CN106952054B - System and method for evaluating sales service quality of automobile 4S store - Google Patents
System and method for evaluating sales service quality of automobile 4S store Download PDFInfo
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- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
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Abstract
The invention particularly relates to an evaluation system and an evaluation method for the sales service quality of an automobile 4S shop, wherein the evaluation is timely and objective, and the evaluation result is high in accuracy. The evaluation system comprises a miniature receiver, wherein the receiver comprises a microphone, a sound card, a signal processor, an auxiliary controller and a signal transmitter; the salesperson wears a miniature somatosensory sensor and a miniature positioning device; the evaluation system is utilized for evaluation, the calculated evaluation index Rn of the salesperson can effectively monitor whether the service attitude and the service expression of the salesperson are in place in the sales process, and whether the etiquette action of the salesperson is in place can be judged by comparing the action information and the position information of the salesperson in En; the client evaluation index Sn can effectively monitor the language and attitude of clients in the sales process, and the evaluation method carried out by the evaluation system is utilized to properly correct the service attitude evaluation of the sales personnel, so that the evaluation system can fairly evaluate the service quality of the sales personnel; the evaluation flow is simple and quick.
Description
Technical Field
The invention relates to the field of automobile 4S shop sales service evaluation, in particular to an automobile 4S shop sales service quality evaluation system and an evaluation method.
Background
The sales mode of the current automobile 4S shop is that sales personnel and clients sell in a one-to-one and face-to-face mode, namely after the clients enter the 4S shop, the sales personnel introduce relevant information of the intention automobile type to the clients, and finally contract and achieve the automobile sales intention through communication and negotiation with the clients. Because the number of 4S stores and the number of sales personnel are numerous, the service attitude, personal quality, communication skills and the like of each sales personnel in the sales process can have an important influence on whether the automobile is finally sold successfully or not, in order to ensure that each service of the sales personnel in the sales process meets the requirements of clients, manufacturers generally evaluate the sales process of the sales personnel.
However, the above evaluation method has the following problems:
1. the questions of the questionnaire are a limited number of questions preset by a manufacturer, and the questions cannot be completely summarized in the sales flow, so that the contents of the answers of the clients deviate from the questions which the clients want to reflect, and the sales evaluation deviates.
2. The individual communication mode of the post-call makes the customers feel tired, so that a part of the customers are unwilling to receive the call, the investigation display is realized, and about 20% -35% of 4S store customers do not answer the evaluation call related to the sales service after the sales process, so that the evaluation system cannot perform timely and effective evaluation on the sales service of a part of sales personnel.
3. In order to collect feedback opinions of clients as much as possible, a manufacturer needs to arrange special personnel for telephone access, the telephone access mode has the conditions of untimely answering, busy line and the like of the clients, and the special personnel is required to follow up the clients for a plurality of times, so that the feedback opinion has hysteresis, the manufacturer resources are wasted greatly, and the labor cost is very high.
4. The telephone communication mode has the action that the client does not apply the answers according to own will, the action is mainly represented by that the client answers yes or not in the questionnaire, and the reasons for the action are mainly two aspects according to the investigation display: one is that sales personnel communicate with customers in advance to instruct customers to answer, so as to improve the service evaluation score of the customers in an evaluation system, which can lead manufacturers to be unable to know whether the sales personnel serve the customers according to the specified sales flow, so that part of sales personnel intentionally omit certain sales flow, such as reducing the introduction of automobile performance or hiding certain service items, seriously damaging the image of a 4S store and affecting the public praise of automobile brands; the other is that sales personnel are served according to the sales flow, but customers feel discontent because the sales price of the automobile does not reach the mind price of the customers during negotiations, or answer 'not' all in questionnaires intentionally due to personal emotion and other reasons, and the evaluation is not caused by the sales personnel, so that the service quality of the sales personnel cannot be truly evaluated, even the sales personnel are not penalized by manufacturers due to the irrational of individual customers, and the mind pressure of the sales personnel is increased.
5. In order to collect ideas and demands of customers, such as types and styles of automobiles liked by customers at present, and evaluations of other brands of automobiles of the same type by customers, the customers often refer to the information in the sales link, but since sales personnel cannot record in real time, effective and systematic collection data cannot be formed, and the manufacturers cannot grasp the real demands of the customers in time.
Therefore, in order to objectively and efficiently, accurately and fairly evaluate the service quality of sales personnel in the process of selling 4S in-store automobiles, and better collect customer demands, the existing evaluation system needs to be improved.
Disclosure of Invention
Aiming at the problems, the invention aims to provide an evaluation system, an evaluation method and an evaluation method for the sales service quality of an automobile 4S shop, which are timely and objective in evaluation and high in accuracy of evaluation results.
In order to achieve the aim of the invention, the invention adopts the following technical scheme: the evaluation system comprises a miniature receiver carried by sales personnel, wherein the receiver comprises a microphone, a sound card, a signal processor, an auxiliary controller and a signal transmitter, the signal transmitter is in communication connection with a host computer arranged in a 4S store in a wireless mode, and the host computer comprises a local processor, a local memory and a signal receiving/transmitting device; the host is connected with a plurality of distributed cloud servers through the Internet, and the cloud servers comprise cloud processors and cloud memories; the corresponding hand position and the corresponding foot position of the salesperson wear the miniature body sensor respectively, the salesperson wears the miniature positioning device simultaneously, the miniature body sensor and the miniature positioning device are respectively in communication connection with the host computer in a wireless mode, and the salesperson also wears a power switch for controlling the on-off of the miniature receiver, the body sensor and the miniature positioning device.
Preferably, the signal processor comprises an adaptive filter, a multi-human sound source separation module and a multi-channel single sound restoration module which are connected in sequence.
The evaluation method of the sales service quality evaluation system of the automobile 4S shop comprises the following steps:
a. the salesperson starts a power switch to start the miniature receiver, the miniature somatosensory sensor and the miniature positioning device; b, the auxiliary controller sends a request to the host through the signal transmitter, a local processor in the host establishes a temporary evaluation file L in a local memory, stores the current time T0 into the L, and then enters the step b;
b. the signal processor receives the multi-person mixed sound signals transmitted by the microphone, separates the multi-person mixed sound signals and restores the multi-person mixed sound signals into a plurality of independent single sound signals, and the independent single sound signals are transmitted to the host through the signal transmitter; the host computer distinguishes the audio characteristics of each of a plurality of independent single sound signals, and the single sound signals with the same audio characteristics are respectively written into sales person audio recordings D1, D2 and … Dn or client audio recordings K1, K2 and … Kn in the temporary evaluation file L according to the time sequence; simultaneously, the miniature body sensor and the miniature positioning device send action information and position information of sales personnel to a host, and the host writes the action information and the position information of the sales personnel corresponding to D1, D2 and … Dn into action track data E1, E2 and … En of the sales personnel; then enter step c;
c. the host judges that the value of Nd+Nk is larger than or equal to the vocabulary trigger threshold, the step e is entered, otherwise, the step d is entered; nd is the sum of the vocabulary numbers in all Dn, nk is the sum of the vocabulary numbers in all Kn;
d. after the time T1 from the current moment, if new data continue to appear in the stored Dn or new data continue to appear in the stored Kn or new Dn or new Kn appears, returning to the step b, otherwise, entering the step x;
e. uploading data which are not uploaded in Dn, kn and En to a cloud server by a host computer, and entering the step f;
f. the cloud server respectively compares the Dn data and the Kn data with standard vocabulary audio data Q stored in a cloud memory of the cloud server in real time, calculates client evaluation indexes S1 and S2 … Sn, and stores client personal information vocabulary data and client personal audio frequency characteristic information appearing in the Kn in real time;
the cloud server compares the Dn data with the standard vocabulary audio data Q stored in the cloud server in real time, compares the En data with the standard action and position data P stored in the cloud server in real time, calculates salesperson evaluation indexes R1 and R2 … Rn, and then enters the step g;
g. e, the host judges that new data appear in one Dn of D1, D2 and … Dn stored in the L at the moment or new data appear in one Kn of K1, K2 and … Kn, and the step E is returned; otherwise, entering the step h;
h. the host judges that the power switch is closed, the step j is carried out, and the step i is carried out if the power switch is not closed;
i. the host judges that new Dn or Kn data appear in the L, the step b is returned, otherwise, the step j is entered;
j. the cloud server judges Sn:
if Sn is greater than 0, the credit rating coefficient H value of the client is increased; the final evaluation index Z=Rn+Sn of sales personnel, and the values of Z, rn and Sn are written into a sales evaluation file An; writing Sn value, personal information vocabulary data of the client, personal audio frequency characteristic information of the client and H value of the client into a client information file Bn; the cloud server stores An and Bn, and the process is finished;
if Sn is less than or equal to 0, decreasing the credit rating factor H value of the customer, the salesperson final evaluation index z=rn+y0, said Y0 value being a fixed positive value; writing Z, rn and Sn values into a sales evaluation file An; writing Sn value, personal information vocabulary data of the client, personal audio frequency characteristic information of the client and H value of the client into a client information file Bn; the cloud server stores An and Bn, and the process is finished;
and x, judging that the sales flow is not established by the host, deleting the L data, closing the power switch, and ending the flow.
Preferably, in the step b, the method for establishing Dn and Kn is as follows:
a local processor in the host computer analyzes the audio characteristics of each of a plurality of independent single sound signals, if the newly acquired audio characteristics are the same as the audio characteristics of sales personnel sound signals stored in a local memory and sales personnel audio records Dn with the audio characteristics exist in L, the single sound signal data are stored in the corresponding Dn in an inserting mode, and if the newly acquired audio characteristics are the same as the audio characteristics of sales personnel sound signals stored in the host computer and are different from the audio characteristics in D1, D2 and … Dn existing in L, a new sales personnel audio record Dn is established and the single sound signal data are stored;
if the newly acquired audio characteristics are the same as those of the audio records Kn of the customer audio with the audio characteristics in L, the single sound signal is stored in the corresponding Kn in an inserting manner, and if the audio characteristics are different from those of the sales person sound signal stored in the host computer and are different from those of the audio records in K1, K2 and … Kn in L, a new customer audio record Kn is established for storing the single sound signal data.
Preferably, in the step f, the calculation method of the salesperson evaluation index Rn is as follows:
wherein a is 1 A is the score added when the Dn data from the 1 st vocabulary to the N th vocabulary appear in the automobile special vocabulary 2 A is the score added when the N-th vocabulary is from the 1 st vocabulary to the N-th vocabulary in Dn data and polite expression appears 3 From the 1 st vocabulary to the N th vocabulary in the Dn data, the score is added when the vocabulary related to the personal information of the client appears; b i From the 1 st data to the nth data among En data corresponding to Dn, a score is added when an etiquette action occurs at a specified location; c i From the 1 st vocabulary to the N st vocabulary in the Dn data, the score is reduced when irregular expression or profoundly-used vocabulary appears; g 2 N is the vocabulary quantity appearing in Dn as the vocabulary quantity weight coefficient; g 1 Is a standard action weight coefficient;
the calculation method of the client evaluation index Sn comprises the following steps:
wherein f 1 From the 1 st vocabulary to the M th vocabulary in the Kn data, which shows the score of D1, D2 or … Dn 2 For the score added when the number of words from 1 to M appears in the Kn data, f 3 A score in the Kn data from the 1 st vocabulary to the M th vocabulary, wherein the score is a score when a specific query sentence appears and the query sentence comprises a vehicle-specific vocabulary; g i From the 1 st vocabulary to the M th vocabulary in the Kn data, the score is reduced when the counter-productive vocabulary appears; m is the number of words present in Kn, and H is the credit rating factor of the customer.
Preferably, the method for calculating the H value comprises the following steps: if the cloud server judges that the personal audio frequency characteristic information of the client in the current Kn is stored in the cloud server, the H value of the client is extracted, and if the personal audio frequency characteristic information of the client in the current Kn does not exist in the cloud server, the H value is 1.
Preferably, in the step f, if the cloud server determines that the sound decibel in Dn or Kn suddenly increases and continues for a certain early warning time, after the early warning time, the cloud server records the audio data in Dn and Kn simultaneously until the sound decibel in Dn and Kn decreases to a certain extent and continues for a certain period of time, the cloud server submits the recorded data to manual audit until a correction value Y1 is obtained, and the cloud server finally calculates rn=rn+y1 and sn=sn+y1.
Preferably, in the step f, if the cloud server determines that a specific question sentence appears in the Kn data, recording audio data including the question sentence in Kn and audio data in a period of time thereafter, and storing the audio data in Bn.
Preferably, in the step f, if the cloud server determines that other automotive brand vocabularies appear in the Kn data, the vocabularies and a plurality of automotive professional vocabularies appearing in the Kn data in a period of time before and after the vocabularies appear are stored in the Bn.
Preferably, before the step j, the cloud server first determines that if the vocabulary number N in Dn or the vocabulary number M in Kn is smaller than or equal to a preset value, the Dn or Kn is deleted, and the En corresponding to the Dn is deleted; if the vocabulary number N in Dn or the vocabulary number M in Kn is larger than the preset value, reserving the corresponding Dn or Kn, and then entering step j.
The invention has the beneficial effects that: the cloud server extracts the vocabulary in the Dn and Kn data, so that the calculated salesperson evaluation index Rn can effectively monitor whether the service attitude and the service expression of the salesperson are in place in the sales process, the cloud server can store the corresponding standard positions in the sales service flow in advance, and then the action information and the position information of the salesperson in En are compared to judge whether the etiquette action of the salesperson is in place, so that the reliability of the evaluation result of the evaluation system is further improved; the client evaluation index Sn can effectively monitor the language and attitude of the client in the sales process, if the salesperson is served according to the sales flow, and the client attitude is still worse or not respecting the salesperson, the evaluation method carried out by the evaluation system is used for properly correcting the service attitude evaluation of the salesperson, so that the salesperson is prevented from being penalized, and meanwhile, the credit rating coefficient H value of the client is reduced, so that the evaluation system can just evaluate the service quality of the salesperson, and also has a constraint function on the client; customer information files stored by the cloud server can be established in real time in the sales process, collected data are more comprehensive, evaluation of service quality is more accurate, and the problem of inaccurate evaluation results caused by human factors is avoided; the data collection and evaluation process is carried out in the sales process, resources are not required to be repeatedly spent afterwards, the evaluation flow is simplified, and the evaluation efficiency is improved.
Drawings
FIG. 1 is a schematic diagram of an evaluation system circuit;
FIG. 2 is a schematic diagram of a signal processor circuit;
fig. 3 is a flowchart of an evaluation method performed by the evaluation system.
Detailed Description
The system for evaluating sales service quality of an automobile 4S shop as shown in fig. 1-2 comprises a miniature receiver 1 carried by sales personnel, wherein the receiver 1 comprises a microphone 11, a sound card 12, a signal processor 13, an auxiliary controller 14 and a signal transmitter 15 which are sequentially connected, the signal transmitter 15 is in communication connection with a host computer 2 arranged in the 4S shop in a wireless mode, and the host computer 2 comprises a local processor, a local memory and a signal receiving/transmitting device; the host 2 is connected with a plurality of distributed cloud servers 3 through the Internet, and the cloud servers 3 comprise cloud processors and cloud memories; the corresponding hand position and the corresponding foot position of the salesperson wear the miniature body sensor 4 respectively, the salesperson wears the miniature positioning device 5 at the same time, and the body sensor 4 can be a three-axis gyroscope type body sensor or a six-axis gyroscope type body sensor, and also can be a three-coordinate type body sensor with the functions of marking positions and sending position parameter information; the positioning device 5 can be a GPS (global positioning system) positioner, an ultrasonic positioner or other positioners; the miniature body sensor 4 and the miniature positioning device 5 are respectively in communication connection with the host computer 2 in a wireless mode, a salesperson also wears a power switch 16 which simultaneously controls the miniature receiver 1, the body sensor 4 and the miniature positioning device 5 to be opened and closed, and the power switch 16 is connected with a miniature lithium ion battery.
When sales personnel communicate with customers or conduct sales negotiations, a single person usually speaks in the same time period, but in some cases, 2 or more people speak at the same time, and in order to better extract sound data, a better implementation is as follows: the microphone 11 is a matrix microphone, and the signal processor 13 comprises an adaptive filter 17, a multi-human sound source separation module 18 and a multi-channel single sound reduction module 19 which are sequentially connected. The multi-person sound source separation module 18 comprises an amplifier, an A/D signal converter and a sound separation calculation processor which are sequentially connected, and the multi-channel single person sound reduction module 19 comprises a sound reduction calculation processor, an A/D signal converter and a multi-channel signal output port which are sequentially connected; in the case of simultaneous speaking of multiple persons, the sound signals of the multiple persons mixed are separated and restored to multiple independent single sound signals.
The signal processor 13 processes the multi-person mixed sound signal as follows: the adaptive filter 17 filters the multi-person mixed sound signal, eliminates or suppresses environmental noise, the multi-person sound source separation module 18 discretizes the filtered multi-person mixed sound signal, extracts mel frequency cepstrum coefficients of the multi-person mixed sound signal as multi-person mixed sound signal characteristic parameters, and establishes a gaussian mixture model; training a Gaussian mixture model by utilizing characteristic parameters of the multi-person mixed sound signals; collecting multi-person mixed sound signals of a measured environment by adopting a microphone array formed by a plurality of microphones, and determining the number of sound sources of the environment and the arrival direction of each sound source beam, namely the incident angle of a sound source to the microphone array; according to the audio signal of each sound source, the conversion relation between the sound source and the microphone, obtaining the sound pressure of the microphone array received by the microphone, the sound pressure gradient of the microphone array in the horizontal direction and the sound pressure gradient of the microphone array in the vertical direction; converting the central sound pressure of the microphone array, the sound pressure gradient of the microphone array in the horizontal direction and the sound pressure gradient of the microphone array in the vertical direction from a time domain to a frequency domain by adopting Fourier transformation; obtaining an intensity vector formula of sound pressure signals in a frequency domain according to the sound pressure of the microphone array in the frequency domain, the gradient of the microphone array in the horizontal direction and the gradient of the sound pressure of the microphone array in the vertical direction, and deducing an intensity vector direction; carrying out statistics on the intensity vector direction to obtain probability density distribution, adopting mixed Feng Mixiu S distribution to carry out fitting to obtain model parameters of which the voice intensity vector direction is subjected to mixed Feng Mixiu S distribution, and further obtaining an intensity vector direction function of each sound pressure signal; the multi-channel single-person sound restoration module 19 obtains a signal of each sound source in a frequency domain according to the intensity vector direction function of each sound pressure signal and the microphone array sound pressure, converts each sound source signal in the frequency domain into a sound source signal in a time domain by adopting inverse fourier transform, and then sends a plurality of individual sound source signals in the time domain to the auxiliary processor 14. The signal processor 13 may also perform reduction and separation on the multi-person mixed sound signal by adopting other calculation methods.
The local memory in the host 2 stores audio features for identifying all sales personnel in the sales personnel' S own 4S store in advance, where the audio features may include feature information such as amplitude, frequency, spectrogram, power spectral density, and other relevant parameters of sound.
As shown in fig. 3, according to the evaluation method of any one of the above-mentioned vehicle 4S shop sales service quality evaluation systems, the evaluation method includes the steps of:
a. the salesperson starts the power switch 16 to start the micro receiver 1, the micro body sensor 4 and the micro positioning device 5; the auxiliary controller 14 sends a request to the host 2 through the signal transmitter 15, the local processor in the host 2 establishes a temporary evaluation file L in the local memory, stores the current time T0 in L, and then proceeds to step b;
b. the signal processor 13 receives the multi-person mixed sound signal transmitted by the microphone 11, separates the multi-person mixed sound signal, and restores the multi-person mixed sound signal into a plurality of independent single sound signals, and the plurality of independent single sound signals are transmitted to the host 2 through the signal transmitter 15; the host computer 2 distinguishes the audio characteristics of each of a plurality of independent single sound signals, and writes the single sound signals with the same audio characteristics into sales person audio recordings D1, D2 and … Dn or client audio recordings K1, K2 and … Kn respectively in the temporary evaluation file L according to the time sequence; simultaneously, the miniature body sensor 4 and the miniature positioning device 5 send action information and position information of sales personnel to the host computer 2, and the host computer 2 writes the action information and the position information of the sales personnel corresponding to the D1, the D2 and the … Dn respectively into action track data E1, E2 and … En of the sales personnel; then enter step c; the action information of the sales person can comprise a complete action such as bow, handshake, hug and the like, and the position information is the specific position of the sales person in the 4S store;
in the step b, the establishment method of Dn and Kn comprises the following steps:
the local processor in the host 2 analyzes the audio characteristics of each of a plurality of independent single sound signals, if the audio characteristics are the same as the audio characteristics of sales personnel stored in the local memory and the sales personnel audio record Dn with the audio characteristics exists in L, the single sound signal data is stored in the corresponding Dn in an inserting way, and if the audio characteristics are the same as the audio characteristics of sales personnel stored in the host 2 and are different from the audio characteristics in D1, D2 and … Dn existing in L, a new sales personnel audio record Dn is established and the single sound signal data is stored;
storing the single person sound signal in a corresponding Kn in an inserted manner if the audio characteristics are different from the audio characteristics of the sales person sound signal stored in the host 2 and there is already a customer audio recording Kn having the audio characteristics in L, and creating a new customer audio recording Kn for storing the single person sound signal data if the audio characteristics are different from the audio characteristics of the sales person stored in the host 2 and are different from the audio characteristics in K1, K2, … Kn already in L;
c. the host computer 2 judges that the value of Nd+Nk is larger than or equal to the vocabulary trigger threshold, then the step e is entered, otherwise, the step d is entered; nd is the sum of the vocabulary numbers in all Dn, nk is the sum of the vocabulary numbers in all Kn;
d. after the time T1 from the current moment, if new data continue to appear in the stored Dn or new data continue to appear in the stored Kn or new Dn or new Kn appears, returning to the step b, otherwise, entering the step x;
e. the host 2 uploads the data which are not uploaded in Dn, kn and En to the cloud server 3, and the step f is entered;
f. the cloud server 3 respectively compares the Dn data and the Kn data with standard vocabulary audio data Q stored in a cloud memory of the cloud server 3 in real time, calculates client evaluation indexes S1 and S2 … Sn, and stores client personal information vocabulary data and client personal audio frequency characteristic information appearing in the Kn in real time; the standard vocabulary audio data Q comprises a special vocabulary library of an automobile, such as a transmission, an engine, a chassis, a steering system, oil consumption, quality assurance and the like, a polite vocabulary library, such as a good-quality vocabulary library, a thank you, a welcome vocabulary library and the like, an irregular vocabulary library and a disfigurative vocabulary library; the client personal information vocabulary data comprises related vocabularies such as client names, client addresses, client work units and the like.
The cloud server 3 compares the Dn data with the standard vocabulary audio data Q stored in the cloud server 3 in real time, compares the En data with the standard action and position data P stored in the cloud server 3 in real time, calculates salesperson evaluation indexes R1 and R2 … Rn, and then enters the step g;
in the step f, the calculation method of the salesperson evaluation index Rn is as follows:
wherein a is 1 From the 1 st vocabulary to the N th vocabulary in Dn data, which appearsScore of the word for automobile, a 2 Score points when polite words appear in the Dn data from the 1 st vocabulary to the N th vocabulary, such as 'you good', 'welcome', and the like; a, a 3 From the 1 st vocabulary to the N th vocabulary in the Dn data, the score of the vocabulary related to the personal information of the client appears, such as related information vocabularies of the client name, work unit, home address and the like; b i From the 1 st data to the nth data in the En data corresponding to Dn, the En data is added with a score when an etiquette action occurs at a specified place, such as a bow, handshake, waving and the like; c i From the 1 st vocabulary to the N st vocabulary in the Dn data, the score is reduced when irregular expression or profoundly-used vocabulary appears; g 2 N is the vocabulary quantity appearing in Dn as the vocabulary quantity weight coefficient; g 1 Is a standard action weight coefficient;
the calculation method of the client evaluation index Sn comprises the following steps:
wherein f 1 From the 1 st vocabulary to the M th vocabulary in the Kn data, which shows the score of D1, D2 or … Dn 2 From the 1 st vocabulary to the M th vocabulary in the Kn data, the score of the score when the score of the score is like good, satisfactory and the like, f 3 From the 1 st word to the M-th word in Kn data, which gives rise to a specific query and the query includes a score for the score of the vehicle-specific word, such as "what is the engine power of the vehicle? "what is the transmission model of the vehicle? "wait for questions; g i From the 1 st vocabulary to the M th vocabulary in the Kn data, the score is reduced when the counter-productive vocabulary appears; m is the number of words present in Kn, and H is the credit rating factor of the customer.
The H value calculating method comprises the following steps: if the cloud server 3 judges that the personal audio frequency characteristic information of the client in the current Kn is stored in the cloud server 3, the H value of the client is extracted, and if the personal audio frequency characteristic information of the client in the current Kn does not exist in the cloud server 3, the H value is 1.
g. The host 2 judges that new data appear in one Dn of D1, D2 and … Dn stored in the L at the moment or new data appear in one Kn of K1, K2 and … Kn, and returns to the step e; otherwise, entering the step h;
h. the host 2 judges that the power switch 16 is closed, the step j is carried out, otherwise, the step i is carried out;
i. the host 2 judges that new Dn or Kn data appear in the L, and returns to the step b, otherwise, the step j is entered;
j. the cloud server 3 judges Sn:
if Sn is greater than 0, the credit rating coefficient H value of the client is increased; the final evaluation index Z=Rn+Sn of sales personnel, and the values of Z, rn and Sn are written into a sales evaluation file An; writing Sn value, personal information vocabulary data of the client, personal audio frequency characteristic information of the client and H value of the client into a client information file Bn; the cloud server 3 stores An and Bn, and the flow is ended;
if Sn is less than or equal to 0, decreasing the credit rating factor H value of the customer, the salesperson final evaluation index z=rn+y0, said Y0 value being a fixed positive value; writing Z, rn and Sn values into a sales evaluation file An; writing Sn value, personal information vocabulary data of the client, personal audio frequency characteristic information of the client and H value of the client into a client information file Bn; the cloud server 3 stores An and Bn, and the flow is ended;
y0 is introduced in the calculation of the final evaluation index Z of the salesperson to effectively restrict the client, and when the cloud server 3 calculates Sn to be less than or equal to 0, the client is considered to not respect the salesperson, and the salesperson is evaluated by adopting no relevant information of the client, but only whether the salesperson has normal service or not, so that the evaluation method is fairer. The introduction of the H value improves the constraint on the client, so that the client more honors sales personnel, and the sales process is effectively maintained and smoothly carried out.
And x, the host computer 2 judges that the sales flow is not established, deletes the L data, turns off the power switch 16, and ends the flow.
In some cases, sales personnel or clients are quarreling, and such quarreling is often difficult to judge both responsibilities, so in order to make the evaluation method fairer, a better embodiment is: in the step f, if the cloud server 3 judges that the sound decibels in Dn or Kn suddenly increase and continues for a certain early warning time, after the early warning time, the cloud server 3 records the audio data in Dn and Kn simultaneously until the sound decibels in Dn and Kn decrease to a certain degree and continue for a certain period of time, in the step j, a manufacturer related person or a special person in a 4S store can listen and judge the recorded data in Dn and Kn, and input a correction value Y1 to the cloud server 3, and the cloud server 3 finally calculates rn=rn+y1, sn=sn+y1.
In some sales processes, the customers may present problems related to the present brand of automobile, such as problems related to fuel consumption, reliability, quality assurance, etc., and the sales person or manufacturer often wants to keep the problems presented by the customers in time, so as to better service the customers later, or improve the automobile products themselves, so that the preferred embodiments are: in the step f, if the cloud server 3 determines that a specific question sentence appears in the Kn data, recording audio data including the question sentence in the Kn and audio data in a period of time thereafter, and storing the audio data in Bn. After the sales process is finished, sales staff can listen to the problems proposed by the clients in Bn to carry out work summary or feed back to manufacturers in time so as to optimize the sales process, improve the service quality or improve the performance of the automobile according to the problems proposed by the clients.
In the sales process, in order to improve the competitiveness of the brand of automobiles, manufacturers often want to collect the comments or views of customers about other brands, so that a better implementation is: in the step f, if the cloud server 3 determines that the Kn data has other car brand vocabulary, the vocabulary and a plurality of car professional vocabulary which have occurred in the Kn data in a period of time before and after the occurrence of the vocabulary are stored in the Bn, and after the evaluation process is finished, the manufacturer or the sales personnel can extract the other car brand vocabulary which has occurred in the Bn and the car professional vocabulary which is related to the other car brand vocabulary, so that the direction or the specific content which the customer cares about the other car brands is found out.
If the vocabulary of a sales person or a customer is too small in the sales process, the evaluation result for the sales person or the customer is less accurate, so that a better implementation mode is that: before the step j, the cloud server firstly judges that if the vocabulary quantity N in Dn or the vocabulary quantity M in Kn is smaller than or equal to a preset value, the Dn or the Kn is deleted, and the En corresponding to the Dn is deleted; if the vocabulary quantity N in Dn or the vocabulary quantity M in Kn is larger than a preset value, reserving the corresponding Dn or Kn, and then entering step j; this can improve the accuracy of An, bn.
The cloud server extracts the vocabulary in the Dn and Kn data, so that the calculated salesperson evaluation index Rn can effectively monitor whether the service attitude and the service expression of the salesperson are in place in the sales process, the cloud server can store the corresponding standard positions in the sales service flow in advance, and then the action information and the position information of the salesperson in En are compared, so that whether the etiquette action of the salesperson is in place is judged, and the reliability of the evaluation result of the evaluation system is further improved.
The client evaluation index Sn can effectively monitor the language and attitude of the client in the sales process, if the salesperson is served according to the sales flow, and the client attitude is still worse or not respecting the salesperson, the evaluation method carried out by the evaluation system is used for properly correcting the service attitude evaluation of the salesperson, so that the salesperson is prevented from being penalized, and meanwhile, the credit rating coefficient H value of the client is reduced, so that the evaluation system can just evaluate the service quality of the salesperson, and also has a constraint function on the client.
Claims (7)
1. A sales service quality evaluation system of an automobile 4S shop is characterized in that: the evaluation system comprises a miniature receiver (1) carried by sales personnel, wherein the miniature receiver (1) comprises a microphone (11), a sound card (12), a signal processor (13), an auxiliary controller (14) and a signal transmitter (15), the signal transmitter (15) is in communication connection with a host (2) arranged in a 4S store in a wireless mode, and the host (2) comprises a local processor, a local memory and a signal receiving/transmitting device; the host (2) is connected with a plurality of distributed cloud servers (3) through the Internet, and the cloud servers (3) comprise cloud processors and cloud memories; the corresponding positions of the hands and feet of the salesperson wear the miniature body sensor (4) respectively, the salesperson wears the miniature positioning device (5) simultaneously, the miniature body sensor (4) and the miniature positioning device (5) are respectively in communication connection with the host computer (2) in a wireless mode, and the salesperson also wears the power switch (16) for controlling the miniature receiver (1), the miniature body sensor (4) and the miniature positioning device (5) to be opened and closed.
2. The system for evaluating sales service quality of an automobile 4S shop according to claim 1, wherein: the signal processor (13) comprises an adaptive filter (17), a multi-human sound source separation module (18) and a multi-channel single sound restoration module (19) which are connected in sequence.
3. The evaluation method of an automobile 4S shop sales service quality evaluation system according to any one of claims 1 to 2, characterized in that: the evaluation method comprises the following steps:
a. a salesperson starts a power switch (16) to start a miniature receiver (1), a miniature somatosensory sensor (4) and a miniature positioning device (5); the auxiliary controller (14) sends a request to the host (2) through the signal transmitter (15), a local processor in the host (2) establishes a temporary evaluation file L in a local memory, stores the current time T0 in the L, and then enters the step b;
b. the signal processor (13) receives the multi-person mixed sound signals transmitted by the microphone (11), separates the multi-person mixed sound signals and restores the multi-person mixed sound signals into a plurality of independent single sound signals, and the independent single sound signals are transmitted to the host (2) through the signal transmitter (15); the host (2) distinguishes the audio characteristics of each of a plurality of independent single sound signals, and writes the single sound signals with the same audio characteristics into sales person audio recordings D1, D2 and … Dn or client audio recordings K1, K2 and … Kn respectively in the temporary evaluation file L according to the time sequence; simultaneously, the miniature body sensor (4) and the miniature positioning device (5) send the action information and the position information of the salesperson to the host (2), and the host (2) writes the action information and the position information of the salesperson corresponding to the D1, the D2 and the … Dn respectively into action track data E1, E2 and … En of the salesperson; then enter step c;
c. the host (2) judges that the value of Nd+Nk is larger than or equal to the vocabulary triggering threshold value, and then enters the step e, otherwise, enters the step d; nd is the sum of the vocabulary numbers in all Dn, nk is the sum of the vocabulary numbers in all Kn;
d. after the time T1 from the current moment, if new data continue to appear in the stored Dn or new data continue to appear in the stored Kn or new Dn or new Kn appears, returning to the step b, otherwise, entering the step x;
e. uploading data which are not uploaded in Dn, kn and En to a cloud server (3) by a host (2), and entering a step f;
f. the cloud server (3) respectively compares the Dn data and the Kn data with standard vocabulary audio data Q stored in a cloud memory of the cloud server (3) in real time, calculates client evaluation indexes S1 and S2 … Sn, and stores client personal information vocabulary data and client personal audio frequency characteristic information appearing in the Kn in real time;
the cloud server (3) compares the Dn data with standard vocabulary audio data Q stored in the cloud server (3) in real time, compares the En data with standard action and position data P stored in the cloud server (3) in real time, calculates salesperson evaluation indexes R1 and R2 … Rn, and then enters the step g;
g. the host (2) judges that new data appear in one Dn of D1, D2 and … Dn stored in the L at the moment or new data appear in one Kn of K1, K2 and … Kn, and returns to the step e; otherwise, entering the step h;
h. the host (2) judges that the power switch (16) is closed, the step j is entered, otherwise, the step i is entered;
i. the host (2) judges that new Dn or Kn data appear in the L, returns to the step b, otherwise, enters the step j;
j. the cloud server (3) judges Sn:
if Sn is greater than 0, the credit rating coefficient H value of the client is increased; the final evaluation index Z=Rn+Sn of sales personnel, and the values of Z, rn and Sn are written into a sales evaluation file An; writing Sn value, personal information vocabulary data of the client, personal audio frequency characteristic information of the client and H value of the client into a client information file Bn; the cloud server (3) stores An and Bn, and the process is finished;
if Sn is less than or equal to 0, decreasing the credit rating factor H value of the customer, the salesperson final evaluation index z=rn+y0, said Y0 value being a fixed positive value; writing Z, rn and Sn values into a sales evaluation file An; writing Sn value, personal information vocabulary data of the client, personal audio frequency characteristic information of the client and H value of the client into a client information file Bn; the cloud server (3) stores An and Bn, and the process is finished;
x, the host (2) judges that the sales flow is not established, deletes the L data, turns off the power switch (16), and ends the flow;
in the step f, the calculation method of the salesperson evaluation index Rn is as follows:
wherein a is 1 A is the score added when the Dn data from the 1 st vocabulary to the N th vocabulary appear in the automobile special vocabulary 2 A is the score added when the N-th vocabulary is from the 1 st vocabulary to the N-th vocabulary in Dn data and polite expression appears 3 From the 1 st vocabulary to the N th vocabulary in the Dn data, the score is added when the vocabulary related to the personal information of the client appears; b i From the 1 st data to the nth data among En data corresponding to Dn, a score is added when an etiquette action occurs at a specified location; c i From the 1 st vocabulary to the N st vocabulary in the Dn data, the score is reduced when irregular expression or profoundly-used vocabulary appears; g 2 N is the vocabulary quantity appearing in Dn as the vocabulary quantity weight coefficient; g 1 Is a standard action weight coefficient;
the calculation method of the client evaluation index Sn comprises the following steps:
wherein f 1 From the 1 st vocabulary to the M th vocabulary in the Kn data, which shows the score of D1, D2 or … Dn 2 For the score added when the number of words from 1 to M appears in the Kn data, f 3 A score in the Kn data from the 1 st vocabulary to the M th vocabulary, wherein the score is a score when a specific query sentence appears and the query sentence comprises a vehicle-specific vocabulary; g i From the 1 st vocabulary to the M th vocabulary in the Kn data, the score is reduced when the counter-productive vocabulary appears; m is the number of words appearing in Kn, H is the credit rating coefficient of the customer; the H value calculating method comprises the following steps: if the cloud server (3) judges that the personal audio frequency characteristic information of the client in the current Kn is stored in the cloud server (3), the H value of the client is extracted, and if the personal audio frequency characteristic information of the client in the current Kn does not exist in the cloud server (3), the H value is 1.
4. A method for evaluating a quality of service evaluation system for sales of 4S shops of automobiles according to claim 3, wherein: in the step b, the establishment method of Dn and Kn comprises the following steps:
a local processor in the host (2) analyzes the audio characteristics of each of a plurality of independent single sound signals, if the newly acquired audio characteristics are the same as the audio characteristics of sales personnel sound signals stored in a local memory and sales personnel audio records Dn with the audio characteristics exist in L, the single sound signal data are stored in the corresponding Dn in an inserting mode, and if the newly acquired audio characteristics are the same as the audio characteristics of sales personnel sound signals stored in the host (2) and are different from the audio characteristics in D1, D2 and … Dn existing in L, a new sales personnel audio record Dn is established and the single sound signal data are stored;
if the newly acquired audio characteristics are the same as those of the audio records Kn of the customer audio having the audio characteristics already existing in L, the single person sound signal is stored in the corresponding Kn in an inserting manner, and if the audio characteristics are different from those of the sales person sound signal stored in the host (2) and are different from those of the audio characteristics existing in K1, K2 and … Kn in L, a new customer audio record Kn is established for storing the single person sound signal data.
5. A method for evaluating a quality of service evaluation system for sales of 4S shops of automobiles according to claim 3, wherein: in the step f, if the cloud server (3) judges that a specific question sentence appears in the Kn data, recording audio data including the question sentence in the Kn and audio data in a period of time later, and storing the audio data in Bn.
6. A method for evaluating a quality of service evaluation system for sales of 4S shops of automobiles according to claim 3, wherein: in the step f, if the cloud server (3) judges that other automobile brand vocabularies appear in the Kn data, the vocabularies and a plurality of automobile professional vocabularies appearing in the Kn data in a period of time before and after the vocabularies appear are stored in the Bn.
7. A method for evaluating a quality of service evaluation system for sales of 4S shops of automobiles according to claim 3, wherein: before the step j, the cloud server (3) firstly judges that if the vocabulary quantity N in Dn or the vocabulary quantity M in Kn is smaller than or equal to a preset value, the Dn or the Kn is deleted, and the En corresponding to the Dn is deleted; if the vocabulary number N in Dn or the vocabulary number M in Kn is larger than the preset value, reserving the corresponding Dn or Kn, and then entering step j.
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