00:05, sales: 9};

{ time: 2020-02-01:06, sales: 12}.

The idea of carrying out data supplementation by adopting the mean value flattening and rounding mode is as follows:

determining that the blank data time is 00:02 and 00:03, and determining that the two time points are 00:01 and 00:04 respectively, wherein the corresponding sub-time periods are 00:01-00:02, 00:02-00:03 and 00:03-00:04 respectively, namely corresponding to 3 sub-time periods;

calculating the sales volume increment of 7 in the 00:01-00:04 time period according to the sales volume of 00:01 and the sales volume of 00:04, increasing by 2.33 sales volumes per minute according to the average value, wherein the sales volume is not required to be less than one, the monitoring granularity is the minute, the increased sales volume is required to be estimated as an integer according to a rounding rule, the increment of 3 sub-time periods is [2, 2 and 2], and the calculated sales volume increment in the 00:01-00:04 time period is 6, which is less than the actual sales volume increment by 1, and the difference is required to be supplemented in a certain sub-time period; according to the concept of inertia economy, the sales increase trend should steadily or continuously decrease and increase, and the middle sudden decrease or sudden increase is not reasonable, so the difference value is selected to be compensated in the last sub-time period, namely, the increment of 3 sub-time periods is [2, 2 and 3];

After determining the increment of 3 sub-time periods as [2, 3], the empty data time requiring the sales volume data supplementation can be subjected to data supplementation, and the supplementation result is as follows:

{ time: 2020-02-01:02, sales: 3},

{ time 2020-02-01:03, sales: 5}.

In this another alternative embodiment, as another alternative embodiment, the data supplementing means supplements sales volume data of each second type of empty data time included in the time set according to the second sales volume data, the first sales volume data, the target number, and the difference value, and may include:

the data supplementing device divides the determined mother time set into a front time set and a rear time set corresponding to the mother time set according to a dichotomy, calculates the sales volume increment of the front time set and the sales volume increment of the rear time set corresponding to the mother time set according to the sales volume increment of the mother time set and the allocation proportion corresponding to the mother time set, caches the sales volume increment of the sub time sets of which the number of sub time periods included in the front time set and the rear time set corresponding to the mother time set meets the preset number condition, and judges whether the sub time sets of which the number of sub time periods included in the front time set and the rear time set does not meet the preset number condition exist in the front time set and the rear time set corresponding to the mother time set;

When the judgment result is negative, the data supplementing device supplements sales volume data of each second type of empty data moment included in the moment set according to the second sales volume data, the first sales volume data and the sales volume increment of all the cached sub-time period sets which meet the preset quantity condition;

and when the judgment result is yes, the data supplementing device determines a sub-time set, of which the number of sub-time periods included in the previous time set and the next time set corresponding to the mother time set does not meet the preset number condition, as a new mother time set, repeatedly executes the operation of dividing the determined mother time set into the previous time set and the next time set corresponding to the mother time set according to the bisection method, calculating the sales volume increment of the previous time set and the sales volume increment of the next time set corresponding to the mother time set according to the sales volume increment of the mother time set and the allocation proportion corresponding to the mother time set, caching the sales volume increment of the sub-time set, of which the number of sub-time periods included in the previous time set and the next time set corresponding to the mother time set meets the preset number condition, and judging whether the sub-time set, of which the number of the included time periods does not meet the preset number condition, exists in the previous time set and the next time set corresponding to the mother time set.

In this alternative embodiment, the number of sub-time periods included in the set of mother time instances may be considered when dividing the set of mother time instances into a preceding set of time instances and a following set of time instances corresponding to the set of mother time instances. If the number is even, the number of the sub-time periods included in the previous time set is consistent with the number of the sub-time periods included in the later time set, namely the mother time set is equally divided into two; if the number is odd, the number of sub-time periods included in the previous time instance set may be 1 or 1 less than the number of sub-time periods included in the subsequent time instance set. The sales volume increment corresponding to the master time set is equal to the sales volume data of the maximum time of the sub time period included in the master time set minus the sales volume data of the minimum time of the sub time period included in the master time set, wherein the maximum time of the sub time period included in the master time set is the adjacent non-empty data time of the maximum time included in the master time set, and the minimum time of the sub time period included in the master time set is the adjacent non-empty data time of the minimum time included in the master time set.

For example, if the null data time included in the master time set is 00:01, 00:02, 00:03, and 00:04, the number of sub-time periods included in the master time set is 5, and is 00:00-00:01, 00:01-00:02, 00:02-00:03, 00:03-00:04, and 00:04-00:05, respectively, so the sub-time period included in the previous time set corresponding to the master time set may be 00:00-00:01, 00:01-00:02, and the sub-time period included in the next time set corresponding to the master time set may be 00:02-00:03, 00:03-00:04, and 00:04-00:05, or the sub-time period included in the previous time set corresponding to the master time set may be 00:00-00:01, 00:01-00:02, and 00:02-00:03, and the sub-time period included in the next time set corresponding to the next time set may be 00:00:00-00:01, 00:01-00:04-00:05.

For example, if the null data time included in the master time set is 00:01, 00:02, and 00:03, the number of sub-time periods included in the master time set is 4, and is 00:00-00:01, 00:01-00:02, 00:02-00:03, and 00:03-00:04, respectively, so that the sub-time period included in the previous time set corresponding to the master time set may be 00:00-00:01, and 00:01-00:02, and the sub-time period included in the later time set corresponding to the master time set may be 00:02-00:03, and 00:03-00:04.

In this alternative embodiment, the allocation proportion corresponding to the master time set includes a first allocation proportion of a preceding time set and a second allocation proportion of a subsequent time set, where the first allocation proportion of the preceding time set is equal to a number of sub-periods included in the preceding time set to a total number of sub-periods included in the master time set, the second allocation proportion of the subsequent time set is equal to a number of sub-periods included in the subsequent time set to a total number of sub-periods included in the master time set, and the sales volume increment of the preceding time set corresponding to the master time set is determined according to a product of the first allocation proportion and the sales volume increment of the master time set, and the sales volume increment of the subsequent time set corresponding to the master time set is determined according to a product of the second allocation proportion and the sales volume increment of the master time set. When the product of one of the allocation ratios and the sales volume increment of the mother time set is not an integer, the product of the allocation ratio and the sales volume increment of the mother time set needs to be rounded in one of up, down and rounding modes, after the product of the allocation ratio and the sales volume increment of the mother time set is rounded to obtain the corresponding sales volume increment, then a substitute value of the product of the other allocation ratio and the sales volume increment of the mother time set can be obtained according to the difference between the sales volume increment of the mother time set and the sales volume increment obtained after rounding, and the substitute value is an integer.

Therefore, the alternative implementation mode can realize the supplementation of the sales volume data at the moment of empty data in a dichotomy mode, compared with a mean value sharing mode, the method can reduce the occurrence of data storm or storm drop in the last error receiving sub-time period, can enable the supplemented sales volume data to accord with the increasing trend of the sales volume data, and improves the rationality and reliability of the supplemented sales volume data. The advantages of the implementation of the dichotomy over the implementation of the mean value sharing will be described below by way of an example.

The data obtained from the crawler data is described as [ (2020-02-01:00, 0) ] (2020-02-02:00, 15129). The empty data time when the data needs to be replenished is the whole minute time of the time period 2020-02-01:01-2020-02-01-23:59. If the sales volume increment of the sub-time period included in 2020-02-01:00-2020-02-01-23:59 is 10 according to the rounding mode of combining mean value allocation with rounding, the sales volume increment of 2020-02-01:59-2020-02-02 00:00 is in a surge 719; if the method is implemented by the dichotomy, the method is divided into two time periods of [ 2020-02-01:00, 2020-02-01:12:00) and [ 2020-02-01:12:00, 2020-02-02:00) firstly, and the sales volume increment of [ 2020-02-01:00, 2020-02-01:12:00) is as follows according to the average value average and the last interval filling difference value principle: 7564, continuing to apportion to know that the sales volume increment of each sub-time period tends to be stable.

Example III

Referring to fig. 3, fig. 3 is a schematic structural diagram of a device for supplementing missing sales data according to an embodiment of the present invention. As shown in fig. 3, the apparatus may include:

an acquiring module 301, configured to acquire sales data of a certain target commodity at each target time of a target interval duration from a start time of a certain target time period.

The judging module 302 is configured to judge whether there is an empty data time when the sales volume data is empty in all the target time according to the acquired sales volume data of all the target time.

And a supplementing module 303, configured to supplement sales data of each empty data time when the judging module 302 judges that at least one empty data time exists in all the target time.

The sales volume data of each target moment is used for calculating sales contribution values brought by each commodity video in all commodity videos of the target commodity in the target time period.

Therefore, the device described in fig. 3 can determine whether the target time has empty data time before calculating the sales contribution value of each of the video with goods for the target commodity in the target time period, if so, the sales volume data of the empty data time needs to be supplemented, which is favorable for obtaining more comprehensive sales volume data, and further is favorable for accurately calculating the sales contribution value of each of the video with goods.

In an alternative embodiment, as shown in fig. 4, the apparatus may further include:

the data fitting module 304 is configured to perform a data fitting operation on sales volume data of all non-empty data time instants remaining except for all empty data time instants in all target time instants after the determining module 302 determines that at least one empty data time instant exists in all target time instants, and before the supplementing module 303 supplements sales volume data of each empty data time instant, so as to obtain a sales volume curve corresponding to a target time period, where the sales volume curve is used to represent a correspondence between time instants and sales volume data in the target time period.

In this alternative embodiment, the specific manner in which the replenishment module 303 supplements sales volume data for each empty data time may be:

and substituting each empty data moment into the sales volume curve in turn to obtain sales volume data of each empty data moment.

It can be seen that the implementation of the apparatus described in fig. 4 is also capable of supplementing sales data at each empty data time by means of curve fitting, which is beneficial to improving the matching degree of the supplemented sales data and the sales increasing trend.

In another alternative embodiment, as shown in fig. 5, the apparatus may further comprise a determining module 305, wherein:

A determining module 305, configured to determine all first type of null data time instants from all null data time instants after the determining module 302 determines that at least one null data time instant exists in all target time instants, and before the supplementing module 303 supplements sales volume data of each null data time instant, where the first type of null data time instant is not adjacent to any null data time instant except the first type of null data time instant; alternatively, all the second type of null data instants are determined from all the null data instants, the second type of null data instants being adjacent to at least one null data instant other than the second type of null data instant.

The specific way of supplementing sales data at each empty data time by the supplementing module 303 is as follows:

In yet another alternative embodiment, the supplementing module 303 supplements sales data of each empty data time according to a data supplementing manner matched with a category of each empty data time, which may include:

for any first type of null data time, sequentially acquiring first sales volume data of each preceding non-null data time in a first preset number of preceding non-null data time and second sales volume data of each following non-null data time in a second preset number of following non-null data time in the first type of null data time from all target time according to the sequence of short and long time lengths from the first type of null data time;

And supplementing sales data of the first type of null data moment according to the first sales data of each preceding non-null data moment and the second sales data of each following non-null data moment.

Further optionally, the first preset number is equal to 1 and the second preset number is equal to 1;

the specific manner of supplementing sales data at the first type of null data time by the supplementing module 303 according to the first sales data at each preceding non-null data time and the second sales data at each following non-null data time is:

calculating an average value of the second sales volume data at the later non-empty data time and the first sales volume data at the earlier non-empty data time;

when the average value is an integer, supplementing sales volume data of the first type of empty data time as the average value;

and when the average value is a non-integer, supplementing sales data at the moment of the first type of empty data as an upward rounding value or a downward rounding value of the average value.

After calculating the average value, the supplementing module 303 may directly supplement the sales volume data at the first type of empty data time to the average value, without determining whether the average value is an integer.

It can be seen that, in this alternative embodiment, when sales volume data is further added to the first type of null data, sales volume data at the first type of null data can be directly added according to the average value of sales volume data at the adjacent preceding non-null data time and the adjacent following non-null data time, so that errors are small, and data adding efficiency is high.

In yet another alternative embodiment, the supplementing module 303 supplements sales data at each empty data time according to a data supplementing mode matched with the category of each empty data time, which is specifically:

for any time set, determining the target number of sub-time periods included in the time set, the minimum second-class empty data time and the maximum second-class empty data time in the time set, and acquiring first sales volume data of a preceding non-empty data time closest to the minimum second-class empty data time and second sales volume data of a following non-empty data time closest to the maximum second-class empty data time from all target time;

calculating the difference value between the second sales volume data and the first sales volume data, and supplementing sales volume data of each second class of empty data moment included in the moment set according to the second sales volume data, the first sales volume data, the target quantity and the difference value;

The sub-time period included in the time set consists of a sub-time period formed by all two directly adjacent second-class empty data time points in the time set, a sub-time period formed by the previous non-empty data time point and the minimum second-class empty data time point, and a sub-time period formed by the latter non-empty data time point and the maximum second-class empty data time point.

In this alternative embodiment, as an alternative implementation manner, the supplementing module 303 supplements, according to the second sales volume data, the first sales volume data, the target number and the difference value, sales volume data of each second type of empty data time included in the time set in a specific manner:

Therefore, the optional embodiment also provides a mean average sales volume data supplementing mode, which can supplement sales volume data corresponding to empty data time, and is further beneficial to subsequent calculation of sales contribution values.

In this alternative embodiment, as another alternative implementation manner, the supplementing module 303 supplements the sales volume data of each second type of empty data time included in the time set according to the second sales volume data, the first sales volume data, the target quantity and the difference value, in a specific manner that:

dividing the determined mother time set into a front time set and a rear time set corresponding to the mother time set according to a dichotomy, calculating the sales volume increment of the front time set and the sales volume increment of the rear time set corresponding to the mother time set according to the sales volume increment of the mother time set and the allocation proportion corresponding to the mother time set, caching the sales volume increment of the sub time sets of which the number of sub time periods included in the front time set and the rear time set corresponding to the mother time set meets the preset number condition, and judging whether the sub time sets of which the number of sub time periods included in the front time set and the rear time set corresponding to the mother time set does not meet the preset number condition exist or not;

when the judgment result is negative, supplementing sales volume data of each second class of empty data moment included in the moment set according to sales volume increment of all the moment sets, wherein the sales volume increment of all the moment sets is met by the quantity of the second sales volume data, the first sales volume data and the cached quantity of the included sub time periods meeting the preset quantity condition;

And when the judgment result is yes, determining a sub-time set, which is included in the previous time set and the next time set and corresponds to the mother time set, of which the number of sub-time periods does not meet the preset number condition as a new mother time set, repeatedly executing the operation of dividing the determined mother time set into the previous time set and the next time set, which are corresponding to the mother time set, according to the bisection method, calculating the sales volume increment of the previous time set and the sales volume increment of the next time set, which are corresponding to the mother time set, according to the sales volume increment of the mother time set and the allocation proportion, and caching the sales volume increment of the sub-time set, which is included in the previous time set and the next time set, of which the number of sub-time periods included in the previous time set and the next time set meets the preset number condition, and judging whether the sub-time set, which is included in the previous time set and the next time set, which does not meet the preset number condition, exists.

The number of the included sub-time periods meets the preset number condition, namely the number of the included sub-time periods is 1, and the number of the included sub-time periods does not meet the preset number condition, namely the number of the included sub-time periods is larger than 1.

The initial determined mother time set is a time set, and the sales increment of the time set is equal to the difference value.

Therefore, the optional embodiment can realize the supplementation of the data at the moment of empty data in a dichotomy mode, and compared with a mean value sharing mode, the method can reduce the occurrence of data storm or storm falling in the last error receiving sub-time period, can enable the supplemented sales volume data to accord with the increasing trend of the sales volume data, and improves the rationality and reliability of the supplemented sales volume data.

Example IV

Referring to fig. 6, fig. 6 is a schematic structural diagram of another device for supplementing missing sales data according to an embodiment of the present invention. As shown in fig. 6, the apparatus may include:

a memory 401 storing executable program codes;

a processor 402 coupled with the memory 401;

the processor 402 invokes executable program code stored in the memory 401 to perform the steps in the supplementing method of sales volume missing data disclosed in the first or second embodiment of the present invention.

Example five

The embodiment of the invention discloses a computer storage medium which stores computer instructions for executing the steps in the method for supplementing sales missing data disclosed in the first or second embodiment of the invention when the computer instructions are called.

The apparatus embodiments described above are merely illustrative, wherein the modules illustrated as separate components may or may not be physically separate, and the components shown as modules may or may not be physical, i.e., may be located in one place, or may be distributed over a plurality of network modules. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of this embodiment. Those of ordinary skill in the art will understand and implement the present invention without undue burden.

From the above detailed description of the embodiments, it will be apparent to those skilled in the art that the embodiments may be implemented by means of software plus necessary general hardware platforms, or of course by means of hardware. Based on such understanding, the foregoing technical solutions may be embodied essentially or in part in the form of a software product that may be stored in a computer-readable storage medium including Read-Only Memory (ROM), random-access Memory (Random Access Memory, RAM), programmable Read-Only Memory (Programmable Read-Only Memory, PROM), erasable programmable Read-Only Memory (Erasable Programmable Read Only Memory, EPROM), one-time programmable Read-Only Memory (OTPROM), electrically erasable programmable Read-Only Memory (EEPROM), compact disc Read-Only Memory (Compact Disc Read-Only Memory, CD-ROM) or other optical disc Memory, magnetic disc Memory, tape Memory, or any other medium that can be used for computer-readable carrying or storing data.

Finally, it should be noted that: the embodiment of the invention discloses a method and a device for supplementing sales missing data, which are disclosed as preferred embodiments of the invention, and are only used for illustrating the technical scheme of the invention, but not limiting the technical scheme; although the invention has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art will understand that; the technical scheme recorded in the various embodiments can be modified or part of technical features in the technical scheme can be replaced equivalently; such modifications and substitutions do not depart from the spirit and scope of the corresponding technical solutions.

Claims

1. A method of supplementing sales missing data, the method comprising:

Wherein sales volume data of each of the target time instants is used to calculate sales contribution values of each of all the shipment videos of the target commodity for the target commodity in the target time period, and sales contribution values of each of all the shipment videos of the target commodity for the target commodity in the target time period are calculated by:

acquiring target data which corresponds to all the video with goods of the target commodity and has an association relation with the sales volume of the target commodity in the target time period by a goods effect determining device;

calculating an allocation weight value of each cargo video according to target data corresponding to each cargo video by the cargo effect determining device;

and calculating a sales contribution value of each video with goods in the target time period according to the allocation weight value of each video with goods, the sum of the allocation weight values of all the videos with goods and the obtained sales data of each target commodity at each target moment in the target time period by the goods effect determining device.

2. The method for supplementing sales volume missing data according to claim 1, wherein before supplementing sales volume data at each of the null data moments, the method further comprises:

3. The sales volume missing data supplementing method according to claim 2, wherein said supplementing sales volume data at each of said empty data time according to a data supplementing manner matched with a category of each of said empty data time comprises:

4. The method of supplementing sales missing data according to claim 3, wherein the first preset number is equal to 1 and the second preset number is equal to 1;

5. The sales volume missing data supplementing method according to claim 2, wherein said supplementing sales volume data at each of said empty data time according to a data supplementing manner matched with a category of each of said empty data time comprises:

6. The method of supplementing missing sales data according to claim 5, wherein the supplementing sales data for each second type of empty data time included in the time set based on the second sales data, the first sales data, the target quantity, and the difference value includes:

7. The method of supplementing missing sales data according to claim 5, wherein the supplementing sales data for each second type of empty data time included in the time set based on the second sales data, the first sales data, the target quantity, and the difference value includes:

8. The method for supplementing sales volume missing data according to claim 1, wherein before supplementing sales volume data at each of the null data moments, the method further comprises:

9. A supplemental device for sales missing data, the device comprising:

10. The sales volume missing data supplementing device according to claim 9, wherein said device further comprises:

11. The sales volume missing data supplementing device according to claim 10, wherein the supplementing module supplements sales volume data at each empty data time according to a data supplementing mode matched with the category of each empty data time, and the specific mode is as follows:

12. The sales volume missing data supplementing device according to claim 10, wherein the supplementing module supplements sales volume data at each empty data time according to a data supplementing mode matched with the category of each empty data time, and the specific mode is as follows:

13. The sales volume missing data supplementing device according to claim 12, wherein the supplementing module supplements sales volume data of each second type of empty data time included in the time set according to the second sales volume data, the first sales volume data, the target number, and the difference value in a specific manner that:

14. The sales volume missing data supplementing device according to claim 12, wherein the supplementing module supplements sales volume data of each second type of empty data time included in the time set according to the second sales volume data, the first sales volume data, the target number, and the difference value in a specific manner that:

15. A supplemental device for sales missing data, the device comprising:

a memory storing executable program code;

a processor coupled to the memory;

the processor invokes the executable program code stored in the memory to perform the supplementing method of sales volume missing data according to any of claims 1-8.

16. A computer storage medium storing computer instructions which, when invoked, are operable to perform the method of supplementing sales volume missing data of any of claims 1-8.