Automotive

Data Population Level: Individual or Household

Number of individuals/households covered: 242.5+ million individuals & 117+ million households

Key Fields: Average Annual Mileage, Age of Auto, Maintenance Preferences, Auto Make Propensity, In Market for Auto, Make of Auto Owned

Data Source: Our data is created in an offline process but leverage offline and online data and behaviors. The vast majority of our database is proprietary although a few publicly available data sources are leveraged in its development AnalyticsIQ sources data from over 100 sources.

These are predominantly public sources including: Core Demographic data from multiple sources; Census Block and Block Group level data; Econometric data from the US government; Summarized credit data from multiple credit bureaus; Property and mortgage information from county courthouses; Occupation information from state licensing boards; Past purchase behavior from catalogers and retailers that contribute their data at a category level.

AnalyticsIQ is not an original compiler as the data above is readily available for purchase out in the market. However, AnalyticsIQ uses superior analytics to make our data best-in-class.

One tool that is completely unique to AnalyticsIQ’s product development process is our proprietary survey data. This is where our Cognitive Sciences Department carefully crafts questions that we serve to a panel of consumers. Survey responses are not directly published on our file, but rather the answers are then modeled across our entire consumer file to create truly unique data points not available anywhere.

Key data points include:

- Auto_Avg_Mileage: Average mileage put on car per year
- Number_of_Autos: Number of autos owned by the household
- AutoProp_Acura_MostLikely: Propensity to drive an Acura
- Auto_Family_Use: Likelihood of using vehicle for family use
- Auto_InMkt_v2: Likelihood of being in market for a vehicle
- Auto_Buyer_Methodical: Likelihood to use vehicle for family use
- Auto_Maint_Dealership: Likelihood of preferring dealership for vehicle maintenance

For users who wish to avoid PII, all AnalyticsIQ data can be anonymized through tokenization thanks to our strong partnership with Datavant, a leading providers of data de-identification services.

数据覆盖层级：个人或家庭

覆盖个体与家庭规模：超2.425亿个体及1.17亿户家庭

核心字段：平均年行驶里程、车辆车龄、保养偏好、汽车品牌购买倾向、有意向购车、已拥有的汽车品牌

数据来源：本数据集通过离线流程生成，同时整合离线与在线数据及用户行为数据。本数据库绝大多数内容为专属专有数据，仅在开发过程中少量引入公开数据源。AnalyticsIQ的数据源覆盖超100个渠道。

这些数据源以公开渠道为主，包括：多渠道核心人口统计数据；普查区块及区块组层级数据；美国政府发布的计量经济数据；多家征信机构汇总的信用数据；县级法院公开的房产与抵押贷款信息；州执业许可委员会提供的职业信息；以及参与数据共享的目录零售商与线下零售商按品类提供的过往购买行为数据。

AnalyticsIQ并非原始数据汇编方，上述数据均可通过市场采购获取。但本公司通过领先的数据分析技术，打造了行业顶尖级别的数据集。

AnalyticsIQ产品开发流程中独有的一项核心工具为专属调研数据。本公司认知科学部门精心设计调研问卷，面向消费者样本组投放。调研结果不会直接同步至用户数据集，而是通过建模将问卷答案推演至全量消费者数据集，从而生成全球独有的、其他渠道无法获取的数据维度。

关键数据点包括：
- Auto_Avg_Mileage：车辆年均行驶里程
- Number_of_Autos：家庭拥有的汽车数量
- AutoProp_Acura_MostLikely：偏好驾驶讴歌（Acura）品牌车辆的倾向
- Auto_Family_Use：车辆用于家庭用途的可能性
- Auto_InMkt_v2：处于购车意向人群的可能性
- Auto_Buyer_Methodical：倾向于将车辆用于家庭用途的可能性
- Auto_Maint_Dealership：倾向于选择经销商进行车辆保养的可能性

对于希望避免接触个人可识别信息（PII, Personal Identifiable Information）的用户，依托与领先的数据去标识服务提供商Datavant的深度合作，AnalyticsIQ所有数据均可通过标记化（Tokenization）实现匿名化处理。

搜集汇总

背景与挑战

背景概述

该数据集覆盖2.425亿个人和1.17亿家庭，提供车辆年均里程、品牌偏好、维护选择等详细信息，结合公开数据与专有调查分析生成。数据可匿名化处理以满足隐私需求。