Dealer or data? Which one matters?,iCARCOMM

Dealer or data? Which one matters?

Among the many policies proposed by the government for the auto parts market, the opening of auto maintenance data has become a sign of the breakthrough development of the industry. After the maintenance data is made public, the fusion of more dimensions of big data can make the entire aftermarket market form a whole, thereby breaking the information asymmetry barriers caused by industry monopoly.

On the basis of big data, merchants in all aspects of the entire industrial chain, such as repairs and maintenance, can focus more on their own industries, and the relevant data needed can only be connected with merchants that specialize in data, so that the entire industry can Do it lightly, and the era of competition and cooperation in the automotive aftermarket also begins.

From the perspective of the industrial chain, the current Chinese auto after-service market can be basically divided into seven categories: maintenance, repair, modification, used cars, auto parts, related e-commerce and financial insurance. These seven categories can actually be subdivided. For example, maintenance includes services such as car wash, beauty, oil and parts replacement.

The seven categories of auto services can be divided into three types: auto services, car networking related, and tool communities. Currently, many businesses in the auto service category are changing from heavy to light, starting from the low-level industry chain to the middle level. To be a "service car service provider" service provider. Whether it is a platform or a vertical service, this type of business is transitioning to "big data" in terms of informatization.

Because merchants found that the competition in the automotive aftermarket service is not about the number of maintenance personnel, but more about the adaptation of data such as original parts, brand accessories, working hours, maintenance information, etc., for example, such as oil filter ( Machine filter for short) needs to be matched with the customer's car model, but the original machine filter is very expensive. The general o2o company uses the Man brand. Which of the Man brand filter is suitable for this customer's model? This requires a database for matching support. In terms of data acquisition, businesses with data accumulation can obtain information through more channels, while those without accumulation will cooperate with professional database companies. The entire industry chain has a heavy demand for big data services.

What big data can bring to the industry lies in the management of customers and business by merchants. These data are specific to the automotive aftermarket, which is the comprehensive management of automotive aftermarket service merchants in communicating with users and business marketing. Especially in terms of flexible retrieval and application of data such as models, accessories, brands, and maintenance, businesses can get close to car owners. You can know the car owner's car information without even asking, which can further provide car owners with a one-stop car service solution.

So, what data does the automotive aftermarket need? A qualified data service provider should do the following:

Data information of all brands, all models and all accessories. There must be a VIN-based wildcard structure for all models and all accessories. The accessories database includes: VIN code identification library, model configuration library, maintenance rule library, and a wildcard database of original parts and brand numbers.

Database association structure synchronized with foreign countries. Synchronizing the information of foreign parts suppliers in real time can ensure that the parts and components of the latest models are filled in the database.

Internet-based API data service. It is guaranteed that every merchant that cooperates with it can connect to and retrieve the required database information through the API interface.

At least 5 years of experience in database creation. The demand for data in the entire automotive aftermarket is increasing, and a larger amount of data is also being generated. Data processing experience and database production experience are particularly important.

The cliché of data maintenance. From the whole brand to the whole car model, massive data mining and matching, it is impossible without a strong enough operation team.

In the DT era, each set of data uploaded by the vehicle has location information and time, and it is easy to form massive data. On the big data platform, based on the processing, analysis, and aggregation of massive information such as vehicle data, road data, and environmental perception data, auto service providers or vehicle manufacturers can obtain relevant vehicle owners' driving conditions, driving behavior, mileage, etc. The data in the process can be used for refined management of car owners based on big data mining.

The above is about the impact of big data on the automotive aftermarket industry in a broad sense. It is reflected in the after-car service. Big data can indeed solve many problems.

Specifically, some of the value of the big data model to the industry can be expressed as the following:

First, to promote the efficiency of industrial chain accessories transactions. At present, the accuracy of B2B spare parts transaction inquiries by telephone is less than 50%. The major databases mentioned above are the basis for ensuring the accuracy of transaction information. Online transactions can provide more detailed spare parts information for merchants and car owners, and repeat the exchange of goods. frequency decreased.

Secondly, a variety of choices bring price advantages to merchants. The database not only provides original parts information for merchants, but also provides replaceable parts of other brands, car owners can choose suitable parts according to the situation, and this is also a sales channel for brand merchants.

Furthermore, it has changed the traditional way of consultation. The traditional one-to-one telephone inquiry method in the auto parts industry has been upgraded to a one-to-many digital inquiry method, which greatly improves the communication efficiency between merchants and car owners, merchants and accessories suppliers.

At the same time, it provides the feasibility of tracing the source of trading accessories. The database has clear records of parts manufacturers, parts distributors, parts chain distributors, car maintenance providers, parts B2B e-commerce platforms and O2O service platforms, and can be reversely queried, so that parts and services can be found in the reverse direction if there is a problem. The source of the transaction solves the problem of transparency and fairness of the automotive aftermarket service, and no need for third-party supervision.

In addition, it is in line with the "homogeneous accessories" strategy advocated by the state. At present, the China Automobile Maintenance Industry Association is vigorously promoting the "homogeneous parts" action to promote the healthy development of the automobile maintenance industry. Homogeneous parts are also "equivalent quality parts", and when it comes to auto parts, it is a substitute for spare parts that can replace the original parts. The price is lower and the cost performance is higher. This policy can enhance the enthusiasm of the national manufacturing industry, and can reduce the maintenance cost of consumers.

In terms of industry influence, in addition to the above points, in the "Internet traditional" industry, the integration of big data into the CRM system of traditional enterprises and forcing traditional enterprises to upgrade and transform is an important way for "Internet" to be implemented.

All in all, big data will provide a more favorable foundation for the progress of the entire automotive aftermarket industry. At the same time, autonomous driving, Internet of Vehicles, smart transportation and Industry 4.0 will also benefit from it.

在政府提出的众多针对汽车汽配市场的政策中，汽车维修数据的开放成为该行业突破性发展的标志。维修数据公开以后，所融合形成的更多维度的大数据能够让整个车后市场形成一个整体，从而打破行业垄断所造成信息不对称壁垒。

　　在大数据基础上，整条产业链上的维修、保养等各环节商家都能更专注与自己所在的行业，所需要的相关数据只要与专门做数据的商家对接即可，这样整个行业就都做轻了，汽车后市场的竞合时代也就由此开始。

　　从产业链来看，当前中国汽车后服务市场基本可分七个大类：包括养护、维修、改装、二手车、汽车配件、相关电商及金融保险等。这七个大类其实可以再做细分，譬如养护就包括洗车、美容、机油及零件更换等服务。

　　七大类汽车服务可以分为汽车服务、车联网相关、及工具社区等三种类型，当前而言，汽车服务类的众多商家正在由重向轻变化，开始由产业链低层向中间层过度，做“服务汽车服务商”的服务商。这一类商家无论是做平台的还是做垂直服务的，在信息化方面都在向“大数据”过渡。

　　因为商家们发现汽车后市场服务中的竞争不在于维修人员的多少，更需要的是对原厂配件、品牌配件、工时、维修信息等数据的适配，举个例子，比如机油滤清器(简称机滤)需要与上门的客户车型匹配，可原厂机滤很贵，一般的o2o公司都使用曼牌的，那曼牌的哪款机滤适合这个客户的车型呢?这就需要用数据库来做匹配支持。在数据获取上，有数据积累的商家可以通过更多的渠道获得信息，没有积累的则会与专业的数据库企业进行合作。整个产业链对大数据服务都有重度需求。

　　大数据能带给行业更多的在于商家对于客户以及业务的管理，这些数据具体到汽车后市场，则是对汽车后市场服务商家在沟通用户以及商业营销的综合性管理。尤其是车型、配件、品牌、保养等数据的灵活调取与应用方面，可以让商家近距离接触车主。甚至不用询问就能了解车主用车信息，可以进一步为车主提供一站式汽车服务方案。

　　那么，汽车后市场需要哪些数据呢?一个合格的数据服务提供商，应该做到以下几点：

　　全品牌全车型全配件的数据信息。要有基于VIN的全车型全配件的通配架构，配件数据库包括：VIN码识别库、车型配置库、保养规则库、配件原厂件号品牌件号通配数据库等。

　　与国外同步的数据库关联结构。即时同步国外零部件供应商的信息，能够保证最新车型的零部件填充数据库。

　　互联网化的API数据服务。保证每一个与其合作的商家，都能通过API接口对接到并调取所需的数据库信息。

　　至少5年以上的数据库制作经验。整个汽车后市场对数据的需求越来越大，同时也正在产生更大量的数据，数据处理经验以及数据库制作经验尤为重要。

　　老生常谈的数据维护。从全品牌到全车款，海量的数据挖掘与匹配，没有一个足够强大的运营团队是不行的。

　　DT时代，车辆上传的每一组数据都带有位置信息和时间，并且容易形成海量数据。在大数据平台上，基于对车辆数据、道路数据、环境感知数据等海量信息的处理、分析、汇总，汽车服务商或整车厂商可获得相关车主的车况、驾驶行为、里程等行车、用车过程中的数据，从而可基于大数据挖掘对车主进行精细化的管理。

　　以上所讲的是广义上大数据对汽车后市场行业的影响，体现在到车后服务方面，大数据确实能够解决很多问题。

　　具体而言，大数据模式对于该行业的一些价值可以表现为以下几点：

　　首先，促进产业链配件交易的效率。目前，B2B配件交易通过电话询问的发单准确度不足50%，前文所述几大数据库是保证交易信息的准确性的基础，网络交易可以为商家及车主提供更详尽的配件信息，重复换货频次降低。

　　其次，多种选择为商家带来价格优势。数据库不只是为商家提供原厂配件信息，同时也提供其他品牌的可替换配件，车主可以根据情况选择合适的配件，同时这也是品牌商家的一个销售渠道。

　　再者，改变了传统的咨询方式。将传统汽配行业1对1电话询件询价方式，提升为1对多的数字化询价方式，极大的提高了商家与车主、商家与配件商的沟通效率。

　　同时，提供了交易配件的追溯源头可行性。数据库对配件厂商、配件分销商、配件连锁分销商、汽车保养商、配件 B2B电商平台及O2O服务平台都有清楚的记录，并能够逆向查询，这样配件以及服务出现问题之后，便可以逆向找到交易源头，解决了汽车后市场服务的透明化与公正性的问题，无需再用第三方监督。

　　还有，符合国家提倡的“同质配件”战略。当前，中国汽车维修行业协会正在大力推广“同质配件”行动，以推进汽车维修行业健康发展。同质配件也就是“质量相当配件”，具体到汽车零配件上也就是可以替换原厂配件的零配件替代品，价格更低同时性价比更高。这个政策可以增强民族制造业积极性，并能够降低消费者维护成本。

　　在行业影响方面，除了以上几点，在“互联网传统”行业方面，大数据融入传统企业的CRM系统并倒逼传统企业升级转型，是“互联网 ”落到实处的一个重要的途径。

　　总而言之，大数据将会为整个汽车后市场行业的进步提供更有利的基础。同时，无人驾驶、车联网、智慧交通及工业4.0等也将受益其中。