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客户画像参考BLUEKAI标签模型_用户画像 标签模型

数据分析 cdadata 4185℃

客户画像参考BLUEKAI标签模型

关键词:用户画像 标签模型用户画像 标签库

Data Type数据类型

Description描述

Availability有效

Qualification条件

Segmentation细分

Intent意向

Consumers who intend to buy a particular product or service in the near term.

消费者最近有意向去购买特定的产品或服务

160+ million uniques

160百万以上独立用户

Actions indicating intent to buy on top tier (一级)ecommerce, financial, retail, online travel agency sites. Sample actions include interactions互动 with a search function (either via search widget搜索小部件, or entering in a keyword输入关键字, product comparison产品对比, loan calculators贷款计算器, etc.

Autos 汽车(ie. by Make and Model汽车的品牌和款式)

Financial services金融服务 (ie. Loans贷款, mortgages抵押, investment products投资产品)

Travel旅游 (ie. by departure起程/destination目的 city, length of stay(逗留时长), air travel(空中旅行), hotel(旅馆), rental cars(租车) and brands品牌)

Education教育 (ie. by education products and services)

Retail零售 (ie. by product type,产品类型categories种类, brands品牌)

Local Goods本土货物 & Services (ie. by products and services)

Real Estate房地产 (ie. intent to purchase or rent倾向于购买还是出租)

B2B

Business consumers商务消费者who are occupationally similar职业相似.

90+ Million Uniques

Business attributes sourced from hundreds of business web sites, active offline records活跃离线记录, and publicly available databases公开现有数据库

Business Professionals: Functional area职能范围, Seniority资历, Other Business and Company attributes: Company size公司规模, Industry, 行业Revenues收益

Past Purchases历史购买记录

Consumers who are more likely to buy based on pervious purchasing habits

客户更愿意基于过去购买习惯去买东西

65+ million uniques

Consistency in online and offline shopping behaviors

线上线下购物习惯一致

By Product Type (e.g. Women’s Apparel, Laptop )

Geo/Demo地理人口统计

Geographically or demographically similar.

TBD

电子商务企业

 

Geo: By State 按洲
Demo: Age, Education Level教育水平, Gender, Homeowner Status户主状态, Household Income, 家庭收入Presence of Children有否有孩

Interest, Lifestyle兴趣,生活方式

Consumers who are more likely to be interested in a topic or fall within a lifestyle category based on modeling from multiple data types

基于多个数据类型的模型,得出客户倾向于对某个主题感兴趣,或落入某个生活方式类别

103+ million uniques

Consistency in online and offline shopping behaviors contrasted with 对比demographic attributes to determine interest, hobbies爱好 and lifestyles.

By Product Type (ie Women’s Apparel衣物, Laptop便携笔记本)

By Lifestyles (e.g. 
Frequent Travelers频繁旅游, High Spenders挥霍型)

By Generations时代 (e.g. Gen X X一代, Baby Boomers婴儿潮)

By Social 社交(e.g. Social Behavior, Social Signals社会化因素, Interest between Friends朋友圈兴趣)

Branded

标签

Consumers sorted by branded sources of data ranging from geo/demo, lifestyle, interest and purchase propensity

依据标签给客户分类 ,如地理/人口统计,生活方式,兴趣和购买倾向

TBD

Contact BlueKai to get a comprehensive list of data providers

Contact BlueKai to learn more about our branded data providers

Qualified Demo

Qualified合格demographic attributes, based on consensus一致 and validation有效性, for targeting audiences受众 at scale按比例

90+ million uniques

If two of more data providers agree on a user’s demographic attributes and no other data provider disagree that is qualified as consensus. Data is tested quarterly to continue to meet the specified standard of excellence in data quality.

数据按季度测试以使数据质量符合优秀规定标准

Age, Gender, Household Income, Marital Status婚姻状态, Presence of Children (new categories coming soon!)

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