CN110111124A - Power customer service preference methods and system based on channel preference and business preference - Google Patents
Power customer service preference methods and system based on channel preference and business preference Download PDFInfo
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- CN110111124A CN110111124A CN201910215906.8A CN201910215906A CN110111124A CN 110111124 A CN110111124 A CN 110111124A CN 201910215906 A CN201910215906 A CN 201910215906A CN 110111124 A CN110111124 A CN 110111124A
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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
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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
- G06Q30/0203—Market surveys; Market polls
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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
- G06Q50/00—Systems or methods specially adapted for specific business sectors, e.g. utilities or tourism
- G06Q50/06—Electricity, gas or water supply
Abstract
The invention belongs to grid service technical fields, and in particular to power customer service preference methods and system based on channel preference and business preference.Step 1 counts power grid client for the cumulative contact frequency X of different grid service channels1Frequency X is handled with for the accumulative of different electrical network business2；Step 2, respectively to power grid client for the cumulative contact frequency X of different grid service channels1Frequency X is handled with for the accumulative of different electrical network business2It is weighted；Step 3 is standardized the obtained different grid service channels weighting frequency, the different business weighting frequency after weighting, the channel liveness matrix for calculating the channel liveness of client according to liveness formula and being considered based on business respectively；Step 4, according to the value of power grid client's channel liveness, determine the preferred service channel of power grid user.The application can meet customer service and attend a banquet and fast, accurately and comprehensively understand customer priorities according to client's liveness, when customer in response demand.
Description
Technical field
The invention belongs to grid service technical fields, and in particular to be taken based on channel preference and the power customer of business preference
Preference methods of being engaged in and system.
Background technique
Electric power hotline service system provides related business by modes such as artificial, automatic speech, short message, E-mail for client
Or the professional services such as business consultation, service handling and complaint suggestion of work, it is the channel of communication of a corporate external service.Electricity
Power hotline service provides outage information inquiry, troublshooting, electricity charge inquiry and pays, business handling, business consultation, complains and lift
The service functions such as report, manual service.Customer service works towards huge numbers of families, and customers are huge and complicated, by client's quality, communication side
The limitation of the factors such as formula, customer service, which is attended a banquet, cannot fast, accurately and comprehensively understand customer priorities, it is difficult to timely respond to client's demand.
Summary of the invention
For the problems of the prior art, it is inclined that the present invention provides the power customer service based on channel preference and business preference
Good method and system, can satisfy customer service and attend a banquet and fast, accurately and comprehensively understand customer priorities, when customer in response demand.
To achieve the above object, the present invention is achieved by the following technical solutions:
The present invention provides the power customer service preference methods based on channel preference and business preference, and special character exists
In:
Step 1 counts power grid client for the cumulative contact frequency X of different grid service channels1With for different power grids
The accumulative of business handles frequency X2；
Step 2 calculates time dimension weighting weight, and different the accumulative of grid service channel are connect to power grid client respectively
Touch frequency X1Frequency X is handled with for the accumulative of different electrical network business2It is weighted；
Step 3, to the different grid service channels weighting frequency of obtaining after weighting, the different business weighting frequency respectively into
Row standardization, the channel liveness square for calculating the channel liveness of client according to liveness formula and being considered based on business
Battle array；
Step 4, according to the value of power grid client's channel liveness, determine the preferred service channel of power grid user；According to channel
Liveness matrix, determine client under the premise of consideration business to the preference of different channels, wherein with enliven angle value maximum
Preferred service channel of the channel as client.
Further, power grid client is counted in step 1 for the cumulative contact frequency of different grid service channels to collect
The form of conjunction forms X1, wherein X1={ x11,x12,x13......,x1n, and statistics power grid client is for different electrical network business
Accumulative handle the frequency and form X in the form gathered2, wherein X2={ x21,x22,x23......,x2n}。
Further, it is filed the time according to the difference of different power grid clients, calculates time dimension and weight weight:
Further, historical record starting month is time threshold, and current month is to handle the time, and month of filing is handling
Before time or the same day.
By customer profile information, inquires client and file the time, according to time threshold respectively to the grid service canal of client
The road frequency and the business handling frequency are calculated,
In the case where handling the time less than or equal to time threshold, the weighting frequency of client is the practical frequency；
In the case where handling the time greater than time threshold, the weighting frequency of client be the practical frequency multiplied by current time and
The difference of time threshold, the ratio between current month and the difference of time threshold, then be the weighting frequency of client later；
Remember the weighting frequency X' of different grid service channels1={ x '11,x’12,x’13,......,x’1nAnd different power grids
Business weights frequency X'2={ x'21,x'22,x'23,......,x'2n, wherein x'1iAnd x'2jRespectively indicate 1i kind channel
Weight the weighting frequency (i, j={ 1,2,3 ..., n }, n is natural number) of the frequency and 2j kind business.
Further, the mean μ and standard deviation sigma of each channel, the business weighting frequency are calculated,
According to standardization formulaTo the frequency X' after weighting1={ x '11,x’12,x’13,......,x’1nAnd
X'2={ x'21,x'22,x'23,......,x'2nBe standardized, wherein the value of x is respectively X'1、X'2In respectively plus
The frequency after power；Frequency X " after being standardized1={ x "11,x”12,x”13,......,x”1nAnd X "2={ x "21,x”22,
x”23,......,x”2n}。
Further, liveness formula is utilizedIt is living to calculate power grid client channel liveness, business
Jerk, wherein H indicates liveness, and x " expression has been standardized the weighting frequency, x "minExpression has been standardized weighting frequency minimum value,
x”maxExpression has been standardized weighting frequency maximum value, (i=1,2,3 ..., m }, j=1,2,3 ..., and n }, m, n are equal
For natural number)；
The business preference of comprehensive client, channel preference, the liveness matrix D for obtaining customer priorities is as follows,
Wherein,HijIt indicates to handle enlivening for i-th kind of business using jth kind channel
Degree, x "ijIndicate that handles i-th kind of business using jth kind channel has been standardized the weighting frequency, x "(ij)minIt indicates to use jth kind
Channel handles having been standardized for all business and weights frequency minimum value, x "(ij)maxAll business have been handled using jth kind channel
Standardization weighting frequency maximum value, (i=1,2,3 ..., m }, j=1,2,3 ..., and n }, m, n are natural number).
The present invention also provides the power customer service preference analysis system based on channel preference and business preference, it is special it
Be in:
Statistical module, for counting power grid client for the cumulative contact frequency of different grid service channels and for difference
The accumulative of electrical network business handles the frequency；
Data weighting module, for the cumulative contact frequency and electricity using time dimension weighting weight to power grid client's channel
Network service is accumulative to be handled the frequency and is weighted；
Data normalization module, for being standardized to the frequency after weighting；
Liveness computing module, for calculating power grid client channel liveness and business liveness using liveness formula,
And comprehensive channel liveness and business liveness result generate liveness matrix；
Preference determining module, for determining the preference of client according to liveness.
Further, the liveness computing module, comprising:
Acquiring unit, for counting all users for the contact frequency X of different services channels1Frequency is handled with different business
Secondary X2And all clients using the grid service channel and handle the mean μ and standard deviation sigma of different business；First meter
Unit is calculated, for the weighting frequency X' using time dimension weighting weight calculation channel1={ x '11,x’12,x’13,......,
x’1nAnd different business weighting frequency X'2={ x'21,x'22,x'23,......,x'2n, wherein x'1iAnd x'2jRespectively indicate
The weighting frequency (i, j={ 1,2,3 ..., n }, n is natural number) of the weighting frequency of 1i kind channel and 2j kind business；
Second computing unit, for according to standardization formulaTo the frequency X' after weighting1={ x '11,x’12,
x’13,......,x’1nAnd X'2={ x'21,x'22,x'23,......,x'2nBe standardized；The wherein value of x point
It Wei not X'1、X'2In each weighting after the frequency；Frequency X " after being standardized1={ x "11,x”12,x”13,......,x”1n}
And X "2={ x "21,x”22,x”23,......,x”2n}；
Third computing unit utilizes liveness formulaCalculate power grid client channel liveness and
Business liveness.
Further, preference determining module includes:
Output unit, the different channels for exporting all user's difference channel liveness tables of data and being considered based on business
Liveness matrix D, it is as follows,
Wherein,HijIt indicates to handle enlivening for i-th kind of business using jth kind channel
Degree, xij" indicate that handles i-th kind of business using jth kind channel has been standardized the weighting frequency, x "(ij)minIt indicates to use jth kind
Channel handles having been standardized for all business and weights frequency minimum value, x "(ij)maxAll business have been handled using jth kind channel
Standardization weighting frequency maximum value, (i=1,2,3 ..., m }, j=1,2,3 ..., and n }, m, n are natural number)；
Preference determination unit determines the channel of specific preference for obtaining liveness in different channels according to user；For root
According to determining client for the preference of channels different in same business based on the channel liveness matrix of business.
Compared with prior art, the present invention it, which has the beneficial effect that, utilizes big data, data mining technology, customer electricity
Customer service preference is analyzed in association between behavior, power grid production and operating activities and client, is attended a banquet for a line customer service
Intelligent information support is provided.By the analysis to user preference, when contact staff is offering customers service, can quickly, it is accurate,
It fully understands ground client, timely responds to client's demand, improve working efficiency.Increase the efficiency and link up matter that customer service is communicated with client
Amount reduces the time cost of communication, reduces customer service operating pressure.It can be seen that being taken based on channel preference and the power customer of business preference
Business preference analysis model can guide client to carry out the transfer of services channels, reduce the cost of serving of electrical power services channel；Pass through
The corresponding electrical power services channel irrelevance tables of data of each type of service client of comparative analysis, it is inclined to find out each type of service client
Good electrical power services channel, to formulate the strategy that guidance client shifts to inexpensive services channels.
Detailed description of the invention
Fig. 1 is flow chart of the method for the present invention.
Specific embodiment
To make the objectives, technical solutions, and advantages of the present invention clearer, below in conjunction with attached drawing to the present invention make into
One step it is described in detail.
For power customer service preference analysis method of the invention, follow the steps below:
Step 1 counts all users for the contact frequency X of different services channels1Frequency X is handled with different business2, with
And all clients use the grid service channel, the mean μ and standard deviation sigma of business channel；
Step 2 is determined for the weighting frequency X' using time dimension weighting weight calculation channel1={ x '11,x’12,
x’13,......,x’1nAnd different business weighting frequency X'2={ x'21,x'22,x'23,......,x'2n, wherein x'1iAnd x'2j
(i, j={ 1,2,3 ..., n }, n is the weighting frequency and the weighting frequency of 2j kind business for respectively indicating 1i kind channel
Natural number)；
Step 3 is used for according to standardization formulaTo the frequency X' after weighting1={ x '11,x’12,x
’13,......,x’1nAnd X'2={ x'21,x'22,x'23,......,x'2nBe standardized, wherein the value of x is distinguished
For X'1、X'2In each weighting after the frequency；Frequency X " after being standardized1={ x "11,x”12,x”13,......,x”1nAnd
X”2={ x "21,x”22,x”23,......,x”2n}；
Step 4 utilizes liveness formulaIt is active to calculate power grid client channel liveness, business
Degree, wherein H indicates liveness, and x " expression has been standardized the weighting frequency, x "minExpression has been standardized weighting frequency minimum value,
x”maxExpression has been standardized weighting frequency maximum value, (i=1,2,3 ..., m }, j=1,2,3 ..., and n }, m, n are equal
For natural number)；
Step 5, the process for repeating 1-4, calculate the liveness index of all channels of all clients and business, and integrated service is living
Jerk index, channel liveness index obtain client's liveness preference matrix.
Principle and step is described in detail especially by embodiment:
Step 1: by customer profile information, inquiring client and file the time；
Step 2: by the managing detailed catalogue of customer historical business handling, 95598 calling information, payment information, statistics is all
Each channel contact frequency of client and each business handle the frequency, and effective starting month 201601 of statistical history record；
Step 3: since certain customers are filed after 201601, channel contact business between each user handles the frequency
Based on time span it is different, normal reaction customer priorities degree is unable to when calculating customer priorities, therefore will be to the frequency of each user
It is secondary to be weighted according to time span；
Step 4: calculating the mean μ and standard deviation sigma of each channel, the business weighting frequency；
Step 5: for according to standardization formulaTo the frequency X' after weighting1={ x '11,x’12,x
’13,......,x’1nAnd
X'2={ x'21,x'22,x'23,......,x'2nBe standardized,
Step 6:
Utilize liveness formulaCalculate power grid client channel liveness and business liveness.
Step 7: integrated service liveness index, channel liveness index obtain customer priorities matrix D, as follows,
Wherein,HijIt indicates to handle enlivening for i-th kind of business using jth kind channel
Degree, xij" indicate that handles i-th kind of business using jth kind channel has been standardized the weighting frequency, x "(ij)minIt indicates to use jth kind
Channel handles having been standardized for all business and weights frequency minimum value, x "(ij)maxAll business have been handled using jth kind channel
Standardization weighting frequency maximum value, (i=1,2,3 ..., m }, j=1,2,3 ..., and n }, m, n are natural number).
Technical solution of the present invention is explained by specific data explanation, as follows to the concrete analysis of client:
Client's essential information data are given before analysis, historical record starting month: 201601, current month is namely done
The time: 201810, overall time span 201810-201601=34 (moon) is managed, month of filing is handling between the time or the same day.
Client files time such as the following table 1.Table 1
| Client | It files month |
| Zhang San | 201505 |
| Li Si | 201102 |
| King five | 201706 |
Calculate time span such as the following table 2 of historical customer data.
Table 2
| Client | Time span (moon) |
| Zhang San | 34 |
| Li Si | 34 |
| King five | 17 |
One, user's channel liveness is calculated
User's channel liveness is calculated, client's channel contacts the frequency such as the following table 3.
Table 3
| Client | Online business hall | 95598 | Business hall |
| Zhang San | 10 | 2 | 10 |
| Li Si | 9 | 10 | 3 |
| King five | 5 | 4 | 1 |
Step 1: calculate client's channel contact weighting frequency:
Wherein, by taking online business hall channel as an example, Zhang San, Li Si file the time earlier than historical record originate month
201601, Zhang San, the online business hall channel weighting frequency of Li Si are equal to the frequency；
The time of filing of king five is later than historical record starting month 201601, and the calculation formula for weighting the frequency is as follows:
Such as the weighting frequency of the online business hall channel of king five is
It is computed, each channel weighting frequency table of user is as follows:
| Client | Online business hall | 95598 | Business hall |
| Zhang San | 10 | 2 | 10 |
| Li Si | 9 | 10 | 3 |
| King five | 10 | 8 | 2 |
Step 2: calculating the mean value and standard deviation of each channel weighting frequency, mean value and standard deviation are calculated as the normal of this field
Rule method, the no longer independent formulas for calculating of the application, it is as follows to obtain result:
| Online business hall | 95598 | Business hall | |
| Mean value | 9.67 | 6.67 | 5 |
| Standard deviation | 0.47 | 3.4 | 3.56 |
Step 3: according to mean value and variance, standardization formulaIt is weighted frequency standardization:
Step 4: calculating liveness, obtain liveness matrix
| Client | Online business hall | 95598 | Business hall |
| Zhang San | 74.14 | 32.54 | 88.1 |
| Li Si | 31.72 | 79.61 | 48.76 |
| King five | 74.14 | 67.84 | 43.14 |
Two, the channel liveness based on business is calculated
Client's channel contacts the frequency
| Client | Class of service | Online business hall | 95598 | Business hall |
| Zhang San | Payment | 10 | 2 | 10 |
| Zhang San | Inquire the electricity charge | 9 | 10 | 3 |
| Zhang San | Consulting has a power failure | 5 | 4 | 1 |
| Zhang San | It reports for repairment | 0 | 1 | 1 |
| Li Si | Payment | 20 | 3 | 2 |
| Li Si | Inquire the electricity charge | 5 | 5 | 0 |
| Li Si | Consulting has a power failure | 0 | 1 | 2 |
| Li Si | It reports for repairment | 1 | 0 | 0 |
| King five | Payment | 11 | 0 | 0 |
| King five | Inquire the electricity charge | 3 | 1 | 3 |
| King five | Consulting has a power failure | 9 | 4 | 5 |
| King five | It reports for repairment | 0 | 0 | 0 |
Step 1: counting all kinds of business in the frequency of exposure of each channel
| Class of service | Online business hall | 95598 | Business hall |
| Payment | 41 | 5 | 12 |
| Inquire the electricity charge | 17 | 16 | 6 |
| Consulting has a power failure | 14 | 9 | 8 |
| It reports for repairment | 1 | 1 | 1 |
Step 2: the mean value and standard deviation of each channel weighting frequency are calculated, it is as a result as follows
| Online business hall | 95598 | Business hall | |
| Mean value | 18.25 | 7.75 | 6.75 |
| Standard deviation | 16.68 | 6.4 | 4.57 |
Class of service directly calculates irrelevance without the concern for time span.
Step 3: calculating irrelevance
| Class of service | Online business hall | 95598 | Business hall |
| Payment | 1.36 | -0.43 | 1.15 |
| Inquire the electricity charge | -0.07 | 1.29 | -0.16 |
| Consulting has a power failure | -0.25 | 0.2 | 0.27 |
| It reports for repairment | -1.03 | -1.06 | -1.26 |
Step 4: calculating liveness
It can be seen according to the channel liveness matrix based on business, in fee payment service, online business hall channel liveness is most
Height judges that preference channel is online business hall when client handles fee payment service；It can similarly obtain, when client handles inquiry electricity charges
Preference channel is 95598；Preference channel is business hall when client handles consulting power failure business；Client handles preference when reporting business for repairment
Channel is online business hall.It can be seen that channel liveness matrix of the basis based on business, when can handle different business to client
Preference channel makes direct judgement.
Power customer service preference analysis model for the application based on channel preference and business preference, comprising:
Statistical module, for counting power grid client for the cumulative contact frequency of different grid service channels and for difference
The accumulative of electrical network business handles the frequency；
Data weighting module, for the cumulative contact frequency and electricity using time dimension weighting weight to power grid client's channel
Network service is accumulative to be handled the frequency and is weighted；
Data normalization module, for being standardized to the frequency after weighting；
Liveness computing module, for calculating power grid client channel liveness and business liveness using liveness formula,
And comprehensive channel liveness and business liveness result generate liveness matrix；
Preference determining module, for determining the preference of client according to liveness.
The liveness computing module, comprising:
Acquiring unit, for counting all users for the contact frequency X of different services channels1Frequency is handled with different business
Secondary X2And all clients using the grid service channel and handle the mean μ and standard deviation sigma of different business；First meter
Unit is calculated, for the weighting frequency X' using time dimension weighting weight calculation channel1={ x '11,x’12,x’13,......,
x’1nAnd different business weighting frequency X'2={ x'21,x'22,x'23,......,x'2n, wherein x'1iAnd x'2jRespectively indicate
The weighting frequency (i, j={ 1,2,3 ..., n }, n is natural number) of the weighting frequency of 1i kind channel and 2j kind business；
Second computing unit, for according to standardization formulaTo the frequency X' after weighting1={ x '11,x’12,
x’13,......,x’1nAnd X'2={ x'21,x'22,x'23,......,x'2nBe standardized；The wherein value of x point
It Wei not X'1、X'2In each weighting after the frequency；Frequency X " after being standardized1={ x "11,x”12,x”13,......,x”1n}
And X "2={ x "21,x”22,x”23,......,x”2n}；
Third computing unit utilizes liveness formulaCalculate power grid client channel liveness and
Business liveness.
Preference determining module includes:
Output unit, the different channels for exporting all user's difference channel liveness tables of data and being considered based on business
Liveness matrix D, it is as follows,
Wherein,HijIt indicates to handle enlivening for i-th kind of business using jth kind channel
Degree, xij" indicate that handles i-th kind of business using jth kind channel has been standardized the weighting frequency, x "(ij)minIt indicates to use jth kind
Channel handles having been standardized for all business and weights frequency minimum value, x "(ij)maxAll business have been handled using jth kind channel
Standardization weighting frequency maximum value, (i=1,2,3 ..., m }, j=1,2,3 ..., and n }, m, n are natural number)；
Preference determination unit determines the channel of specific preference for obtaining liveness in different channels according to user；For root
According to determining client for the preference of channels different in same business based on the channel liveness matrix of business.
It is obvious to a person skilled in the art that invention is not limited to the details of the above exemplary embodiments, Er Qie
In the case where without departing substantially from spirit or essential attributes of the invention, the present invention can be realized in other specific forms.Therefore, no matter
From the point of view of which point, the present embodiments are to be considered as illustrative and not restrictive, and the scope of the present invention is by appended power
Benefit requires rather than above description limits, it is intended that all by what is fallen within the meaning and scope of the equivalent elements of the claims
Variation is included within the present invention.
In addition, it should be understood that although this specification is described in terms of embodiments, but not each embodiment includes
One independent technical solution, this description of the specification is merely for the sake of clarity, and those skilled in the art should incite somebody to action
As a whole, the technical solutions in the various embodiments may also be suitably combined for specification, and forming those skilled in the art can
With the other embodiments of understanding.
Claims (9)
1. the power customer service preference methods based on channel preference and business preference, it is characterised in that:
Step 1 counts power grid client for the cumulative contact frequency X of different grid service channels1With for different electrical network business
It is accumulative to handle frequency X2；
Step 2 calculates time dimension weighting weight, respectively to power grid client for the cumulative contact frequency of different grid service channels
Secondary X1Frequency X is handled with for the accumulative of different electrical network business2It is weighted；
Step 3 marks the obtained different grid service channels weighting frequency, the different business weighting frequency after weighting respectively
Quasi-ization processing, the channel liveness matrix for calculating the channel liveness of client according to liveness formula and being considered based on business；
Step 4, according to the value of power grid client's channel liveness, determine the preferred service channel of power grid user；It is active according to channel
Spend matrix, determine client under the premise of consideration business to the preference of different channels, wherein to enliven the maximum canal of angle value
Preferred service channel of the road as client.
2. the power customer service preference methods based on channel preference and business preference, feature exist as described in claim 1
In:
The form that statistics power grid client gathers the cumulative contact frequency of different grid service channels in step 1 forms X1,
Wherein X1={ x11,x12,x13......,x1n, and statistics power grid client for different electrical network business it is accumulative handle the frequency with
The form of set forms X2, wherein X2={ x21,x22,x23......,x2n}。
3. the power customer service preference methods based on channel preference and business preference, feature exist as claimed in claim 2
In:
It is filed the time according to the difference of different power grid clients, calculates time dimension and weight weight:
。
4. the power customer service preference methods based on channel preference and business preference, feature exist as claimed in claim 3
In:
It is time threshold that historical record, which originates month, and current month is to handle the time, and month of filing before handling the time or works as
Day.
It by customer profile information, inquires client and files the time, according to time threshold respectively to the grid service channel frequency of client
The secondary and business handling frequency is calculated,
In the case where handling the time less than or equal to time threshold, the weighting frequency of client is the practical frequency；
In the case where handling the time greater than time threshold, the weighting frequency of client is the practical frequency multiplied by current time and time
The difference of threshold value, the ratio between current month and the difference of time threshold, then be the weighting frequency of client later；
Remember the weighting frequency X' of different grid service channels1={ x '11,x′12,x′13,......,x′1nAnd different electrical network business
Weight frequency X'2={ x'21,x'22,x'23,......,x'2n, wherein x'1iAnd x'2jRespectively indicate the weighting of 1i kind channel
The weighting frequency (i, j={ 1,2,3 ..., n }, n is natural number) of the frequency and 2j kind business.
5. the power customer service preference methods based on channel preference and business preference, feature exist as claimed in claim 4
In: the mean μ and standard deviation sigma of each channel, the business weighting frequency are calculated,
According to standardization formulaTo the frequency X' after weighting1={ x '11,x′12,x′13,......,x′1nAnd X'2=
{x'21,x'22,x'23,......,x'2nBe standardized, wherein the value of x is respectively X'1、X'2In it is each weighting after
The frequency；Frequency X " after being standardized1={ x "11,x″12,x″13,......,x″1nAnd X "2={ x "21,x″22,x
″23,......,x″2n}。
6. the power customer service preference methods based on channel preference and business preference, feature exist as claimed in claim 5
In: utilize liveness formulaCalculate power grid client channel liveness, business liveness, wherein H table
Show liveness, x " expression has been standardized the weighting frequency, x "minExpression has been standardized weighting frequency minimum value, x "maxIndicate standard
Change weighting frequency maximum value, (i=1,2,3 ..., m }, j=1,2,3 ..., and n }, m, n are natural number)；
The business preference of comprehensive client, channel preference, the liveness matrix D for obtaining customer priorities is as follows,
Wherein,HijIndicate the liveness that i-th kind of business is handled using jth kind channel, xij″
Indicate that handles i-th kind of business using jth kind channel has been standardized the weighting frequency, x "(ij)minExpression is done using jth kind channel
That manages all business has been standardized weighting frequency minimum value, x "(ij)maxHaving been standardized for all business is handled using jth kind channel
Frequency maximum value is weighted, (i=1,2,3 ..., m }, j=1,2,3 ..., and n }, m, n are natural number).
7. the power customer service preference analysis system based on channel preference and business preference, it is characterised in that:
Statistical module, for counting power grid client for the cumulative contact frequency of different grid service channels and for different power grids
The accumulative of business handles the frequency；
Data weighting module, for the cumulative contact frequency and power grid industry using time dimension weighting weight to power grid client's channel
Business is accumulative to be handled the frequency and is weighted；
Data normalization module, for being standardized to the frequency after weighting；
Liveness computing module, for calculating power grid client channel liveness and business liveness using liveness formula, and it is comprehensive
It closes channel liveness and business liveness result generates liveness matrix；
Preference determining module, for determining the preference of client according to liveness.
8. the power customer service preference analysis system based on channel preference and business preference as claimed in claim 7, special
Sign is:
The liveness computing module, comprising:
Acquiring unit, for counting all users for the contact frequency X of different services channels1Frequency X is handled with different business2,
And all clients using the grid service channel and handle the mean μ and standard deviation sigma of different business；First calculates list
Member, for the weighting frequency X' using time dimension weighting weight calculation channel1={ x '11,x′12,x′13,......,x′1nAnd
Different business weights frequency X'2={ x'21,x'22,x'23,......,x'2n, wherein x'1iAnd x'2jRespectively indicate 1i kind canal
The weighting frequency (i, j={ 1,2,3 ..., n }, n is natural number) of the weighting frequency in road and 2j kind business；
Second computing unit, for according to standardization formulaTo the frequency X' after weighting1={ x '11,x′12,x
′13,......,x′1nAnd X'2={ x'21,x'22,x'23,......,x'2nBe standardized；The wherein value difference of x
For X'1、X'2In each weighting after the frequency；Frequency X " after being standardized1={ x "11,x″12,x″13,......,x″1nAnd
X″2={ x "21,x″22,x″23,......,x″2n}；
Third computing unit utilizes liveness formulaCalculate power grid client channel liveness and business
Liveness.
9. the power customer service preference analysis system based on channel preference and business preference as claimed in claim 8, special
Sign is:
Preference determining module includes:
Output unit, the different channels for exporting all user's difference channel liveness tables of data and being considered based on business are enlivened
Matrix D is spent, it is as follows,
Wherein,HijIndicate the liveness that i-th kind of business is handled using jth kind channel, xij”
Indicate that handles i-th kind of business using jth kind channel has been standardized the weighting frequency, x "(ij)minExpression is done using jth kind channel
That manages all business has been standardized weighting frequency minimum value, x "(ij)maxHaving been standardized for all business is handled using jth kind channel
Frequency maximum value is weighted, (i=1,2,3 ..., m }, j=1,2,3 ..., and n }, m, n are natural number)；
Preference determination unit determines the channel of specific preference for obtaining liveness in different channels according to user；For according to base
Determine the client for the preference of channels different in same business in the channel liveness matrix of business.
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