CN102487523A - User compliant analysis method and device - Google Patents

User compliant analysis method and device Download PDF

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CN102487523A
CN102487523A CN2010105762766A CN201010576276A CN102487523A CN 102487523 A CN102487523 A CN 102487523A CN 2010105762766 A CN2010105762766 A CN 2010105762766A CN 201010576276 A CN201010576276 A CN 201010576276A CN 102487523 A CN102487523 A CN 102487523A
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CN102487523B (en
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李威
默燕红
高鹏
袁捷
李秋中
周胜
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China Mobile Communications Group Co Ltd
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China Mobile Communications Group Co Ltd
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Abstract

The invention discloses a user compliant analysis method and device, wherein the user compliant analysis method comprises the following steps: collecting the number of complaints of each type of users; making statistics of average compliant probability of the complaints of each type of the users; and calculating the predicted number of the complaints of each type of the users according to the number of the complaints of each type of the users and the average compliant probability of the complaints of each type of the users. According to the user compliant analysis method and device, disclosed by the invention, the collected number of the user complaints is amplified by introducing an amplification coefficient (such as average compliant rate of the complaints of the users, correlation coefficient among the complaints of the different types of the users, the number of the solved complaints of one type of the users and the like), so that the comprehensive situation of network quality can be indicated through the complaints of part of the users. According to the user compliant analysis method and device disclosed by the invention, problems in a network can be made clear through the situation that the complaints of the different types of the users are formed, then the network can be optimized according to the demands of user perception and the pertinency of network optimization can be further improved.

Description

Customer complaint analytical method and device
Technical field
The present invention relates to a kind of network management technology, relate in particular to a kind of customer complaint analytical method and device.
Background technology
Present mobile/wireless communication system is carrying increasing business; Continuous aggravation along with the mobile communication market competition; Network quality becomes the key factor that strengthens enterprise competitiveness more; Also be that operator carries out link the most key in market and the business development, so the network optimization has become the emphasis that network operation is safeguarded.
Various Key Performance Indicators in the main network-oriented of the network optimization (KPI, Key PerformanceIndicator), to main businesses such as speeches, subregion, the normal operation that divides specialty guarantee network; Along with the continuous prosperity of business, network optimization demand side carries out differentiation, optimizes end to end to the service quality of mixed service to the user experience quality of complicated business, guarantees that the user uses the normal operation and the Quality of experience of miscellaneous service.
For operator, can the most directly embody the user to the network quality perception be exactly customer complaint, customer complaint quantity, classification that operator receives have direct directive significance to the network optimization.The technical scheme of carrying out the network optimization according to customer complaint is at present normally collected, is classified the customer complaint of being received, and carries out the feedback of failure judgment and complaint according to the rule of appointment.But the defective of these schemes is:
1, the problem of the just certain customers of customer complaint reflection but not comprehensive problem; For some network coverages less than the place possibly have situation about can't complain; And the user uses some the inconvenient perhaps not good contents of perception in the business not complain, and at present processing and the corresponding optimization work complained is not considered;
2, only be directed against up-to-date customer complaint of receiving usually to processing such as the collection of customer complaint, classification; But do not consider customer complaint in the past; Particularly same client is directed against the complaint repeatedly of same problem, and in fact the statistical analysis of interior customer complaint of a period of time has more directive significances for the network optimization.
Summary of the invention
The objective of the invention is to, a kind of customer complaint analytical method and device are provided, obtain more comprehensive customer complaint information through the complaint of certain customers.
For realizing above-mentioned purpose, according to an aspect of the present invention, a kind of customer complaint analytical method is provided, comprising: the quantity of gathering every type of customer complaint;
Add up the average complaint probability of every type of customer complaint;
The quantity of estimating that goes out every type of customer complaint based on the average complaint probability calculation of the quantity of said every type of customer complaint and every type of customer complaint is:
T i=N i/ C i, wherein, T iBe the quantity of estimating of i class customer complaint, N iBe the quantity of every type of customer complaint collecting, C iAverage complaint probability for every type of customer complaint.
For realizing above-mentioned purpose, according to another aspect of the present invention, a kind of customer complaint analytical method is provided, comprising: the quantity of gathering every type of customer complaint;
Calculate the coefficient correlation between the dissimilar customer complaints;
Estimate quantity T according to what the quantity of said coefficient correlation and every type of customer complaint calculated every type of customer complaint iFor:
Figure BSA00000375658300021
Wherein, R JiIt is the coefficient correlation between customer complaint of j class and the customer complaint of i class.
Preferably, this method also comprises: further estimate quantity T according to every type of customer complaint of average complaint probability calculation of every type of customer complaint iFor:
Wherein, C iAverage complaint probability for every type of customer complaint.
For realizing above-mentioned purpose, according to another aspect of the present invention, a kind of customer complaint analytical method is provided, comprising: the wherein quantity of one type of customer complaint that is captured in the quantity of every type of customer complaint in the certain hour section and in this time period, is resolved;
Estimate quantity T according to what the quantity of the quantity of the said wherein one type of customer complaint that is resolved and every type of customer complaint calculated next time period every type of customer complaint iFor:
Wherein, T i(t) the customer complaint quantity that collects in the time period for t; S i(t) quantity that is resolved for i class customer complaint in the t time period.
Preferably, this method also comprises: further the quantity of estimating according to every type of customer complaint of the calculating of the coefficient correlation between the dissimilar customer complaints is:
Figure BSA00000375658300031
Wherein, R JiIt is the coefficient correlation between customer complaint of j class and the customer complaint of i class.
More preferably, this method also comprises: further the quantity of estimating based on every type of customer complaint of average complaint probability calculation of every type of customer complaint is:
Wherein, C iAverage complaint probability for every type of customer complaint.
More preferably, this method also comprises: further the quantity of estimating based on every type of customer complaint of average complaint probability calculation of every type of customer complaint is:
Figure BSA00000375658300033
Wherein, C iAverage complaint probability for every type of customer complaint.
For realizing above-mentioned purpose, according to another aspect of the present invention, a kind of customer complaint analytical equipment is provided, comprising: acquisition module is used to gather the quantity of every type of customer complaint;
Statistical module is used to add up the average complaint probability of every type of customer complaint;
Computing module is used for the quantity of estimating that average complaint probability calculation according to the quantity of said every type of customer complaint and every type of customer complaint goes out every type of customer complaint and is:
T i=N i/ C i, wherein, T iBe the quantity of estimating of i class customer complaint, N iBe the quantity of every type of customer complaint collecting, C iAverage complaint probability for every type of customer complaint.
For realizing above-mentioned purpose, according to another aspect of the present invention, a kind of customer complaint analytical equipment is provided, comprising: acquisition module is used to gather the quantity of every type of customer complaint;
First computing module is used to calculate the coefficient correlation between the dissimilar customer complaints;
Second computing module, what be used for that quantity according to said coefficient correlation and every type of customer complaint calculates every type of customer complaint estimates quantity T iFor:
Figure BSA00000375658300041
Wherein, R JiIt is the coefficient correlation between customer complaint of j class and the customer complaint of i class.
For realizing above-mentioned purpose; According to another aspect of the present invention; A kind of customer complaint analytical equipment is provided, comprises: first acquisition module is used to the wherein quantity of one type of customer complaint that is captured in the quantity of every type of customer complaint in the certain hour section and in this time period, is resolved;
The 3rd calculates module, and what be used for that quantity according to the quantity of the said wherein one type of customer complaint that is resolved and every type of customer complaint calculates next time period every type of customer complaint estimates quantity T iFor:
Figure BSA00000375658300042
Wherein, S i(t) quantity that is resolved for i class customer complaint in the t time period.
Customer complaint analytical method of the present invention and device; Through introducing amplification coefficient (like average the rate of complaints of customer complaint, coefficient correlation and quantity of wherein one type of customer complaint of being resolved etc. between the variety classes customer complaint) the customer complaint quantity that has collected is amplified, realize appearing comprehensive situation of network quality through the complaint of certain customers.The present invention is through forming the situation of dissimilar customer complaints, the problem that exists in can definite network, and then can network be optimized according to the demand of user's perception, improve the specific aim of the network optimization.
Description of drawings
Fig. 1 is the flow chart of network optimization process of the present invention;
Fig. 2 is the structure chart of customer complaint analytical equipment embodiment of the present invention;
Fig. 3 is the structure chart of another embodiment of customer complaint analytical equipment of the present invention;
Fig. 4 is the customer complaint analytical equipment of the present invention structure chart of an embodiment again.
Embodiment
Below in conjunction with accompanying drawing the present invention is elaborated.
The present invention mainly on the customer complaint basis of classification, reasonably amplifies customer complaint.Suppose to have collected the customer complaint of M class in the section sometime in certain zone at present, every type is complained the actual quantity of collecting is (N 1, N 2..., N M).Customer complaint analytical method of the present invention mainly contains following several kinds of modes:
One, is (C according to average the rate of complaints (being the probability that the user complains) of the user being investigated every type of customer complaint of statistics when such problem occurs 1, C 2..., C M), 0＜C i≤1,0＜i≤M and be integer;
Quantity N according to every type of customer complaint iAnd the average complaint probability C of every type of customer complaint iThe quantity of estimating that calculates the customer complaint of i class is:
T i＝N i/C i。
Two, because there is correlation in certain customers between complaining; For example in fact the complaint to call drop in the communication process possibly imply the bad problem that covers; Calculate the coefficient correlation between the dissimilar complaints through Delphi method (being expert's scoring), like the coefficient R between customer complaint of j class and the customer complaint of i class Ji, wherein, 0＜R Ji≤1,0＜i, j≤M and be integer, R when j=i Ji=1, consider two types of reciprocities of complaining coefficient correlations to exist, the use that should reduce by half of actual coefficient correlation;
According to coefficient R JiQuantity N with every type of customer complaint iWhat calculate every type of customer complaint estimates quantity T iFor:
T i = Σ j = 1 M N i · R ji / 2 ;
Preferably, can be further according to the average complaint probability C of every type of customer complaint iThat calculates every type of customer complaint estimates quantity T iFor:
T i = Σ j = 1 M R ji / 2 · N i / C i .
If three, owing to exist same type to complain particularly under the situation by same customer complaint in the customer complaint in the past, client perception can sharply descend, therefore need be based on complained the analysis that adds up in the past.
Be captured in the quantity S of the i class customer complaint that t is resolved in the time period i(t), obvious S i(t) should be not more than the customer complaint quantity T that collects in this time period i(t), i.e. 0＜S i(t)≤T i(t), then the customer complaint of t+1 time period i class is estimated quantity and is:
T i ( t + 1 ) = N i ( t ) · ( 1 + Σ t T i ( t ) - S i ( t ) T i ( t ) ) ;
Preferably, can be in this mode further according to the coefficient R between the dissimilar customer complaints JiThe quantity of estimating of calculating every type of customer complaint is:
T i ( t + 1 ) = ( 1 + Σ t T i ( t ) - S i ( t ) T i ( t ) ) · Σ j = 1 M N i · R ji / 2 ;
More preferably, in this mode, can also be further according to the average complaint probability C of every type of customer complaint iThe quantity of estimating of calculating every type of customer complaint is:
T i ( t + 1 ) = ( 1 + Σ t T i ( t ) - S i ( t ) T i ( t ) ) · Σ j = 1 M R ji / 2 · N i / C i .
Also can be according to the quantity S of the i class customer complaint that obtains solving in this time period i(t), the customer complaint quantity T that collects in this time period i(t) and the average complaint probability C of every type of customer complaint iThe quantity of estimating of calculating every type of customer complaint is:
T i ( t + 1 ) = ( 1 + Σ t T i ( t ) - S i ( t ) T i ( t ) ) · N i / C i .
In addition, be the accuracy of guarantee amplifying and comprehensive, in above-mentioned three kinds of modes, average the rate of complaints C i, coefficient R JiAll should regularly bring in constant renewal in.
Customer complaint analytical method of the present invention; Not only to some customer complaints of newly receiving; Also be not limited to small number of users complain reflection problem; More considered some since the network coverage less than and can't complain or the user uses some inconvenient or the not good contents of perception possibly the not complained situation in the business; Through introducing amplification coefficient (like the quantity of average the rate of complaints, coefficient correlation and wherein one type of customer complaint of being resolved etc.) the customer complaint quantity that has collected is amplified, realize comprehensive situation that complaint through certain customers presents network quality through forming the situation of dissimilar customer complaints, the problem that exists in can definite network; And then can network be optimized according to the demand of user's perception, improve the specific aim of the network optimization.
As shown in Figure 1, obtain every type of customer complaint estimate quantity after, according to the data that obtain network is optimized, concrete network optimization flow process is following:
Step 102 sorts the quantity of estimating of variety classes customer complaint, can sort according to the size of estimating quantity;
Step 104; Problem and zone according to all types of user complaint; Obtain the current performance index value of certain entity in this zone passage testing equipment or network management, monitoring system; Contrast existing network entity performance index value and the predefined performance index threshold value of operator are confirmed the performance index that do not meet the demands, need optimize;
Step 106, the operation personnel are according to experience or device parameter function were divided the parameter of confirming to influence performance index value in the past.
Step 108 is confirmed the size that this parameter need be adjusted;
Step 110, corresponding adjustment parameter;
Step 112 compares adjusted network entity performance index value and corresponding predefined performance index threshold value, judges whether it satisfies predetermined requirement, if, execution in step 114; If not, execution in step 118;
Step 114 is obtained current other performance index values of certain entity through testing equipment or network management, monitoring system;
Step 116 compares adjusted other network entity performance index values and corresponding threshold value, judges whether it satisfies predetermined requirement, if, show that the new capability desired value satisfies predetermined requirement, use adjustment back parameter value later on, optimizing process is accomplished; If, do not return execution in step 104;
Step 116 judges whether adjusted parameter value has exceeded predetermined parameters value scope, if return execution in step 106; If, do not return execution in step 108.
For example: the customer complaint quantity of complaining certain regional signal to insert is 5, and complaining probability is 25%, and then according to above-mentioned analytical method one, the quantity of estimating of customer complaint is 5/0.25=20;
Whether be lower than certain threshold according to this complaint value observation call completing rate and actual test access level afterwards, adjustment inserts level threshold and neighbor cell configuration, guarantees that the user can insert;
Whether test access level and call completing rate reach certain threshold once more at last, and carry out the real road test and see that the access situation judges whether to meet the demands.
As shown in Figure 2, customer complaint analytical equipment embodiment of the present invention comprises:
Acquisition module 22 is used to gather the quantity of every type of customer complaint;
Statistical module 24 is used to add up the average complaint probability of every type of customer complaint;
Computing module 26 is used for the quantity of estimating that average complaint probability calculation according to the quantity of said every type of customer complaint and every type of customer complaint goes out every type of customer complaint and is: T i=N i/ C i
As shown in Figure 3, another embodiment of customer complaint analytical equipment of the present invention comprises:
Acquisition module 32 is used to gather the quantity of every type of customer complaint;
First computing module 34 is used to calculate the coefficient correlation between the dissimilar customer complaints;
Second computing module 36, what be used for that quantity according to said coefficient correlation and every type of customer complaint calculates every type of customer complaint estimates quantity T iFor:
Figure BSA00000375658300081
Preferably, this device also comprises statistical module 38, is used to add up the average complaint probability of every type of customer complaint;
Second computing module 36 is used for further estimating quantity T according to every type of customer complaint of average complaint probability calculation of every type of customer complaint iFor:
Figure BSA00000375658300082
As shown in Figure 4, a customer complaint analytical equipment of the present invention embodiment again comprises:
Acquisition module 42 is used to the wherein quantity of one type of customer complaint that is captured in the quantity of every type of customer complaint in the certain hour section and in this time period, is resolved;
Second computing module 44, what be used for that quantity according to the quantity of the said wherein one type of customer complaint that is resolved and every type of customer complaint calculates next time period every type of customer complaint estimates quantity T iFor:
T i ( t + 1 ) = N i ( t ) · ( 1 + Σ t T i ( t ) - S i ( t ) T i ( t ) ) .
Preferably, this device also comprises:
First computing module 46 is used to calculate the coefficient correlation between the dissimilar customer complaints;
Second computing module 44, the quantity of estimating that is used for further calculating according to the coefficient correlation between the dissimilar customer complaints every type of customer complaint is:
T i ( t + 1 ) = ( 1 + Σ t T i ( t ) - S i ( t ) T i ( t ) ) · Σ j = 1 M N i · R ji / 2 .
More preferably, this device also comprises:
Statistical module 48 is used to add up the average complaint probability of every type of customer complaint;
Second computing module 44, be used for further according to the quantity of estimating of every type of customer complaint of average complaint probability calculation of every type of customer complaint be:
T i ( t + 1 ) = ( 1 + Σ t T i ( t ) - S i ( t ) T i ( t ) ) · Σ j = 1 M R ji / 2 · N i / C i .
Preferably, this device comprises: acquisition module 42, second computing module 44 and statistical module 48,
Second computing module 44, be used for further according to the quantity of estimating of every type of customer complaint of average complaint probability calculation of every type of customer complaint be:
Figure BSA00000375658300092
Wherein, C iAverage complaint probability for every type of customer complaint.
The customer complaint analytical equipment of above-mentioned three embodiment; Not only to some customer complaints of newly receiving; Also be not limited to small number of users complain reflection problem; More considered some since the network coverage less than and can't complain or the user uses some inconvenient or the not good contents of perception possibly the not complained situation in the business; Through introducing amplification coefficient (like the quantity of average the rate of complaints, coefficient correlation and wherein one type of customer complaint of being resolved etc.) the customer complaint quantity that has collected is amplified, realize comprehensive situation that complaint through certain customers presents network quality through forming the situation of dissimilar customer complaints, the problem that exists in can definite network; And then can network be optimized according to the demand of user's perception, improve the specific aim of the network optimization.
What should explain is: above embodiment is only unrestricted in order to explanation the present invention, and the present invention also is not limited in above-mentioned giving an example, and all do not break away from the technical scheme and the improvement thereof of the spirit and scope of the present invention, and it all should be encompassed in the claim scope of the present invention.

Claims (14)

1. a customer complaint analytical method is characterized in that, comprising:
Gather the quantity of every type of customer complaint;
Add up the average complaint probability of every type of customer complaint;
The quantity of estimating that goes out every type of customer complaint based on the average complaint probability calculation of the quantity of said every type of customer complaint and every type of customer complaint is:
T i=N i/ C i, wherein, T iBe the quantity of estimating of i class customer complaint, N iBe the quantity of every type of customer complaint collecting, C iAverage complaint probability for every type of customer complaint.
2. a customer complaint analytical method is characterized in that, comprising:
Gather the quantity of every type of customer complaint;
Calculate the coefficient correlation between the dissimilar customer complaints;
Estimate quantity T according to what the quantity of said coefficient correlation and every type of customer complaint calculated every type of customer complaint iFor:
Figure FSA00000375658200011
Wherein, R JiIt is the coefficient correlation between customer complaint of j class and the customer complaint of i class.
3. customer complaint analytical method according to claim 2 is characterized in that, also comprises:
Further estimate quantity T according to every type of customer complaint of average complaint probability calculation of every type of customer complaint iFor:
Wherein, C iAverage complaint probability for every type of customer complaint.
4. a customer complaint analytical method is characterized in that, comprising:
The wherein quantity of one type of customer complaint that is captured in the quantity of every type of customer complaint in the certain hour section and in this time period, is resolved;
Estimate quantity T according to what the quantity of the quantity of the said wherein one type of customer complaint that is resolved and every type of customer complaint calculated next time period every type of customer complaint iFor:
Figure FSA00000375658200013
Wherein, T i(t) the customer complaint quantity that collects in the time period for t; S i(t) quantity that is resolved for i class customer complaint in the t time period.
5. customer complaint analytical method according to claim 4 is characterized in that, also comprises:
Further the quantity of estimating according to every type of customer complaint of the calculating of the coefficient correlation between the dissimilar customer complaints is:
Figure FSA00000375658200021
Wherein, R JiIt is the coefficient correlation between customer complaint of j class and the customer complaint of i class.
6. customer complaint analytical method according to claim 5 is characterized in that, also comprises:
Further the quantity of estimating based on every type of customer complaint of average complaint probability calculation of every type of customer complaint is:
Figure FSA00000375658200022
Wherein, C iAverage complaint probability for every type of customer complaint.
7. customer complaint analytical method according to claim 4 is characterized in that, also comprises:
Further the quantity of estimating based on every type of customer complaint of average complaint probability calculation of every type of customer complaint is:
Wherein, C iAverage complaint probability for every type of customer complaint.
8. a customer complaint analytical equipment is characterized in that, comprising:
Acquisition module is used to gather the quantity of every type of customer complaint;
Statistical module is used to add up the average complaint probability of every type of customer complaint;
Computing module is used for the quantity of estimating that average complaint probability calculation according to the quantity of said every type of customer complaint and every type of customer complaint goes out every type of customer complaint and is:
T i=N i/ C i, wherein, T iBe the quantity of estimating of i class customer complaint, N iBe the quantity of every type of customer complaint collecting, C iAverage complaint probability for every type of customer complaint.
9. a customer complaint analytical equipment is characterized in that, comprising:
Acquisition module is used to gather the quantity of every type of customer complaint;
First computing module is used to calculate the coefficient correlation between the dissimilar customer complaints;
Second computing module, what be used for that quantity according to said coefficient correlation and every type of customer complaint calculates every type of customer complaint estimates quantity T iFor:
Figure FSA00000375658200031
Wherein, R JiIt is the coefficient correlation between customer complaint of j class and the customer complaint of i class.
10. customer complaint analytical equipment according to claim 9 is characterized in that, also comprises:
Statistical module is used to add up the average complaint probability of every type of customer complaint;
Said second computing module is used for further estimating quantity T according to every type of customer complaint of average complaint probability calculation of every type of customer complaint iFor:
Figure FSA00000375658200032
Wherein, C iAverage complaint probability for every type of customer complaint.
11. a customer complaint analytical equipment is characterized in that, comprising:
First acquisition module is used to the wherein quantity of one type of customer complaint that is captured in the quantity of every type of customer complaint in the certain hour section and in this time period, is resolved;
The 3rd calculates module, and what be used for that quantity according to the quantity of the said wherein one type of customer complaint that is resolved and every type of customer complaint calculates next time period every type of customer complaint estimates quantity T iFor:
Figure FSA00000375658200033
Wherein, S i(t) quantity that is resolved for i class customer complaint in the t time period.
12. customer complaint analytical equipment according to claim 11 is characterized in that, also comprises:
First computing module is used to calculate the coefficient correlation between the dissimilar customer complaints;
The said the 3rd calculates module, and the quantity of estimating that is used for further calculating according to the coefficient correlation between the dissimilar customer complaints every type of customer complaint is:
Wherein, R JiIt is the coefficient correlation between customer complaint of j class and the customer complaint of i class.
13. customer complaint analytical equipment according to claim 12 is characterized in that, also comprises:
Statistical module is used to add up the average complaint probability of every type of customer complaint;
The said the 3rd calculates module, is used for further according to the quantity of estimating of every type of customer complaint of average complaint probability calculation of every type of customer complaint being:
Figure FSA00000375658200042
Wherein, C iAverage complaint probability for every type of customer complaint.
14. customer complaint analytical equipment according to claim 11 is characterized in that, also comprises:
Statistical module is used to add up the average complaint probability of every type of customer complaint;
The said the 3rd calculates module, is used for further according to the quantity of estimating of every type of customer complaint of average complaint probability calculation of every type of customer complaint being:
Figure FSA00000375658200043
Wherein, C iAverage complaint probability for every type of customer complaint.
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