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Financial Services Data for Marketing

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Snowflake2023-03-15 更新2024-05-01 收录
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https://app.snowflake.com/marketplace/listing/GZTDZ5LRG5
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资源简介:
Our Financial Services audiences are drawn from insight on 51 million adults and 26 million households in the UK and provide a deep understanding of consumers financial behaviours. Containing a range of actual and modelled attributes, segmentations and propensities our Financial Services data can help to enrich your customer information for insight and to more effectively manage customer relationships and provide a deep understanding of consumers financial behaviours including their: Savings Investments Card ownership Unsecured and secured borrowing Risk attitudes Financial aspirations Our Financial Services data includes: Personal Attributes • Affluence • Personal income • Household income • Mortgage value • Employment type • Directorship type • Shareholding • Business from home • Home owner • Renter • Property type • No. Bedrooms • Property value • Take Financial Advice • Investable Assets Value Product Attributes • Bank account • Bank Savings account • Investment products • Credit cards • NS&I • Cash ISA • Investment ISA • Home Insurance • Type of mortgage • Type of savings product held • Type of Insurance held • Type of Investments held • Type of Pension held • Pension value • Type of Retirement provision held • Application channel used for financial products How the data flow process works: Snowflake user will make available their customer and / or prospect lists with Experian by extracting the file from their account and sharing via Experian’s secure file transfer application. Subject to a signed contractual agreement, Experian will match the customer file(s) against our Financial Services data and where a match is found, will append the required datasets to the customer file(s). Experian will return the customer file via Snowflake's secure data share. Experian's Linkage capabilities provide increased match rates between customer files and our Financial Services data. Matching using combinations of full name, UK postal address, postcode, email address and mobile telephone number are all viable matching data points.
提供机构:
Experian UK
创建时间:
2023-03-10
搜集汇总
数据集介绍
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背景与挑战
背景概述
该数据集基于英国5100万成年人和2600万家庭的洞察,提供消费者金融行为的深度理解,涵盖储蓄、投资、借贷等个人与产品属性。它通过安全的数据匹配流程,帮助丰富客户信息,以优化客户关系管理和营销策略。
以上内容由遇见数据集搜集并总结生成
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