CN109274842A - Key factor localization method, device and the equipment of customer service level fluctuation - Google Patents
Key factor localization method, device and the equipment of customer service level fluctuation Download PDFInfo
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- CN109274842A CN109274842A CN201811089397.0A CN201811089397A CN109274842A CN 109274842 A CN109274842 A CN 109274842A CN 201811089397 A CN201811089397 A CN 201811089397A CN 109274842 A CN109274842 A CN 109274842A
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04M—TELEPHONIC COMMUNICATION
- H04M3/00—Automatic or semi-automatic exchanges
- H04M3/42—Systems providing special services or facilities to subscribers
- H04M3/50—Centralised arrangements for answering calls; Centralised arrangements for recording messages for absent or busy subscribers ; Centralised arrangements for recording messages
- H04M3/51—Centralised call answering arrangements requiring operator intervention, e.g. call or contact centers for telemarketing
- H04M3/5175—Call or contact centers supervision arrangements
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04M—TELEPHONIC COMMUNICATION
- H04M3/00—Automatic or semi-automatic exchanges
- H04M3/22—Arrangements for supervision, monitoring or testing
- H04M3/2227—Quality of service monitoring
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04M—TELEPHONIC COMMUNICATION
- H04M3/00—Automatic or semi-automatic exchanges
- H04M3/22—Arrangements for supervision, monitoring or testing
- H04M3/36—Statistical metering, e.g. recording occasions when traffic exceeds capacity of trunks
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04M—TELEPHONIC COMMUNICATION
- H04M2203/00—Aspects of automatic or semi-automatic exchanges
- H04M2203/40—Aspects of automatic or semi-automatic exchanges related to call centers
Abstract
This specification embodiment provides key factor localization method, device and the equipment of a kind of customer service level fluctuation, obtains the traffic data in current period.Determine at least one index for assessing customer service level.The index has the impact factor of multiple dimensions, and the impact factor of each dimension is corresponding with a sets of factors.The contribution degree that each factor fluctuates customer service level in Multiple factors set corresponding with the index is determined according to above-mentioned traffic data to each index.According to the contribution degree, the factor that is affected is chosen from each factor of Multiple factors set.The factor of being affected corresponding with each index is carried out summarizing calculating, to determine the key factor of the customer service level fluctuation in current period.
Description
Technical field
This specification one or more embodiment be related to field of computer technology more particularly to a kind of customer service level fluctuation
Key factor localization method, device and equipment.
Background technique
Customer calling center has become the important channel and tool that various industries are engaged in customer service at present, customer calling center
Service level (abbreviation customer service is horizontal) is an important factor for influencing companies' soft powers such as corporate reputation, user's stickiness.It is competing in industry
It strives more and more fierce today, how while not increasing existing operation cost, the key factor of positioning customer service level fluctuation,
To rational allocation resource, the service that higher quality is more suitable for is provided for user, it is urgent to become current each customer calling center
Problem to be solved.
Current existing scheme are as follows: the key factor fluctuated based on service scenarios to customer service level is analyzed.Namely it passes
It can only be the key factor that the fluctuation of customer service level is positioned based on single-factor (e.g., service scenarios) in system technology.Therefore, it is necessary to
A kind of key factor localization method of more accurately customer service level fluctuation is provided.
Summary of the invention
This specification one or more embodiment describes key factor localization method, the device of a kind of customer service level fluctuation
And equipment, the accuracy of the key factor positioning of customer service level fluctuation can be improved.
In a first aspect, providing a kind of key factor localization method of customer service level fluctuation, comprising:
Obtain the traffic data in current period；
Determine that at least one index for assessing customer service level, the index have the impact factor of multiple dimensions, often
The impact factor of a dimension is corresponding with a sets of factors；
Each factor pair in Multiple factors set corresponding with the index is determined according to the traffic data to each index
The contribution degree of customer service level fluctuation；
According to the contribution degree, the factor that is affected is chosen from each factor of the multiple sets of factors；
The factor of being affected corresponding with each index is carried out summarizing calculating, to determine, customer service is horizontal in current period
The key factor of fluctuation.
Second aspect provides a kind of key factor positioning device of customer service level fluctuation, comprising:
Acquiring unit, for obtaining the traffic data in current period；
Determination unit, for determining that at least one index for assessing customer service level, the index have multiple dimensions
Impact factor, the impact factor of each dimension is corresponding with a sets of factors；
The determination unit is also used to each index, and according to the traffic data, determination is corresponding with the index multiple
The contribution degree that each factor fluctuates customer service level in sets of factors；
Selection unit, the contribution degree for being determined according to the determination unit, from each of the multiple sets of factors
The factor that is affected is chosen in factor；
Collection unit, for summarizing to the factor of being affected corresponding with each index that the selection unit is chosen
It calculates, to determine the key factor of the customer service level fluctuation in current period.
The third aspect provides a kind of key factor positioning device of customer service level fluctuation, comprising:
Memory；
One or more processors；And
One or more programs wherein the storage of one or more of programs is in the memory, and are configured to
It is executed by one or more of processors, described program performs the steps of when being executed by the processor
Obtain the traffic data in current period；
Determine that at least one index for assessing customer service level, the index have the impact factor of multiple dimensions, often
The impact factor of a dimension is corresponding with a sets of factors；
Each factor pair in Multiple factors set corresponding with the index is determined according to the traffic data to each index
The contribution degree of customer service level fluctuation；
According to the contribution degree, the factor that is affected is chosen from each factor of the multiple sets of factors；
The factor of being affected corresponding with each index is carried out summarizing calculating, to determine, customer service is horizontal in current period
The key factor of fluctuation.
The key factor localization method for the customer service level fluctuation that this specification one or more embodiment provides and is set device
It is standby, obtain the traffic data in current period.Determine at least one index for assessing customer service level.The index has more
The impact factor of a dimension, the impact factor of each dimension are corresponding with a sets of factors.To each index, according to above-mentioned words
Business data, determine the contribution degree that each factor fluctuates customer service level in Multiple factors set corresponding with the index.According to the tribute
Degree of offering chooses the factor that is affected from each factor of Multiple factors set.To the factor that is affected corresponding with each index
It carries out summarizing calculating, to determine the key factor of the customer service level fluctuation in current period.It can thus be seen that this specification mentions
The scheme of confession can be based on the impact factor of multiple dimensions, to position the key factor of customer service level fluctuation.Thus, it is possible to improve
The accuracy of the key factor positioning of customer service level fluctuation.
Detailed description of the invention
In order to illustrate more clearly of the technical solution of this specification embodiment, will make below to required in embodiment description
Attached drawing is briefly described, it should be apparent that, the accompanying drawings in the following description is only some embodiments of this specification, right
For those of ordinary skill in the art, without creative efforts, it can also be obtained according to these attached drawings
Its attached drawing.
Fig. 1 is the application scenarios schematic diagram of the key factor localization method for the customer service level fluctuation that this specification provides；
Fig. 2 is the key factor localization method flow chart for the customer service level fluctuation that this specification one embodiment provides；
Fig. 3 is the corresponding relation determining method flow chart between index value and factor that this specification provides；
Fig. 4 is the key factor positioning device schematic diagram for the customer service level fluctuation that this specification one embodiment provides；
Fig. 5 is the key factor positioning device schematic diagram for the customer service level fluctuation that this specification one embodiment provides.
Specific embodiment
With reference to the accompanying drawing, the scheme provided this specification is described.
The key factor localization method for the customer service level fluctuation that this specification one or more embodiment provides can be applied
In scene as shown in Figure 1.In Fig. 1, user can request to service by corresponding terminal to customer calling center.Wherein,
Request channel can include but is not limited to short message, phone or APP etc..Customer calling center divides when there is user to request service
It (is referred to as servicing small two) and provides service for it with corresponding people or machine.Wherein, process of the service small two in service user
Obtained in data be properly termed as traffic data.
It should be noted that the quality in order to guarantee customer calling center service provided, it usually needs periodically to visitor
The service level (abbreviation customer service is horizontal) of family call center is assessed.In one implementation, following one can be passed through
A or multiple indexs assess customer service level: average call duration (Average Talk Time, ATT), average call
Operating time (After Call Work/After Call Wrap-up, ACW), absolute satisfaction, investigation satisfaction, head are asked afterwards
Fix-rate (First-call resolution, FCR), switching-out rate, final election rate, ten thousand throwing rates and ten thousand one-tenth rates.Wherein, ATT refers to
Service the small two average durations talked online with user.ACW refers to needed for servicing small two after end and user's communication at once
The average duration of the task or work completed.Absolute satisfaction refers to that user clicks after taking on the telephone and is satisfied with key
Accounting.Investigation satisfaction refers to that user indicates the accounting to service satisfactory in investigation questionnaire.FCR refers to user in this phone
The accounting that do not send a telegram here in 24 hours after service.Switching-out rate refers to that service small two transfers user to other services after service
Small two accountings serviced.Final election rate refers to that service small two when meeting the multiple service demands of user in logical service, is chosen more
The accounting of a service classification.Ten thousand throwing rates refer to the complaint number generated in every 10,000 logical services.Ten thousand refer to every 10,000 logical clothes at rate
Number is set up in the complaint generated in business.
It is understood that can all lead to the fluctuation of customer service level when any of the above-described index fluctuates.However actually
Does is it the fluctuation which type of factor will lead to index? the reason of consideration may be business aspect first, e.g., service scenarios etc..
Secondly as the service small two for providing service may be people, and personnel's otherness generally also will affect These parameters.Therefore, originally
The scheme that specification provides can analyze the fluctuation of index by two personnel, business aspects.Such as, it can receive respectively
Collect the factor (e.g., personnel's distribution of the factor (e.g., service scenarios etc.) and personnel's attribute for portraying the service attribute of each index
Deng).Using multiple factors of collection as the impact factor of multiple dimensions of each index.In addition, in order to the horizontal wave of customer service
Dynamic reason carries out finer positioning, and this specification can be based on corresponding service logic, by the impact factor of each dimension
It is split as Multiple factors.Wherein, it may be constructed a sets of factors with Multiple factors corresponding to the impact factor of each dimension.
The fluctuation of above-mentioned customer service level can refer to each index based on two periods (e.g., current period and the upper period)
Index value, the having differences property of polygon drawn out in radar map.Here period can be one day, one week or one
Month.
It should be noted that this specification provide scheme be namely based in sets of factors as above because usually to each index
The factor of fluctuation is positioned.The factor fluctuated later according to each index, the key factor to fluctuate to customer service level are determined
Position.
Fig. 2 is the key factor localization method flow chart for the customer service level fluctuation that this specification one embodiment provides.Institute
The executing subject for stating method can be the customer calling center in Fig. 1.As shown in Fig. 2, the method can specifically include:
Step 202, the traffic data in current period is obtained.
Such as, it can be and obtain above-mentioned traffic data from the background data base of customer calling center.Here period can be with
It is one day, one week or one month.And above-mentioned traffic data can include but is not limited to: service small two mark, is led at the service date
Talk about duration and service classification etc..
Step 204, at least one index for assessing customer service level is determined.
Here index can include but is not limited to: ATT, ACW, absolute satisfaction, investigation satisfaction, FCR, switching-out rate,
Final election rate, ten thousand throwing rates and ten thousand one-tenth rates etc..
It should be noted that the index in this specification can have the impact factor of multiple dimensions.Such as, service scenarios with
And personnel's distribution etc..The impact factor of each dimension is corresponding with a sets of factors.Here the factor in sets of factors can
To be based on corresponding service logic, by what is obtained after the impact factor refinement of corresponding dimension.With certain index tool, there are three dimensions
Impact factor, respectively indicate are as follows: for for factors A, factor B and factor C, factor corresponding with the impact factor of each dimension
Set can respectively indicate are as follows: { a1, a2 ..., an }, { b1, b2 ..., bm }, { c1, c2 ..., ck }, wherein a1, a2 etc. are indicated
Factor in sets of factors, n, m and k respectively indicate the number of the factor in each sets of factors.
It should be understood that different indexs, the impact factor of corresponding multiple dimensions can be the same or different.In addition,
The same affect factor of different indexs, the factor in corresponding sets of factors can be the same or different, this specification pair
This is not construed as limiting.
Step 206, it to each index, according to the traffic data, determines each in Multiple factors set corresponding with the index
The contribution degree that factor fluctuates customer service level.
In one implementation, the determination method of the contribution degree of certain factor can be such that the traffic according to current period
Data, statistical considerations current period index value, factor current period magnitude accounting and current period overall performane value.Acquisition factor
A period magnitude accounting and upper period overall performane value in upper cyclical indicator value, factor.Referred to according to the factor in two periods
Scale value, factor magnitude accounting and overall performane value determine the contribution degree that the factor fluctuates customer service level.
In one example, according to the factor index value, factor magnitude accounting and overall performane value in two periods, determining should
The contribution degree that factor fluctuates customer service level, comprising:
Determine the contribution degree that certain factor fluctuates customer service level according to the following formula: contribution degree=(factor current period refers to
A period magnitude accounting in a cyclical indicator value * factor in scale value * factor current period magnitude accounting-factor)/(current period
The upper period overall performane value of overall performane value -).
It should be noted that factor current period index value, factor current period magnitude accounting and current period always refer to
The calculation method of scale value is subsequent to be illustrated.A cyclical indicator value is similar with the definition of factor current period index value in factor,
A period magnitude accounting is similar with the definition of factor current period magnitude accounting in factor, upper period overall performane value and current week
The phase definition of overall performane value is similar.It is understood that the related data in a upper period, which can be, had counted it in a upper period
After be recorded in corresponding storage unit, it is subsequent directly from the storage unit read.
Step 208, according to contribution degree, the factor that is affected is chosen from each factor of Multiple factors set.
It in one implementation, can be according to the sequence of contribution degree from big to small to the factor in each sets of factors
It is ranked up.Later, the forward factor that sorts is chosen from each sets of factors as the factor that is affected.
In another implementation, the factor of being affected can also be chosen suddenly by following steps:
Step a can choose influence factor from each sets of factors according to contribution degree, to obtain multiple influence factors.
Here influence factor can refer to the maximum factor of contribution degree in each sets of factors.Such as, it can indicate are as follows: ai,
Bj and cl etc., wherein ai indicates sets of factors: the maximum factor of contribution degree in { a1, a2 ..., an }；Bj indicates factor
Set: the maximum factor of contribution degree in { b1, b2 ..., bm }；Cl indicates sets of factors: the contribution degree in { c1, c2 ..., ck }
Maximum factor.
Step b calculates similarity to multiple influence factors two-by-two.
Such as, the similarity between ai and bj, ai and cl and bj and cl can be calculated separately.
It in one example, can be above-mentioned similar to calculate by calculating the Jaccard similarity factor between influence factor
Degree.For for calculating the similarity between ai and bj, the calculation formula of the similarity can be indicated are as follows: similarity=min
(ai, bj intersection are to the contribution degree/ai integrally fluctuated to the contribution degree integrally fluctuated, ai, contribution of the bj intersection to integrally fluctuating
Degree/bj is to the contribution degree integrally fluctuated).
It should be noted that above-mentioned ai is contribution degree of the ai to service level to the contribution degree integrally fluctuated, bj is to whole
The dynamic contribution degree of bulk wave is contribution degree of the bj to service level, which has passed through step 206 and be calculated.It is right
In ai, bj intersection is to the contribution degree integrally fluctuated, it is assumed that ai is that small two, the bj in middle section is stolen scene, then during it can be understood as
Section small two is under stolen scene to the contribution degree of customer service level fluctuation.Circular can be found in the contribution degree in step 206
Calculation formula does not repeat again herein.
Step c determines factor to be refined according to above-mentioned similarity from multiple influence factors.
Specifically, to multiple influence factor, it can judge two-by-two whether similarity is greater than threshold value.If certain two influences
Similarity between factor is not more than threshold value, then two influence factors is determined as factor to be refined.If certain two shadow
Similarity between the factor of sound is greater than threshold value, then contribution degree large effect factor is chosen from two influence factors, by this
Contribution degree large effect factor is determined as factor to be refined.
The above-mentioned principle that similarity compares with threshold value can be with are as follows: if the similarity of two influence factors is little
In threshold value, then illustrate that the degree of overlapping of two influence factors is smaller.And since two influence factors are all likely to become influence
The reason of current criteria fluctuates, therefore have the necessity further refined, so that the rwo to be chosen for factor to be refined.Together
Reason illustrates that the degree of overlapping of two influence factors is bigger if the similarity of two influence factors is greater than threshold value, the rwo
It is also similar to the influence power of current criteria.Therefore it only chooses contribution degree large effect factor to be refined, to reduce to thin
The number of change factor, and then promote location efficiency.
Now in conjunction with actual scene, above-mentioned steps a- step c is exemplified below: assuming that a sets of factors are as follows: { leading portion is small
Two, middle section is small two, small two } of back segment, and the contribution degree in middle section small two is maximum；Another sets of factors are as follows: { stolen scene is cheated
Scene }, and the contribution degree of stolen scene is maximum.The similarity between middle section small two and stolen scene can so be calculated.If
Similarity is greater than 50%, then judges whether the contribution degree in middle section small two is larger, if it is, small to the middle section two refine；
If it is not, then being refined to stolen scene.If similarity no more than 50%, small to middle section two and stolen scene into
Row refinement.
Step d treats refinement factor and is refined, thus factor after being refined.
Herein, it can be through being refined because usually treating refinement factor in prescription factors set, be also possible to lead to
Selection target factor set is crossed, is refined later by what target factor was concentrated because usually treating refinement factor.
When choosing target factor set, the selection process of the target factor set can be with are as follows: determines other factors collection
Factor in conjunction treats information state obtained after refinement factor is refined.According to information state obtained, from other
Target factor set is chosen in sets of factors.Refinement factor is treated with the factor in target factor set to be refined, thus
Factor after to refinement.
Here other factors set refers in the corresponding all sets of factors of current criteria except wait refine collection belonging to factor
Sets of factors outside conjunction.With the corresponding all sets of factors of current criteria are as follows: and a1, a2 ..., an }, b1, b2 ..., bm },
{ c1, c2 ..., ck }, factor to be refined are as follows: for for ai, other factors set can refer to { b1, b2 ..., bm } and
{c1,c2,…,ck}。
In one example, it can be through following formula and determine above- mentioned information situation.
Information delta=Σ-p (xi) ln (p (xi))
Wherein, xi is factor after refinement, and when with sets of factors: each factor in { b1, b2 ..., bm } treats refinement factor:
When ai is refined, xi be respectively as follows: aib1, aib2 ..., aibm, wherein the number of x be m.Similarly, when with sets of factors:
Each factor in { c1, c2 ..., ck } treats refinement factor: when ai is refined, xi be respectively as follows: aic1, aic2 ..., aick,
Wherein, the number of x is k.Assuming that with sets of factors: each factor in { b1, b2 ..., bm } treats refinement factor: ai is refined
Afterwards, the information delta obtained is larger.{ b1, b2 ..., bm } can be then chosen for target factor set, and factor point after refinement
Not are as follows: aib1, aib2 ..., aibm.
Step e calculates the contribution degree that factor fluctuates customer service level after refining.
With factor after refinement are as follows: for for aib1, can be understood as ai, b1 to the contribution degree of customer service level fluctuation
Intersection is to the contribution degree integrally fluctuated.The calculation method of the contribution degree of factor can refer to the contribution degree in step 206 after each refinement
Calculation formula does not repeat again herein.
Step f, according to the contribution degree of factor after refinement, from choosing the factor that is affected after refinement in factor.
Such as, factor after refinement can be ranked up according to the sequence of contribution degree from big to small.It is forward therefrom to choose sequence
And the sum of contribution degree is used as the factor that is affected greater than factor after the refinement of threshold value.
Such as previous example, it is assumed that after the refinement after sequence factor be respectively as follows: aib1, aib2, aib3 ..., aibm, and assume
The sum of contribution degree of aib1, aib2 and aib3 is greater than 80%, then by aib1, aib2 and aib3 be chosen for being affected because
Element.
Now in conjunction with actual scene, above-mentioned steps d- step f being exemplified below: assuming that factor to be refined are as follows: middle section is small by two, and
Target factor set are as follows: { stolen scene, cheated scene } can then extract middle section small two in each service scenarios to customer service level
The biggish scene of fluctuation contribution degree is as the factor that is affected.
It is understood that repeating above-mentioned steps 206- step 208, so that it may obtain shadow corresponding with each index
Ring larger factor.
Step 210, the factor of being affected corresponding with each index is carried out summarizing calculating, to determine in current period
The key factor of customer service level fluctuation.
Specifically, the total degree that the larger factor of Different Effects respectively occurs can be counted.Choose the maximum influence of total degree
Larger factor is as the key factor that customer service level fluctuates in current period.As an example it is assumed that it is directed to this index of ATT,
The factor that is affected chosen are as follows: a1b2, a2b3；And it is directed to this index of absolute satisfaction, the factor that is affected of selection are as follows:
a1b2.Therefore there are two the factors that is affected in total: a1b2 and a2b3, there is total degree and is respectively as follows: 2 times and 1 time in the rwo.
So a1b2 is determined as the key factor that customer service level fluctuates in current period.
To sum up, this specification embodiment is carrying out factor refinement using the single-factor control screening higher factor of priority
When analysis, factor junior is disassembled by comentropy and carries out beta pruning, algorithm is developed to the factor at the same level by Jaccard similarity factor
Carry out beta pruning.It can find that personnel and the business of industry factor to the reason of influence of fluctuations maximum, will not omit simultaneously by this algorithm
Or misjudgement key factor.
Below to factor current period index value, factor current period magnitude accounting and the current period in step 206
The calculation method of overall performane value is illustrated.
It, can be first according to the traffic data of current period, respectively from multiple dimension meters before executing above-mentioned calculating process
The index value of certain index is calculated, to obtain the index value of multiple dimensions.According to Grubbs (Grubbs) method of inspection and statistics
Standard deviation carries out abnormality processing to obtained index value.To the index value of each dimension after abnormality processing, from the dimension
Impact factor corresponding to corresponding factor is determined in sets of factors.Later, according to the index value of each dimension and factor it
Between corresponding relationship, determine the factor current period index of each factor in sets of factors corresponding to the impact factor of the dimension
The current period overall performane value of value, factor current period magnitude accounting and all factors.
The index value of certain index is determined with the dimension being distributed from personnel, the impact factor of current dimension is personnel point in other words
Cloth, and corresponding sets of factors are as follows: leading portion is small two, middle section is small two, for small two } of back segment for, the index value of the dimension and because
Corresponding relationship determination process between element can be as shown in Figure 3.In Fig. 3, it may include steps of:
Step 302, statistics services the index value of small two certain index in every call business of current period.
For by taking the index is ATT as an example, it is assumed that be collected into 100 calls business in advance, then can be the every call of statistics here
Small two ATT value is serviced in business accordingly.
Step 304, small to different services by two, calculate the average value and standard deviation of corresponding index value.
In previous example, the service small two in 100 call business in the traffic of part may be identical.For identical service
It is small by two, according to its ATT value in multi-pass traffic, determine corresponding average value and standard deviation.
Step 306, to it is identical service it is small by two, judge corresponding each index value whether before and after its mean value three standard deviations
Outside range.If so, thening follow the steps 308；It is no to then follow the steps 310.
Step 308, the index value before and after its mean value outside three standard deviation ranges is rejected.
Step 310, the corresponding relationship in each index value and above-mentioned factor set between each factor is established.
Such as, it can be determined that whether certain index value is less than the mean value of corresponding with service small two and the difference of standard deviation, if it is less,
The index value is small by two labeled as leading portion；If it is not, then judging whether the index value is greater than the mean value of corresponding with service small two
The sum of with standard deviation, if it is greater, then the index value is small by two labeled as leading portion；If it is not greater, then the index value is marked
It is small by two for middle section.
After each index value as above mark, so that it may obtain the corresponding relationship between each index value and factor
?.
Assuming that the corresponding relationship between each index value and factor is as shown in table 1.
Table 1
| It services small by two | Index value | Factor |
| Zhang San | 10s | Leading portion is small by two |
| Zhang San | 50s | Middle section is small by two |
| Li Si | 15s | Leading portion is small by two |
| King five | 100s | Back segment is small by two |
For by taking the corresponding relationship in table 1 as an example, it is assumed that factor are as follows: leading portion is small by two, then factor current period index value are as follows:
(10s+15s)/2=12.5s.Current period overall performane value are as follows: (10s+50s+15s+100s)/4=43.75s.Factor is currently all
Phase magnitude accounting=2/4=50%.Namely factor current period magnitude accounting can be factor service times and affiliated set of factors
The ratio of each factor service total degree in conjunction.
To sum up, the key factor positioning side of the customer service level fluctuation provided by this specification one or more embodiment
Method, can be distributed from personnel and multiple dimension discoveries such as service scenarios are to the factor of the horizontal influence of fluctuations of customer service, will not omit
Or misjudgement key factor.Further, since the scheme of this specification introduces the impact factor of multiple dimensions, thus the practicality and
Validity is preferable.Finally, due to which the algorithm model coupling that this specification provides is relatively low, those skilled in the art can draw at any time
Enter more impact factors, therefore its scalability is preferable.
Accordingly, this specification one embodiment also provides the key factor localization method fluctuated with above-mentioned customer service level
A kind of key factor positioning device of customer service level fluctuation, as shown in figure 4, the apparatus may include:
Acquiring unit 402, for obtaining the traffic data in current period.
Determination unit 404, for determining that at least one index for assessing customer service level, the index have multiple dimensions
Impact factor, the impact factor of each dimension is corresponding with a sets of factors.
Here index may include following one or more: operating time after average call duration ATT, average call
ACW, absolute satisfaction, investigation satisfaction, head ask fix-rate FCR, switching-out rate, final election rate, ten thousand throwing rates and ten thousand one-tenth rates etc..
Determination unit 404 is also used to each index, and according to above-mentioned traffic data, determination is corresponding with the index multiple
The contribution degree that each factor fluctuates customer service level in sets of factors.
Determination unit 404 specifically can be used for:
To each factor in sets of factors, according to the traffic data of current period, statistical considerations current period index value,
Factor current period magnitude accounting and current period overall performane value.
A cyclical indicator value in acquisition factor, a period magnitude accounting and upper period overall performane value in factor.
According to the factor index value, factor magnitude accounting and overall performane value in two periods, determine factor to customer service level
The contribution degree of fluctuation.
Determination unit 404 also specifically can be used for:
According to the traffic data of current period, the index value of the index is calculated from multiple dimensions respectively, to obtain multiple
The index value of dimension.
It is poor according to Grubbs Law and SS, abnormality processing is carried out to index value.
To the index value of each dimension after abnormality processing, sets of factors corresponding to the impact factor from the dimension
The corresponding factor of middle determination.
According to the corresponding relationship between the index value and factor of each dimension, determine corresponding to the impact factor of the dimension
The current week of the factor current period index value of each factor, factor current period magnitude accounting and all factors in sets of factors
Phase overall performane value.
Selection unit 406, the contribution degree for being determined according to determination unit 404, from each factor of Multiple factors set
Selection is affected factor.
Selection unit 406 specifically can be used for:
According to contribution degree, influence factor is chosen from each sets of factors, to obtain multiple influence factors.
To multiple influence factors, similarity is calculated two-by-two.
According to similarity, factor to be refined is determined from multiple influence factors.
It treats refinement factor to be refined, thus factor after being refined.
Calculate the contribution degree that factor fluctuates customer service level after refining.
According to the contribution degree of factor after refinement, from the factor that is affected is chosen after refinement in factor.
Selection unit 406 also specifically can be used for:
It determines and treats information state obtained after refinement factor is refined with the factor in other factors set.
According to information state obtained, target factor set is chosen from other factors set.
It treats refinement factor with the factor in target factor set to be refined, thus factor after being refined.
Selection unit 406 also specifically can be used for:
To multiple influence factors, judge whether similarity is greater than threshold value two-by-two.
If similarity between certain two influence factor is not more than threshold value, by two influence factors be determined as to
Refinement factor.
If the similarity between certain two influence factor is greater than threshold value, contribution degree is chosen from two influence factors
The contribution degree large effect factor is determined as factor to be refined by large effect factor.
Selection unit 406 also specifically can be used for:
Factor after refinement is ranked up according to the sequence of contribution degree from big to small.
Forward and the sum of the contribution degree that sorts therefrom is chosen greater than factor after the refinement of threshold value as the factor that is affected.
Collection unit 408, for being converged to the factor of being affected corresponding with each index that selection unit 406 is chosen
It is total to calculate, to determine the key factor of the customer service level fluctuation in current period.
Collection unit 408 specifically can be used for:
The total degree that the statistics larger factor of Different Effects respectively occurs.
The maximum factor that is affected of total degree is chosen as the key factor that customer service level fluctuates in current period.
The function of each functional module of this specification above-described embodiment device can pass through each step of above method embodiment
Rapid to realize, therefore, the specific work process for the device that this specification one embodiment provides does not repeat again herein.
The key factor positioning device for the customer service level fluctuation that this specification one embodiment provides, acquiring unit 402 obtain
Take the traffic data in current period.Determination unit 404 determines at least one index for assessing customer service level, the index
Impact factor with multiple dimensions, the impact factor of each dimension are corresponding with a sets of factors.Determination unit 404 is to every
A index determines that each factor fluctuates customer service level in Multiple factors set corresponding with the index according to above-mentioned traffic data
Contribution degree.Selection unit 406 chooses the factor that is affected according to above-mentioned contribution degree from each factor of Multiple factors set.
Collection unit 408 carries out summarizing calculating to the factor of being affected corresponding with each index, to determine the customer service in current period
The key factor of level fluctuation.Thus, it is possible to improve the accuracy of the key factor positioning of customer service level fluctuation.
The key factor positioning device for the customer service level fluctuation that this specification one embodiment provides can be client in Fig. 1
A module or unit for call center.
Accordingly, this specification embodiment additionally provides one kind to the key factor localization method fluctuated with above-mentioned customer service level
The key factor positioning device of customer service level fluctuation, as shown in figure 5, the equipment may include: memory 502, one or more
Processor 504 and one or more programs.Wherein, which is stored in memory 502, and is configured
It is executed at by one or more processors 504, which performs the steps of when being executed by processor 504
Obtain the traffic data in current period.
Determine that at least one index for assessing customer service level, the index have the impact factor of multiple dimensions, each
The impact factor of dimension is corresponding with a sets of factors.
To each index, according to traffic data, determine that each factor is to customer service in Multiple factors set corresponding with the index
The contribution degree of level fluctuation.
According to contribution degree, the factor that is affected is chosen from each factor of Multiple factors set.
The factor of being affected corresponding with each index is carried out summarizing calculating, to determine, customer service is horizontal in current period
The key factor of fluctuation.
The key factor positioning device for the customer service level fluctuation that this specification one embodiment provides, can be improved customer service water
The accuracy of the key factor positioning of flat fluctuation.
All the embodiments in this specification are described in a progressive manner, same and similar portion between each embodiment
Dividing may refer to each other, and each embodiment focuses on the differences from other embodiments.Especially for equipment reality
For applying example, since it is substantially similar to the method embodiment, so being described relatively simple, related place is referring to embodiment of the method
Part explanation.
The step of method in conjunction with described in this disclosure content or algorithm can realize in a manner of hardware,
It can be and the mode of software instruction is executed by processor to realize.Software instruction can be made of corresponding software module, software
Module can be stored on RAM memory, flash memory, ROM memory, eprom memory, eeprom memory, register, hard
Disk, mobile hard disk, CD-ROM or any other form well known in the art storage medium in.A kind of illustrative storage Jie
Matter is coupled to processor, to enable a processor to from the read information, and information can be written to the storage medium.
Certainly, storage medium is also possible to the component part of processor.Pocessor and storage media can be located in ASIC.In addition, should
ASIC can be located in server.Certainly, pocessor and storage media can also be used as discrete assembly and be present in server.
Those skilled in the art are it will be appreciated that in said one or multiple examples, function described in the invention
It can be realized with hardware, software, firmware or their any combination.It when implemented in software, can be by these functions
Storage in computer-readable medium or as on computer-readable medium one or more instructions or code transmitted.
Computer-readable medium includes computer storage media and communication media, and wherein communication media includes convenient for from a place to another
Any medium of one place transmission computer program.Storage medium can be general or specialized computer can access it is any
Usable medium.
It is above-mentioned that this specification specific embodiment is described.Other embodiments are in the scope of the appended claims
It is interior.In some cases, the movement recorded in detail in the claims or step can be come according to the sequence being different from embodiment
It executes and desired result still may be implemented.In addition, process depicted in the drawing not necessarily require show it is specific suitable
Sequence or consecutive order are just able to achieve desired result.In some embodiments, multitasking and parallel processing be also can
With or may be advantageous.
Above-described specific embodiment has carried out into one the purpose of this specification, technical scheme and beneficial effects
Step is described in detail, it should be understood that being not used to limit this foregoing is merely the specific embodiment of this specification
The protection scope of specification, all any modifications on the basis of the technical solution of this specification, made, change equivalent replacement
Into etc., it should all include within the protection scope of this specification.
Claims (19)
1. a kind of key factor localization method of customer service level fluctuation, comprising:
Obtain the traffic data in current period；
Determine that at least one index for assessing customer service level, the index have the impact factor of multiple dimensions, Mei Gewei
The impact factor of degree is corresponding with a sets of factors；
To each index, according to the traffic data, determine that each factor is to customer service in Multiple factors set corresponding with the index
The contribution degree of level fluctuation；
According to the contribution degree, the factor that is affected is chosen from each factor of the multiple sets of factors；
The factor of being affected corresponding with each index is carried out summarizing calculating, to determine, customer service level is fluctuated in current period
Key factor.
2. according to the method described in claim 1, described according to the contribution degree, from each factor of the multiple sets of factors
Selection is affected factor, comprising:
According to the contribution degree, influence factor is chosen from each sets of factors, to obtain multiple influence factors；
To the multiple influence factor, similarity is calculated two-by-two；
According to the similarity, factor to be refined is determined from the multiple influence factor；
The factor to be refined is refined, thus factor after being refined；
Calculate the contribution degree that factor after the refinement fluctuates customer service level；
According to the contribution degree of factor after the refinement, from the factor that is affected described in selection in factor after the refinement.
3. according to the method described in claim 2, described refine the factor to be refined, thus after being refined because
Element, comprising:
It determines with the factor in other factors set to the information state obtained after refining factor and refining；
According to information state obtained, target factor set is chosen from the other factors set；
The factor to be refined is refined with the factor in the target factor set, thus after obtaining the refinement because
Element.
4. according to the method described in claim 2, described according to the similarity, determined from the multiple influence factor to
Refinement factor, comprising:
To the multiple influence factor, judge whether similarity is greater than threshold value two-by-two；
If the similarity between certain two influence factor is not more than threshold value, described two influence factors are determined as to thin
Change factor；
If similarity between certain two influence factor is greater than threshold value, chosen from described two influence factors contribution degree compared with
The contribution degree large effect factor is determined as factor to be refined by big influence factor.
5. according to the method described in claim 2, the contribution degree according to factor after the refinement, from factor after the refinement
Be affected factor described in middle selection, comprising:
Factor after the refinement is ranked up according to the sequence of the contribution degree from big to small；
Forward and the sum of the contribution degree that sorts therefrom is chosen greater than the factor that is affected described in factor conduct after the refinement of threshold value.
6. according to the method described in claim 1, described according to the traffic data, determining Multiple factors corresponding with the index
The contribution degree that each factor fluctuates customer service level in set, comprising:
To each factor in the sets of factors, according to the traffic data of current period, statistical considerations current period index value,
Factor current period magnitude accounting and current period overall performane value；
A cyclical indicator value in acquisition factor, a period magnitude accounting and upper period overall performane value in factor；
According to the factor index value, factor magnitude accounting and overall performane value in two periods, determine the factor to customer service level
The contribution degree of fluctuation.
7. according to the method described in claim 6, the traffic data according to current period, statistical considerations current period index
Value, factor current period magnitude accounting and current period overall performane value, comprising:
According to the traffic data of current period, the index value of the index is calculated from the multiple dimension respectively, to obtain more
The index value of a dimension；
It is poor according to Grubbs Law and SS, abnormality processing is carried out to the index value；
To the index value of each dimension after abnormality processing, in sets of factors corresponding to the impact factor from the dimension really
Fixed corresponding factor；
According to the corresponding relationship between the index value and factor of each dimension, factor corresponding to the impact factor of the dimension is determined
The current period of the factor current period index value of each factor, factor current period magnitude accounting and all factors is total in set
Index value.
8. according to the method described in claim 1, described carry out summarizing calculating to the factor of being affected corresponding with each index,
To determine the key factor of the customer service level fluctuation in current period, comprising:
The total degree that the statistics larger factor of Different Effects respectively occurs；
The maximum factor that is affected of total degree is chosen as the key factor that customer service level fluctuates in current period.
9. method according to claim 1-8, the index includes following one or more: average call duration
Operating time ACW after ATT, average call, absolute satisfaction, investigation satisfaction, head ask fix-rate FCR, switching-out rate, final election rate,
Ten thousand throwing rates and ten thousand one-tenth rates.
10. a kind of key factor positioning device of customer service level fluctuation, comprising:
Acquiring unit, for obtaining the traffic data in current period；
Determination unit, for determining that at least one index for assessing customer service level, the index have the shadow of multiple dimensions
The factor is rung, the impact factor of each dimension is corresponding with a sets of factors；
The determination unit is also used to, according to the traffic data, determine Multiple factors corresponding with the index to each index
The contribution degree that each factor fluctuates customer service level in set；
Selection unit, the contribution degree for being determined according to the determination unit, from each factor of the multiple sets of factors
It is middle to choose the factor that is affected；
Collection unit, based on summarizing to the factor of being affected corresponding with each index that the selection unit is chosen
It calculates, to determine the key factor of the customer service level fluctuation in current period.
11. device according to claim 10, the selection unit is specifically used for:
According to the contribution degree, influence factor is chosen from each sets of factors, to obtain multiple influence factors；
To the multiple influence factor, similarity is calculated two-by-two；
According to the similarity, factor to be refined is determined from the multiple influence factor；
The factor to be refined is refined, thus factor after being refined；
Calculate the contribution degree that factor after the refinement fluctuates customer service level；
According to the contribution degree of factor after the refinement, from the factor that is affected described in selection in factor after the refinement.
12. device according to claim 11, the selection unit also particularly useful for:
It determines with the factor in other factors set to the information state obtained after refining factor and refining；
According to information state obtained, target factor set is chosen from the other factors set；
The factor to be refined is refined with the factor in the target factor set, thus after obtaining the refinement because
Element.
13. device according to claim 11, the selection unit also particularly useful for:
To the multiple influence factor, judge whether similarity is greater than threshold value two-by-two；
If the similarity between certain two influence factor is not more than threshold value, described two influence factors are determined as to thin
Change factor；
If similarity between certain two influence factor is greater than threshold value, chosen from described two influence factors contribution degree compared with
The contribution degree large effect factor is determined as factor to be refined by big influence factor.
14. device according to claim 11, the selection unit also particularly useful for:
Factor after the refinement is ranked up according to the sequence of the contribution degree from big to small；
Forward and the sum of the contribution degree that sorts therefrom is chosen greater than the factor that is affected described in factor conduct after the refinement of threshold value.
15. device according to claim 10, the determination unit is specifically used for:
To each factor in the sets of factors, according to the traffic data of current period, statistical considerations current period index value,
Factor current period magnitude accounting and current period overall performane value；
A cyclical indicator value in acquisition factor, a period magnitude accounting and upper period overall performane value in factor；
According to the factor index value, factor magnitude accounting and overall performane value in two periods, determine the factor to customer service level
The contribution degree of fluctuation.
16. device according to claim 15, the determination unit also particularly useful for:
According to the traffic data of current period, the index value of the index is calculated from the multiple dimension respectively, to obtain more
The index value of a dimension；
It is poor according to Grubbs Law and SS, abnormality processing is carried out to the index value；
To the index value of each dimension after abnormality processing, in sets of factors corresponding to the impact factor from the dimension really
Fixed corresponding factor；
According to the corresponding relationship between the index value and factor of each dimension, factor corresponding to the impact factor of the dimension is determined
The current period of the factor current period index value of each factor, factor current period magnitude accounting and all factors is total in set
Index value.
17. device according to claim 10, the collection unit is specifically used for:
The total degree that the statistics larger factor of Different Effects respectively occurs；
The maximum factor that is affected of total degree is chosen as the key factor that customer service level fluctuates in current period.
18. the described in any item devices of 0-17 according to claim 1, the index includes following one or more: average talk
Operating time ACW, absolute satisfaction, investigation satisfaction, head ask fix-rate FCR, switching-out rate, final election after duration ATT, average call
Rate, ten thousand throwing rates and ten thousand one-tenth rates.
19. a kind of key factor positioning device of customer service level fluctuation, comprising:
Memory；
One or more processors；And
One or more programs wherein the storage of one or more of programs is in the memory, and are configured to by institute
One or more processors execution is stated, described program performs the steps of when being executed by the processor
Obtain the traffic data in current period；
Determine that at least one index for assessing customer service level, the index have the impact factor of multiple dimensions, Mei Gewei
The impact factor of degree is corresponding with a sets of factors；
To each index, according to the traffic data, determine that each factor is to customer service in Multiple factors set corresponding with the index
The contribution degree of level fluctuation；
According to the contribution degree, the factor that is affected is chosen from each factor of the multiple sets of factors；
The factor of being affected corresponding with each index is carried out summarizing calculating, to determine, customer service level is fluctuated in current period
Key factor.
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