CN105931076A - Advertisement price adjustment device and method based on real-time bidding - Google Patents
Advertisement price adjustment device and method based on real-time bidding Download PDFInfo
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- CN105931076A CN105931076A CN201610243243.7A CN201610243243A CN105931076A CN 105931076 A CN105931076 A CN 105931076A CN 201610243243 A CN201610243243 A CN 201610243243A CN 105931076 A CN105931076 A CN 105931076A
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q30/00—Commerce
- G06Q30/02—Marketing; Price estimation or determination; Fundraising
- G06Q30/0241—Advertisements
- G06Q30/0249—Advertisements based upon budgets or funds
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q30/00—Commerce
- G06Q30/02—Marketing; Price estimation or determination; Fundraising
- G06Q30/0283—Price estimation or determination
Abstract
The present invention discloses an advertisement price adjustment device and method based on real-time bidding. The device comprises an acquisition module for collecting the data set by an advertiser and an advertisement agency, a statistics module for counting the expense of a day, real-time bidding success rate and the time lengths of purchasing advertising spaces in different schedules, a calculating module for calculating the expense of expected purchased advertising spaces in a unit time and the time of the purchased advertising spaces, a comparison module for comparing an expected bidding success rate and the real-time bidding success rate and comparing the counted purchase expense of the day and the expected purchase expense of the day obtained by the calculation module at the same time, and an adjustment module for adjusting the expected bidding success rate and a target price of purchasing the advertising spaces according to a preset rule according to the comparison result of the comparison module. According to the method, the advertising bidding can be adjusted, as many advertising spaces as possible can be purchased with limited budget, and thus the advertisement agented by the advertiser can obtain more exposures.
Description
Technical field
The present invention relates to advertisement field, particularly relate to a kind of advertising rates based on real time bid and adjust
Regulating device and method.
Background technology
Industry throws in the most fixing bid of mode of advertisement bid at present, and which is with constant valency
Lattice participate in bidding of advertisement transaction platform, remain in the thinking of monthly payment advertisement, are not enough to reply
The change of different periods advertising rates in real time bid.Currently, a kind of new algorithm is needed badly, visitor
After user's orientation and advertising budget are fixed in family, adjustment advertisement bid, so that limited budget exists
Impression as much as possible can have been bought in the time of regulation.
Summary of the invention
The technical problem that present invention mainly solves is to provide a kind of advertising rates based on real time bid
Adjusting means and method, it is possible to adjust advertisement bid, so that limited budget can have been bought the most
Advertisement position, the advertisement making advertiser act on behalf of obtains more impression.
For solving above-mentioned technical problem, the technical scheme that the present invention uses is: provide a kind of base
In the advertising rates adjusting means of real time bid, including: acquisition module, it is used for gathering advertiser and sets
Spent budget, target price and the ceiling price of purchase advertisement position the fixed same day, browsed according to netizen
The webpage time set to the waiting of release time and in different waitings advertiser buy advertisement position
Weight, gather the expectation that the ad-agency of advertiser sets and bid success rate, adopt in real time simultaneously
Collection ad-agency calculated real time bid success rate；Wherein, waiting include the first waiting,
Second waiting ..., the n-th waiting；Statistical module, is used for adding up advertiser and spent the same day,
Set the real time bid success rate in time interval the last period of current time and in different waitings
The time span of interior purchase advertisement position, wherein, time span include the very first time, second time
Between ..., the n-th time；Computing module, for obtain according to acquisition module and statistical module
Data, the cost V of the anticipated purchase advertisement position in the unit of account time and bought advertisement position time
Between T, the two product is the anticipated cost buying advertisement position, and wherein, the computing formula spending V is
V=spent the same day budget/(first waiting * the first weight the+the second waiting * the second weight+...+the n-th
Waiting * the n-th weight)；The computing formula of time T is to weigh T=the first weight * very first time+the second
Second time of weight *+... the+the n-th n-th time of weight *；Contrast module, is used for contrasting expectation and bids
Success rate and real time bid success rate, cost and the meter that the same day obtained has been bought is added up in contrast simultaneously
Calculate module and estimate the cost of purchase the calculated same day；And, adjustment module, for according to right
The ratio comparing result of module, is expected bid success rate and buy the mesh of advertisement position by preset rules regulation
Marked price lattice.
For solving above-mentioned technical problem, the technical scheme that the present invention uses is: provide a kind of base
In the advertising rates control method of real time bid, the step of the method includes: gathers advertiser and sets
The same day spend budget, buy advertisement position target price and ceiling price, browse net according to netizen
The page time set to the waiting of release time and in different waitings advertiser buy advertisement position
Weight, gathers the expectation that the ad-agency of advertiser sets and bids success rate, simultaneously Real-time Collection
Ad-agency calculated real time bid success rate；Wherein, waiting include the first waiting,
Two waitings ..., the n-th waiting；Statistics advertiser spent the same day, the last period of current time
Set the real time bid success rate in time interval and buy in different waitings advertisement position time
Between length, wherein, time span includes the very first time, the second time ..., the n-th time；
According to the data obtained, the cost V of the anticipated purchase advertisement position in the unit of account time and having bought
The time T of advertisement position, the two product is the anticipated cost buying advertisement position, wherein, spends V's
Computing formula is that V=spent budget/(first waiting * the first weight the+the second waiting * the second weight the same day
+ ...+the n-th waiting * the n-th weight)；When the computing formula of time T is T=the first weight * the first
Between the+the second second time of weight *+... the+the n-th n-th time of weight *；Contrast expectation is bidded successfully
Rate and real time bid success rate, cost that contrast statistics simultaneously has been bought same day of obtaining and calculate mould
Block estimated the cost of purchase the calculated same day；According to comparing result, regulate the phase by preset rules
Hope and bid success rate and buy the target price of advertisement position.
Being different from prior art, the advertising rates adjusting means based on real time bid of the present invention connects
Buy the purchase module of advertisement position to advertiser, automatically adjust bid price, in advertisement in one day
In the input period of main setting, ad-request flow and advertising budget according to different periods control
Bid price, has bought more flow with same budget, that is has bought more impression,
Realize the maximization of income.
Accompanying drawing explanation
Fig. 1 is the structure of a kind of based on real time bid the advertising rates adjusting means that the present invention provides
Schematic diagram；
Fig. 2 is the flow process of a kind of based on real time bid the advertising rates control method that the present invention provides
Schematic diagram.
Detailed description of the invention
Make to retouch the most in more detail to technical scheme below in conjunction with detailed description of the invention
State.Obviously, described embodiment is only a part of embodiment rather than all of the present invention
Embodiment.Based on the embodiment in the present invention, those of ordinary skill in the art are not making wound
The every other embodiment obtained on the premise of the property made work, all should belong to the model of present invention protection
Enclose.
RTB (RealTime Bidding) real time bid, be one utilize third party technology number with
Show, for each user, the skill of bidding that behavior is estimated and bids on the website of million meters
Art.Different from making a big purchase the input frequency in large quantities, real time bid has been evaded invalid audient and has been arrived, for
Significant user buys.Its core is DSP platform (party in request's platform).RTB pair
For media, more advertisement sales volume can be brought, realize sales process automatization and lower each
The expenditure of item expense.And for advertiser and agency, the most direct benefit improves exactly
Effect and rate of return on investment.
RTB is not fangle, and in advertising sector, what's frequently heard can be repeated in detail already for it.Traditional interconnection
Net advertisement ecological chain the most at most only has tripartite, is advertiser, advertiser (i.e. advertising company) respectively
And the Internet media.And in RTB advertisement trade mode, original advertisement ecological chain there occurs
Change, whole ecological chain includes advertiser, DSP, advertisement transaction platform and the Internet media four
Individual main body.The want advertisement of oneself is put in DSP platform by advertiser, and the Internet media is by oneself
Ad traffic resource be put into advertisement transaction platform, DSP is by the technology pair with advertisement transaction platform
Connect purchase of bidding.
Therefore, when user accesses a website, SSP i.e. media service platform is to Ad Exchange
Advertisement transaction platform sends user and accesses signal, and the specifying information of advertisement position then can be through DMP subsequently
It is sent to DSP after the analysis coupling of (Data-Management Platform) i.e. data management platform,
This will be bidded by DSP, and valency height person can obtain this showing advertisement chance, and by targeted customer
Seeing and complete from starting to bid to throw in, this series of process only needs 50 milliseconds, all
Support machine completes.
Tradable commodity under RTB advertisement mode is no longer media advertisement position, but user.In reality
In running, RTB advertisement mode exposes according to the displaying of each user, is supporting Wei Kerui auction
Carrying out real time bid in the environment of pattern, this is a kind of based on auction theory flexible, fair, saturating
Bright pricing method.Multiple buyeies (DSP platform) are according to constraints and the assessment of Flow Value
Bidding, seller's (SSP platform) is according to oneself service ability and level charge, in auction simultaneously
Jie's (Ad Exchange platform) safeguards that auction rules, ruling highest bidder obtain this user's
Show chance for exposure.Finally, transaction value pays with the second high bid.This mode can be encouraged
The buyer makes a higher bid, and makes media resource provider obtain bigger income.Specifically, RTB
The flow process of bidding of advertisement mode is through three steps: the first step, media resource provider (SSP)
ID, ad spot information, lowest offer etc. are provided to advertisement transaction platform；Second step, advertisement
Transaction platform invites the bid of each big advertiser agent (DSP)；3rd step, each big advertiser's generation
Reason business (DSP) decides whether bid by the analysis being worth this user and goes out how many valencys, by extensively
Accuse the transaction platform ruling the highest DSP of bid and obtain the advertising display chance of this user.
The most key in this auction flow process is the bidding strategies of advertiser agent (DSP).
Due to advertiser's purchase is no longer certain media advertisement position, but certain specific user.Advertisement
Whether master agent business (DSP) bids and goes out how many valencys, is built upon having this user how much
On the basis of solution, this is accomplished by, by big data technique, digging user behavior and relevant information
Pick and in-depth analysis.Therefore, bid process is no longer necessary to pay close attention to the bid feelings of other rivals
Condition, strategy and overall market assessment, it is not required that consider the market supply and demand situation of media resource, and
Being that main attention is placed in the data mining to targeted customer and value assessment, this just promotes advertisement
Master agent industry (DSP platform) seeks technological innovation, utilizes information technology and data, services to make mutually
The commercially available more preferable resource distribution of networked advertisement.
It addition, the real-time of RTB advertisement mode running so that effect of advertising feedback is also real-time,
Thus the price for RTB advertisement mode provides more efficient adjustment space.Advertiser agent
(DSP) reality can be carried out according to the live effect data that certain user is thrown in throwing in strategy
Shi Youhua.If it is to say, effect fails to reach expection, then upper once bid time just may be used
Reduce bid, or no longer this user is bidded.So guarantee that advertiser's media throw in expense
Maximizing the benefits.
As can be seen here, under RTB advertisement mode, on the one hand, size advertiser can be with together
Run and bid with numerous competitor's justices on line, and price transparent.On the other hand, RTB advertisement mould
Formula makes website three, the residue stock of the level Four page and medium and small website can also participate in advertisement transaction
, obtain income with reasonable prices.Additionally, each advertisement position resource is because of the visit of different user
Ask and can repeat to sell in one day, thus improve media income.
Present invention advertising rates based on real time bid adjusting means controls to buy advertisement by regulation
The price of position, is advertiser or advertiser has bought more flow, Yi Jimai with same budget
To more impression, it is achieved the maximization of income.
It is a kind of based on real time bid the advertising rates regulation that the present invention provides refering to Fig. 1, Fig. 1
The structural representation of device.This device 100 includes: acquisition module 110, statistical module 120,
Computing module 130, contrast module 140 and adjustment module.
Wherein, to connect advertiser wide for buying the purchase module of advertisement position and this for acquisition module 110
Accuse main ad-agency 101, spend the same day set for gathering advertiser budget, purchase wide
Accuse target price and the ceiling price of position, browse the setting of webpage time according to netizen to the release time
Waiting and in different waitings advertiser buy the weight of advertisement position, gather the advertisement generation of advertiser
The expectation that reason business sets is bidded success rate, and Real-time Collection ad-agency is calculated in real time simultaneously
Bid success rate.Wherein, waiting includes the first waiting, the second waiting ..., the n-th waiting.
In the present embodiment, spent the same day budget D to represent, waiting was divided into three kinds of waitings, respectively
For peak period, common phase and low ebb phase.Selected ' 00', ' 20', ' 21', ' 22', ' 23' these five hours
For peak period, ' 01', ' 02', ' 03', ' 04', ' 05', ' 06', ' 07' these seven hours is the low ebb phase,
Other period is the common phase.Day part is respectively 5 hours, 12 hours and 7 hours.Expect to bid
Success rate is that the ad-agency of advertiser initially sets, and is that ad-agency is according to long-term behaviour
The advertiser that meets of the accumulation setting making experience buys the successful probability of purchase of advertisement position, the widest
Accuse agent and calculate in advertiser's a period of time before current time in real time, buy advertisement position success
Real time bid success rate.In the present embodiment, before real time bid success rate is current time 5
Success rate of bidding in minutes.
Statistical module 120 is added up advertiser and was spent the same day, and the last period of current time sets the time
Real time bid success rate in interval and buy the time span of advertisement position in different waitings, its
In, time span includes the very first time, the second time ..., the n-th time；Current time it
Set the real time bid success rate in time interval the last period and may be set to 5 points before current time
In clock.Time span includes the very first time, the second time and the 3rd time in the present embodiment,
It is illustrated respectively in peak period, common phase and the time span of low ebb phase purchase advertisement position.Statistical module
120 statistics buy the time span of advertisement position in above-mentioned different periods, add up as a, b, c.
The data that computing module 130 obtains according to acquisition module 110 and statistical module 120, calculate
The cost V of the anticipated purchase advertisement position in the unit interval and bought the time T of advertisement position, the two
Product is the anticipated cost buying advertisement position, and wherein, the computing formula spending V is V=flower on the same day
Take budget/(peak period * the first weight+common phase * the second weight+low ebb phase * the 3rd weight)；Time
The computing formula of T is T=the first weight * a+ the second weight * b+ the 3rd weight * c.Wherein, the first power
The most corresponding peak period of weight, the second weight, the 3rd weight, common phase and low ebb phase, peak period is purchased
The number of buying can excess budget average number, and the low ebb phase buys number less than the average number of budget.
Therefore setting the first weight as 1.25, the second weight is 1, and the 3rd weight is 0.5.Therefore the current phase
Hope to buy and spend as VT=D/ (1.25*5+1*12+0.5*7) * (1.25*a+1*b+
0.5*c)=D/21.75* (1.25*a+1*b+0.5*c).
Contrast module 140 contrasts expectation and bids success rate and real time bid success rate, contrasts system simultaneously
Cost that meter has been bought same day of obtaining and computing module estimated the flower bought the calculated same day
Take.Contrast module 140 includes the first contrast unit 141 and the second contrast unit 142.Wherein,
First contrast unit 141 is used for contrasting expectation and bids success rate and real time bid success rate；Second pair
Than unit 142 for the comparing result according to the first contrast unit, the same day that contrast statistics obtains is
The cost bought and computing module 130 estimated the cost of purchase the calculated same day.Real time bid
Success rate is the success rate of bidding of 5 minutes that statistical module 120 statistics obtains.
Adjustment module 150 is according to the comparing result of contrast module 140, by preset rules regulation expectation
Success rate of bidding and the target price of purchase advertisement position.Adjustment module 150 includes that expectation is bidded successfully
Rate regulation unit 151 and target price regulation unit 152, it is desirable to success rate of bidding regulation unit 151
For bidding success rate less than or equal to real time bid success rate and the cost bought the same day in expectation
Turn down expectation when estimating, less than computing module, the cost bought the calculated same day to bid success rate,
Or expectation bid success rate more than real time bid success rate and the cost bought the same day more than meter
Calculate module to estimate to heighten during the cost bought expectation the calculated same day and bid success rate；Target prices
Style joint unit 152 is for and working as less than or equal to real time bid success rate in expectation success rate of bidding
That has bought day heightens when spending the cost estimating purchase more than computing module the calculated same day
Target price, or and bought the same day more than real time bid success rate in expectation success rate of bidding
Target price is turned down when spending the cost estimating purchase less than computing module the calculated same day.
Calculate equal to computing module 120 when contrast module 140 contrasts the cost bought the same day
To the same day estimate buy cost time, target price regulation unit 152 target price is not carried out
Regulation operation.And target price regulation unit 152 is when heightening target price, sets less than advertiser
The fixed ceiling price buying advertisement position.
Being different from prior art, the advertising rates adjusting means based on real time bid of the present invention connects
Buy the purchase module of advertisement position to advertiser, automatically adjust bid price, in advertisement in one day
In the input period of main setting, ad-request flow and advertising budget according to different periods control
Bid price, has bought more flow with same budget, that is has bought more impression,
Realize the maximization of income.
It is a kind of based on real time bid the advertising rates regulation that the present invention provides refering to Fig. 2, Fig. 2
The schematic flow sheet of method.The step of the method includes:
S201: gather advertiser set the same day spend budget, buy advertisement position target price and
Ceiling price, browse the webpage time according to netizen and set the waiting of release time and arrange in difference
In phase, advertiser buys the weight of advertisement position, and the expectation of the ad-agency setting gathering advertiser is competing
Valency success rate, simultaneously Real-time Collection ad-agency calculated real time bid success rate；Wherein,
Waiting includes the first waiting, the second waiting ..., the n-th waiting.
In the present embodiment, spent the same day budget D to represent, waiting be divided into three kinds of waitings,
It is respectively peak period, common phase and low ebb phase.Selected ' 00', ' 20', ' 21', ' 22', ' 23' these five
Hour be peak period, ' 01', ' 02', ' 03', ' 04', ' 05', ' 06', ' 07' these seven hours is low ebb
Phase, other period is the common phase, and day part is respectively 5 hours, 12 hours and 7 hours.Expect
Success rate of bidding is that the ad-agency of advertiser initially sets, and is that ad-agency is according to long-term
Operating experience accumulation set the advertiser that meets buy the successful probability of purchase of advertisement position, with
Time ad-agency calculate in advertiser's a period of time before current time in real time, buy advertisement position
Successfully real time bid success rate.In the present embodiment, real time bid success rate is current time
Success rate of bidding in front 5 minutes.
S202: statistics advertiser spent the same day, and the last period of current time sets in time interval
Real time bid success rate and in different waitings, buy the time span of advertisement position, wherein, time
Between length include the very first time, the second time ..., the n-th time.
Set the real time bid success rate in time interval the last period of current time to may be set to work as
In before the front moment 5 minutes.Time span include in the present embodiment the very first time, second
Time and the 3rd time, be illustrated respectively in peak period, common phase and low ebb phase buy advertisement position time
Between length.Statistics buys the time span of advertisement position in above-mentioned different periods, add up into a, b,
c。
S203: according to the data obtained, the cost of the anticipated purchase advertisement position in the unit of account time
V and bought the time T of advertisement position, the two product is the anticipated cost buying advertisement position, wherein,
The computing formula spending V is that V=spent budget/(first waiting * the first weight the+the second waiting the same day
* the second weight+...+the n-th waiting * the n-th weight)；The computing formula of time T is that T=first weighs
The second time of the+the second weight * weight * very first time+... the+the n-th n-th time of weight *.
The most corresponding peak period of first weight, the second weight, the 3rd weight, common phase and low ebb phase,
Number is bought in peak period can excess budget average number, and the low ebb phase is bought number and puts down less than budget
All numbers.Therefore setting the first weight as 1.25, the second weight is 1, and the 3rd weight is 0.5.Cause
This expectation at present is bought and is spent as VT=D/21.75* (1.25*a+1*b+0.5*c).
S204: contrast expectation is bidded success rate and real time bid success rate, contrast statistics obtains simultaneously
The cost bought on the same day and computing module estimated the cost bought the calculated same day.
Real time bid success rate is the statistics success rate of bidding of 5 minutes.
S205: according to comparing result, bidded success rate by preset rules regulation expectation and bought advertisement
The target price of position.
Bid success rate less than or equal to real time bid success rate and the cost bought the same day in expectation
Turn down expectation when estimating, less than computing module, the cost bought the calculated same day to bid success rate,
Or expectation bid success rate more than real time bid success rate and the cost bought the same day more than meter
Calculate module to estimate to heighten during the cost bought expectation the calculated same day and bid success rate；In expectation
Success rate of bidding less than or equal to real time bid success rate and the cost bought the same day more than calculating mould
Block was estimated to heighten target price during the cost bought the calculated same day, or bidded successfully in expectation
Rate is calculated less than computing module more than real time bid success rate and the cost bought the same day
Estimated the same day to turn down target price during the cost bought.
Contrast to the same day bought spend equal to the calculated same day estimate buy cost time,
Target price is not adjusted operation.And when heightening target price, set less than advertiser
Buy the ceiling price of advertisement position.
Being different from prior art, the advertising rates control method based on real time bid of the present invention passes through
Automatically bid price is adjusted, according to different periods within the input period that advertiser sets in one day
Ad-request flow and advertising budget control bid price, bought more with same budget
Flow, that is bought more impression, it is achieved the maximization of income.
The foregoing is only embodiments of the present invention, not thereby limit the scope of the claims of the present invention,
Every equivalent structure utilizing description of the invention and accompanying drawing content to be made or equivalence flow process conversion, or
Directly or indirectly being used in other relevant technical fields, the patent being the most in like manner included in the present invention is protected
In the range of protecting.
Claims (10)
1. an advertising rates adjusting means based on real time bid, connects advertiser and is used for buying extensively
Accuse purchase module and the ad-agency of described advertiser of position, it is characterised in that including:
Acquisition module, for gather described advertiser set the same day spend budget, buy described extensively
Accuse target price and the ceiling price of position, browse the setting of webpage time according to netizen to the release time
Waiting and in different described waitings described advertiser buy the weight of advertisement position, gather described extensively
Accuse the expectation that main ad-agency sets to bid success rate, simultaneously advertisement agency described in Real-time Collection
Business's calculated real time bid success rate；Wherein, described waiting includes the first waiting, second row
Phase ..., the n-th waiting；
Statistical module, is used for adding up described advertiser and spent the same day, and the last period of current time sets
Fix time interval in real time bid success rate and in different described waitings, buy described advertisement
The time span of position；Wherein, described time span include the very first time, the second time ...,
N-th time；
Computing module, for the data obtained according to described acquisition module and described statistical module, meter
Calculate the cost V of the anticipated purchase advertisement position in the unit interval and bought the time T of described advertisement position,
The two product is the anticipated cost buying described advertisement position；Wherein, the computing formula of described cost V
For V=spent the same day budget/(first waiting * the first weight the+the second waiting * the second weight+...+
N-th waiting * the n-th weight)；The computing formula of described time T is T=the first weight * very first time
+ the second second time of weight *+... the+the n-th n-th time of weight *；
Contrast module, is used for contrasting described expectation and bids success rate and described real time bid success rate,
Cost and described computing module that the described same day that contrast statistics simultaneously obtains has been bought are calculated
The same day estimate buy cost；And,
Adjustment module, for the comparing result according to described contrast module, regulates institute by preset rules
State expect to bid success rate and the target price of described purchase advertisement position.
Advertising rates adjusting means the most according to claim 1, it is characterised in that described right
The first contrast unit and the second contrast unit is included than module；
Wherein, described first contrast unit be used for contrasting described expectation bid success rate and described in real time
Bid success rate；Described second contrast unit is used for the comparing result according to described first contrast unit,
Cost that contrast statistics has been bought described same day of obtaining and described computing module is calculated works as
The day anticipated cost bought.
Advertising rates adjusting means the most according to claim 1, it is characterised in that described tune
Joint module include expectation bid success rate regulation unit and target price regulation unit；
Wherein, described expectation bids success rate regulation unit for little in described expectation success rate of bidding
In the cost bought equal to described real time bid success rate and the described same day less than described calculating mould
Block was estimated to turn down during the cost bought described expectation the calculated same day and is bidded success rate, or in institute
State expectation and bid success rate more than described real time bid success rate and the cost bought the described same day
Estimated to heighten described expectation during the cost of purchase the calculated same day more than described computing module competing
Valency success rate；Described target price regulation unit is for being less than or equal in described expectation success rate of bidding
The cost that described real time bid success rate and the described same day have been bought calculates more than described computing module
Estimated the same day obtained to heighten described target price during the cost bought, or bidded in described expectation
Power more than described real time bid success rate and the cost bought the described same day less than described calculating
Module was estimated to turn down described target price during the cost bought the calculated same day.
Advertising rates adjusting means the most according to claim 3, it is characterised in that when described
That bought the same day spends the cost estimating purchase equal to described computing module the calculated same day
Time, described adjustment module is not adjusted operation.
Advertising rates adjusting means the most according to claim 3, it is characterised in that described mesh
When mark price adjustment unit heightens described target price, less than the highest price buying described advertisement position
Lattice.
6. an advertising rates control method based on real time bid, it is characterised in that including:
The same day gathering described advertiser setting spends budget, buys the target price of described advertisement position
With ceiling price, browse according to netizen the webpage time set to the waiting of release time and in difference
In described waiting, described advertiser buys the weight of advertisement position, gathers the advertisement agency of described advertiser
The expectation that business sets is bidded success rate, the simultaneously calculated reality of ad-agency described in Real-time Collection
Time bid success rate；Wherein, described waiting include the first waiting, the second waiting ..., n-th
Waiting；
Adding up described advertiser to spend the same day, the last period of current time sets in time interval
Real time bid success rate and buy the time span of described advertisement position in different described waitings, its
In, described time span includes the very first time, the second time ..., the n-th time；
According to the data obtained, the cost V of the anticipated purchase advertisement position in the unit of account time and
Buying the time T of described advertisement position, the two product is the anticipated cost buying described advertisement position, its
In, the computing formula of described cost V be V=spent the same day budget/(first waiting * the first weight+
Second waiting * the second weight+...+the n-th waiting * the n-th weight)；The calculating of described time T is public
Formula be T=the second time of the first weight * very first time the+the second weight *+... the+the n-th weight * n-th
Time；
Contrasting described expectation to bid success rate and described real time bid success rate, contrast simultaneously is added up
To the cost bought on the described same day and anticipated bought on described computing module calculated same day
Cost；
According to comparing result, by preset rules regulate described expectation bid success rate and described purchase wide
Accuse the target price of position.
Advertising rates control method the most according to claim 6, it is characterised in that in contrast
Described expectation is bidded success rate and described real time bid success rate, and it is described that contrast statistics simultaneously obtains
Spend and the described computing module bought the same day estimated the cost of purchase the calculated same day
In step, including step:
Contrast described expectation to bid success rate and described real time bid success rate；
According to comparing result, cost and the described calculating that the described same day obtained has been bought is added up in contrast
Module estimated the cost of purchase the calculated same day.
Advertising rates control method the most according to claim 6, it is characterised in that in basis
Comparing result, regulates described expectation by preset rules and bids success rate and the mesh of described purchase advertisement position
In the step of marked price lattice, including step:
Bidded success rate less than or equal to described real time bid success rate and the described same day in described expectation
That has bought adjusts when spending the cost estimating purchase less than described computing module the calculated same day
Low described expectation is bidded success rate, or becomes more than described real time bid in described expectation success rate of bidding
The cost that power and the described same day have been bought was estimated more than described computing module the calculated same day
Heighten described expectation during the cost bought to bid success rate；
Bidded success rate less than or equal to described real time bid success rate and the described same day in described expectation
That has bought adjusts when spending the cost estimating purchase more than described computing module the calculated same day
High described target price, or described expectation bid success rate more than described real time bid success rate,
And the cost bought on described same day is anticipated less than described computing module calculated same day buys
Cost time turn down described target price.
Advertising rates control method the most according to claim 8, it is characterised in that when described
That bought the same day spends the cost estimating purchase equal to described computing module the calculated same day
Time, it is not adjusted operation.
Advertising rates control method the most according to claim 8, it is characterised in that heighten institute
When stating target price, less than the ceiling price buying described advertisement position.
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| CN106960359A (en) * | 2017-02-10 | 2017-07-18 | 上海智子信息科技股份有限公司 | A kind of full-automatic bid optimization method and system calculated based on streaming |
| CN107153970A (en) * | 2017-04-24 | 2017-09-12 | 郑州埃文计算机科技有限公司 | A kind of bid and budget method of estimation towards real time bid advertisement |
| WO2018121253A1 (en) * | 2016-12-28 | 2018-07-05 | 北京奇虎科技有限公司 | Method, device and equipment for adjusting advertisement delivery rate |
| CN108256982A (en) * | 2016-12-28 | 2018-07-06 | 北京奇虎科技有限公司 | A kind of flow response method, device and equipment |
| CN108846696A (en) * | 2018-06-07 | 2018-11-20 | 北京金山安全软件有限公司 | Advertisement space guaranteed price dynamic adjusting method and device, electronic equipment and storage medium |
| CN109272339A (en) * | 2018-07-16 | 2019-01-25 | 北京三快在线科技有限公司 | Advertisement bid method, apparatus, electronic equipment and readable storage medium storing program for executing |
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| CN112488757A (en) * | 2020-11-30 | 2021-03-12 | 上海酷量信息技术有限公司 | System and method for automatically adjusting bids according to time dimension |
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| CN106960359A (en) * | 2017-02-10 | 2017-07-18 | 上海智子信息科技股份有限公司 | A kind of full-automatic bid optimization method and system calculated based on streaming |
| CN107153970A (en) * | 2017-04-24 | 2017-09-12 | 郑州埃文计算机科技有限公司 | A kind of bid and budget method of estimation towards real time bid advertisement |
| CN108846696A (en) * | 2018-06-07 | 2018-11-20 | 北京金山安全软件有限公司 | Advertisement space guaranteed price dynamic adjusting method and device, electronic equipment and storage medium |
| WO2020006619A1 (en) * | 2018-07-06 | 2020-01-09 | Sanches Rodrigo | Method for performance-based pricing in offline media advertising |
| CN109272339A (en) * | 2018-07-16 | 2019-01-25 | 北京三快在线科技有限公司 | Advertisement bid method, apparatus, electronic equipment and readable storage medium storing program for executing |
| CN110992114A (en) * | 2019-12-24 | 2020-04-10 | 斑马网络技术有限公司 | Advertisement transaction method, platform, electronic device and computer readable storage medium |
| CN112163894A (en) * | 2020-10-14 | 2021-01-01 | 广州欢网科技有限责任公司 | RTB-based DSP bidding method and system |
| CN112488757A (en) * | 2020-11-30 | 2021-03-12 | 上海酷量信息技术有限公司 | System and method for automatically adjusting bids according to time dimension |
| CN113240458A (en) * | 2021-04-26 | 2021-08-10 | 西安点告网络科技有限公司 | Method, system, terminal and storage medium for reliably guaranteeing advertisement bidding timeout rate |
| CN113240458B (en) * | 2021-04-26 | 2023-11-03 | 西安点告网络科技有限公司 | Advertisement bidding timeout rate reliable guarantee method, system, terminal and storage medium |
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