CN113240347A

CN113240347A - Service behavior data analysis method, system, storage medium and electronic device

Info

Publication number: CN113240347A
Application number: CN202110673359.5A
Authority: CN
Inventors: 顾婉晴; 王岩; 梁志婷
Original assignee: Enyike Beijing Data Technology Co ltd
Current assignee: Enyike Beijing Data Technology Co ltd
Priority date: 2021-06-17
Filing date: 2021-06-17
Publication date: 2021-08-10

Abstract

The application discloses a method, a system, a storage medium and an electronic device for analyzing service behavior data, wherein the analysis method comprises the following steps: a data acquisition step: acquiring welcome behavior speech technology data of each employee in working time from a database; and (3) data analysis step: carrying out structuralization processing and analysis of at least one operation dimension on the voice acquisition time information corresponding to the welcome behavior phone data and the welcome behavior phone data to obtain an operation report of at least one operation dimension of the store; a report feedback step: and feeding back the store welcome entrance call use report to a receiving end. By analyzing and applying the staff service behavior data, the invention provides beneficial help for optimizing the shop staff service capability, improving the shop sales service efficiency and the customer satisfaction and further improving the sales performance.

Description

Service behavior data analysis method, system, storage medium and electronic device

Technical Field

The invention belongs to the application field of service behavior data, and particularly relates to an analysis method, a system, a storage medium and electronic equipment of service behavior data.

Background

In the online sale service scene, the welcome guests are important components of the standard service process of the offline retail industry and are key nodes for completing the sale closed loop, the complete welcome guests can bring good shopping experience to the customer, the mood of the customer can be influenced to a certain degree, the purchase desire and the repurchase rate can be increased, and the sale performance is improved. From the perspective of an operation manager of a store, after mastering accurate service behavior data and distribution data of different dialects, how to apply the data has important significance for improving sales service efficiency and customer satisfaction.

The existing application scheme has several modes:

firstly, the receiving capacity of a store clerk can be calculated through the statistical result of the welcome guests, and the time-interval passenger flow condition of the retail store under the line can be reflected by combining the distribution condition of time;

secondly, providing support data, namely denominator, for subsequent sales conversion analysis on the basis of obtaining the receiving quantity;

thirdly, by combining the statistical data of the distribution results of different dialogues, whether the store clerk uses the greeting and delivery dialogues in reception or not and the distribution conditions of the different dialogues, such as what you need, walk slowly, congratulate on health and the like, and the support is provided for improving the training effect while the ability of the store clerk is inspected;

and fourthly, whether the salesman uses forbidden dialogues and frequency of use when meeting guests is examined, for example, in the process of selling medicines, the dialogues of 'welcoming next time' cannot be used.

Disclosure of Invention

The embodiment of the application provides an analysis method, a system, a storage medium and electronic equipment for service behavior data, and aims to at least solve the problem that the sales service efficiency is low when the existing analysis method for service behavior data is used for improving the sales service efficiency.

The invention provides a service behavior data analysis method, which comprises the following steps:

a data acquisition step: acquiring welcome behavior speech technology data of each employee in working time from a database;

and (3) data analysis step: carrying out structuralization processing and analysis of at least one operation dimension on the voice acquisition time information corresponding to the welcome behavior phone data and the welcome behavior phone data to obtain an operation report of at least one operation dimension of the store;

a report feedback step: and feeding back the store welcome entrance call use report to a receiving end.

The method, wherein the analyzing of the at least one operation dimension includes:

passenger flow analysis dimension: acquiring the number of times of welcoming each employee in a certain period of time, acquiring total receptivity according to the number of times of welcoming each employee, and acquiring the time distribution of passenger flow according to the distribution condition of the total receptivity in time;

the method, wherein the time distribution of the passenger flow includes: peak traffic hours and low traffic hours.

The method, wherein the analyzing of the at least one operation dimension further comprises:

sales conversion analysis dimension: obtaining reception data of each store clerk according to the number of welcomes, and obtaining an effective sales tactical index statistical result and a conversion rate of a corresponding index according to the reception data;

store clerk ability survey dimension: comparing the real-time extracted speech result data used by the employee when the employee is welcomed and sent to a preset standard speech library, checking whether the employee uses standard welcoming speech and/or forbidden speech during reception according to the comparison result, and outputting an employee capacity result based on a preset employee capacity index calculation model;

communication disabled telephony dimensions: and obtaining forbidden phone operation data of a specific application scene, and obtaining the use condition of forbidden phone operations during employee communication according to the forbidden phone operation data and the distribution data.

The method further includes:

acquiring the greeting and guest behavioral speech data from a voice database; the voice data in the voice database is derived from voice collecting equipment carried by store personnel or voice collecting equipment deployed in a physical store.

The invention also provides an analysis system of the service behavior data, which comprises the following steps:

the data acquisition module acquires the number of times of welcoming and delivering guests and the distribution data of the welcoming and delivering guest dialect of each employee in the working time from a database;

the analysis module is used for obtaining an entrance shop greeting and delivery speech use report comprising at least one of a passenger flow index, a sales index, an employee capability index and a forbidden user speech monitoring condition according to the distribution data and/or the number of times of greeting and delivery;

and the report feedback module feeds back the store welcome entrance call use report to a receiving end.

The invention also provides an electronic device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, wherein the processor implements any of the analysis methods when executing the computer program.

The invention also provides a storage medium having a computer program stored thereon, wherein the program, when executed by a processor, implements any of the analysis methods described herein.

The invention belongs to the field of speech recognition and processing under deep learning, and has the beneficial effects that:

through the analysis and the application of the staff service behavior data, the beneficial help is provided for optimizing the shop assistant service capability, improving the shop sales service efficiency and the customer satisfaction and further improving the sales performance.

Drawings

The accompanying drawings, which are included to provide a further understanding of the application and are incorporated in and constitute a part of this application, illustrate embodiment(s) of the application and together with the description serve to explain the application and not to limit the application.

In the drawings:

FIG. 1 is a flow chart of a method of analyzing service activity data of the present invention;

FIG. 2 is a framework diagram of the application of the service activity data of the present invention;

FIG. 3 is a schematic diagram of the structure of the service activity data analysis system of the present invention;

fig. 4 is a frame diagram of an electronic device according to an embodiment of the present invention.

Detailed Description

In order to make the objects, technical solutions and advantages of the present application more apparent, the present application will be described and illustrated below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the present application and are not intended to limit the present application. All other embodiments obtained by a person of ordinary skill in the art based on the embodiments provided in the present application without any inventive step are within the scope of protection of the present application.

It is obvious that the drawings in the following description are only examples or embodiments of the present application, and that it is also possible for a person skilled in the art to apply the present application to other similar contexts on the basis of these drawings without inventive effort. Moreover, it should be appreciated that in the development of any such actual implementation, as in any engineering or design project, numerous implementation-specific decisions must be made to achieve the developers' specific goals, such as compliance with system-related and business-related constraints, which may vary from one implementation to another.

Reference in the specification to "an embodiment" means that a particular feature, structure, or characteristic described in connection with the embodiment can be included in at least one embodiment of the specification. The appearances of the phrase in various places in the specification are not necessarily all referring to the same embodiment, nor are separate or alternative embodiments mutually exclusive of other embodiments. Those of ordinary skill in the art will explicitly and implicitly appreciate that the embodiments described herein may be combined with other embodiments without conflict.

Unless defined otherwise, technical or scientific terms referred to herein shall have the ordinary meaning as understood by those of ordinary skill in the art to which this application belongs. Reference to "a," "an," "the," and similar words throughout this application are not to be construed as limiting in number, and may refer to the singular or the plural. The present application is directed to the use of the terms "including," "comprising," "having," and any variations thereof, which are intended to cover non-exclusive inclusions; for example, a process, method, system, article, or apparatus that comprises a list of steps or modules (elements) is not limited to the listed steps or elements, but may include other steps or elements not expressly listed or inherent to such process, method, article, or apparatus. Reference to "connected," "coupled," and the like in this application is not intended to be limited to physical or mechanical connections, but may include electrical connections, whether direct or indirect. The term "plurality" as referred to herein means two or more. "and/or" describes an association relationship of associated objects, meaning that three relationships may exist, for example, "A and/or B" may mean: a exists alone, A and B exist simultaneously, and B exists alone. The character "/" generally indicates that the former and latter associated objects are in an "or" relationship. Reference herein to the terms "first," "second," "third," and the like, are merely to distinguish similar objects and do not denote a particular ordering for the objects.

The present invention is described in detail with reference to the embodiments shown in the drawings, but it should be understood that these embodiments are not intended to limit the present invention, and those skilled in the art should understand that functional, methodological, or structural equivalents or substitutions made by these embodiments are within the scope of the present invention.

Before describing in detail the various embodiments of the present invention, the core inventive concepts of the present invention are summarized and described in detail by the following several embodiments.

The first embodiment is as follows:

based on the sales service scene, the invention starts with 4 analyses such as passenger flow, sales conversion analysis, salesman capability investigation, communication forbidden dialect monitoring and the like based on the structured data statistical results of the guest greeting and delivery behaviors and different greeting and delivery dialogues to support the application of the salesman in the aspects of modification of stores, optimization of salesman service capability, training result investigation and the like, thereby improving the sales service efficiency and the customer satisfaction of the stores and further improving the sales performance. Particularly, in an online sale service scene, the welcoming guests are important components of a standard service process of the offline retail industry and are key nodes for completing a sale closed loop, the complete welcoming guests can bring good shopping experience to the customers, the mood of the customers can be influenced to a certain extent, the purchase desire and the repurchase rate can be increased, and the sale performance is improved.

Referring to fig. 1, fig. 1 is a flowchart of a method for analyzing service behavior data. As shown in fig. 1, the method for analyzing service behavior data of the present invention includes:

data acquisition step S1: and acquiring welcome behavior speech operation data of each employee in the working time from the database.

Specifically, the number of times of welcoming and sending guests of each employee in each period of time and the distribution data of the welcoming and sending guest talk are obtained from a database; distributing data into four directions: analyzing customer flow, analyzing sales conversion, inspecting the ability of store personnel, and prohibiting user talk monitoring.

Data analysis step S2: and performing structuralization processing and analysis of at least one operation dimension on the voice acquisition time information corresponding to the welcome behavior phone operation data in combination with the welcome behavior phone operation data to obtain an operation report of at least one operation dimension of the store.

Report feedback step S3: and feeding back the store welcome entrance call use report to a receiving end.

Specifically, the analysis results are integrated to obtain a use report of the store welcome entrance call, and the use report is submitted to an operation department of the store to support the improvement of the store, the capability evaluation of store personnel, the research of training results and the like.

The method, wherein the method for analyzing the service behavior data further includes:

a report display step: and the receiving end displays the entrance shop welcome entrance call operation report.

Wherein the performing of the analysis of the at least one operational dimension comprises:

wherein the time distribution of the passenger flow volume comprises: peak traffic hours and low traffic hours.

Wherein the performing of the analysis of the at least one operational dimension further comprises:

Wherein, still include:

Specifically, the passenger flow is analyzed: acquiring the number of times of welcoming guests of a store in a certain period of time, summing the number of times of welcoming guests of all the stores in the store to obtain total receiving capacity, acquiring the time distribution of the passenger flow according to the distribution condition of the receiving capacity in time, acquiring the analysis conclusion of the peak time period and the low valley time period of the passenger flow, and taking corresponding measures to improve the passenger flow; sales transformation analysis: acquiring the number of welcomes, calculating the reception conditions of different store employees, calculating the conversion rate of an index according to specific segmentation requirements and the proportion conditions of other conditions, such as stock condition mentioning rate, preferential activity mentioning rate and the like, providing specific data support, and adopting related means to improve the index for the dimensionality with low mentioning rate;

shop assistant competency survey: extracting the speech operation result data used by the store clerk when meeting guests, checking whether the store clerk uses a standard meeting guest speech operation, such as what is needed, walking slowly, and congratulating health, and providing support for improving training effect while inspecting the ability of the store clerk;

communication is disabled: according to a specific application scene, whether the forbidden dialogues are used by store personnel, such as the word "welcome next time" in retail of a pharmacy, is confirmed, relevant data of the communication forbidden dialogues are called from a database, the use condition is analyzed, and further the sales standardization process is improved.

FIG. 2 is a block diagram of the present invention showing data collection by the data layer; the analysis layer analyzes the collected data to obtain an analysis result; and the application layer is applied according to the analysis result to obtain the effects of improving passenger flow volume, improving related indexes, improving training results and improving training results.

Example two:

referring to fig. 3, fig. 3 is a schematic structural diagram of a service behavior data analysis system according to the present invention. Fig. 3 shows an analysis system of service behavior data according to the present invention, which includes:

Example three:

referring to fig. 4, this embodiment discloses a specific implementation of an electronic device. The electronic device may include a processor 81 and a memory 82 storing computer program instructions.

Specifically, the processor 81 may include a Central Processing Unit (CPU), or A Specific Integrated Circuit (ASIC), or may be configured to implement one or more Integrated circuits of the embodiments of the present Application.

Memory 82 may include, among other things, mass storage for data or instructions. By way of example, and not limitation, memory 82 may include a Hard Disk Drive (Hard Disk Drive, abbreviated HDD), a floppy Disk Drive, a Solid State Drive (SSD), flash memory, an optical Disk, a magneto-optical Disk, tape, or a Universal Serial Bus (USB) Drive or a combination of two or more of these. Memory 82 may include removable or non-removable (or fixed) media, where appropriate. The memory 82 may be internal or external to the data processing apparatus, where appropriate. In a particular embodiment, the memory 82 is a Non-Volatile (Non-Volatile) memory. In particular embodiments, Memory 82 includes Read-Only Memory (ROM) and Random Access Memory (RAM). The ROM may be mask-programmed ROM, Programmable ROM (PROM), Erasable PROM (EPROM), Electrically Erasable PROM (EEPROM), Electrically rewritable ROM (EAROM), or FLASH Memory (FLASH), or a combination of two or more of these, where appropriate. The RAM may be a Static Random-Access Memory (SRAM) or a Dynamic Random-Access Memory (DRAM), where the DRAM may be a Fast Page Mode Dynamic Random-Access Memory (FPMDRAM), an Extended data output Dynamic Random-Access Memory (EDODRAM), a Synchronous Dynamic Random-Access Memory (SDRAM), and the like.

The memory 82 may be used to store or cache various data files for processing and/or communication use, as well as possible computer program instructions executed by the processor 81.

The processor 81 implements any one of the above-described service activity data analysis methods in the embodiments by reading and executing the computer program instructions stored in the memory 82.

In some of these embodiments, the electronic device may also include a communication interface 83 and a bus 80. As shown in fig. 4, the processor 81, the memory 82, and the communication interface 83 are connected via the bus 80 to complete communication therebetween.

The communication interface 83 is used for implementing communication between modules, devices, units and/or equipment in the embodiment of the present application. The communication port 83 may also be implemented with other components such as: the data communication is carried out among external equipment, image/data acquisition equipment, a database, external storage, an image/data processing workstation and the like.

The bus 80 includes hardware, software, or both to couple the components of the electronic device to one another. Bus 80 includes, but is not limited to, at least one of the following: data Bus (Data Bus), Address Bus (Address Bus), Control Bus (Control Bus), Expansion Bus (Expansion Bus), and Local Bus (Local Bus). By way of example, and not limitation, Bus 80 may include an Accelerated Graphics Port (AGP) or other Graphics Bus, an Enhanced Industry Standard Architecture (EISA) Bus, a Front-Side Bus (Front Side Bus), an FSB (FSB), a Hyper Transport (HT) Interconnect, an ISA (ISA) Bus, an Infini Band Interconnect, a Low Pin Count (LPC) Bus, a memory Bus, a microchannel Architecture (MCA) Bus, a PCI (Peripheral Component Interconnect) Bus, a PCI-Express (PCI-X) Bus, a Serial Advanced Technology Attachment (SATA) Bus, a Video Electronics Bus (audio Electronics Association), abbreviated VLB) bus or other suitable bus or a combination of two or more of these. Bus 80 may include one or more buses, where appropriate. Although specific buses are described and shown in the embodiments of the application, any suitable buses or interconnects are contemplated by the application.

The electronic device may implement the method described in connection with fig. 1 based on the application of service activity data.

In addition, in combination with the analysis method of the service behavior data in the foregoing embodiments, the embodiments of the present application may provide a computer-readable storage medium to implement. The computer readable storage medium having stored thereon computer program instructions; the computer program instructions, when executed by a processor, implement a method of analyzing service activity data as in any one of the above embodiments.

The technical features of the embodiments described above may be arbitrarily combined, and for the sake of brevity, all possible combinations of the technical features in the embodiments described above are not described, but should be considered as being within the scope of the present specification as long as there is no contradiction between the combinations of the technical features.

In conclusion, the beneficial effects of the invention are that through the analysis and application of the employee service behavior data, beneficial help is provided for optimizing the shop clerk service capability, improving the shop sales service efficiency and the customer satisfaction, and further improving the sales performance.

The above-mentioned embodiments only express several embodiments of the present application, and the description thereof is more specific and detailed, but not construed as limiting the scope of the invention. It should be noted that, for a person skilled in the art, several variations and modifications can be made without departing from the concept of the present application, which falls within the scope of protection of the present application. Therefore, the protection scope of the present invention shall be subject to the protection scope of the appended claims.

Claims

1. A method for analyzing service behavior data, comprising:

2. The analysis method of claim 1, wherein said performing an analysis of at least one operational dimension comprises:

passenger flow analysis dimension: acquiring the number of times of welcoming each employee in a certain period of time, acquiring the total receptivity according to the number of times of welcoming each employee, and acquiring the time distribution of the passenger flow according to the distribution condition of the total receptivity in time.

3. The analysis method of claim 1, wherein the time distribution of the passenger flow volume comprises: peak traffic hours and low traffic hours.

4. The analysis method of claim 1, wherein said performing an analysis of at least one operational dimension further comprises:

sales conversion analysis dimension: and obtaining reception data of each store clerk according to the number of times of welcoming, and obtaining an effective sales tactical index statistical result and the conversion rate of the corresponding index according to the reception data.

5. The analysis method of claim 1, wherein said performing an analysis of at least one operational dimension further comprises:

store clerk ability survey dimension: comparing the real-time extracted speech result data used by the employee when the employee is welcomed and sent to a preset standard speech library, checking whether the employee uses standard welcoming speech and/or forbidden speech during reception according to the comparison result, and outputting an employee capacity result based on a preset employee capacity index calculation model.

6. The analysis method of claim 1, wherein said performing an analysis of at least one operational dimension further comprises:

7. The analytical method of claim 1, further comprising:

8. A system for analyzing service behavior data, comprising:

9. An electronic device comprising a memory, a processor, and a computer program stored on the memory and executable on the processor, wherein the processor implements the analysis method of any one of claims 1 to 7 when executing the computer program.

10. A storage medium on which a computer program is stored which, when being executed by a processor, carries out the analysis method according to any one of claims 1 to 7.