CN113781078A

CN113781078A - Data processing method and device, electronic equipment and computer readable medium

Info

Publication number: CN113781078A
Application number: CN202010922786.8A
Authority: CN
Inventors: 梁创逸; 廖恢齐
Original assignee: Beijing Wodong Tianjun Information Technology Co Ltd
Current assignee: Beijing Wodong Tianjun Information Technology Co Ltd
Priority date: 2020-09-04
Filing date: 2020-09-04
Publication date: 2021-12-10

Abstract

The disclosure relates to a data processing method, a data processing device, electronic equipment and a computer readable medium, and belongs to the technical field of computers. The method comprises the following steps: acquiring information to be displayed of a user platform to which the information belongs, and dividing the information to be displayed into an original value information set and an adjusted value information set; acquiring historical data of a user platform to which target users call information through information to be displayed in different information display platforms, and determining the user type and the call probability of the target users; adjusting the value data of the information to be displayed in the adjustment value information set according to the adjustment coefficient; obtaining a cost parameter according to the value data of the information to be displayed and the call-up probability; and pushing the cost parameter of the information to be displayed in the original value information set and the cost parameter of the information to be displayed in the adjusted value information set to an information display platform for comparison and display. The cost parameter of the information to be displayed can be reduced by setting different values for the information to be displayed of different target users.

Description

Data processing method and device, electronic equipment and computer readable medium

Technical Field

The present disclosure relates to the field of computer technologies, and in particular, to a data processing method, a data processing apparatus, an electronic device, and a computer-readable medium.

Background

With the development of the internet, internet advertising has become one of the most common types of advertising. There are many bidding ways for internet advertisement, and for advertisers, there are still problems of single service scene, high cost of visitors, etc. in various advertising bidding ways, which causes the cost of advertisement delivery to be too high and cannot meet the diversified scene appeal of advertisers.

In view of the above, there is a need in the art for a method that can reduce the cost of ad placement.

It is to be noted that the information disclosed in the above background section is only for enhancement of understanding of the background of the present disclosure, and thus may include information that does not constitute prior art known to those of ordinary skill in the art.

Disclosure of Invention

The present disclosure is directed to a data processing method, a data processing apparatus, an electronic device, and a computer-readable medium, so as to reduce advertisement delivery cost at least to some extent.

According to a first aspect of the present disclosure, there is provided a data processing method comprising:

the method comprises the steps of obtaining information to be displayed of a user platform to which the information belongs, dividing the information to be displayed into a plurality of information units, and dividing the information to be displayed in each information unit into an original value information set and an adjustment value information set;

acquiring historical data of a user platform to which target users call information to be displayed through the information to be displayed in different information display platforms, and determining the user type and the call probability of the target users in each information display platform according to the historical data;

determining an adjustment coefficient according to the user type of the target user, and adjusting the value data of the information to be displayed in the adjustment value information set according to the call-up probability and the adjustment coefficient;

obtaining a cost parameter of the information to be displayed according to the value data of the information to be displayed and the call-up probability of the target user;

and pushing the cost parameters of the information to be displayed in the original value information set and the cost parameters of the information to be displayed in the adjusted value information set to an information display platform for comparison and display.

In an exemplary embodiment of the present disclosure, the dividing the information to be displayed into a plurality of information units, and dividing the information to be displayed in each of the information units into an original value information set and an adjusted value information set includes:

dividing the information to be displayed into different information units according to the information type of the information to be displayed;

acquiring first attribute identification information of the information to be displayed, and dividing the information to be displayed in each information unit into an original value information set and an adjusted value information set according to a preset proportion according to the first attribute identification information.

In an exemplary embodiment of the present disclosure, the obtaining of the first attribute identification information of the information to be displayed includes:

acquiring a plurality of attribute information of the information to be displayed;

and splicing the plurality of attribute information of the information to be displayed according to a preset sequence, and converting the attribute information into first attribute identification information of the information to be displayed through a hash function.

In an exemplary embodiment of the present disclosure, the obtaining of historical data of a user platform to which the target user calls the information through the information to be displayed in different information display platforms includes:

acquiring second attribute identification information of information to be displayed when a target user calls a first type page and a second type page of a user platform to which the information belongs through the information to be displayed in different information display platforms within a preset time period;

and generating historical data of the information to be displayed according to the second attribute identification information of the information to be displayed.

In an exemplary embodiment of the present disclosure, the determining, according to the historical data, a user type and a call-starting probability of a target user in each of the information presentation platforms includes:

if the target user calls a user platform to which the information belongs through the information to be displayed in the information display platform, marking the target user as a first target user, and determining the call probability of the first target user as a first probability value;

if the target user calls a user platform to which the information belongs through the information to be displayed in other information display platforms, marking the target user as a second target user, and determining the calling probability of the second target user as a second probability value according to the historical data;

if the target user does not call the user platform to which the information belongs through any information to be displayed in the information display platform, the target user is marked as a third target user, and the call probability of the third target user is determined as a third probability value.

In an exemplary embodiment of the present disclosure, the determining an adjustment coefficient according to the user type of the target user includes:

setting the adjustment coefficients of the first target user and the second target user in a first coefficient adjustment interval;

and setting the adjustment coefficient of the third target user in a second coefficient adjustment interval.

In an exemplary embodiment of the present disclosure, the adjusting, according to the call-up probability and the adjustment coefficient, the value data of the information to be shown in the adjusted value information set includes:

acquiring original value data of the information to be displayed;

determining the total consumption of the information to be displayed in the original value information set according to the number of target users of the information to be displayed in the original value information set and the original value data of the information to be displayed;

determining the total consumption of the information to be displayed in the adjusted value information set according to the total consumption of the information to be displayed in the original value information set;

determining a first target adjustment coefficient from the first coefficient adjustment interval according to the total consumption of the information to be displayed in the adjustment value information set, and determining a second target adjustment coefficient from the second coefficient adjustment interval;

according to the original value data of the information to be displayed, the first target adjustment coefficient and the first probability value, determining the value data of the information to be displayed in the adjustment value information set called by the first target user;

determining value data of the information to be displayed in the adjustment value information set called by the second target user according to the original value data of the information to be displayed, the first target adjustment coefficient and the second probability value;

and determining the value data of the information to be displayed in the adjustment value information set called by the third target user according to the original value data of the information to be displayed, the second target adjustment coefficient and the third probability value.

According to a second aspect of the present disclosure, there is provided a data processing apparatus comprising:

the information to be displayed dividing module is used for acquiring each information to be displayed of a user platform to which the information belongs, dividing the information to be displayed into a plurality of information units, and dividing the information to be displayed in each information unit into an original value information set and an adjusted value information set;

the system comprises a calling probability determining module, a calling probability determining module and a calling probability determining module, wherein the calling probability determining module is used for acquiring historical data of a user platform to which target users call information to be displayed in different information display platforms, and determining the user types and the calling probabilities of the target users in the information display platforms according to the historical data;

the value data adjusting module is used for determining an adjusting coefficient according to the user type of the target user and adjusting the value data of the information to be displayed in the adjusting value information set according to the call-up probability and the adjusting coefficient;

the cost parameter determination module is used for obtaining the cost parameter of the information to be displayed according to the value data of the information to be displayed and the call-up probability of the target user;

and the parameter comparison and display module is used for pushing the cost parameters of the information to be displayed in the original value information set and the cost parameters of the information to be displayed in the adjusted value information set to an information display platform for comparison and display.

According to a third aspect of the present disclosure, there is provided an electronic device comprising: a processor; and a memory for storing executable instructions of the processor; wherein the processor is configured to perform any one of the data processing methods described above via execution of the executable instructions.

According to a fourth aspect of the present disclosure, there is provided a computer readable medium having stored thereon a computer program which, when executed by a processor, implements the data processing method of any one of the above.

The exemplary embodiments of the present disclosure may have the following advantageous effects:

in the data processing method of the embodiment of the disclosure, different value data are set for the information to be displayed called by different target users according to the calling conditions of the information to be displayed in different information display platforms, so as to reduce the cost parameter of the information to be displayed, and the adjusted cost parameter and the original cost parameter are displayed on the information display platform in a comparison manner. The data processing method in the disclosed example embodiment can automatically adjust the value data of the information to be displayed according to the calling conditions of the target users with different qualities, and improve the calling rate of the information to be displayed and maximize the number of the drainage streams of the target users on the premise of unchanged total consumption, thereby reducing the cost parameters of the information to be displayed.

It is to be understood that both the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the disclosure.

Drawings

The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present disclosure and together with the description, serve to explain the principles of the disclosure. It is to be understood that the drawings in the following description are merely exemplary of the disclosure, and that other drawings may be derived from those drawings by one of ordinary skill in the art without the exercise of inventive faculty.

FIG. 1 shows a flow diagram of a data processing method of an example embodiment of the present disclosure;

fig. 2 shows a flow diagram of the partitioning of information to be presented according to an example embodiment of the present disclosure;

FIG. 3 illustrates a flow diagram for adjusting value data for information to be presented in accordance with an exemplary embodiment of the present disclosure;

FIG. 4 shows a flow diagram of a data processing method in accordance with one embodiment of the present disclosure;

FIG. 5 illustrates a block flow diagram for calculating an origination probability in accordance with one embodiment of the present disclosure;

FIG. 6 shows a block diagram of a data processing apparatus of an example embodiment of the present disclosure;

FIG. 7 illustrates a schematic structural diagram of a computer system suitable for use in implementing the electronic device of an embodiment of the present disclosure.

Detailed Description

Example embodiments will now be described more fully with reference to the accompanying drawings. Example embodiments may, however, be embodied in many different forms and should not be construed as limited to the examples set forth herein; rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the concept of example embodiments to those skilled in the art. The described features, structures, or characteristics may be combined in any suitable manner in one or more embodiments. In the following description, numerous specific details are provided to give a thorough understanding of embodiments of the disclosure. One skilled in the relevant art will recognize, however, that the subject matter of the present disclosure can be practiced without one or more of the specific details, or with other methods, components, devices, steps, and the like. In other instances, well-known technical solutions have not been shown or described in detail to avoid obscuring aspects of the present disclosure.

Furthermore, the drawings are merely schematic illustrations of the present disclosure and are not necessarily drawn to scale. The same reference numerals in the drawings denote the same or similar parts, and thus their repetitive description will be omitted. Some of the block diagrams shown in the figures are functional entities and do not necessarily correspond to physically or logically separate entities. These functional entities may be implemented in the form of software, or in one or more hardware modules or integrated circuits, or in different networks and/or processor devices and/or microcontroller devices.

Internet advertisement refers to commercial advertisement that directly or indirectly promotes goods or services in the form of words, pictures, audio, video or other forms through internet media such as websites, web pages, internet applications and the like. In recent years, the bidding mode in internet advertisement also goes through many different stages, from the beginning of CPM bidding (Cost Per mill, thousands of bids), to CPC bidding (Cost Per Click) bidding mode, to the latter intelligent bidding products, including tcap (target CPA, target conversion bid), based on which bidding is performed, the algorithm converts the advertiser's target bid into Click bid or exposure bid according to the flow and crowd estimated conversion rate, Click rate, in order to reach the advertiser's expected target Cost; eCPC (enhanced CPC, converted CPC for adjusting price), an advertiser manually bids through the CPC, and the algorithm adjusts the price up and down in the price adjusting range according to the flow conversion rate, so that the ROI and the conversion amount can be increased.

However, the above mentioned advertisement bidding products have some problems, for example, for the traditional bidding methods, such as CPC and CPM bidding, which do not use algorithm to adjust price, and use the same bidding for different quality of traffic, so the conversion rate, ROI (Return On Investment), etc. of the advertisement unit are significantly lower than the intelligent bidding products. For several intelligent bidding products in the bidding products, the service scene is single, and the method has limitation, and the price adjustment based on the current flow conversion rate only meets the conversion requirement of the advertiser but does not meet the diversified scene appeal of the advertiser. Therefore, no matter the traditional bidding mode or the existing intelligent bidding mode is limited to convert the final link target of the e-commerce and cannot meet the requirement of activity type and brand type advertiser drainage, under the current scene, the advertiser still uses the traditional CPC bidding mode, cannot introduce more UV (Visitor) quantity under the same consumption, and the UV cost is high.

At present, no proper algorithm exists for the optimization of the drainage target, and an advertiser puts in the advertisement with fixed budget according to the traditional CPC bidding mode in the process of putting the advertisement, and manually creates different plans and sets different bids for different crowds.

To solve the above problem and optimize the cost of visitors, the exemplary embodiment first provides a data processing method, which can be applied to the advertisement bidding product to obtain eUV (enhanced UV, visitor cost optimized price adjustment) bidding mode. The bidding mode can meet the conversion requirement, can also find out the requirement of an advertiser on the cost of visitors in actual delivery, and achieves the purpose of optimizing the cost of visitors aiming at brand advertisements and activity advertisements under the condition that the advertiser pays attention to the overall UV cost. Referring to fig. 1, the data processing method may include the steps of:

s110, obtaining each piece of information to be displayed of a user platform to which the information belongs, dividing the information to be displayed into a plurality of information units, and dividing the information to be displayed in each information unit into an original value information set and an adjustment value information set.

S120, obtaining historical data of a user platform to which the target user calls information through the information to be displayed in different information display platforms, and determining the user type and the call probability of the target user in each information display platform according to the historical data.

And S130, determining an adjusting coefficient according to the user type of the target user, and adjusting the value data of the information to be displayed in the adjusting value information set according to the calling probability and the adjusting coefficient.

And S140, obtaining a cost parameter of the information to be displayed according to the value data of the information to be displayed and the call-up probability of the target user.

S150, pushing the cost parameters of the information to be displayed in the original value information set and the cost parameters of the information to be displayed in the adjusted value information set to an information display platform for comparison and display.

The above steps of the present exemplary embodiment will be described in more detail with reference to fig. 2 and 3.

In step S110, each piece of information to be displayed of the user platform to which the information belongs is acquired, the information to be displayed is divided into a plurality of information units, and the information to be displayed in each information unit is divided into an original value information set and an adjusted value information set.

In this exemplary embodiment, the user platform to which the information belongs refers to a user platform to which an advertiser is located, and the information to be displayed is an advertisement to be delivered by the advertiser. The information elements refer to eUV ad elements created by the advertiser.

In this exemplary embodiment, as shown in fig. 2, dividing information to be displayed into a plurality of information units, and dividing information to be displayed in each information unit into an original value information set and an adjusted value information set, may specifically include the following steps:

and S210, dividing the information to be displayed into different information units according to the information type of the information to be displayed.

First, the advertiser creates eUV ad units based on the type of information, i.e., the type of advertisement, of the different information to be presented.

In this example embodiment, the advertiser need not create different CPC units for different demographics and traffic, and only need eUV to reach the automatic pricing of the algorithm.

Step S220, acquiring first attribute identification information of the information to be displayed, and dividing the information to be displayed in each information unit into an original value information set and an adjusted value information set according to a preset proportion according to the first attribute identification information.

The first attribute identification information refers to a character string formed by splicing a plurality of attribute information of the information to be displayed, not only contains a plurality of attribute information of the information to be displayed, but also can be used for distinguishing different information to be displayed and grouping the information to be displayed.

In this example embodiment, the first attribute identification information of the information to be displayed is obtained by obtaining a plurality of attribute information of the information to be displayed, splicing the plurality of attribute information of the information to be displayed according to a preset sequence, and converting the spliced information into the first attribute identification information of the information to be displayed through a hash function.

For example, the advertisement server may perform character string splicing according to an advertisement user ID (Identity document), a terminal device ID, a user account, an advertisement type identifier, and an advertisement unit identifier, and output first attribute identification information of the advertisement through a hash function.

After first attribute identification information of the information to be displayed is obtained, the information to be displayed in each information unit is sequentially divided into an original value information set and an adjustment value information set according to a preset proportion. The value data of the information to be displayed in the original value information set is set according to the original value data, and the value data of the information to be displayed in the adjusted value information set is adjusted according to the subsequent steps.

For example, an advertiser may adjust the consumption rate in the original value information set and the adjusted value information set to 20%: 80 percent, the advertisement in the original value information set is bid by adopting a CPC request set by an advertiser without adjusting the price, the advertisement in the adjusted value information set is logically adjusted in price, and finally the advertisement is pushed to a delivery end to allow the advertiser to visually check eUV the difference of UV related data between the adjusted price and the traditional CPC bidding mode.

In step S120, historical data of a user platform to which the target user calls information through information to be displayed in different information display platforms is obtained, and the user type and the call probability of the target user in each information display platform are determined according to the historical data.

In this exemplary embodiment, the call-up probability of the target user may be estimated through historical data accumulated in a preset time period. The method for acquiring the historical data of the user platform to which the target user calls the information to be displayed in different information display platforms specifically comprises the following steps:

acquiring second attribute identification information of information to be displayed when a target user calls a first type page and a second type page of a user platform to which the information belongs through the information to be displayed in different information display platforms within a preset time period; and generating historical data of the information to be displayed according to the second attribute identification information of the information to be displayed.

In the internet advertisement, the first type page refers to a H5 page, i.e., a page implemented in compliance with the HTML5(Hyper Text Markup Language5, a Language description way of constructing Web content), and the second type page refers to a native page. In the present exemplary embodiment, only the above-described two types of pages are counted.

The second attribute identification information of the advertisement can be obtained according to the terminal device ID, the terminal device type (ios system or android system), the advertisement type identification and the page type identification of the advertisement delivery. The call-up rate in the historical time period can be calculated by counting the call-up conditions of the users in each channel, storing the counted call-up states and call-up rates of the users in different channels into a Jimdb library and a User library, carrying out total update every day and updating the increment every hour.

When the user type and the calling probability of a target user in each information display platform are determined according to historical data, if the target user calls the user platform to which information to be displayed belongs through the information to be displayed in the information display platform, the target user is marked as a first target user, and the calling probability of the first target user is determined as a first probability value; if the target user calls a user platform to which the information belongs through the information to be displayed in other information display platforms, marking the target user as a second target user, and determining the call probability of the second target user as a second probability value according to historical data; and if the target user does not call the user platform to which the information to be displayed belongs through any information display platform, marking the target user as a third target user, and determining the call probability of the third target user as a third probability value.

In this exemplary embodiment, the first target user refers to a target user who has called a user platform to which the information belongs through a channel of the information presentation platform, and the call probability p of the target user can be set to 1; the second target user refers to a user platform to which the information belongs but is not called through the channel of the information display platform, but the user platform to which the information belongs is called through the channels of other information display platforms, and the calling probability p of the part of users is based on the calling rate of historical statistics; the third target user refers to a target user who has not called the user platform to which the information belongs from any channel of the information presentation platform, and the calling probability p of the third target user can be set to 0.

In step S130, an adjustment coefficient is determined according to the user type of the target user, and the value data of the information to be displayed in the adjustment value information set is adjusted according to the call-up probability and the adjustment coefficient.

In the present exemplary embodiment, when determining the adjustment coefficient according to the user type of the target user, the adjustment coefficients of the first target user and the second target user are set in the first coefficient adjustment interval; and setting the adjustment coefficient of the third target user in the second coefficient adjustment interval.

Since the first target user and the second target user are target users who have called the user platform to which the information belongs, and the third target user is a target user who has not called the user platform to which the information belongs, different adjustment coefficients need to be set for them. For example, the adjustment coefficients of the first target user and the second target user may be set in the first coefficient adjustment interval [1, 1.2], the adjustment coefficient of the third target user may be set in the second coefficient adjustment interval [0, 1], and then the specific adjustment coefficient is further determined according to the total value consumption.

In this exemplary embodiment, as shown in fig. 3, the method for adjusting the value data of the information to be displayed in the adjustment value information set according to the call-up probability and the adjustment coefficient may specifically include the following steps:

and S310, acquiring original value data of the information to be displayed.

In the internet advertisement putting, the original value data of the information to be displayed refers to the original advertisement bid, and the advertiser can set the CPC request bid.

And S320, determining the total consumption of the information to be displayed in the original value information set according to the number of target users of the information to be displayed in the original value information set and the original value data of the information to be displayed.

The total consumption of the information to be displayed is the product of the number of target users and the original value data of the information to be displayed. Wherein, the target user number is the product of the total user number and the call-starting probability.

And S330, determining the total consumption of the information to be displayed in the adjusted value information set according to the total consumption of the information to be displayed in the original value information set.

Because the information to be displayed in the original value information set and the adjusted value information set is distributed according to the preset proportion, the total consumption is calculated according to the fixed proportion. For example, if the consumption ratio of the original value information set and the adjusted value information set is controlled at 20%: 80%, in order to use the consumption of the original value information set as a price adjustment basis of the adjustment value information set, determining the total consumption of the information to be displayed in the adjustment value information set as 1/4 of the total consumption of the information to be displayed in the original value information set, so as to ensure that the consumption ratio of the original value information set to the adjustment value information set is controlled to be 1: 4.

step S340, determining a first target adjustment coefficient from the first coefficient adjustment interval according to the total consumption of the information to be displayed in the adjustment value information set, and determining a second target adjustment coefficient from the second coefficient adjustment interval.

In the present exemplary embodiment, the coefficients need to be adjusted according to the consumption proportions of the original value information set and the adjusted value information set. When 1/4 the consumption of the adjustment value information set is larger than the consumption of the original value information set, the coefficient is reduced, wherein the adjustment coefficient of the user who does not call is reduced preferentially until the consumption is leveled; if the adjustment coefficient of the un-called subscriber has been adjusted to 0, the adjustment coefficients of the part of subscribers that can be called are adjusted down. When the consumption of the adjusted value information set is less than that of the original value information set at 1/4, the adjustment coefficient is increased, wherein the adjustment coefficients of the part of the users which can be called are preferentially increased until the consumption is leveled, and if the adjustment coefficients of the part of the users which can be called are adjusted to the upper limit of 1.2, the adjustment coefficients of the users which are not called are increased.

The regulation and control of the adjustment coefficient can be realized according to PID control (proportional (proportion), integral (integral) and differential (differential) controllers), and specific parameters are as follows: the error term cost _ error ═ 1/4 adjusted value information set consumption-original value information set consumption)/original value information set consumption. The proportion term is as follows: the adjusted and original value information sets consume a difference, cost _ error, every half hour. Integral term: accumulation of error terms for the last 3 hours, i.e., integral _ cost _ error1+ cost _ error2+ cost _ error3+ cost _ error4+ cost _ error5+ cost _ e rror6, where cost _ error1 through cost _ error6 are error terms for every half hour of the last 3 hours. A differential term: the difference between the current error term and the previous 3-hour error term, i.e., derivative _ error7-cost _ error8, where cost _ error7 is the current error term and cost _ error8 is the error term for the previous 3-hour whole.

And S350, determining the value data of the information to be displayed in the adjustment value information set called by the first target user according to the original value data, the first target adjustment coefficient and the first probability value of the information to be displayed.

The value data of the information to be displayed called by the first target user is the product of the original value data, the first target adjustment coefficient and the first probability value.

And S360, determining the value data of the information to be displayed in the adjustment value information set called by the second target user according to the original value data of the information to be displayed, the first target adjustment coefficient and the second probability value.

The value data of the information to be displayed called by the second target user is the product of the original value data, the second target adjustment coefficient and the second probability value.

And step S370, determining the value data of the information to be displayed in the adjustment value information set called by the third target user according to the original value data of the information to be displayed, the second target adjustment coefficient and the third probability value.

And the value data of the information to be displayed called by the third target user is the product of the original value data, the third target adjustment coefficient and the third probability value.

In step S140, a cost parameter of the information to be displayed is obtained according to the value data of the information to be displayed and the call probability of the target user.

The cost parameter of the information to be displayed is the quotient of the total consumption of the information to be displayed and the number of the called target users, wherein the total consumption of the information to be displayed is the product of the value data of the information to be displayed and the total number of the target users.

For example, an advertisement in the original value information set bids 1 yuan, and competes for 50 users, consuming 50 yuan. Assuming that the call-up rate of the platform is advertised to be 50%, i.e., 25 users are called up, the UV cost of the information to be presented is the number of consumed/called-up UV, and the UV cost is 2 yuan.

For example, the cost parameter obtained by adjusting the value data of the information to be displayed in the adjustment value information set according to the call-up probability and the adjustment coefficient may include the following two cases:

the first condition is as follows: the consumption situation is satisfied only by bidding on the part of the users who can be called.

The bid price of the user capable of calling in the value information set is gradually increased from 1 yuan to 1.2 yuan, and the consumption is between 50 and 60 yuan if 50 users are competitive in total, because the part of users have historical calling records in the last month, and the UV cost is between 1.25 and 1.5 yuan and is lower than 2 yuan of the original bid group if the calling rate is 80% and the number of calling users is 50 x 80% — 40.

Case two: a situation is required where the user who has not called also bids.

The bid price of the user capable of calling in the adjusted value information set is gradually increased from 1 yuan to 1.2 yuan, and the number of the calling users is 20 on the assumption that 25 users are bid and consumed between 25-30 yuan, and the calling rate of the part of users is 80%.

If the price of the user who does not call is increased gradually from 0 to 0.5 and 80 users are bid, the consumption is between 0 and 40 yuan, and the call-up rate of the user is low, namely 20%, the call-up user is 16; at the moment, the total consumption in the adjustment value information set is between 25 and 70 RMB, the number of the called UV is 36 in total, the UV cost is between 0.69 and 1.94 RMB, and is lower than 2 RMB of the original bidding group.

In step S150, the cost parameter of the information to be displayed in the original value information set and the cost parameter of the information to be displayed in the adjusted value information set are pushed to the information display platform for comparison and display.

After the information to be displayed is subjected to call starting point click duplication elimination based on the ID of the terminal equipment, the cost parameters of the information to be displayed in the original value information set and the cost parameters of the information to be displayed in the adjusted value information set are pushed to an information display platform for comparison display, so that the advertiser can clearly determine eUV implementation effect.

According to experimental data, the eUV advertisement bidding method obtained by the data processing method in the exemplary embodiment can reduce the UV cost by about 10% -60% under different conditions, and the call-up rate is obviously improved. The UV cost is significantly reduced whether by plan level comparison or by ad spot specification level comparison.

Fig. 4 shows a complete flowchart in one embodiment of the present disclosure, which is an illustration of the above steps in this exemplary embodiment, and the specific steps in the flowchart are as follows:

step S410. create eUV an ad unit.

And S420, dividing each advertisement unit into a price adjustment effective group and an original bidding group.

The original bid group adopts CPC set by the advertiser to bid the request, and does not adjust the price; the price-adjusting effective group carries out logic price adjustment according to the method in the disclosure, and the consumption proportion of the original bidding group and the price-adjusting effective group is controlled to be 20%: 80 percent.

And S430, calculating the call-up rate of the user and estimating the call-up probability.

And counting the calling state and the calling rate of the User in each media, storing the counted calling state and the calling rate of the User in a Jimdb library and a User library in different channels, updating the calling state and the calling rate of the User in the morning all the time every day, and updating the increment every hour.

And S440, obtaining a price adjustment coefficient.

Setting the calling-up user's tuning coefficient as bid _ server _ call _ ratio with interval of [1, 1.2], setting the calling-up user's tuning coefficient as bid _ server _ notcall _ ratio with interval of [0, 1], wherein the adjustment of the coefficient is determined by comparing the consumption proportion of the original bid group and the tuning effective group of 1/4.

And S440, adjusting the price of the price adjusting effective group by taking the UV call-in probability as a reference.

For the user capable of calling, the Bid is Bid, and the user incapable of calling is Bid.

And S460, controlling the consumption proportion of the price-adjusting effective group and the original bid group.

The original bid group and the price-adjusted effect group are in terms of flow 20%: 80% of the original bidding groups are divided, the purpose is to take the consumption of the original bidding groups as the price adjusting basis of the price adjusting effective groups, and simultaneously, the contrast effect is presented to the advertiser, so that the consumption proportion of the price adjusting effective groups and the original bidding groups is controlled to be 4: 1.

and S470, displaying the data after the data are removed from the duplicate at the releasing end for comparison and display.

And (4) carrying out equipment ID-based call start point duplicate removal on the data, calculating call start rate, UV cost and other indexes, and displaying the indexes on a delivery end for an advertiser to clearly define eUV effects.

And S480, finishing the releasing.

Fig. 5 is a block flow diagram for calculating the call-up probability in an embodiment of the present disclosure, which is an illustration of the step S430, and the specific content of the block flow diagram is as follows:

firstly, data are obtained through an advertisement exposure click stream 501, then, in the User dimension, the call starting state of a User is counted through a media call starting state counting module 502 of the User, and the call starting state is stored in a Jimdb library 503 and a User library 504; in the dimension of the advertisement space, the call-up rate of the user is counted by the call-up rate counting module 505 and stored in the domain name call-up rate word list 506. On the other hand, the UV cost targeted advertisement unit 508 is acquired through the data retrieval module 507, the user call-up information 510 is acquired through the user server 509, the calculation of the call-up probability is performed in the UV call-up probability calculation module 512 in the advertisement server 511 in combination with the call-up rate of the user, and finally the calculation result is input into the advertisement bidding module 513 for subsequent application.

It should be noted that although the various steps of the methods of the present disclosure are depicted in the drawings in a particular order, this does not require or imply that these steps must be performed in this particular order, or that all of the depicted steps must be performed, to achieve desirable results. Additionally or alternatively, certain steps may be omitted, multiple steps combined into one step execution, and/or one step broken down into multiple step executions, etc.

Further, the present disclosure also provides a data processing apparatus. Referring to fig. 6, the data processing apparatus may include an information to be presented dividing module 610, a call-up probability determining module 620, a value data adjusting module 630, a cost parameter determining module 640, and a parameter comparison presenting module 650. Wherein:

the to-be-displayed information dividing module 610 may be used as an to-be-displayed information dividing module, and is configured to acquire each to-be-displayed information of a user platform to which the information belongs, divide the to-be-displayed information into a plurality of information units, and divide the to-be-displayed information in each information unit into an original value information set and an adjusted value information set;

the call-out probability determining module 620 may be configured to obtain historical data of a user platform to which the target user calls out information through information to be displayed in different information display platforms, and determine a user type and a call-out probability of the target user in each information display platform according to the historical data;

the value data adjusting module 630 may be configured to determine an adjustment coefficient according to the user type of the target user, and adjust the value data of the information to be displayed in the adjustment value information set according to the call probability and the adjustment coefficient;

the cost parameter determining module 640 may be configured to obtain a cost parameter of the information to be displayed according to the value data of the information to be displayed and the call-up probability of the target user;

the parameter comparison and display module 650 may be configured to push the cost parameter of the information to be displayed in the original value information set and the cost parameter of the information to be displayed in the adjusted value information set to the information display platform for comparison and display.

In some exemplary embodiments of the present disclosure, the to-be-presented information dividing module 610 may include an information unit dividing unit and an information set dividing unit. Wherein:

the information unit dividing unit can be used for dividing the information to be displayed into different information units according to the information type of the information to be displayed;

the information set dividing unit may be configured to acquire first attribute identification information of information to be displayed, and divide the information to be displayed in each information unit into an original value information set and an adjusted value information set according to a preset ratio according to the first attribute identification information.

In some exemplary embodiments of the present disclosure, the information set dividing unit may include a unit and a first attribute identification information determining unit. Wherein:

the attribute information acquisition unit can be used for acquiring a plurality of attribute information of the information to be displayed;

the first attribute identification information determining unit may be configured to splice a plurality of attribute information of the information to be displayed according to a preset sequence, and convert the multiple attribute information into the first attribute identification information of the information to be displayed through a hash function.

In some exemplary embodiments of the present disclosure, the call origination probability determination module 620 may include a unit and a historical data generation unit. Wherein:

the second attribute identification information determining unit may be configured to obtain second attribute identification information of the information to be displayed when the target user calls the first type page and the second type page of the user platform to which the information belongs through the information to be displayed in different information display platforms within a preset time period;

the historical data generating unit may be configured to generate historical data of the information to be displayed according to the second attribute identification information of the information to be displayed.

In some exemplary embodiments of the present disclosure, the origination probability determination module 620 may further include a first target user probability determination unit, a second target user probability determination unit, and a third target user probability determination unit. Wherein:

the first target user probability determining unit may be configured to mark the target user as a first target user and determine the call probability of the first target user as a first probability value if the target user calls the user platform to which the information to be displayed in the information display platform belongs;

the second target user probability determining unit may be configured to mark the target user as a second target user if the target user calls the user platform to which the information to be displayed in the other information display platforms belongs through the information to be displayed, and determine the call probability of the second target user as a second probability value according to the history data;

the third target user probability determining unit may be configured to mark the target user as a third target user and determine the call-up probability of the third target user as a third probability value if the target user does not call up the user platform to which the information to be displayed in any information display platform belongs.

In some exemplary embodiments of the present disclosure, the value data adjusting module 630 may include first and second adjustment coefficient determining units and a third adjustment coefficient determining unit. Wherein:

the first and second adjustment coefficient determining units may be configured to set adjustment coefficients of the first target user and the second target user in a first coefficient adjustment interval;

the third adjustment coefficient determination unit may be configured to set the adjustment coefficient of the third target user in the second coefficient adjustment section.

In some exemplary embodiments of the present disclosure, the value data adjusting module 630 may further include an original value data acquiring unit, an original information total consumption determining unit, an adjustment information total consumption determining unit, a target adjustment coefficient determining unit, a first value data determining unit, a second value data determining unit, and a third value data determining unit. Wherein:

the original value data acquisition unit can be used for acquiring original value data of the information to be displayed;

the original information total consumption determining unit can be used for determining the total consumption of the information to be displayed in the original value information set according to the number of target users of the information to be displayed in the original value information set and the original value data of the information to be displayed;

the adjustment information total consumption determining unit may be configured to determine total consumption of information to be displayed in the adjustment value information set according to total consumption of information to be displayed in the original value information set;

the target adjustment coefficient determining unit may be configured to determine a first target adjustment coefficient from the first coefficient adjustment interval according to total consumption of information to be displayed in the adjustment value information set, and determine a second target adjustment coefficient from the second coefficient adjustment interval;

the first value data determining unit can be used for determining the value data of the information to be displayed in the adjustment value information set called by the first target user according to the original value data, the first target adjustment coefficient and the first probability value of the information to be displayed;

the second value data determining unit can be used for determining the value data of the information to be shown in the adjustment value information set called by the second target user according to the original value data of the information to be shown, the first target adjustment coefficient and the second probability value;

the third value data determining unit may be configured to determine, according to the original value data of the information to be presented, the second target adjustment coefficient, and the third probability value, value data of the information to be presented in the adjustment value information set called by the third target user.

The details of each module/unit in the data processing apparatus have been described in detail in the corresponding method embodiment section, and are not described herein again.

FIG. 7 illustrates a schematic structural diagram of a computer system suitable for use with the electronic device to implement an embodiment of the invention.

It should be noted that the computer system 700 of the electronic device shown in fig. 7 is only an example, and should not bring any limitation to the function and the scope of the application of the embodiment of the present invention.

As shown in fig. 7, the computer system 700 includes a Central Processing Unit (CPU)701, which can perform various appropriate actions and processes in accordance with a program stored in a Read Only Memory (ROM)702 or a program loaded from a storage section 708 into a Random Access Memory (RAM) 703. In the RAM 703, various programs and data necessary for system operation are also stored. The CPU 701, the ROM 702, and the RAM 703 are connected to each other via a bus 704. An input/output (I/O) interface 705 is also connected to bus 704.

The following components are connected to the I/O interface 705: an input portion 706 including a keyboard, a mouse, and the like; an output section 707 including a display such as a Cathode Ray Tube (CRT), a Liquid Crystal Display (LCD), and the like, and a speaker; a storage section 708 including a hard disk and the like; and a communication section 709 including a network interface card such as a LAN card, a modem, or the like. The communication section 709 performs communication processing via a network such as the internet. A drive 710 is also connected to the I/O interface 705 as needed. A removable medium 711 such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, or the like is mounted on the drive 710 as necessary, so that a computer program read out therefrom is mounted into the storage section 708 as necessary.

In particular, according to an embodiment of the present invention, the processes described below with reference to the flowcharts may be implemented as computer software programs. For example, embodiments of the invention include a computer program product comprising a computer program embodied on a computer-readable medium, the computer program comprising program code for performing the method illustrated in the flow chart. In such an embodiment, the computer program can be downloaded and installed from a network through the communication section 709, and/or installed from the removable medium 711. The computer program executes various functions defined in the system of the present application when executed by a Central Processing Unit (CPU) 701.

It should be noted that the computer readable media shown in the present disclosure may be computer readable signal media or computer readable storage media or any combination of the two. A computer readable storage medium may be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination of the foregoing. More specific examples of the computer readable storage medium may include, but are not limited to: an electrical connection having one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing. In the present disclosure, a computer readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device. In contrast, in the present disclosure, a computer-readable signal medium may include a propagated data signal with computer-readable program code embodied therein, for example, in baseband or as part of a carrier wave. Such a propagated data signal may take many forms, including, but not limited to, electro-magnetic, optical, or any suitable combination thereof. A computer readable signal medium may also be any computer readable medium that is not a computer readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device. Program code embodied on a computer readable medium may be transmitted using any appropriate medium, including but not limited to: wireless, wire, fiber optic cable, RF, etc., or any suitable combination of the foregoing.

The flowchart and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods and computer program products according to various embodiments of the present disclosure. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that, in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams or flowchart illustration, and combinations of blocks in the block diagrams or flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.

As another aspect, the present application also provides a computer-readable medium, which may be contained in the electronic device described in the above embodiments; or may exist separately without being assembled into the electronic device. The computer readable medium carries one or more programs which, when executed by an electronic device, cause the electronic device to implement the method as described in the embodiments below.

It should be noted that although in the above detailed description several modules of the device for action execution are mentioned, this division is not mandatory. Indeed, the features and functionality of two or more of the modules described above may be embodied in one module, in accordance with embodiments of the present disclosure. Conversely, the features and functions of one module described above may be further divided into embodiments by a plurality of modules.

Other embodiments of the disclosure will be apparent to those skilled in the art from consideration of the specification and practice of the disclosure disclosed herein. This application is intended to cover any variations, uses, or adaptations of the disclosure following, in general, the principles of the disclosure and including such departures from the present disclosure as come within known or customary practice within the art to which the disclosure pertains.

It will be understood that the present disclosure is not limited to the precise arrangements described above and shown in the drawings and that various modifications and changes may be made without departing from the scope thereof. The scope of the present disclosure is limited only by the appended claims.

Claims

1. A data processing method, comprising:

2. The data processing method according to claim 1, wherein the dividing the information to be shown into a plurality of information units and dividing the information to be shown in each of the information units into an original value information set and an adjusted value information set comprises:

3. The data processing method according to claim 2, wherein the obtaining of the first attribute identification information of the information to be presented includes:

4. The data processing method according to claim 1, wherein the obtaining of the historical data of the user platform to which the target user calls the information belongs through the information to be displayed in different information display platforms comprises:

5. The data processing method according to claim 1, wherein the determining the user type and the call-up probability of the target user in each of the information presentation platforms according to the historical data comprises:

6. The data processing method of claim 5, wherein the determining an adjustment factor according to the user type of the target user comprises:

7. The data processing method according to claim 6, wherein the adjusting the value data of the information to be shown in the adjusted value information set according to the call-up probability and the adjustment coefficient comprises:

acquiring original value data of the information to be displayed;

8. A data processing apparatus, comprising:

9. An electronic device, comprising:

a processor; and

memory for storing one or more programs which, when executed by the one or more processors, cause the one or more processors to implement a data processing method as claimed in any one of claims 1 to 7.

10. A computer-readable medium, on which a computer program is stored, which, when being executed by a processor, carries out the data processing method of any one of claims 1 to 7.