CN104539814A - Customer service call forwarding method and device - Google Patents
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Abstract
The disclosure relates to a customer service call forwarding method and device, and belongs to the field of communication. The method comprises the following steps: receiving a call request initiated by a terminal; acquiring the feature vector of a user of the terminal; comparing the feature vector of the user with the feature vectors of a plurality of customer service persons according to a preset rule, and determining a customer service person matched with the user; and forwarding the call request to the customer service person. The device comprises a receiving module, an acquisition module, a matching module and a forwarding module. Through adoption of the method and the device, a more suitable customer service person can be provided for the user; the gap between the customer service person and the user is narrowed; and the communication efficiency is increased. Moreover, the matched customer service person can know the demands of the user more deeply; a better customer service is provided for the user; the customer service quality is enhanced; and the satisfaction of the user with the customer service is improved.
Description
Technical Field
The present disclosure relates to the field of communications, and in particular, to a method and an apparatus for forwarding a customer service call.
Background
In order to provide better service for users and facilitate users to fully understand company products and businesses, many companies provide a customer service hot line; the user can communicate with the customer service staff by dialing the customer service hotline to answer the puzzles of the user.
At present, the traditional customer service system simply performs random distribution and switching on the telephone of the user, and when customer service personnel communicate with the user, a gap may occur, and the customer service personnel cannot really understand the appeal of the user, so that the service quality is reduced.
Disclosure of Invention
In view of the above, in order to solve the technical problem of the quality of the customer service degradation in the foregoing technology, the present disclosure provides a method and an apparatus for forwarding a customer service call, so as to improve the quality of the customer service.
According to a first aspect of the embodiments of the present disclosure, there is provided a method for forwarding a customer service call, the method including:
receiving a call request of a terminal;
acquiring a characteristic vector of a user of the terminal;
comparing the characteristic vector of the user with the characteristic vectors of a plurality of customer service personnel according to a preset rule, and determining the customer service personnel matched with the user;
and forwarding the call request to the customer service personnel.
Optionally, the comparing, according to a preset rule, the feature vector of the user with feature vectors of a plurality of customer service staff, and determining the customer service staff matched with the user includes:
selecting a customer service person in an idle state from the plurality of customer service persons;
calculating the similarity between the characteristic vector of the user and the characteristic vector of each customer service person in an idle state;
and selecting the maximum similarity from the obtained multiple similarities, and determining the customer service personnel corresponding to the maximum similarity as the customer service personnel matched with the user.
Optionally, the comparing, according to a preset rule, the feature vector of the user with feature vectors of a plurality of customer service staff, and determining the customer service staff matched with the user includes:
setting priorities for the features and ordering the features from high to low according to the priorities;
taking the highest priority as the current priority, respectively obtaining the characteristics of the current priority from the characteristic vector of the user and the characteristic vectors of the customer service personnel and comparing the characteristics, and if the characteristics of the customer service personnel are matched with the characteristics of the user, determining the customer service personnel as the customer service personnel matched with the user; and if the characteristics of the customer service personnel are not matched with the characteristics of the user, sequentially determining the next priority as the current priority according to the sequence of the priorities from high to low, repeating the comparison step until the characteristics of the customer service personnel are matched with the characteristics of the user, and determining the customer service personnel as the customer service personnel matched with the user.
Optionally, the method further includes:
after the call is finished, collecting user feedback information sent by the terminal, and if the evaluation of the user on the customer service staff in the user feedback information is the highest level, directly transferring the call request to the customer service staff when the user initiates a call request again through the terminal; or,
and after the call is finished, acquiring user feedback information sent by the terminal, and adjusting parameters in a similarity calculation algorithm of the user characteristic vector and the characteristic vector of the customer service staff according to the evaluation of the user on the customer service staff in the user feedback information.
Optionally, the comparing, according to a preset rule, the feature vector of the user with feature vectors of a plurality of customer service staff, and determining the customer service staff matched with the user includes:
calculating the similarity between the characteristic vector of the user and the characteristic vector of each customer service person;
selecting the maximum similarity from the obtained multiple similarities;
if the customer service staff corresponding to the maximum similarity is in an idle state, determining the customer service staff as the customer service staff matched with the user;
and if the customer service personnel corresponding to the maximum similarity are in a service state, sequentially selecting the customer service personnel with the maximum similarity from the rest customer service personnel until the idle customer service personnel are selected, and determining the selected customer service personnel with the maximum similarity and the idle customer service personnel as the customer service personnel matched with the user.
Optionally, the method further includes:
collecting characteristics of each customer service staff in advance, and forming characteristic vectors of the customer service staff by the collected characteristics; moreover, characteristics are collected in advance for the user of the terminal, and the collected characteristics form a characteristic vector of the user;
the number and the type of the features collected by the customer service staff are the same as those collected by the user.
According to a second aspect of the embodiments of the present disclosure, there is provided an apparatus for customer service call forwarding, the apparatus comprising:
the receiving module is used for receiving a call request initiated by a terminal;
the acquisition module is used for acquiring the characteristic vector of the user of the terminal;
the matching module is used for comparing the characteristic vector of the user with the characteristic vectors of a plurality of customer service personnel according to a preset rule and determining the customer service personnel matched with the user;
and the switching module is used for switching the call request to the customer service staff.
Optionally, the matching module includes:
the selection submodule is used for selecting the customer service personnel in an idle state from the plurality of customer service personnel;
the first calculation submodule is used for calculating the similarity between the characteristic vector of the user and the characteristic vector of each customer service person in an idle state;
and the similarity matching submodule is used for selecting the maximum similarity from the multiple similarities obtained by the first calculation submodule and determining the customer service personnel corresponding to the maximum similarity as the customer service personnel matched with the user.
Optionally, the matching module includes:
the sorting submodule is used for setting priority for the features and sorting the features from high to low according to the priority;
the priority matching submodule is used for taking the highest priority as the current priority, respectively acquiring the characteristics of the current priority from the characteristic vector of the user and the characteristic vectors of the plurality of customer service personnel and comparing the characteristics, and if the characteristics of the customer service personnel are matched with the characteristics of the user, determining the customer service personnel as the customer service personnel matched with the user; and if the characteristics of the customer service personnel are not matched with the characteristics of the user, sequentially determining the next priority as the current priority according to the sequence of the priorities from high to low, repeating the comparison step until the characteristics of the customer service personnel are matched with the characteristics of the user, and determining the customer service personnel as the customer service personnel matched with the user.
Optionally, the apparatus further comprises:
the first adjusting module is used for acquiring user feedback information sent by the terminal after the call is finished, and directly switching the call request to the customer service staff when the user initiates the call request again through the terminal if the user in the user feedback information evaluates the customer service staff to the highest level; or,
and the second adjusting module is used for acquiring user feedback information sent by the terminal after the call is finished, and adjusting parameters in a similarity calculation algorithm of the user characteristic vector and the customer service staff characteristic vector according to the evaluation of the user on the customer service staff in the user feedback information.
Optionally, the matching module includes:
the second calculation submodule is used for calculating the similarity between the feature vector of the user and the feature vector of each customer service person;
a determining submodule for selecting a maximum similarity from the plurality of similarities obtained by the second calculating submodule; if the customer service staff corresponding to the maximum similarity is in an idle state, determining the customer service staff as the customer service staff matched with the user; and if the customer service personnel corresponding to the maximum similarity are in a service state, sequentially selecting the customer service personnel with the maximum similarity from the rest customer service personnel until the idle customer service personnel are selected, and determining the selected customer service personnel with the maximum similarity and the idle customer service personnel as the customer service personnel matched with the user.
Optionally, the apparatus further comprises:
the acquisition module is used for acquiring characteristics of each customer service staff in advance, and the acquired characteristics form characteristic vectors of the customer service staff; moreover, characteristics are collected in advance for the user of the terminal, and the collected characteristics form a characteristic vector of the user; the number and the type of the features collected by the customer service staff are the same as those collected by the user.
According to a third aspect of the embodiments of the present disclosure, there is provided an apparatus for customer service call forwarding, the apparatus comprising:
a processor and a memory for storing processor-executable instructions;
wherein the processor is configured to:
receiving a call request initiated by a terminal;
acquiring a characteristic vector of a user of the terminal;
comparing the characteristic vector of the user with the characteristic vectors of a plurality of customer service personnel according to a preset rule, and determining the customer service personnel matched with the user;
and forwarding the call request to the customer service personnel.
The technical scheme provided by the embodiment of the disclosure can have the following beneficial effects: the method comprises the steps of obtaining a feature vector of a user of a terminal by receiving a call request initiated by the terminal, comparing the feature vector of the user with feature vectors of a plurality of customer service personnel according to a preset rule, determining the customer service personnel matched with the user, and transferring the call request to the customer service personnel. Moreover, matched customer service personnel can more deeply know the appeal of the user, better customer service is provided for the user, the service quality of the customer service is improved, and the satisfaction degree of the user on the customer service is also improved.
It is to be understood that both the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the disclosure.
Drawings
The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the invention and together with the description, serve to explain the principles of the invention.
Fig. 1 is a flow diagram illustrating a method of customer service call forwarding in accordance with an exemplary embodiment.
Fig. 2 is a flow chart illustrating a method of customer service call forwarding according to another exemplary embodiment.
Fig. 3 is a flow chart illustrating a method of customer service call forwarding according to another exemplary embodiment.
Fig. 4 is a block diagram illustrating an apparatus for service call forwarding in accordance with another exemplary embodiment.
Fig. 5 is a block diagram illustrating an apparatus for customer service call forwarding in accordance with another exemplary embodiment.
Fig. 6 is a block diagram illustrating an apparatus for service call forwarding in accordance with another exemplary embodiment.
Fig. 7 is a block diagram illustrating an apparatus for service call forwarding in accordance with another exemplary embodiment.
Fig. 8 is a block diagram illustrating an apparatus for service call forwarding in accordance with another exemplary embodiment.
Fig. 9 is a block diagram illustrating an apparatus for service call forwarding in accordance with another exemplary embodiment.
Fig. 10 is a block diagram illustrating an apparatus for service call forwarding in accordance with another exemplary embodiment.
Fig. 11 is a block diagram illustrating an apparatus for service call forwarding in accordance with another exemplary embodiment.
Fig. 12 is a block diagram illustrating an apparatus for service call forwarding in accordance with another exemplary embodiment.
Detailed Description
Reference will now be made in detail to the exemplary embodiments, examples of which are illustrated in the accompanying drawings. When the following description refers to the accompanying drawings, like numbers in different drawings represent the same or similar elements unless otherwise indicated. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with the present invention. Rather, they are merely examples of apparatus and methods consistent with certain aspects of the invention, as detailed in the appended claims.
Fig. 1 is a flow chart illustrating a method for service call forwarding, as shown in fig. 1, for use in a terminal, according to an exemplary embodiment, including the following steps.
In step S11, a call request initiated by the terminal is received.
The call request refers to a call initiated by a user for a customer service by using a terminal, and the terminal is usually a mobile terminal, such as a mobile phone.
In step S12, a feature vector of the user of the terminal is acquired.
In step S13, the feature vector of the user is compared with the feature vectors of a plurality of service persons according to a preset rule, and the service person matching the user is determined.
In this embodiment, optionally, the method may further include:
collecting characteristics of each customer service staff in advance, and forming a characteristic vector of the customer service staff by the collected characteristics; collecting characteristics of a user of the terminal in advance, and forming a characteristic vector of the user by the collected characteristics; the number and the type of the features collected by the customer service staff are the same as those collected by the user.
The collected features are at least one, and usually a plurality, including but not limited to: age, gender, hobbies, education level, region, etc. The number and type of features can be set as desired, such as setting that users and customer service personnel all collect three features, including: age, sex, and hobby.
When the characteristics of the user are collected, permission of the user can be obtained firstly, for example, authorization options are provided for the user, and if the user sets authorized collection characteristics, behavior data of the user on the terminal is collected and analyzed. The behavioral data include, but are not limited to: downloading behavior, browsing behavior, purchasing behavior, or usage behavior of each application, etc., without limitation. The characteristics of the user can be obtained by calculating the behavior data by using a preset algorithm, so that the characteristic vector of the user is generated.
In this embodiment, when the feature vector of the user is saved, the identifier of the terminal may be stored as the identifier of the feature vector of the user, for example, the number of each terminal is an identifier, and a user may be uniquely identified, and the identifier of the terminal and the feature vector of the user of the terminal are bound and stored.
In step S14, the call request is forwarded to the customer service person.
After the switching-over is connected, the customer service personnel provides services for the user and solves various problems of the user.
In this embodiment, optionally, the comparing the feature vector of the user with the feature vectors of a plurality of customer service staff according to a preset rule to determine the customer service staff matched with the user may include:
selecting a customer service person in an idle state from the plurality of customer service persons;
calculating the similarity between the characteristic vector of the user and the characteristic vector of each customer service person in an idle state;
and selecting the maximum similarity from the obtained multiple similarities, and determining the customer service personnel corresponding to the maximum similarity as the customer service personnel matched with the user.
In this embodiment, optionally, the comparing the feature vector of the user with the feature vectors of a plurality of customer service staff according to a preset rule to determine the customer service staff matched with the user may include:
setting priorities for the features and ordering the features from high to low according to the priorities;
taking the highest priority as the current priority, respectively obtaining the characteristics of the current priority from the characteristic vector of the user and the characteristic vectors of the customer service personnel and comparing the characteristics, and if the characteristics of the customer service personnel are matched with the characteristics of the user, determining the customer service personnel as the customer service personnel matched with the user; and if the characteristics of the customer service personnel are not matched with the characteristics of the user, sequentially determining the next priority as the current priority according to the sequence of the priorities from high to low, repeating the comparison step until the characteristics of the customer service personnel are matched with the characteristics of the user, and determining the customer service personnel as the customer service personnel matched with the user.
In this embodiment, optionally, the method may further include:
when the call is finished, collecting user feedback information sent by the terminal, and if the evaluation of the user to the customer service staff in the user feedback information is the highest level, directly forwarding the call request to the customer service staff when the user initiates a call request again through the terminal; or,
and after the call is finished, acquiring user feedback information sent by the terminal, and adjusting parameters in a similarity calculation algorithm of the user characteristic vector and the characteristic vector of the customer service staff according to the evaluation of the user on the customer service staff in the user feedback information.
In this embodiment, optionally, the comparing the feature vector of the user with the feature vectors of a plurality of customer service staff according to a preset rule to determine the customer service staff matched with the user may include:
calculating the similarity between the characteristic vector of the user and the characteristic vector of each customer service person;
selecting the maximum similarity from the obtained multiple similarities;
if the customer service staff corresponding to the maximum similarity is in an idle state, determining the customer service staff as the customer service staff matched with the user;
and if the customer service personnel corresponding to the maximum similarity are in a service state, sequentially selecting the customer service personnel with the maximum similarity from the rest customer service personnel until the idle customer service personnel are selected, and determining the selected customer service personnel with the maximum similarity and the idle customer service personnel as the customer service personnel matched with the user.
According to the method provided by the embodiment, through a matching mode according to the preset rule, more suitable customer service personnel can be provided for the user, the gap between the customer service personnel and the user is reduced, and the communication efficiency is improved. Moreover, matched customer service personnel can more deeply know the appeal of the user, better customer service is provided for the user, the service quality of the customer service is improved, and the satisfaction degree of the user on the customer service is also improved.
Fig. 2 is a flowchart illustrating a method for service call forwarding, as shown in fig. 2, for use in a terminal, according to another exemplary embodiment, including the following steps.
In step S21, a call request initiated by the terminal is received.
In step S22, a feature vector of the user of the terminal is acquired.
In step S23, a serviceman in an idle state is selected from the plurality of servicemen.
In step S24, the similarity between the feature vector of the user and the feature vector of each customer service person in the idle state is calculated.
In this embodiment, optionally, there are a plurality of customer service staff members, and any customer service staff member may be in a service state or an idle state. When calculating the similarity, the similarity between the feature vector of the user and the feature vector of each customer service person in the idle state needs to be calculated, and the similarity does not need to be calculated for the customer service persons in the service state, so that the calculation efficiency can be improved.
For example, the feature vector of the user a is Va, there are 5 customer service staff b, c, d, e and f in an idle state, and the feature vectors are Vb, Vc, Vd, Ve and Vf respectively, then the similarity between the feature vectors Va and Vb, the similarity between the feature vectors Va and Vc, the similarity between the feature vectors Va and Vd, the similarity between the feature vectors Va and Ve, and the similarity between the feature vectors Va and Vf are calculated respectively, and 5 similarities are obtained in total.
In step S25, the highest similarity among the obtained similarities is selected, and the customer service person corresponding to the highest similarity is determined as the customer service person who matches the user.
In this embodiment, optionally, the step of calculating the similarity may be replaced by the following steps:
calculating the similarity between the characteristic vector of the user and the characteristic vector of each customer service person;
selecting the maximum similarity from the obtained multiple similarities;
if the customer service staff corresponding to the maximum similarity is in an idle state, determining the customer service staff as the customer service staff matched with the user;
and if the customer service personnel corresponding to the maximum similarity are in a service state, sequentially selecting the customer service personnel with the maximum similarity from the rest customer service personnel until the idle customer service personnel are selected, and determining the selected customer service personnel with the maximum similarity and the idle customer service personnel as the customer service personnel matched with the user.
For example, if there are 10 calculated similarities, and the similarities are arranged from m1 to m10 in descending order, then m1 is selected for the first time, if the customer service person corresponding to m1 is in a service state, then m2 with the largest remaining similarity is selected, if the customer service person corresponding to m2 is in a service state, then m3 with the largest remaining similarity is selected, and so on until the currently selected customer service person with the largest similarity is in an idle state.
The method for matching the customer service personnel by using the similarity calculation ensures that the matching result is more accurate, and can improve the customer service quality and the satisfaction degree of the user.
In step S26, the call request is forwarded to the customer service person.
In this embodiment, optionally, the method may further include:
collecting characteristics of each customer service staff in advance, and forming a characteristic vector of the customer service staff by the collected characteristics; collecting characteristics of a user of the terminal in advance, and forming a characteristic vector of the user by the collected characteristics;
the number and the type of the features collected by the customer service staff are the same as those collected by the user.
In this embodiment, optionally, the method may further include:
when the call is finished, collecting user feedback information sent by the terminal, and if the evaluation of the user to the customer service staff in the user feedback information is the highest level, directly forwarding the call request to the customer service staff when the user initiates a call request again through the terminal; or,
and after the call is finished, acquiring user feedback information sent by the terminal, and adjusting parameters in a similarity calculation algorithm of the user characteristic vector and the characteristic vector of the customer service staff according to the evaluation of the user on the customer service staff in the user feedback information.
According to the method provided by the embodiment, through a matching mode according to the preset rule, more suitable customer service personnel can be provided for the user, the gap between the customer service personnel and the user is reduced, and the communication efficiency is improved. Moreover, matched customer service personnel can more deeply know the appeal of the user, better customer service is provided for the user, the service quality of the customer service is improved, and the satisfaction degree of the user on the customer service is also improved.
Fig. 3 is a flowchart illustrating a method for service call forwarding, as shown in fig. 3, for use in a terminal, according to another exemplary embodiment, including the following steps.
In step S31, a call request initiated by the terminal is received.
In step S32, a feature vector of the user of the terminal is acquired.
In step S33, the features are prioritized and sorted from high to low in priority.
The feature is included in the feature vector of the user and the feature vector of the customer service person, and may be one, and usually, a plurality of features are included. In setting the priority, a different priority may be set for each feature. For example, there are three features: age, gender and hobby, the priority is respectively set as: second, third and first. The characteristics are sequenced from high to low according to the priority to obtain: hobby- > age- > sex.
In step S34, taking the highest priority as the current priority, obtaining the features of the current priority from the feature vector of the user and the feature vectors of the plurality of service staff respectively, and comparing them, if the features of the service staff match the features of the user, determining the service staff as the service staff matching the user; and if the characteristics of the customer service personnel are not matched with the characteristics of the user, sequentially determining the next priority as the current priority according to the sequence of the priorities from high to low, repeating the comparison step until the characteristics of the customer service personnel are matched with the characteristics of the user, and determining the customer service personnel as the customer service personnel matched with the user.
For example, the feature vector of the user and the feature vector of the customer service staff each include three features: age, sex, and hobby. The preset priorities are as follows from high to low: hobby, age, and gender. During matching, firstly, aiming at the features with the highest priority, the hobbies of the user are obtained from the feature vector of the user, the hobbies of the customer service staff are obtained from the feature vector of each customer service staff, and the hobbies of the user and the hobbies of each customer service staff are respectively compared to obtain the customer service staff with matched hobbies. And if the hobbies of all the customer service personnel are not matched, the age of the user is obtained in the feature vector of the user by considering the feature of the next priority, the age of the customer service personnel is obtained in the feature vector of each customer service personnel, and the age of the user is compared with the age of each customer service personnel to obtain age-matched customer service personnel. And if the ages of all the customer service personnel are not matched, considering the characteristics of the next priority, and repeating the steps until the matched customer service personnel are obtained. It is worth mentioning that if no customer service personnel are matched in all the priorities, one customer service personnel can be randomly allocated to the user.
When comparing the features, it may be determined whether the two features are matched according to a preset rule, if the two features are equal, the two features are matched within the same range, or the difference between the two features is matched within a specified range, or the two features are matched if they belong to the same category, and the like, which is not specifically limited in this embodiment. For example, gender identity is a match, or ages no more than 10 years are matches, or ages within 30-40 are matches, or a match is considered if one prefers basketball and football and belongs to the sports category, and so on.
The above-mentioned mode of directly matching using the features in the feature vector is more direct, more convenient, and the calculation is simple, realizes easily, and the priority can be adjusted as required, and the flexibility is strong.
In step S35, the call request is forwarded to the customer service person.
In this embodiment, optionally, the method may further include:
collecting characteristics of each customer service staff in advance, and forming a characteristic vector of the customer service staff by the collected characteristics; collecting characteristics of a user of the terminal in advance, and forming a characteristic vector of the user by the collected characteristics;
the number and the type of the features collected by the customer service staff are the same as those collected by the user.
In this embodiment, optionally, the method may further include:
when the call is finished, collecting user feedback information sent by the terminal, and if the evaluation of the user to the customer service staff in the user feedback information is the highest level, directly forwarding the call request to the customer service staff when the user initiates a call request again through the terminal; or,
and after the call is finished, acquiring user feedback information sent by the terminal, and adjusting parameters in a similarity calculation algorithm of the user characteristic vector and the characteristic vector of the customer service staff according to the evaluation of the user on the customer service staff in the user feedback information.
After the call is finished, the message can be sent to the terminal, the user is requested to evaluate the service quality of the customer service staff in the finished call process, and the user feedback information sent by the terminal is received, such as very satisfied, general, poor and the like. When the evaluation of the user to the customer service staff in the user feedback information is in the highest level, if the evaluation is very satisfactory, an identifier can be set for the corresponding customer service staff, and when the call of the terminal is received again, the customer service staff corresponding to the identifier is directly distributed to the user of the terminal. For example, if the evaluation of Zhang three to the customer service person A is very satisfactory, then Zhang three is preferentially switched to the customer service person A when the customer service is called next time, which is more favorable for providing more satisfactory customer service persons for users, more favorable for both parties to communicate and improving the service quality.
In addition, when adjusting parameters in the similarity calculation algorithm between the user feature vector and the feature vector of the customer service staff according to the evaluation of the user on the customer service staff in the user feedback information, one or more of the parameters may be adjusted, which is not specifically limited in this embodiment.
According to the method provided by the embodiment, through a matching mode according to the preset rule, more suitable customer service personnel can be provided for the user, the gap between the customer service personnel and the user is reduced, and the communication efficiency is improved. Moreover, matched customer service personnel can more deeply know the appeal of the user, better customer service is provided for the user, the service quality of the customer service is improved, and the satisfaction degree of the user on the customer service is also improved.
Fig. 4 is a block diagram illustrating an apparatus for service call forwarding in accordance with another exemplary embodiment. Referring to fig. 4, the apparatus includes a receiving module 121, an obtaining module 122, a matching module 123, and a transferring module 124.
The receiving module 121 is configured to receive a call request initiated by a terminal.
The obtaining module 1222 is configured to obtain feature vectors of users of the terminal.
The matching module 123 is configured to compare the feature vector of the user with feature vectors of a plurality of customer service staff according to a preset rule, and determine a customer service staff matched with the user.
The forwarding module 124 is configured to forward the call request to the customer service person.
Referring to fig. 5, in this embodiment, optionally, the matching module 123 may include: a selection submodule 123a, a first calculation submodule 123b and a similarity matching submodule 123 c.
The selection sub-module 123a is configured to select a servicer in an idle state among the plurality of servicers.
The first calculating submodule 123b is configured to calculate similarity between the feature vector of the user and the feature vector of each customer service person in the idle state.
The similarity matching sub-module 123c is configured to select the largest similarity from the multiple similarities obtained by the first calculation sub-module, and determine the customer service person corresponding to the largest similarity as the customer service person matched with the user.
Referring to fig. 6, in the present embodiment, optionally, the matching module 123 may include: a sorting sub-module 123d and a priority matching sub-module 123 e.
The sorting submodule 123d is configured to prioritize the features and sort the features from high to low according to the priority.
The priority matching sub-module 123e is configured to take the highest priority as the current priority, obtain the features of the current priority from the feature vector of the user and the feature vectors of the plurality of customer service staff respectively and compare the features, and if the features of the customer service staff are matched with the features of the user, determine the customer service staff as the customer service staff matched with the user; and if the characteristics of the customer service personnel are not matched with the characteristics of the user, sequentially determining the next priority as the current priority according to the sequence of the priorities from high to low, repeating the comparison step until the characteristics of the customer service personnel are matched with the characteristics of the user, and determining the customer service personnel as the customer service personnel matched with the user.
Referring to fig. 7, in the present embodiment, optionally, the apparatus may further include: a first adjustment module 125 or a second adjustment module 126.
The first adjusting module 125 is configured to collect user feedback information sent by the terminal after the call is ended, and if the user evaluation on the customer service staff in the user feedback information is the highest level, directly forward the call request to the customer service staff when the user initiates a call request again through the terminal.
The second adjusting module 126 is configured to collect user feedback information sent by the terminal after the call is ended, and adjust parameters in a similarity calculation algorithm between the user feature vector and the feature vector of the customer service staff according to the evaluation of the user on the customer service staff in the user feedback information.
Referring to fig. 8, in the present embodiment, optionally, the matching module 123 may include: a second calculation submodule 123f and a determination submodule 123 g.
The second calculating submodule 123f is configured to calculate a similarity between the feature vector of the user and the feature vector of each customer service person.
The determining submodule 123g is configured to select a maximum similarity from the plurality of similarities obtained by the second calculating submodule; if the customer service staff corresponding to the maximum similarity is in an idle state, determining the customer service staff as the customer service staff matched with the user; and if the customer service personnel corresponding to the maximum similarity are in a service state, sequentially selecting the customer service personnel with the maximum similarity from the rest customer service personnel until the idle customer service personnel are selected, and determining the selected customer service personnel with the maximum similarity and the idle customer service personnel as the customer service personnel matched with the user.
Referring to fig. 9, in this embodiment, optionally, the apparatus may further include: an acquisition module 127.
The acquisition module 127 is configured to acquire characteristics of each customer service person in advance, and the acquired characteristics form a characteristic vector of the customer service person; collecting characteristics of a user of the terminal in advance, and forming a characteristic vector of the user by the collected characteristics; the number and the type of the features collected by the customer service staff are the same as those collected by the user.
With regard to the apparatus in the above-described embodiment, the specific manner in which each module performs the operation has been described in detail in the embodiment related to the method, and will not be elaborated here.
According to the device provided by the embodiment, through a matching mode according to the preset rules, more suitable customer service personnel can be provided for the user, the gap between the customer service personnel and the user is reduced, and the communication efficiency is improved. Moreover, matched customer service personnel can more deeply know the appeal of the user, better customer service is provided for the user, the service quality of the customer service is improved, and the satisfaction degree of the user on the customer service is also improved.
Fig. 10 is a block diagram illustrating an apparatus for service call forwarding in accordance with another exemplary embodiment. Referring to fig. 10, the apparatus includes:
a processor 1001 and a memory 1002 for storing processor-executable instructions;
wherein the processor 1001 is configured to:
receiving a call request initiated by a terminal;
acquiring a characteristic vector of a user of the terminal;
comparing the characteristic vector of the user with the characteristic vectors of a plurality of customer service personnel according to a preset rule, and determining the customer service personnel matched with the user;
and forwarding the call request to the customer service personnel.
Fig. 11 is a block diagram illustrating an apparatus 800 for service call forwarding in accordance with another exemplary embodiment. For example, the apparatus 800 may be a mobile phone, a computer, a digital broadcast terminal, a messaging device, a game console, a tablet device, a medical device, an exercise device, a personal digital assistant, and the like.
Referring to fig. 11, the apparatus 800 may include one or more of the following components: processing component 802, memory 804, power component 806, multimedia component 808, audio component 810, input/output (I/O) interface 812, sensor component 814, and communication component 816.
The processing component 802 generally controls overall operation of the device 800, such as operations associated with display, telephone calls, data communications, camera operations, and recording operations. The processing elements 802 may include one or more processors 820 to execute instructions to perform all or a portion of the steps of the methods described above. Further, the processing component 802 can include one or more modules that facilitate interaction between the processing component 802 and other components. For example, the processing component 802 can include a multimedia module to facilitate interaction between the multimedia component 808 and the processing component 802.
The memory 804 is configured to store various types of data to support operation at the device 800. Examples of such data include instructions for any application or method operating on device 800, contact data, phonebook data, messages, pictures, videos, and so forth. The memory 804 may be implemented by any type or combination of volatile or non-volatile memory devices such as Static Random Access Memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic memory, flash memory, magnetic or optical disks.
Power component 806 provides power to the various components of device 800. The power components 806 may include a power management system, one or more power sources, and other components associated with generating, managing, and distributing power for the device 800.
The multimedia component 808 includes a screen that provides an output interface between the device 800 and a user. In some embodiments, the screen may include a Liquid Crystal Display (LCD) and a Touch Panel (TP). If the screen includes a touch panel, the screen may be implemented as a touch screen to receive an input signal from a user. The touch panel includes one or more touch sensors to sense touch, slide, and gestures on the touch panel. The touch sensor may not only sense the boundary of a touch or slide action, but also detect the duration and pressure associated with the touch or slide operation. In some embodiments, the multimedia component 808 includes a front facing camera and/or a rear facing camera. The front-facing camera and/or the rear-facing camera may receive external multimedia data when the device 800 is in an operating mode, such as a shooting mode or a video mode. Each front camera and rear camera may be a fixed optical lens system or have a focal length and optical zoom capability.
The audio component 810 is configured to output and/or input audio signals. For example, the audio component 810 includes a Microphone (MIC) configured to receive external audio signals when the apparatus 800 is in an operational mode, such as a call mode, a recording mode, and a voice recognition mode. The received audio signals may further be stored in the memory 804 or transmitted via the communication component 816. In some embodiments, audio component 810 also includes a speaker for outputting audio signals.
The I/O interface 812 provides an interface between the processing component 802 and peripheral interface modules, which may be keyboards, click wheels, buttons, etc. These buttons may include, but are not limited to: a home button, a volume button, a start button, and a lock button.
The sensor assembly 814 includes one or more sensors for providing various aspects of state assessment for the device 800. For example, the sensor assembly 814 may detect the open/closed state of the device 800, the relative positioning of the components, such as a display and keypad of the apparatus 800, the sensor assembly 814 may also detect a change in position of the apparatus 800 or a component of the apparatus 800, the presence or absence of user contact with the apparatus 800, orientation or acceleration/deceleration of the apparatus 800, and a change in temperature of the apparatus 800. Sensor assembly 814 may include a proximity sensor configured to detect the presence of a nearby object without any physical contact. The sensor assembly 814 may also include a light sensor, such as a CMOS or CCD image sensor, for use in imaging applications. In some embodiments, the sensor assembly 814 may also include an acceleration sensor, a gyroscope sensor, a magnetic sensor, a pressure sensor, or a temperature sensor.
The communication component 816 is configured to facilitate communications between the apparatus 800 and other devices in a wired or wireless manner. The device 800 may access a wireless network based on a communication standard, such as WiFi, 2G or 3G, or a combination thereof. In an exemplary embodiment, the communication component 816 receives a broadcast signal or broadcast associated information from an external broadcast management system via a broadcast channel. In an exemplary embodiment, the communications component 816 further includes a Near Field Communication (NFC) module to facilitate short-range communications. For example, the NFC module may be implemented based on Radio Frequency Identification (RFID) technology, infrared data association (IrDA) technology, Ultra Wideband (UWB) technology, Bluetooth (BT) technology, and other technologies.
In an exemplary embodiment, the apparatus 800 may be implemented by one or more Application Specific Integrated Circuits (ASICs), Digital Signal Processors (DSPs), Digital Signal Processing Devices (DSPDs), Programmable Logic Devices (PLDs), Field Programmable Gate Arrays (FPGAs), controllers, micro-controllers, microprocessors or other electronic components for performing the above-described methods.
In an exemplary embodiment, a non-transitory computer-readable storage medium comprising instructions, such as the memory 804 comprising instructions, executable by the processor 820 of the device 800 to perform the above-described method is also provided. For example, the non-transitory computer readable storage medium may be a ROM, a Random Access Memory (RAM), a CD-ROM, a magnetic tape, a floppy disk, an optical data storage device, and the like.
A non-transitory computer readable storage medium having instructions therein which, when executed by a processor of a mobile terminal, enable the mobile terminal to perform a method of customer service call forwarding, the method comprising:
receiving a call request initiated by a terminal;
acquiring a characteristic vector of a user of the terminal;
comparing the characteristic vector of the user with the characteristic vectors of a plurality of customer service personnel according to a preset rule, and determining the customer service personnel matched with the user;
and forwarding the call request to the customer service personnel.
Optionally, the comparing, according to a preset rule, the feature vector of the user with feature vectors of a plurality of customer service staff, and determining the customer service staff matched with the user includes:
selecting a customer service person in an idle state from the plurality of customer service persons;
calculating the similarity between the characteristic vector of the user and the characteristic vector of each customer service person in an idle state;
and selecting the maximum similarity from the obtained multiple similarities, and determining the customer service personnel corresponding to the maximum similarity as the customer service personnel matched with the user.
Optionally, the comparing, according to a preset rule, the feature vector of the user with feature vectors of a plurality of customer service staff, and determining the customer service staff matched with the user includes:
setting priorities for the features and ordering the features from high to low according to the priorities;
taking the highest priority as the current priority, respectively obtaining the characteristics of the current priority from the characteristic vector of the user and the characteristic vectors of the customer service personnel and comparing the characteristics, and if the characteristics of the customer service personnel are matched with the characteristics of the user, determining the customer service personnel as the customer service personnel matched with the user; and if the characteristics of the customer service personnel are not matched with the characteristics of the user, sequentially determining the next priority as the current priority according to the sequence of the priorities from high to low, repeating the comparison step until the characteristics of the customer service personnel are matched with the characteristics of the user, and determining the customer service personnel as the customer service personnel matched with the user.
Optionally, the method further includes:
after the call is finished, collecting user feedback information sent by the terminal, and if the evaluation of the user on the customer service staff in the user feedback information is the highest level, directly transferring the call request to the customer service staff when the user initiates a call request again through the terminal; or,
and after the call is finished, acquiring user feedback information sent by the terminal, and adjusting parameters in a similarity calculation algorithm of the user characteristic vector and the characteristic vector of the customer service staff according to the evaluation of the user on the customer service staff in the user feedback information.
Optionally, the comparing, according to a preset rule, the feature vector of the user with feature vectors of a plurality of customer service staff, and determining the customer service staff matched with the user includes:
calculating the similarity between the characteristic vector of the user and the characteristic vector of each customer service person;
selecting the maximum similarity from the obtained multiple similarities;
if the customer service staff corresponding to the maximum similarity is in an idle state, determining the customer service staff as the customer service staff matched with the user;
and if the customer service personnel corresponding to the maximum similarity are in a service state, sequentially selecting the customer service personnel with the maximum similarity from the rest customer service personnel until the idle customer service personnel are selected, and determining the selected customer service personnel with the maximum similarity and the idle customer service personnel as the customer service personnel matched with the user.
Optionally, the method further includes:
collecting characteristics of each customer service staff in advance, and forming characteristic vectors of the customer service staff by the collected characteristics; moreover, characteristics are collected in advance for the user of the terminal, and the collected characteristics form a characteristic vector of the user;
the number and the type of the features collected by the customer service staff are the same as those collected by the user.
The non-transitory computer-readable storage medium provided in this embodiment can provide more suitable customer service staff for a user by performing matching according to a preset rule, reduce the gap between the customer service staff and the user, and improve the communication efficiency. Moreover, matched customer service personnel can more deeply know the appeal of the user, better customer service is provided for the user, the service quality of the customer service is improved, and the satisfaction degree of the user on the customer service is also improved.
Fig. 12 is a block diagram illustrating an apparatus 1900 for service call forwarding according to an example embodiment. For example, the apparatus 1900 may be provided as a server. Referring to fig. 12, the device 1900 includes a processing component 1922 further including one or more processors and memory resources, represented by memory 1932, for storing instructions, e.g., applications, executable by the processing component 1922. The application programs stored in memory 1932 may include one or more modules that each correspond to a set of instructions. Further, the processing component 1922 is configured to execute instructions to perform the above-described method.
The device 1900 may also include a power component 1926 configured to perform power management of the device 1900, a wired or wireless network interface 1950 configured to connect the device 1900 to a network, and an input/output (I/O) interface 1958. The device 1900 may operate based on an operating system stored in memory 1932, such as Windows Server, Mac OSXTM, UnixTM, LinuxTM, FreeBSDTM, or the like.
According to the device provided by the embodiment, through a matching mode according to the preset rules, more suitable customer service personnel can be provided for the user, the gap between the customer service personnel and the user is reduced, and the communication efficiency is improved. Moreover, matched customer service personnel can more deeply know the appeal of the user, better customer service is provided for the user, the service quality of the customer service is improved, and the satisfaction degree of the user on the customer service is also improved.
Other embodiments of the invention will be apparent to those skilled in the art from consideration of the specification and practice of the invention disclosed herein. This application is intended to cover any variations, uses, or adaptations of the invention following, in general, the principles of the invention and including such departures from the present disclosure as come within known or customary practice within the art to which the invention pertains. It is intended that the specification and examples be considered as exemplary only, with a true scope and spirit of the invention being indicated by the following claims.
It will be understood that the invention is not limited to the precise arrangements described above and shown in the drawings and that various modifications and changes may be made without departing from the scope thereof. The scope of the invention is limited only by the appended claims.
Claims (13)
1. A method of customer service call forwarding, the method comprising:
receiving a call request initiated by a terminal;
acquiring a characteristic vector of a user of the terminal;
comparing the characteristic vector of the user with the characteristic vectors of a plurality of customer service personnel according to a preset rule, and determining the customer service personnel matched with the user;
and forwarding the call request to the customer service personnel.
2. The method of claim 1, wherein comparing the feature vector of the user with feature vectors of a plurality of service people according to a preset rule to determine a service person matching the user comprises:
selecting a customer service person in an idle state from the plurality of customer service persons;
calculating the similarity between the characteristic vector of the user and the characteristic vector of each customer service person in an idle state;
and selecting the maximum similarity from the obtained multiple similarities, and determining the customer service personnel corresponding to the maximum similarity as the customer service personnel matched with the user.
3. The method of claim 1, wherein comparing the feature vector of the user with feature vectors of a plurality of service people according to a preset rule to determine a service person matching the user comprises:
setting priorities for the features and ordering the features from high to low according to the priorities;
taking the highest priority as the current priority, respectively obtaining the characteristics of the current priority from the characteristic vector of the user and the characteristic vectors of the customer service personnel and comparing the characteristics, and if the characteristics of the customer service personnel are matched with the characteristics of the user, determining the customer service personnel as the customer service personnel matched with the user; and if the characteristics of the customer service personnel are not matched with the characteristics of the user, sequentially determining the next priority as the current priority according to the sequence of the priorities from high to low, repeating the comparison step until the characteristics of the customer service personnel are matched with the characteristics of the user, and determining the customer service personnel as the customer service personnel matched with the user.
4. The method of claim 1, further comprising:
after the call is finished, collecting user feedback information sent by the terminal, and if the evaluation of the user on the customer service staff in the user feedback information is the highest level, directly transferring the call request to the customer service staff when the user initiates a call request again through the terminal; or,
and after the call is finished, acquiring user feedback information sent by the terminal, and adjusting parameters in a similarity calculation algorithm of the user characteristic vector and the characteristic vector of the customer service staff according to the evaluation of the user on the customer service staff in the user feedback information.
5. The method of claim 1, wherein comparing the feature vector of the user with feature vectors of a plurality of service people according to a preset rule to determine a service person matching the user comprises:
calculating the similarity between the characteristic vector of the user and the characteristic vector of each customer service person;
selecting the maximum similarity from the obtained multiple similarities;
if the customer service staff corresponding to the maximum similarity is in an idle state, determining the customer service staff as the customer service staff matched with the user;
and if the customer service personnel corresponding to the maximum similarity are in a service state, sequentially selecting the customer service personnel with the maximum similarity from the rest customer service personnel until the idle customer service personnel are selected, and determining the selected customer service personnel with the maximum similarity and the idle customer service personnel as the customer service personnel matched with the user.
6. The method of claim 1, further comprising:
collecting characteristics of each customer service staff in advance, and forming characteristic vectors of the customer service staff by the collected characteristics; moreover, characteristics are collected in advance for the user of the terminal, and the collected characteristics form a characteristic vector of the user;
the number and the type of the features collected by the customer service staff are the same as those collected by the user.
7. An apparatus for service call forwarding, the apparatus comprising:
the receiving module is used for receiving a call request initiated by a terminal;
the acquisition module is used for acquiring the characteristic vector of the user of the terminal;
the matching module is used for comparing the characteristic vector of the user with the characteristic vectors of a plurality of customer service personnel according to a preset rule and determining the customer service personnel matched with the user;
and the switching module is used for switching the call request to the customer service staff.
8. The apparatus of claim 7, wherein the matching module comprises:
the selection submodule is used for selecting the customer service personnel in an idle state from the plurality of customer service personnel;
the first calculation submodule is used for calculating the similarity between the characteristic vector of the user and the characteristic vector of each customer service person in an idle state;
and the similarity matching submodule is used for selecting the maximum similarity from the multiple similarities obtained by the first calculation submodule and determining the customer service personnel corresponding to the maximum similarity as the customer service personnel matched with the user.
9. The apparatus of claim 7, wherein the matching module comprises:
the sorting submodule is used for setting priority for the features and sorting the features from high to low according to the priority;
the priority matching submodule is used for taking the highest priority as the current priority, respectively acquiring the characteristics of the current priority from the characteristic vector of the user and the characteristic vectors of the plurality of customer service personnel and comparing the characteristics, and if the characteristics of the customer service personnel are matched with the characteristics of the user, determining the customer service personnel as the customer service personnel matched with the user; and if the characteristics of the customer service personnel are not matched with the characteristics of the user, sequentially determining the next priority as the current priority according to the sequence of the priorities from high to low, repeating the comparison step until the characteristics of the customer service personnel are matched with the characteristics of the user, and determining the customer service personnel as the customer service personnel matched with the user.
10. The apparatus of claim 7, further comprising:
the first adjusting module is used for acquiring user feedback information sent by the terminal after the call is finished, and directly switching the call request to the customer service staff when the user initiates the call request again through the terminal if the user in the user feedback information evaluates the customer service staff to the highest level; or,
and the second adjusting module is used for acquiring user feedback information sent by the terminal after the call is finished, and adjusting parameters in a similarity calculation algorithm of the user characteristic vector and the customer service staff characteristic vector according to the evaluation of the user on the customer service staff in the user feedback information.
11. The apparatus of claim 7, wherein the matching module comprises:
the second calculation submodule is used for calculating the similarity between the feature vector of the user and the feature vector of each customer service person;
a determining submodule for selecting a maximum similarity from the plurality of similarities obtained by the second calculating submodule; if the customer service staff corresponding to the maximum similarity is in an idle state, determining the customer service staff as the customer service staff matched with the user; and if the customer service personnel corresponding to the maximum similarity are in a service state, sequentially selecting the customer service personnel with the maximum similarity from the rest customer service personnel until the idle customer service personnel are selected, and determining the selected customer service personnel with the maximum similarity and the idle customer service personnel as the customer service personnel matched with the user.
12. The apparatus of claim 7, further comprising:
the acquisition module is used for acquiring characteristics of each customer service staff in advance, and the acquired characteristics form characteristic vectors of the customer service staff; moreover, characteristics are collected in advance for the user of the terminal, and the collected characteristics form a characteristic vector of the user; the number and the type of the features collected by the customer service staff are the same as those collected by the user.
13. An apparatus for service call forwarding, the apparatus comprising:
a processor and a memory for storing processor-executable instructions;
wherein the processor is configured to:
receiving a call request initiated by a terminal;
acquiring a characteristic vector of a user of the terminal;
comparing the characteristic vector of the user with the characteristic vectors of a plurality of customer service personnel according to a preset rule, and determining the customer service personnel matched with the user;
and forwarding the call request to the customer service personnel.
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