面向潜在客户数据挖掘的机器人流程自动化开发及其在PT. XYZ中的实现

Ninna Novila, Andi Wahju Rahardjo Emanuel, Stephanie Pamela Adithama
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引用次数: 0

摘要

PT XYZ是一家从事贷款业务的金融公司。其活动包括分支机构,旨在增加新客户的获取。需要潜在客户数据来确定他们的潜力和最近分支机构的位置。PT.XYZ之前使用了第三方,但结果与要求的不相等,公司被迫付费以获得与要求相等的数据。谷歌地图是一个可供使用和免费访问的数据源。这项研究使用机器人过程自动化收集了潜在客户的数据。机器人过程自动化是使用UiPath与谷歌地图和Plus代码作为数据源开发的。Haversine方法用于确定最近分支机构的位置。595份潜在客户记录是通过机器人流程自动化使用七个搜索关键字获得的。579名潜在客户的结果是正确的,但16名客户的结果不正确。Haversine方法适用于582份潜在客户记录;然而,剩下的记录缺少纬度和经度,使得Haversine方法不适用。
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Development of Robotic Process Automation for Scraping Prospective Customer Data and Implementation Haversine in PT. XYZ
PT XYZ is a finance company that engages in lending. Its activities include branch offices, aiming to increase new customer acquisition. Prospective customer data is required to determine their potential and the location of the nearest branch office. PT. XYZ previously used a third party, but the result was not equal to what was required, and the company was forced to pay to obtain data equal to what was required. Google Maps is a data source that is utilized and freely accessible. This study scraped prospective customer data using robotic process automation. Robotic process automation was developed using UiPath with Google Maps and Plus Codes as data sources. The Haversine method is used to determine the location of the nearest branch office. 595 prospective customer records were obtained through robotic process automation using seven search keywords. The result for 579 prospective customers is correct, but the result for 16 is incorrect. Haversine Method applies to 582 prospective customer records; however, the remaining records lack latitude and longitude, making Haversine Method inapplicable.
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审稿时长
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