CN106021547B - Customer vehicle maintenance loss identification and analysis method and system based on Internet of vehicles - Google Patents
Customer vehicle maintenance loss identification and analysis method and system based on Internet of vehicles Download PDFInfo
- Publication number
- CN106021547B CN106021547B CN201610365702.9A CN201610365702A CN106021547B CN 106021547 B CN106021547 B CN 106021547B CN 201610365702 A CN201610365702 A CN 201610365702A CN 106021547 B CN106021547 B CN 106021547B
- Authority
- CN
- China
- Prior art keywords
- vehicle
- maintenance
- remaining
- vehicles
- mileage
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
Images
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/90—Details of database functions independent of the retrieved data types
- G06F16/903—Querying
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- 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
- G06Q10/00—Administration; Management
- G06Q10/20—Administration of product repair or maintenance
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- 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
- G06Q30/00—Commerce
- G06Q30/01—Customer relationship services
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- 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
- G06Q30/00—Commerce
- G06Q30/02—Marketing; Price estimation or determination; Fundraising
- G06Q30/0201—Market modelling; Market analysis; Collecting market data
Landscapes
- Engineering & Computer Science (AREA)
- Business, Economics & Management (AREA)
- Theoretical Computer Science (AREA)
- Strategic Management (AREA)
- Accounting & Taxation (AREA)
- Development Economics (AREA)
- General Physics & Mathematics (AREA)
- Finance (AREA)
- Physics & Mathematics (AREA)
- Marketing (AREA)
- Entrepreneurship & Innovation (AREA)
- Economics (AREA)
- General Business, Economics & Management (AREA)
- Databases & Information Systems (AREA)
- Data Mining & Analysis (AREA)
- Human Resources & Organizations (AREA)
- Computational Linguistics (AREA)
- Game Theory and Decision Science (AREA)
- General Engineering & Computer Science (AREA)
- Operations Research (AREA)
- Quality & Reliability (AREA)
- Tourism & Hospitality (AREA)
- Management, Administration, Business Operations System, And Electronic Commerce (AREA)
Abstract
Customer vehicle maintenance loss identification analysis method and system based on Internet of vehicles comprises the following steps: collecting driving data of the vehicle, wherein the driving data comprises information of remaining maintenance mileage, remaining maintenance days and the like of the vehicle, and uploading the driving data to a cloud platform through a mobile network; uploading the CRM data to a cloud platform through a network; traversing all vehicle information of a 4S shop, and judging whether the vehicle is maintained; and finally, judging whether the vehicle is maintained in the shop. The invention can accurately judge the maintenance time of the vehicle, and automatically judge whether the maintenance is in the shop or not and whether the loss of the vehicle maintenance occurs or not.
Description
Technical Field
The invention belongs to the technical field of Internet of vehicles, and particularly relates to a customer vehicle maintenance loss identification and analysis method and system based on the Internet of vehicles.
Background
The current automobile sales are entering the low profit era, and the car dealer is a necessary result of market competition in terms of after-sales service. However, after-sales departments are anxious, the customer loss rate which is higher and higher in recent years becomes a difficult pain in car dealers, 4S shops develop rapidly, car repair shops are distributed all around, and under the strong competition, the loss signs are increased continuously and the situation is severe.
For 4s stores, finding out which customers are lost in the fastest time can play a crucial role in customer relationship maintenance. At present, the customer collection mode of maintenance loss is basically to judge the loss of customers through manual return visit or according to actions of fuzzy customers that do not go to store for maintenance, repair, decoration, activities and the like within a specified time.
The method of manual return visit needs more manpower to track the state of the client, consumes a large amount of manpower and material resources, and cannot estimate the disturbance cost of the client. The method for counting the customer loss by the existing after-sale service system according to the customer store-in period has the advantages of simple and fuzzy algorithm and large error.
Disclosure of Invention
Aiming at the defects and shortcomings in the prior art, the invention provides a customer vehicle maintenance loss identification analysis method and system based on the Internet of vehicles.
In order to achieve the purpose, the invention provides a customer vehicle maintenance loss identification and analysis method based on an internet of vehicles, which comprises the following steps:
step 1, collecting driving data of a vehicle, and uploading the driving data to a cloud platform through a mobile network;
step 2, CRM data are uploaded to a cloud platform through a network;
step 3, traversing all vehicle information of the 4S shop, and judging whether the vehicle is maintained;
and 4, finally judging whether the vehicle is maintained in the shop.
Specifically, the driving data in step 1 includes information such as remaining maintenance mileage and remaining maintenance days of the vehicle.
Specifically, the step 3 of judging whether the vehicle is maintained includes the following steps: traversing all vehicle information of a 4S shop regularly every day, inquiring the remaining maintenance mileage uploaded by the vehicle, comparing the remaining maintenance mileage of the vehicle stored last time with the remaining maintenance mileage of the time according to judgment, and if the remaining maintenance mileage of the time is larger than the remaining maintenance mileage of the vehicle stored last time, maintaining the vehicle; and if the remaining maintenance mileage of the current time is less than the remaining maintenance mileage of the vehicle stored last time, no maintenance is performed.
Specifically, the step 4 of determining whether the vehicle is maintained in the shop specifically includes:
if no maintenance occurs, storing the remaining maintenance mileage of the vehicle during the statistics to a database for comparison at the next time;
if the vehicle is maintained, the vehicle is inquired whether the vehicle has maintenance information in the near future of the store.
More specifically, if the maintenance information exists, the vehicle is maintained in the store, and the current maintenance mileage of the vehicle is recorded for the next calculation; if there is no maintenance information, the cart is marked for maintenance in its store.
More specifically, the automatic traversal analysis summarizes the maintenance history of all vehicles, and provides a list summary of maintenance lost vehicles to the 4S shop.
The invention also provides a customer vehicle maintenance loss identification and analysis system based on the Internet of vehicles, which specifically comprises the following steps:
the Internet of things vehicle-mounted equipment is used for acquiring driving data of a vehicle and uploading the driving data to the cloud platform through a mobile network;
the channel synchronization system uploads the CRM data to the cloud platform through a network;
the vehicle maintenance judging module is used for judging whether the vehicle is maintained;
and the maintenance module is used for judging whether the vehicle is maintained in the shop.
Further, the above system further comprises: and the database is used for storing the remaining maintenance mileage of the vehicle during each counting.
Further, the system further comprises: and the maintenance loss system automatically traverses, analyzes and summarizes the maintenance history conditions of all vehicles and provides a list of maintenance loss vehicles for 4S stores.
As a further example, the system further includes a cloud storage module, configured to store the analyzed driving data and CRM data.
Due to the adoption of the technical scheme, the invention can obtain the following technical effects: the method can be practically applied to the practical vehicle repairing industry of 4s shops and automobile repair factories, has great help for helping customer service consultants and loss relation teams to analyze whether the vehicles are subjected to maintenance loss or not, and can directly position lost vehicles and client information.
The system can also help manufacturers to collect maintenance loss conditions after the vehicles are actually used, and can greatly help to improve maintenance work related to customers.
Drawings
The invention has the following figures 2:
FIG. 1 is a block diagram of a customer vehicle maintenance loss identification analysis architecture based on an Internet of vehicles.
FIG. 2 is a flow chart of a customer vehicle maintenance churn identification analysis based on an Internet of vehicles.
Detailed Description
The technical solution of the present invention is further specifically described below by way of examples with reference to the accompanying drawings.
Example 1
Customer vehicle maintenance loss identification and analysis method based on Internet of vehicles comprises the following steps:
step 1, collecting driving data of a vehicle, wherein the driving data comprises information of remaining maintenance mileage, remaining maintenance days and the like of the vehicle, and uploading the driving data to a cloud platform through a mobile network;
step 2, CRM data are uploaded to a cloud platform through a network; the CRM data refers to vehicle repair record information in the dealer customer relationship system, including the time of entry to the store, and the like.
Step 3, traversing all vehicle information of the 4S shop, and judging whether the vehicle is maintained:
traversing all vehicle information of a 4S shop regularly every day, inquiring the remaining maintenance mileage uploaded by the vehicle, comparing the remaining maintenance mileage of the vehicle stored last time with the remaining maintenance mileage of the time according to judgment, and if the remaining maintenance mileage of the time is larger than the remaining maintenance mileage of the vehicle stored last time, maintaining the vehicle; and if the remaining maintenance mileage of the current time is less than the remaining maintenance mileage of the vehicle stored last time, no maintenance is performed.
And 4, finally judging whether the vehicle is maintained in the shop:
if no maintenance occurs, storing the remaining maintenance mileage of the vehicle during the statistics to a database for comparison at the next time; if the vehicle is maintained, inquiring whether the vehicle has maintenance information in the recent period of the store, such as 2 days or 3 days:
if the maintenance information exists, the vehicle is maintained in the store, and the current maintenance mileage of the vehicle is recorded for the next calculation; if there is no maintenance information, the cart is marked for maintenance in its store.
Example 2
As a supplement to embodiment 1, in order to accurately record the loss status of each maintenance of the vehicle, the most accurate customer loss information is fed back to the loss management staff, and the customer loss status is analyzed and managed in time: and automatically traversing, analyzing and summarizing the maintenance history conditions of all vehicles, and providing a list summary of maintenance lost vehicles for the 4S shop.
Example 3
The invention also provides a customer vehicle maintenance loss identification and analysis system based on the Internet of vehicles, which specifically comprises the following steps:
the Internet of things vehicle-mounted equipment is used for acquiring driving data of a vehicle and uploading the driving data to the cloud platform through a mobile network;
the channel synchronization system uploads the CRM data to the cloud platform through a network;
the vehicle maintenance judging module is used for judging whether the vehicle is maintained;
and the maintenance module is used for judging whether the vehicle is maintained in the shop.
And the database is used for storing the remaining maintenance mileage of the vehicle during each counting.
And the maintenance loss system automatically traverses, analyzes and summarizes the maintenance history conditions of all vehicles and provides a list of maintenance loss vehicles for 4S stores.
The system further comprises a cloud storage module, wherein the cloud storage module is used for storing the analyzed driving data and the CRM data.
According to the invention, the method of vehicle networking big data analysis and CRM data verification is adopted, so that the maintenance time of the vehicle can be accurately judged, and whether the maintenance is in a local store or not and whether the loss of vehicle maintenance is caused or not can be automatically judged.
The above description is only for the preferred embodiment of the present invention, but the scope of the present invention is not limited thereto, and any person skilled in the art should be able to cover the technical solutions and the inventive concepts of the present invention within the technical scope of the present invention.
Claims (3)
1. Customer vehicle maintenance loss identification and analysis method based on Internet of vehicles is characterized by comprising the following steps:
step 1, collecting driving data of a vehicle, and uploading the driving data to a cloud platform through a mobile network;
step 2, CRM data are uploaded to a cloud platform through a network;
step 3, traversing all vehicle information of the 4S shop, and judging whether the vehicle is maintained;
step 4, finally judging whether the vehicle is maintained in the shop;
the driving data in the step 1 comprises information of the remaining maintenance mileage, the remaining maintenance days and the like of the vehicle;
step 3, the concrete steps of judging whether the vehicle is maintained are as follows: traversing all vehicle information of a 4S shop regularly every day, inquiring the remaining maintenance mileage uploaded by the vehicle, comparing the remaining maintenance mileage of the vehicle stored last time with the remaining maintenance mileage of the time according to judgment, and if the remaining maintenance mileage of the time is larger than the remaining maintenance mileage of the vehicle stored last time, maintaining the vehicle; if the remaining maintenance mileage of the current time is less than the remaining maintenance mileage of the vehicle stored last time, no maintenance is performed;
step 4, judging whether the vehicle is maintained in the shop specifically comprises the following steps:
if no maintenance occurs, storing the remaining maintenance mileage of the vehicle during the statistics to a database for comparison at the next time;
if the vehicle is maintained, inquiring whether the vehicle has maintenance information in the near term of the store;
the method is implemented in a customer vehicle maintenance loss identification and analysis system, which comprises:
the Internet of things vehicle-mounted equipment is used for acquiring driving data of a vehicle and uploading the driving data to the cloud platform through a mobile network;
the channel synchronization system uploads the CRM data to the cloud platform through a network;
the vehicle maintenance judging module is used for judging whether the vehicle is maintained;
the vehicle maintenance judging module is used for judging whether the vehicle is maintained in the shop;
the database is used for storing the remaining maintenance mileage of the vehicle during each counting; the maintenance and loss system automatically traverses, analyzes and summarizes the maintenance history conditions of all vehicles and provides a list summary of maintenance and loss vehicles for 4S stores; and the cloud storage module is used for storing the analyzed driving data and the CRM data.
2. The customer vehicle maintenance loss identification and analysis method based on the internet of vehicles as claimed in claim 1, wherein if there is maintenance information, it indicates that the vehicle is maintained in the store, and records the current maintenance mileage of the vehicle for the next calculation; if there is no maintenance information, the cart is marked for maintenance in its store.
3. The internet-of-vehicles based customer vehicle maintenance churn recognition analysis method of claim 1, wherein maintenance history status of all vehicles is automatically traversed, analyzed and summarized, and a 4S shop is provided with a list summary of maintenance churn vehicles.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201610365702.9A CN106021547B (en) | 2016-05-27 | 2016-05-27 | Customer vehicle maintenance loss identification and analysis method and system based on Internet of vehicles |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201610365702.9A CN106021547B (en) | 2016-05-27 | 2016-05-27 | Customer vehicle maintenance loss identification and analysis method and system based on Internet of vehicles |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN106021547A CN106021547A (en) | 2016-10-12 |
| CN106021547B true CN106021547B (en) | 2020-03-24 |
Family
ID=57091082
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201610365702.9A Active CN106021547B (en) | 2016-05-27 | 2016-05-27 | Customer vehicle maintenance loss identification and analysis method and system based on Internet of vehicles |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN106021547B (en) |
Families Citing this family (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN107992879B (en) * | 2017-11-07 | 2021-11-02 | 上海炬宏信息技术有限公司 | Method for automatically judging potential loss risk of vehicle maintenance user |
| CN108090519A (en) * | 2018-01-08 | 2018-05-29 | 雅马哈发动机（厦门）信息***有限公司 | A kind of customer's group technology and system based on after-sales service data |
| CN109740891B (en) * | 2018-12-24 | 2021-08-03 | 斑马网络技术有限公司 | User state detection method, device and system |
Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101419684A (en) * | 2008-12-11 | 2009-04-29 | 徐立 | Interactive customer relationship management system in automobile industry |
| CN101776523A (en) * | 2009-12-17 | 2010-07-14 | 南京航空航天大学 | Automatic guided vehicle maintenance and repair prompt guiding device |
| CN105139476A (en) * | 2015-08-05 | 2015-12-09 | 武汉理工大学 | Mining area vehicle maintenance information prompting method |
Family Cites Families (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20130332396A1 (en) * | 2012-06-12 | 2013-12-12 | Microsoft Corporation | Manipulation of multi-dimensional pricing structures |
-
2016
- 2016-05-27 CN CN201610365702.9A patent/CN106021547B/en active Active
Patent Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101419684A (en) * | 2008-12-11 | 2009-04-29 | 徐立 | Interactive customer relationship management system in automobile industry |
| CN101776523A (en) * | 2009-12-17 | 2010-07-14 | 南京航空航天大学 | Automatic guided vehicle maintenance and repair prompt guiding device |
| CN105139476A (en) * | 2015-08-05 | 2015-12-09 | 武汉理工大学 | Mining area vehicle maintenance information prompting method |
Non-Patent Citations (3)
| Title |
|---|
| 基于CRM***的4S店信息挖掘;饶旭;《经济研究导刊》;20121231(第32期);第193-194页 * |
| 基于SOA的协同售后服务平台架构设计;孙丽萍;《中国优秀硕士学位论文全文数据库信息科技辑》;20140815(第08期);I139-78 * |
| 基于客户行为的4S店客户细分及其变化挖掘;郭崇慧等;《管理工程学报》;20151231;第29卷(第4期);第18-25页 * |
Also Published As
| Publication number | Publication date |
|---|---|
| CN106021547A (en) | 2016-10-12 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| US9365217B2 (en) | Mobile pothole detection system and method | |
| CN110390262A (en) | Video analysis method, apparatus, server and storage medium | |
| US20160078695A1 (en) | Method and system for managing a fleet of remote assets and/or ascertaining a repair for an asset | |
| US20070268158A1 (en) | System and Method for Reducing Driving Risk With Insight | |
| CN108335377B (en) | GIS technology-based automatic check method for road inspection vehicle service | |
| CN106021547B (en) | Customer vehicle maintenance loss identification and analysis method and system based on Internet of vehicles | |
| CN106650157B (en) | Method, device and system for estimating fault occurrence probability of vehicle parts | |
| CN112884325A (en) | Method and system for application analysis and health condition evaluation of customer station equipment | |
| CN113538072A (en) | Intelligent travel chain identification method and device for freight vehicle and electronic equipment | |
| CN109493449B (en) | Freight train cargo state estimation method based on freight train GPS track data and high-speed transaction data | |
| CN112862233A (en) | Fault relevance analysis system and method based on Internet of vehicles data | |
| CN107992879B (en) | Method for automatically judging potential loss risk of vehicle maintenance user | |
| CN114841712B (en) | Method and device for determining illegal operation state of network appointment vehicle tour and electronic equipment | |
| CN102622883B (en) | Method and device for judging release of traffic incident | |
| CN109409563B (en) | Method, system and storage medium for analyzing real-time number of people in public transport operation vehicle | |
| CN116485266B (en) | Internet of things-based intelligent management method and system for oiling oil | |
| CN111582527A (en) | Travel time estimation method and device, electronic equipment and storage medium | |
| CN113537752A (en) | Traffic transportation big data scheduling method and scheduling platform based on multiple data sources | |
| CN108665723B (en) | Information acquisition method and device | |
| CN108182558A (en) | A kind of haul distance computational methods and device based on statistical nature | |
| WO2012082700A1 (en) | Automated automobile management system | |
| CN116862591A (en) | Information pushing method, device, computer equipment and readable storage medium | |
| CN109633716B (en) | GPS-based urban distribution vehicle travel chain and characteristic identification method and equipment thereof | |
| Moosavi et al. | Simulation-based sensitivity analysis for evaluating factors affecting bus service reliability: a big and smart data implementation | |
| CN110686700B (en) | Railway wagon running mileage statistical method and system |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| C06 | Publication | ||
| PB01 | Publication | ||
| C10 | Entry into substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |