WO2022246923A1 - 一种潜在客户筛选方法 - Google Patents

一种潜在客户筛选方法 Download PDF

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WO2022246923A1
WO2022246923A1 PCT/CN2021/099668 CN2021099668W WO2022246923A1 WO 2022246923 A1 WO2022246923 A1 WO 2022246923A1 CN 2021099668 W CN2021099668 W CN 2021099668W WO 2022246923 A1 WO2022246923 A1 WO 2022246923A1
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screening
customer
website
potential
potential customers
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PCT/CN2021/099668
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English (en)
French (fr)
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曼吉特
严诚
高登
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中山世达模型制造有限公司
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Publication of WO2022246923A1 publication Critical patent/WO2022246923A1/zh

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    • 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
    • G06F16/95—Retrieval from the web
    • G06F16/951—Indexing; Web crawling techniques
    • 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
    • G06F16/95—Retrieval from the web
    • G06F16/953—Querying, e.g. by the use of web search engines
    • G06F16/9536—Search customisation based on social or collaborative filtering
    • 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
    • G06F16/95—Retrieval from the web
    • G06F16/957—Browsing optimisation, e.g. caching or content distillation
    • 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
    • G06F16/95—Retrieval from the web
    • G06F16/958—Organisation or management of web site content, e.g. publishing, maintaining pages or automatic linking

Definitions

  • the invention relates to a method for screening potential customers.
  • Finding new customers is one of the most important factors in business development. But looking for new customers is a very difficult process. At this stage, most of the customers are found through phone calls, emails, door-to-door promotions, etc., so it requires a lot of time and money investment, and it still cannot guarantee the smooth development of new customers .
  • the present invention overcomes the shortcomings of the above technologies and provides a method for screening potential customers.
  • the present invention adopts the following technical solutions:
  • a method for screening potential customers the steps are as follows:
  • Screening model 1 identifies and captures key data of potential customers' websites, and screening model 2 analyzes whether potential customers can be converted into real customers based on key data of potential customers' websites.
  • a method for screening potential customers as described above is characterized in that: it also includes S1.1, the screening model in the website screening system—identifying and capturing key historical customer data in a third-party system.
  • the method for screening potential customers as described above is characterized in that: in S3, the URLs of potential customers are screened by uploading a list of URLs of potential customers, or the URLs of potential customers are screened by searching for URLs of potential customers on the Internet.
  • a method for screening potential customers as described above is characterized in that: S4.1, the website screening system analyzes and marks the possibility score of converting potential customers into real customers according to the analysis of the second screening model.
  • the method for screening potential customers as described above is characterized in that it further includes S5, displaying the analysis result by the user account and/or sending the analysis result to the mailbox set by the user.
  • a kind of potential client screening method as above it is characterized in that: also include S0, create user account in website screening system;
  • a potential customer screening method as described above is characterized in that: the first screening model is a natural language processing model, and the natural language processing model recognizes and captures key words.
  • a potential customer screening method as described above is characterized in that: the key data of the historical customer website in S1 includes the information of the management personnel of the enterprise, the main industry of the enterprise, the scale of the enterprise, the structure of the enterprise, and the information of the honor of the enterprise.
  • a method for screening potential customers as described above is characterized in that: the key historical customer data is financial data, including enterprise registered assets, enterprise equity structure, enterprise annual sales, and enterprise tax payment.
  • a potential customer screening method as described above is characterized in that: marking a heat value from 0% to 100% as the conversion possibility score of the potential customer.
  • the screening model in the website screening system of the present invention intelligently recognizes and captures key data of historical customer websites of historical customers, such as enterprise management personnel information, enterprise main industry, enterprise scale, enterprise structure, enterprise honor information, etc., and establishes the key Database and create screening model 2; Screening model 1 identifies and captures key data of potential customers' websites and analyzes through screening model 2 to obtain the possibility score of potential customers converting to real customers, helping users identify the most likely to convert into real customers potential customers, and provide the possibility ranking of potential customers, the goal of this algorithm is to greatly speed up the customer acquisition process.
  • the present invention can also cooperate with a third party that stores the financial information of the enterprise, so that the website screening system can be connected with the third-party system, and the screening model can identify and capture key data of historical customers in the third-party system, such as enterprise registered assets, enterprise equity Financial information such as structure, enterprise annual sales, enterprise tax payment, etc., key data of historical customer websites and key data of historical customers jointly form a key database, and create a screening model 2 based on the sub-key database to more accurately screen potential customers and speed up the process of customer expansion And help users use resources more efficiently to ensure the acquisition of new business opportunities.
  • key data of historical customers in the third-party system such as enterprise registered assets, enterprise equity Financial information such as structure, enterprise annual sales, enterprise tax payment, etc.
  • key data of historical customer websites and key data of historical customers jointly form a key database, and create a screening model 2 based on the sub-key database to more accurately screen potential customers and speed up the process of customer expansion And help users use resources more efficiently to ensure the acquisition of new business opportunities.
  • the present invention screens potential customers, it can obtain and screen potential customer websites by uploading the potential customer website list, or obtain and screen potential customer websites by automatically searching for potential customer websites in the Internet, so as to realize multiple ways to obtain and transmit potential customer website, which can be obtained according to Users actually need to obtain potential customer URLs.
  • the screening model 2 of the present invention analyzes the conversion possibility score of the potential customer according to the key data of the potential customer website, and marks a heat value from 0% to 100% as the conversion possibility score of the potential customer, and passes Use classification names similar to water temperature, such as boiling, boiling hot, warm, ice cold, ice cold, and extremely cold to mark analyzed potential customers, so that users can quickly and intuitively distinguish the possibility of converting each potential customer into a real customer.
  • the screening model 2 of the present invention analyzes potential customer conversion possibility scores according to the key data of potential customer websites, and the user can directly display and inquire in the website screening system, and at the same time send the analysis results to the mailbox set by the user. It is convenient for users to query the analysis results anytime and anywhere.
  • the user can create a user account in the website screening system, and can create multiple screening algorithm libraries according to different screening key data through the user account.
  • a certain algorithm may be based on a certain product line of the user, or different services, The top 20 customers, high-value customers, high-profit customers, etc. are uploaded as independent data sets, resulting in completely different screening results.
  • the potential customer screening method of the present invention can also be made into a browser-based plug-in, which allows the user to quickly use its specific algorithm to scan a certain website, and gives an analysis result, which will be saved in the user's account In the process, the accurate and rapid evaluation of potential customers is realized; at the same time, the analysis results are displayed in a graphical and audible presentation, such as a happy sniffing puppy wagging its head and tail representing "yes" and a dejected puppy with its tail between its legs stands for "No", and even some text to describe the result.
  • Fig. 1 is a flowchart of Embodiment 1 of the present invention.
  • Fig. 2 is the flow chart of the second embodiment of the present invention.
  • Fig. 3 is a flowchart of Embodiment 3 of the present invention.
  • Fig. 4 is a flowchart of Embodiment 4 of the present invention.
  • Embodiment 1 As shown in Figure 1, a potential customer screening method is implemented by screening the key data of historical customer URLs and uploading the list of potential customer URLs. The steps are as follows:
  • S0 Create a user account in the website screening system; set a confidentiality agreement to protect the data uploaded by the user and prevent data leakage.
  • the user can create different screening algorithm libraries according to different screening key data;
  • the screening model in the website screening system will intelligently identify and capture the key data of historical customer URLs according to the list of historical customer URLs; among them, historical customer URLs
  • the key data is the key data that is most closely related to the ideal customer group.
  • the key data of the historical customer website includes the information of the company's management personnel, the company's main industry, the company's scale, the company's structure, the company's honor information, and other customer website public information;
  • the website screening system intelligently recognizes and captures the key data of historical customer websites according to the screening model 1 to establish a key database, and creates and trains the screening model 2 according to the key database. After completion, it displays a visual success confirmation message and the user sets the mailbox to receive a A reminder email with a notification link, through which users can view relevant analysis results;
  • the user organizes the potential customer website list by himself, and after uploading, the website screening system screens the potential customer website according to the acquisition;
  • Screening model 1 in the website screening system intelligently identifies and captures key data of potential customer websites according to potential customer websites, and screening model 2 analyzes whether potential customers can be converted into real customers according to the key data of potential customer website;
  • the website screening system marks the possibility score of converting potential customers into real customers, and marks a heat value from 0% to 100% as the conversion possibility score of potential customers , and by using classification names similar to water temperature, such as boiling, boiling hot, warm, ice cold, ice cold, and extremely cold to mark the analyzed potential customers, users can quickly and intuitively distinguish the possibility of each potential customer being converted into a real customer;
  • the website screening system displays the analysis results of real customer conversion possibility scores through the user account, and sends the analysis results to the mailbox set by the user, which is convenient for users to query the analysis results anytime and anywhere. Users can more accurately screen potential customers and accelerate expansion. Customer processes and help users use resources more efficiently to ensure the acquisition of new business opportunities.
  • Embodiment 2 As shown in Figure 2, a potential customer screening method is implemented by screening key data of historical customer website addresses and historical customer key data in a third-party system, and uploading a list of potential customer website addresses. The steps are as follows:
  • S0 Create a user account in the website screening system; set a confidentiality agreement to protect the data uploaded by the user and prevent data leakage.
  • the user can create different screening algorithm libraries according to different screening key data;
  • the screening model in the website screening system will intelligently identify and capture the key data of historical customer URLs according to the list of historical customer URLs; among them, historical customer URLs
  • the key data is the key data that is most closely related to the ideal customer group.
  • the key data of the historical customer website includes the information of the company's management personnel, the company's main industry, the company's scale, the company's structure, the company's honor information, and other customer website public information;
  • the website screening system can also cooperate with a third-party system that collects and stores corporate financial information data, so that the website screening system can be connected with the third-party system.
  • the screening model in the website screening system is based on the list of historical customer URLs in the third party
  • the system identifies and captures key historical customer data, which includes financial information such as corporate registered assets, corporate equity structure, corporate annual sales, and corporate tax payments;
  • the website screening system intelligently recognizes and captures the key data of historical customer websites and key data of historical customers according to the screening model 1 to establish a key database, and creates and trains the screening model 2 according to the key database.
  • the key data of historical customer websites and key data of historical customers are combined
  • the creation of screening model 2 can further improve the accuracy of potential customer screening.
  • a visual success confirmation message will be displayed and the user will receive a reminder email with a notification link in the mailbox set by the user. Users can view relevant analysis results through the link;
  • the user organizes the potential customer website list by himself, and after uploading, the website screening system screens the potential customer website according to the acquisition;
  • Screening model 1 in the website screening system intelligently identifies and captures key data of potential customer websites according to potential customer websites, and screening model 2 analyzes whether potential customers can be converted into real customers according to the key data of potential customer website;
  • the website screening system marks the possibility score of converting potential customers into real customers according to the analysis of the second screening model, and also marks a heat value from 0% to 100% as the conversion possibility score of potential customers, And by using classification names similar to water temperature, such as boiling, scalding, warm, ice cold, ice cold, and extremely cold to mark the analyzed potential customers, users can quickly and intuitively distinguish the possibility of converting each potential customer into a real customer;
  • the website screening system displays the analysis results of real customer conversion possibility scores through the user account, and sends the analysis results to the mailbox set by the user, which is convenient for users to query the analysis results anytime and anywhere. Users can more accurately screen potential customers and accelerate expansion. Customer processes and help users use resources more efficiently to ensure the acquisition of new business opportunities.
  • Embodiment three as shown in Figure 3, a kind of potential customer screening method, realizes screening by screening key data of historical customer website and automatically looking for potential customer website, its steps are as follows:
  • S0 Create a user account in the website screening system; set a confidentiality agreement to protect the data uploaded by the user and prevent data leakage.
  • the user can create different screening algorithm libraries according to different screening key data;
  • the screening model in the website screening system will intelligently identify and capture the key data of historical customer URLs according to the list of historical customer URLs; among them, historical customer URLs
  • the key data is the key data that is most closely related to the ideal customer group.
  • the key data of the historical customer website includes the information of the company's management personnel, the company's main industry, the company's scale, the company's structure, the company's honor information, and other customer website public information;
  • the website screening system intelligently recognizes and captures the key data of historical customer websites according to the screening model 1 to establish a key database, and creates and trains the screening model 2 according to the key database. After completion, it displays a visual success confirmation message and the user sets the mailbox to receive a A reminder email with a notification link, through which users can view relevant analysis results;
  • Screening model 1 in the website screening system intelligently identifies and captures key data of potential customer websites according to potential customer websites, and screening model 2 analyzes whether potential customers can be converted into real customers according to the key data of potential customer website;
  • the website screening system marks the possibility score of converting potential customers into real customers, and marks a heat value from 0% to 100% as the conversion possibility score of potential customers , and by using classification names similar to water temperature, such as boiling, boiling hot, warm, ice cold, ice cold, and extremely cold to mark the analyzed potential customers, users can quickly and intuitively distinguish the possibility of each potential customer being converted into a real customer;
  • the website screening system displays the analysis results of real customer conversion possibility scores through the user account, and sends the analysis results to the mailbox set by the user, which is convenient for users to query the analysis results anytime and anywhere. Users can more accurately screen potential customers and accelerate expansion. Customer processes and help users use resources more efficiently to ensure the acquisition of new business opportunities.
  • Embodiment 4 As shown in Figure 4, a potential customer screening method, by screening the key data of historical customer website and the key data of historical customer in the third-party system, and automatically looking for potential customer website to realize screening, its steps are as follows:
  • S0 Create a user account in the website screening system; set a confidentiality agreement to protect the data uploaded by the user and prevent data leakage.
  • the user can create different screening algorithm libraries according to different screening key data;
  • the screening model in the website screening system will intelligently identify and capture the key data of historical customer URLs according to the list of historical customer URLs; among them, historical customer URLs
  • the key data is the key data that is most closely related to the ideal customer group.
  • the key data of the historical customer website includes the information of the company's management personnel, the company's main industry, the company's scale, the company's structure, the company's honor information, and other customer website public information;
  • the website screening system can also cooperate with a third-party system that collects and stores corporate financial information data, so that the website screening system can be connected with the third-party system.
  • the screening model in the website screening system is based on the list of historical customer URLs in the third party
  • the system identifies and captures key historical customer data, which includes financial information such as corporate registered assets, corporate equity structure, corporate annual sales, and corporate tax payments;
  • the website screening system intelligently identifies and captures the key data of historical customer websites and key data of historical customers according to the screening model 1 to establish a key database, and creates and trains the screening model 2 according to the key database.
  • the key data of historical customer websites and key data of historical customers are combined
  • the creation of screening model 2 can further improve the accuracy of potential customer screening.
  • a visual success confirmation message will be displayed and the user will receive a reminder email with a notification link in the mailbox set by the user. Users can view relevant analysis results through the link;
  • Screening model 1 in the website screening system intelligently identifies and captures key data of potential customer websites according to potential customer websites, and screening model 2 analyzes whether potential customers can be converted into real customers according to the key data of potential customer website;
  • the S website screening system marks the possibility score of converting potential customers into real customers, and also marks a heat value from 0% to 100% as the conversion possibility score of potential customers, and passes Use classification names similar to water temperature, such as boiling, boiling hot, warm, ice cold, ice cold, and extremely cold to mark analyzed potential customers, so that users can quickly and intuitively distinguish the possibility of each potential customer being converted into a real customer;
  • the website screening system displays the analysis results of real customer conversion possibility scores through the user account, and sends the analysis results to the mailbox set by the user, which is convenient for users to query the analysis results anytime and anywhere. Users can more accurately screen potential customers and accelerate expansion. Customer processes and help users use resources more efficiently to ensure the acquisition of new business opportunities.
  • the screening model one is a natural language processing model, and the natural language processing model recognizes and captures key words.
  • the natural language processing model deletes the punctuation marks in the URL, and restores the stemming and lemmatization in the URL, and converts the word into its original form of vocabulary;
  • the natural language processing model is a bag of words model, and the principle of the model is is to create a vocabulary containing different sets of words, each associated with the number of occurrences, and subsequently use this vocabulary to create d-dimensional feature vectors.
  • the second screening model is a multinomial naive Bayesian model, and the multinomial naive Bayesian model is
  • A is the vocabulary in the key database of the customer website
  • B is the intelligent recognition and capture of the key vocabulary of the non-customer website
  • P(A) is the prior probability of A
  • P(B) is the prior probability of B
  • P(B) is the prior probability of B
  • A occurs.
  • conditional probability When the event B that has a certain relationship with A has occurred, the probability of event A occurring is called the conditional probability, and the conditional probability for
  • the accuracy rate of the modeled multinomial naive Bayesian model in the training data set is 94%; the accuracy rate of the multinomial naive Bayesian model in the test data set is 84.3%; it can accurately screen potential customers and speed up the customer acquisition process And help users use resources more efficiently to ensure the acquisition of new business opportunities.

Abstract

一种潜在客户筛选方法，其步骤如下，向网站筛选系统上传历史客户网址清单，网站筛选系统中的筛选模型一识别并抓取历史客户网址关键数据；建立关键数据库，根据关键数据库创建筛选模型二；获取筛选潜在客户网址；筛选模型一识别并抓取潜在客户网址关键数据，筛选模型二根据潜在客户网址关键数据分析潜在客户是否可转化为真实客户，帮助用户识别最有可能转化为真实客户的潜在客户，并提供潜在客户的可能性排名，该方法的目标是大大加速拓客流程。

Description

一种潜在客户筛选方法 [技术领域]
本发明涉及一种潜在客户筛选方法。
[背景技术]
开发新客户是业务发展最重要的因素之一。但寻找新客户是一个非常困难的过程，现阶段寻找客户大部分通过电话尝试联系、电子邮件联系、上门拜访推广等形式，因此需要大量时间和金钱的投资，而且仍然不能保证新客户的顺利开发。
同时现今社会网络发展迅速，因此大部分企业用户为了方便自身推广以及方便客户咨询，大多设有企业网址，其中企业网址中含有大量的企业自身的信息数据，因而目前我们迫切需要一种利用网址大数据快捷准确筛选出有需要的潜在客户的方法。
[发明内容]
本发明克服了上述技术的不足，提供了一种潜在客户筛选方法。
为实现上述目的，本发明采用了下列技术方案：
一种潜在客户筛选方法，其步骤如下：
S1、向网站筛选系统上传历史客户网址清单，网站筛选系统中的筛选模型一识别并抓取历史客户网址关键数据；
S2、建立关键数据库，根据关键数据库创建筛选模型二；
S3、获取筛选潜在客户网址；
S4、筛选模型一识别并抓取潜在客户网址关键数据，筛选模型二根据 潜在客户网址关键数据分析潜在客户是否可转化为真实客户。
如上所述的一种潜在客户筛选方法，其特征在于：还包括有S1.1、网站筛选系统中的筛选模型一在第三方系统识别并抓取历史客户关键数据。
如上所述的一种潜在客户筛选方法，其特征在于：S3中通过上传潜在客户网址清单获取筛选潜在客户网址，或通过在互联网中寻找潜在客户网址获取筛选潜在客户网址。
如上所述的一种潜在客户筛选方法，其特征在于：还包括有S4.1、网站筛选系统根据筛选模型二分析，标记潜在客户转化为真实客户的可能性分值。
如上所述的一种潜在客户筛选方法，其特征在于：还包括有S5、用户账号显示分析结果和/或将分析结果送到用户设定邮箱中。
如上所述的一种潜在客户筛选方法，其特征在于：还包括有S0、在网站筛选系统创建用户账号；
如上所述的一种潜在客户筛选方法，其特征在于：筛选模型一为自然语言处理模型，自然语言处理模型识别并抓取关键词汇。
如上所述的一种潜在客户筛选方法，其特征在于：S1中的历史客户网址关键数据包括有企业管理人员信息、企业主营行业、企业规模、企业架构、企业荣誉信息。
如上所述的一种潜在客户筛选方法，其特征在于：历史客户关键数据为财务数据，包括有企业注册资产、企业股权结构、企业年销售额、企业缴税额。
如上所述的一种潜在客户筛选方法，其特征在于：通过标记一个从0％ 到100％之间的热度值作为潜在客户的转化可能性分值。
本发明的有益效果是：
1、本发明网站筛选系统中的筛选模型一智能识别并抓取历史客户的历史客户网址关键数据，如企业管理人员信息、企业主营行业、企业规模、企业架构、企业荣誉信息等，建立关键数据库并创建筛选模型二；筛选模型一识别并抓取潜在客户网址的关键数据并通过筛选模型二分析，得出潜在客户转化真是客户的可能性分值，帮助用户识别最有可能转化为真实客户的潜在客户，并提供潜在客户的可能性排名，该算法的目标是大大加速拓客流程。
2、本发明还可与存储有企业财务信息的第三方合作，使网站筛选系统与第三方系统连接，筛选模型一在第三方系统识别并抓取历史客户关键数据，如企业注册资产、企业股权结构、企业年销售额、企业缴税额等财务信息，历史客户网址关键数据与历史客户关键数据共同组建关键数据库，根据次关键数据库创建筛选模型二，更准确地筛选潜在客户，加速拓客流程以及帮助用户更有效地使用资源来确保新的商机的获取。
3、本发明筛选潜在客户时，可通过上传潜在客户网址清单获取筛选潜在客户网址，或通过在互联网中自动寻找潜在客户网址获取筛选潜在客户网址，实现多种方式获取传潜在客户网址，可根据用户实际需求获取潜在客户网址。
4、本发明筛选模型二根据潜在客户网址关键数据分析潜在客户转化可能性分值后，还通过标记一个从0％到100％之间的热度值作为潜在客户的 转化可能性分值，并通过使用类似水温的分类名称，如沸腾、滚烫、温暖、冰凉、冰冷、极冷标记分析后的潜在客户，使用户能快速直观地在区分各潜在客户转化为真实客户的可能性。
5、本发明筛选模型二根据潜在客户网址关键数据分析潜在客户转化可能性分值后，用户可通过在网站筛选系统中直接显示和查询，同时也可将分析结果送到用户设定邮箱中，方便用户随时随地查询分析结果。
6、本发明中用户可在网站筛选系统创建用户账号，可通过用户账号根据不同的筛选关键数据创建多个筛选算法库，比如某个算法可能基于用户的某个产品线，或不同的服务、前20的客户、高价值客户、高利润客户等被上传为独立的数据集，产生完全不同的筛选结果。
7、本发明的潜在客户筛选方法还可制成基于浏览器的插件，插件允许用户快速地使用其特定的算法扫描某个网址，并给出一个分析结果，此结果将被保存在用户的账户中，实现了精准快速的潜在客户的评定；同时分析结果以一个图形化以及有声的呈现结果展示，比如一个开心的摇头摆尾的嗅探小狗代表了“是”以及一个垂头丧气夹着尾巴的小狗代表“否”，甚至一些文字来描述这个结果。
[附图说明]
图1为本发明实施例一流程图；
图2为本发明实施例二流程图；
图3为本发明实施例三流程图；
图4为本发明实施例四流程图。
[具体实施方式]
下面结合附图与本实用新型的实施方式作进一步详细的描述：
实施例一：如图1所示，一种潜在客户筛选方法，通过筛选历史客户网址关键数据以及上传潜在客户网址清单实现筛选，其步骤如下：
S0、在网站筛选系统创建用户账号；设定保密协议保护用户上传的数据，防止数据泄露，同时在用户账号中用户可根据不同的筛选关键数据创建不同的筛选算法库；
S1、在网站筛选系统中登录用户账号，并向网站筛选系统上传历史客户网址清单，网站筛选系统中的筛选模型一根据历史客户网址清单智能识别并抓取历史客户网址关键数据；其中历史客户网址关键数据为与理想客户群关系最紧密的关键数据，历史客户网址关键数据包括有企业管理人员信息、企业主营行业、企业规模、企业架构、企业荣誉信息等客户网址公开信息；
S2、网站筛选系统根据筛选模型一智能识别并抓取历史客户网址关键数据建立关键数据库，并根据关键数据库创建以及训练筛选模型二，完成后显示一个可视化成功确认信息以及用户设定邮箱收到一封带有通知链接的提醒邮件，通过链接用户查看相关的分析结果；
S3、用户自整理潜在客户网址清单，上传后使网站筛选系统根据获取筛选潜在客户网址；
S4、网站筛选系统中的筛选模型一根据潜在客户网址智能识别并抓取潜在客户网址关键数据，筛选模型二根据潜在客户网址关键数据分析潜在客户是否可转化为真实客户；
S4.1、网站筛选系统根据筛选模型二分析，标记潜在客户转化为真实客户的可能性分值，还通过标记一个从0％到100％之间的热度值作为潜在客户的转化可能性分值，并通过使用类似水温的分类名称，如沸腾、滚烫、温暖、冰凉、冰冷、极冷标记分析后的潜在客户，使用户能快速直观地在区分各潜在客户转化为真实客户的可能性；
S5、网站筛选系统通过用户账号显示真实客户转化可能性分值的分析结果，将分析结果送到用户设定邮箱中，方便用户随时随地查询分析结果，用户可更准确地筛选潜在客户，加速拓客流程以及帮助用户更有效地使用资源来确保新的商机的获取。
实施例二：如图2所示，一种潜在客户筛选方法，通过筛选历史客户网址关键数据和第三方系统中的历史客户关键数据，以及上传潜在客户网址清单实现筛选，其步骤如下：
S0、在网站筛选系统创建用户账号；设定保密协议保护用户上传的数据，防止数据泄露，同时在用户账号中用户可根据不同的筛选关键数据创建不同的筛选算法库；
S1、在网站筛选系统中登录用户账号，并向网站筛选系统上传历史客户网址清单，网站筛选系统中的筛选模型一根据历史客户网址清单智能识别并抓取历史客户网址关键数据；其中历史客户网址关键数据为与理想客 户群关系最紧密的关键数据，历史客户网址关键数据包括有企业管理人员信息、企业主营行业、企业规模、企业架构、企业荣誉信息等客户网址公开信息；
S1.1、网站筛选系统还可与收集并存储有企业财务信息数据的第三方系统合作，使网站筛选系统与第三方系统连接，网站筛选系统中的筛选模型一根据历史客户网址清单在第三方系统识别并抓取历史客户关键数据，其中历史客户关键数据包括有企业注册资产、企业股权结构、企业年销售额、企业缴税额等财务信息；
S2、网站筛选系统根据筛选模型一智能识别并抓取历史客户网址关键数据和历史客户关键数据建立关键数据库，并根据关键数据库创建以及训练筛选模型二，历史客户网址关键数据和历史客户关键数据结合创建筛选模型二可进一步提高潜在客户筛选的精准性，完成后显示一个可视化成功确认信息以及用户设定邮箱收到一封带有通知链接的提醒邮件，通过链接用户查看相关的分析结果；
S3、用户自整理潜在客户网址清单，上传后使网站筛选系统根据获取筛选潜在客户网址；
S4、网站筛选系统中的筛选模型一根据潜在客户网址智能识别并抓取潜在客户网址关键数据，筛选模型二根据潜在客户网址关键数据分析潜在客户是否可转化为真实客户；
S4.1网站筛选系统根据筛选模型二分析，标记潜在客户转化为真实客户的可能性分值，还通过标记一个从0％到100％之间的热度值作为潜在客户的转化可能性分值，并通过使用类似水温的分类名称，如沸腾、滚烫、 温暖、冰凉、冰冷、极冷标记分析后的潜在客户，使用户能快速直观地在区分各潜在客户转化为真实客户的可能性；
S5、网站筛选系统通过用户账号显示真实客户转化可能性分值的分析结果，将分析结果送到用户设定邮箱中，方便用户随时随地查询分析结果，用户可更准确地筛选潜在客户，加速拓客流程以及帮助用户更有效地使用资源来确保新的商机的获取。
实施例三：如图3所示，一种潜在客户筛选方法，通过筛选历史客户网址关键数据以及自动寻找潜在客户网址实现筛选，其步骤如下：
S0、在网站筛选系统创建用户账号；设定保密协议保护用户上传的数据，防止数据泄露，同时在用户账号中用户可根据不同的筛选关键数据创建不同的筛选算法库；
S1、在网站筛选系统中登录用户账号，并向网站筛选系统上传历史客户网址清单，网站筛选系统中的筛选模型一根据历史客户网址清单智能识别并抓取历史客户网址关键数据；其中历史客户网址关键数据为与理想客户群关系最紧密的关键数据，历史客户网址关键数据包括有企业管理人员信息、企业主营行业、企业规模、企业架构、企业荣誉信息等客户网址公开信息；
S2、网站筛选系统根据筛选模型一智能识别并抓取历史客户网址关键数据建立关键数据库，并根据关键数据库创建以及训练筛选模型二，完成后显示一个可视化成功确认信息以及用户设定邮箱收到一封带有通知链接的提醒邮件，通过链接用户查看相关的分析结果；
S3、用户还可通过网站筛选系统自动寻找潜在客户的功能寻找客户，使用自动寻找潜在客户的功能后，网站筛选系统通过在互联网中智能寻找潜在客户网址；
S4、网站筛选系统中的筛选模型一根据潜在客户网址智能识别并抓取潜在客户网址关键数据，筛选模型二根据潜在客户网址关键数据分析潜在客户是否可转化为真实客户；
S4.1、网站筛选系统根据筛选模型二分析，标记潜在客户转化为真实客户的可能性分值，还通过标记一个从0％到100％之间的热度值作为潜在客户的转化可能性分值，并通过使用类似水温的分类名称，如沸腾、滚烫、温暖、冰凉、冰冷、极冷标记分析后的潜在客户，使用户能快速直观地在区分各潜在客户转化为真实客户的可能性；
S5、网站筛选系统通过用户账号显示真实客户转化可能性分值的分析结果，将分析结果送到用户设定邮箱中，方便用户随时随地查询分析结果，用户可更准确地筛选潜在客户，加速拓客流程以及帮助用户更有效地使用资源来确保新的商机的获取。
实施例四：如图4所示，一种潜在客户筛选方法，通过筛选历史客户网址关键数据和第三方系统中的历史客户关键数据，以及自动寻找潜在客户网址实现筛选，其步骤如下：
S0、在网站筛选系统创建用户账号；设定保密协议保护用户上传的数据，防止数据泄露，同时在用户账号中用户可根据不同的筛选关键数据创建不同的筛选算法库；
S1、在网站筛选系统中登录用户账号，并向网站筛选系统上传历史客户网址清单，网站筛选系统中的筛选模型一根据历史客户网址清单智能识别并抓取历史客户网址关键数据；其中历史客户网址关键数据为与理想客户群关系最紧密的关键数据，历史客户网址关键数据包括有企业管理人员信息、企业主营行业、企业规模、企业架构、企业荣誉信息等客户网址公开信息；
S1.1、网站筛选系统还可与收集并存储有企业财务信息数据的第三方系统合作，使网站筛选系统与第三方系统连接，网站筛选系统中的筛选模型一根据历史客户网址清单在第三方系统识别并抓取历史客户关键数据，其中历史客户关键数据包括有企业注册资产、企业股权结构、企业年销售额、企业缴税额等财务信息；
S2、网站筛选系统根据筛选模型一智能识别并抓取历史客户网址关键数据和历史客户关键数据建立关键数据库，并根据关键数据库创建以及训练筛选模型二，历史客户网址关键数据和历史客户关键数据结合创建筛选模型二可进一步提高潜在客户筛选的精准性，完成后显示一个可视化成功确认信息以及用户设定邮箱收到一封带有通知链接的提醒邮件，通过链接用户查看相关的分析结果；
S3、用户还可通过网站筛选系统自动寻找潜在客户的功能寻找客户，使用自动寻找潜在客户的功能后，网站筛选系统通过在互联网中智能寻找潜在客户网址；
S4、网站筛选系统中的筛选模型一根据潜在客户网址智能识别并抓取潜在客户网址关键数据，筛选模型二根据潜在客户网址关键数据分析潜在 客户是否可转化为真实客户；
S网站筛选系统根据筛选模型二分析，标记潜在客户转化为真实客户的可能性分值，还通过标记一个从0％到100％之间的热度值作为潜在客户的转化可能性分值，并通过使用类似水温的分类名称，如沸腾、滚烫、温暖、冰凉、冰冷、极冷标记分析后的潜在客户，使用户能快速直观地在区分各潜在客户转化为真实客户的可能性；
S5、网站筛选系统通过用户账号显示真实客户转化可能性分值的分析结果，将分析结果送到用户设定邮箱中，方便用户随时随地查询分析结果，用户可更准确地筛选潜在客户，加速拓客流程以及帮助用户更有效地使用资源来确保新的商机的获取。
上述实施例中，筛选模型一为自然语言处理模型，自然语言处理模型识别并抓取关键词汇。处理时自然语言处理模型删除网址中的标点符号，并使网址中的词干还原和词形归并，将单词转换成其原始形式的词汇；具体地，自然语言处理模型为词袋模型，模型原理是创建包含不同单词集合的词汇表，每个单词都与出现的次数相关联，随后使用该词汇表创建d维特征向量。
筛选模型二为多项式朴素贝叶斯模型，多项式朴素贝叶斯模型为
Figure PCTCN2021099668-appb-000001
其中，A为客户网站的关键数据库中的词汇，B为非客户网站的智能识别并抓取关键词汇，P(A)为A的先验概率，
Figure PCTCN2021099668-appb-000002
为已知B发生后A的条件概率， P(B)为B的先验概率，
Figure PCTCN2021099668-appb-000003
为已知A发生后B的条件概率。
其中，条件概率
Figure PCTCN2021099668-appb-000004
为当与A有一定关系的事件B已经发生时，事件A发生的概率称为条件概率，条件概率
Figure PCTCN2021099668-appb-000005
为
Figure PCTCN2021099668-appb-000006
其中P(A)大于零。
[根据细则26改正09.08.2021]　
建模后的多项式朴素贝叶斯模型在训练数据集的准确率得分为94％；多项式朴素贝叶斯模型在测试数据集的准确率为84.3％；可准确地筛选潜在客户，加速拓客流程以及帮助用户更有效地使用资源来确保新的商机的获取。
以上对本发明实施例所提供的一种利用社交软件大数据找寻潜在客户的方法进行了详细介绍，本文中应用了具体个例对本发明的原理及实施方式进行了阐述，以上实施例的说明只是用于帮助理解本发明的方法及其核心思想；同时，对于本领域的一般技术人员，依据本发明的思想，在具体实施方式及应用范围上均会有改变之处，综上所述，本说明书内容不应理解为对本发明的限制。

Claims (10)

  1. 一种潜在客户筛选方法，其步骤如下：
    S1、向网站筛选系统上传历史客户网址清单，网站筛选系统中的筛选模型一识别并抓取历史客户网址关键数据；
    S2、建立关键数据库，根据关键数据库创建筛选模型二；
    S3、获取筛选潜在客户网址；
    S4、筛选模型一识别并抓取潜在客户网址关键数据，筛选模型二根据潜在客户网址关键数据分析潜在客户是否可转化为真实客户。
  2. 根据权利要求1所述的一种潜在客户筛选方法，其特征在于：还包括有S1.1、网站筛选系统中的筛选模型一在第三方系统识别并抓取历史客户关键数据。
  3. 根据权利要求1所述的一种潜在客户筛选方法，其特征在于：S3中通过上传潜在客户网址清单获取筛选潜在客户网址，或通过在互联网中寻找潜在客户网址获取筛选潜在客户网址。
  4. 根据权利要求1所述的一种潜在客户筛选方法，其特征在于：还包括有S4.1、网站筛选系统根据筛选模型二分析，标记潜在客户转化为真实客户的可能性分值。
  5. 根据权利要求1所述的一种潜在客户筛选方法，其特征在于：还包括有S5、用户账号显示分析结果和/或将分析结果送到用户设定邮箱中。
  6. 根据权利要求1所述的一种潜在客户筛选方法，其特征在于：还包括有S0、在网站筛选系统创建用户账号；
  7. 根据权利要求1所述的一种潜在客户筛选方法，其特征在于：筛选模型一为自然语言处理模型，自然语言处理模型识别并抓取关键词汇。
  8. 根据权利要求1所述的一种潜在客户筛选方法，其特征在于：S1中的历史客户网址关键数据包括有企业管理人员信息、企业主营行业、企业规模、企业架构、企业荣誉信息。
  9. 根据权利要求2所述的一种潜在客户筛选方法，其特征在于：历史客户关键数据为财务数据，包括有企业注册资产、企业股权结构、企业年销售额、企业缴税额。
  10. 根据权利要求4所述的一种潜在客户筛选方法，其特征在于：通过标记一个从0％到100％之间的热度值作为潜在客户的转化可能性分值。
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