CN110189037A - A kind of method for evaluating quality of paid promotion channel - Google Patents
A kind of method for evaluating quality of paid promotion channel Download PDFInfo
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- CN110189037A CN110189037A CN201910476751.3A CN201910476751A CN110189037A CN 110189037 A CN110189037 A CN 110189037A CN 201910476751 A CN201910476751 A CN 201910476751A CN 110189037 A CN110189037 A CN 110189037A
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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
- G06Q10/00—Administration; Management
- G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
- G06Q10/063—Operations research, analysis or management
- G06Q10/0639—Performance analysis of employees; Performance analysis of enterprise or organisation operations
- G06Q10/06395—Quality analysis or management
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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
- G06Q30/0201—Market modelling; Market analysis; Collecting market data
Abstract
The invention discloses a kind of method for evaluating quality of paid promotion channel, belong to big data technical field, establish the Evaluation Model on Quality of channels, the Evaluation Model on Quality of channels includes channels statistical module, calculate standard parameter module, calculates that channels obtain sub-module and calculating is examined and made cuts ratio module, solves the technical issues of channels marking is carried out by the way of Rate Based On The Extended Creep Model, the present invention can automatically give a mark to all channels, it is greatly saved manpower, has saved cost.
Description
Technical field
The invention belongs to big data technical field, in particular to a kind of method for evaluating quality of paid promotion channel.
Background technique
Channels are the important referential datas of network promotion quality, and network promotion company is newly-increased in order to improve, need with
Numerous forms select and purchase the user of non-natural channels, or are and third party's marketplace platform cooperation, progress paid promotion.
On the one hand, the channels substantial amounts of popularization, on the other hand, due to each way of promotion difference, channels
Quality is irregular.
Therefore the network promotion is there is an urgent need to establish model to measure channels quality in a manner of digitized, thus to height
Quality channels pay more expense to encourage to increase magnitude, examine and make cuts to low quality channels to save market cost.
Summary of the invention
The object of the present invention is to provide a kind of method for evaluating quality of paid promotion channel, solve using Rate Based On The Extended Creep Model
Mode carries out the technical issues of channels marking.
To achieve the above object, the invention adopts the following technical scheme:
A kind of method for evaluating quality of paid promotion channel, includes the following steps:
Step 1: establishing central server, the Evaluation Model on Quality of channels is established in central server, promote canal
The Evaluation Model on Quality in road include channels statistical module, calculate standard parameter module, calculate channels obtain sub-module and
Calculating is examined and made cuts ratio module；
Step 2: user is to the channel information of all channels of central server typing, and central server is by channel information
It is stored in channels statistical module；Channel information include: channels list, for participate in calculate effective period of time and
The date in red-letter day for being included in effective period of time；Channels list includes channels title and the amount of Adding User data；
Step 3: calculating standard parameter module and the thresholding ginseng that can be compared is provided for the Retention of all channels
Number, and the Retention of all channels is cleaned, suppressing exception data, its step are as follows:
Step A1: the threshold value of the Retention of some channels A, the threshold value N of DNU are set；
Step A2: cleaning the minimum tolerable DNU of the product to be promoted of channels A, deletes the popularization of DNU < N
Channel, the value of N are integer；
Step A3: cleaning the Retention on the date in red-letter day of channels A, deletes the Retention on date in red-letter day, and
Channels A several days average residence rates for closing on the date in red-letter day are replaced to the Retention on date in red-letter day；
Step A4: will ensure not meeting lower quartile and add and subtract very poor abnormal point and be removed outside, including walk as follows
It is rapid:
First choice finds the position of quartile, and upper quartile position=(n+1) × 0.25, n is the sum of channels, with
Upper quartile position is boundary point, the very poor value before the upper quartile position of calculatings, upper quartile is very poor be worth=go up quartile it
Preceding next day retention ratio maximum value-goes up next day retention ratio minimum value before quartile；
The position of lower quartile, lower quartile position=(n+1) × 0.75, n is the sum of channels, with lower quartile
Position is boundary point, calculates the very poor value after lower quartile position, and next day is stayed after the very poor value=lower quartile of lower quartile
Deposit next day retention ratio minimum value after rate maximum value-lower quartile；
Need to reject is exactly the data except normal range (NR), and normal range (NR) is that { upper quartile subtracts quartile pole
Difference, lower quartile add the very poor value of lower quartile }；
Step A5: the obtained data of step A1 to step A3 are subjected to coefficient of variation calculating, and do standardization；
Step 4: it calculates channels and obtains sub-module to each channels progress quality score, its step are as follows:
Step B1: calculating channels score module calls any one channel information A, and by itself and normalizing parameter into
Row compares, and calculates channels S1 belonging to channel information A in the score of some day；
Step B2: repeating step B1, calculates the score of every day of channels S1；
Step B3: step B1 is repeated to step B2, obtains each of channels belonging to each channel information
It score；
Step B4: according to step B3's as a result, calculate the sum of the score of all channels, and average mark is calculated；
Step 5: the ratio of examining and making cuts of each channels is calculated, its step are as follows:
Step C1: the ratio of examining and making cuts is to be compared the daily score of each channels with the C that divides equally of all channels,
If score, which is greater than, divides equally C, ratio of examining and making cuts is 100%；Divide equally if score is less than, ratio of examining and making cuts is 100% × (daily score ÷ institute
There are channels to divide equally)；After obtaining the daily ratio of examining and making cuts of each channels, then the channels are calculated with the following method
Overall ratio of examining and making cuts: by the ratio of examining and making cuts of channels A every day respectively multiplied by the newly-increased number of channels A, by every day
The ratio of examining and making cuts sum to obtain the total core inspection amount of channels, with the total core inspection amount of channels divided by the sum of newly-increased number of channels,
Obtain the ratio of examining and making cuts；
Step C2: the ratio of examining and making cuts of all channels is calculated according to the method for step C1；
Step C3: judge whether to need the behave for implementing save the cost for it according to the ratio of examining and making cuts of channels, and raw
At channels score list；
Step 6: channels score list is sent to the client of user by internet by central server, and is shown
It is checked to user.
Preferably, the channels list is provided by third party's data statistics tool, and third party's data statistics tool is
Friendly alliance API.
Preferably, when executing step A1, the Retention of all channels includes retaining the next day of all channels
Rate, retention ratios on the 2nd, the retention ratios on the 3rd of all channels, retention ratios on the 4th of all channels, institute of all channels
There are retention ratios on the 7th of retention ratios on the 5th of channels, retention ratios on the 6th of all channels and all channels, calculates mark
Quasi- parameter module is respectively retention ratios on the 2nd of all channels, retention ratios on the 3rd of all channels, all channels
Retention ratios on the 4th, retention ratios on the 5th of all channels, retention ratios on the 6th of all channels and all channels 7
Day retention ratio sets different threshold values.
Preferably, DNU is Daily New User, is in a few days Added User.
Preferably, when executing step C1, newly-increased number is the quantity to Add User day.
A kind of method for evaluating quality of paid promotion channel of the present invention, solve by the way of Rate Based On The Extended Creep Model into
The technical issues of row channels are given a mark, the present invention can automatically give a mark to all channels, be greatly saved people
Power has saved cost.
Detailed description of the invention
Fig. 1 is flow chart of the invention.
Specific embodiment
A kind of method for evaluating quality of paid promotion channel as shown in Figure 1, includes the following steps:
Step 1: establishing central server, the Evaluation Model on Quality of channels is established in central server, promote canal
The Evaluation Model on Quality in road include channels statistical module, calculate standard parameter module, calculate channels obtain sub-module and
Calculating is examined and made cuts ratio module；
Step 2: user is to the channel information of all channels of central server typing, and central server is by channel information
It is stored in channels statistical module；Channel information include: channels list, for participate in calculate effective period of time and
The date in red-letter day for being included in effective period of time；Channels list includes channels title and the amount of Adding User data；
Step 3: calculating standard parameter module and the thresholding ginseng that can be compared is provided for the Retention of all channels
Number, and the Retention of all channels is cleaned, suppressing exception data, its step are as follows:
Step A1: the threshold value of the Retention of some channels A, the threshold value N of DNU are set；
Step A2: cleaning the minimum tolerable DNU of the product to be promoted of channels A, deletes the popularization of DNU < N
Channel, the value of N are integer；
Step A3: cleaning the Retention on the date in red-letter day of channels A, deletes the Retention on date in red-letter day, and
Channels A several days average residence rates for closing on the date in red-letter day are replaced to the Retention on date in red-letter day；
Step A4: to ensure not meeting lower quartile and add and subtract very poor abnormal point and be removed outside；
It is mainly used to reject and is retained much higher than common channel, or the abnormal point retained far below common channel.The present embodiment
If the following table 1 is the next day retention ratio list of channel in certain period, totally 12 project.
| Channel | Next day retention ratio | Mark |
| 1 | 15% | |
| 2 | 26% | |
| 3 | 27% | Upper quartile |
| 4 | 28% | |
| 5 | 29% | |
| 6 | 30% | |
| 7 | 31% | |
| 8 | 32% | |
| 9 | 33% | |
| 10 | 34% | Lower quartile |
| 11 | 36% | |
| 12 | 40% |
Table 1
First choice finds the position of quartile, upper quartile position=(n+1) × 0.25=(12+1) × 0.25=3.25.
I.e. upper quartile be third position, 27%.
Then the position of lower quartile, lower quartile position=(n+1) × 0.75=(12+1) × 0.75=9.75 are found.
I.e. lower quartile be the tenth, 34%.
Subsequently calculate very poor, very poor=next day retention ratio maximum value-next day retention ratio minimum value=40%-15%=
25%；
Need to reject is exactly the data except normal range (NR), and normal range (NR) is that { upper quartile subtracts very poor, lower quartile
Adding very poor, i.e., the data outside { 27%-25%, 34%+25% }={ 2%, 59% } range need to reject.
Step A5: the obtained data of step A1 to step A3 are subjected to coefficient of variation calculating, and do standardization；
Step 4: it calculates channels and obtains sub-module to each channels progress quality score, its step are as follows:
Step B1: calculating channels score module calls any one channel information A, and by itself and normalizing parameter into
Row compares, and calculates channels S1 belonging to channel information A in the score of some day；
Step B2: repeating step B1, calculates the score of every day of channels S1；
Step B3: step B1 is repeated to step B2, obtains each of channels belonging to each channel information
It score；
Step B4: according to step B3's as a result, calculate the sum of the score of all channels, and average mark is calculated；
Step 5: the ratio of examining and making cuts of each channels is calculated, its step are as follows:
Step C1: the ratio of examining and making cuts is to be compared the daily score of each channels with the C that divides equally of all channels,
If score, which is greater than, divides equally C, ratio of examining and making cuts is 100%；Divide equally if score is less than, ratio of examining and making cuts is 100% × (daily score ÷ institute
There are channels to divide equally)；After obtaining the daily ratio of examining and making cuts of each channels, then the channels are calculated with the following method
Overall ratio of examining and making cuts: by the ratio of examining and making cuts of channels A every day respectively multiplied by the newly-increased number of channels A, by every day
The ratio of examining and making cuts sum to obtain the total core inspection amount of channels, with the total core inspection amount of channels divided by the sum of newly-increased number of channels,
Obtain the ratio of examining and making cuts；
Step C2: the ratio of examining and making cuts of all channels is calculated according to the method for step C1；
Step C3: judge whether to need the behave for implementing save the cost for it according to the ratio of examining and making cuts of channels, and raw
At channels score list；
Step 6: channels score list is sent to the client of user by internet by central server, and is shown
It is checked to user.
Preferably, the channels list is provided by third party's data statistics tool, and third party's data statistics tool is
Friendly alliance API.
Preferably, when executing step A1, the Retention of all channels includes retaining the next day of all channels
Rate, retention ratios on the 2nd, the retention ratios on the 3rd of all channels, retention ratios on the 4th of all channels, institute of all channels
There are retention ratios on the 7th of retention ratios on the 5th of channels, retention ratios on the 6th of all channels and all channels, calculates mark
Quasi- parameter module is respectively retention ratios on the 2nd of all channels, retention ratios on the 3rd of all channels, all channels
Retention ratios on the 4th, retention ratios on the 5th of all channels, retention ratios on the 6th of all channels and all channels 7
Day retention ratio sets different threshold values.
Preferably, DNU is Daily New User, is in a few days Added User.
Preferably, when executing step C1, newly-increased number is the quantity to Add User day.
A kind of method for evaluating quality of paid promotion channel of the present invention, solve by the way of Rate Based On The Extended Creep Model into
The technical issues of row channels are given a mark, the present invention can automatically give a mark to all channels, be greatly saved people
Power has saved cost.
Claims (5)
1. a kind of method for evaluating quality of paid promotion channel, characterized by the following steps:
Step 1: central server is established, the Evaluation Model on Quality of channels is established in central server, channels
Evaluation Model on Quality include channels statistical module, calculate standard parameter module, calculate channels obtain sub-module and calculating
Ratio of examining and making cuts module；
Step 2: for user to the channel information of all channels of central server typing, central server deposits channel information
Storage is in channels statistical module；Channel information include: channels list, for participate in calculate effective period of time and effectively
The date in red-letter day for being included in period；Channels list includes channels title and the amount of Adding User data；
Step 3: standard parameter module is calculated as the Retention of all channels, and the threshold parameter that can be compared is provided, and
The Retention of all channels is cleaned, suppressing exception data, its step are as follows:
Step A1: the threshold value of the Retention of some channels A, the threshold value N of DNU are set；
Step A2: cleaning the minimum tolerable DNU of the product to be promoted of channels A, deletes the popularization canal of DNU < N
Road, the value of N are integer；
Step A3: cleaning the Retention on the date in red-letter day of channels A, deletes the Retention on date in red-letter day, and will push away
Several days average residence rates that wide channel A closes on the date in red-letter day replace the Retention on date in red-letter day；
Step A4: will ensure not meeting lower quartile and add and subtract very poor abnormal point and be removed outside, include the following steps:
First choice finds the position of quartile, and upper quartile position=(n+1) × 0.25, n is the sum of channels, and above four
Quartile position is boundary point, the very poor value in calculating before quartile position, the upper very poor value of quartile=above quartile is previous
Next day retention ratio minimum value before the upper quartile of day retention ratio maximum value-；
The position of lower quartile, lower quartile position=(n+1) × 0.75, n is the sum of channels, with lower quartile position
For boundary point, the very poor value after lower quartile position, next day retention ratio after the very poor value=lower quartile of lower quartile are calculated
Next day retention ratio minimum value after maximum value-lower quartile；
Need to reject is exactly the data except normal range (NR), normal range (NR) be upper quartile subtracts the very poor value of quartile,
Lower quartile adds the very poor value of lower quartile }；
Step A5: the obtained data of step A1 to step A3 are subjected to coefficient of variation calculating, and do standardization；
Step 4: it calculates channels and obtains sub-module to each channels progress quality score, its step are as follows:
Step B1: channels score module calls any one channel information A is calculated, and it is compared with normalizing parameter
Compared with score of the channels S1 belonging to calculating channel information A in some day；
Step B2: repeating step B1, calculates the score of every day of channels S1；
Step B3: step B1 is repeated to step B2, obtains every day of channels belonging to each channel information
Score；
Step B4: according to step B3's as a result, calculate the sum of the score of all channels, and average mark is calculated；
Step 5: the ratio of examining and making cuts of each channels is calculated, its step are as follows:
Step C1: the ratio of examining and making cuts is to be compared the daily score of each channels with the C that divides equally of all channels, if obtaining
Divide to be greater than and divide equally C, ratio of examining and making cuts is 100%；If score be less than divide equally, ratio of examining and making cuts be 100% × (daily score ÷ is all to be pushed away
Wide channel is divided equally)；After obtaining the daily ratio of examining and making cuts of each channels, then channels totality is calculated with the following method
Ratio of examining and making cuts: by the ratio of examining and making cuts of channels A every day respectively multiplied by the newly-increased number of channels A, by the core of every day
Subtract ratio to sum to obtain the total core inspection amount of channels, with the total core inspection amount of channels divided by the sum of newly-increased number of channels, obtain
It examines and makes cuts ratio；
Step C2: the ratio of examining and making cuts of all channels is calculated according to the method for step C1；
Step C3: judge whether to need the behave for implementing save the cost for it according to the ratio of examining and making cuts of channels, and generate and push away
Wide channel score list；
Step 6: channels score list is sent to the client of user by internet by central server, and shows use
Family is checked.
2. a kind of method for evaluating quality of paid promotion channel as described in claim 1, it is characterised in that: the channels
List is provided by third party's data statistics tool, and third party's data statistics tool is friend alliance API.
3. a kind of method for evaluating quality of paid promotion channel as described in claim 1, it is characterised in that: executing step A1
When, the Retention of all channels includes the next day retention ratio of all channels, retention ratios on the 2nd of all channels,
Retention ratios on the 3rd of all channels, retention ratios on the 5th of all channels, own retention ratios on the 4th of all channels
Retention ratios on the 6th of channels and retention ratios on the 7th of all channels, calculating standard parameter module is respectively all popularization canals
The retention ratios on the 2nd in road, retention ratios on the 3rd of all channels, retention ratios on the 4th of all channels, all channels 5
Retention ratios on the 7th of day retention ratio, retention ratios on the 6th of all channels and all channels set different threshold values.
4. a kind of method for evaluating quality of paid promotion channel as described in claim 1, it is characterised in that: DNU is
DailyNewUser in a few days Adds User.
5. a kind of method for evaluating quality of paid promotion channel as described in claim 1, it is characterised in that: executing step C1
When, newly-increased number is the quantity to Add User day.
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Cited By (2)
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| CN111898887A (en) * | 2020-07-16 | 2020-11-06 | 北京网聘咨询有限公司 | Flow quality evaluation method |
| CN116385080A (en) * | 2023-04-17 | 2023-07-04 | 云洞(上海)科技股份有限公司 | Mobile internet user data statistics popularization system based on artificial intelligence |
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