HealthIQ - Health and Wellness (US Only)

Health & Wellness Attributes – Offline contains individual or household level data variables that provide and predict a variety of unique characteristics related to health ranging from diet and health-related interests to exercise level and social determinants of health and more.

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## Use Cases
Health & Wellness Attributes – Offline can be used for personalized and targeted marketing communications by allowing marketers to optimize messaging, creative, and offer based on specific consumer characteristics, behaviors, and preferences. This facilitates better customer retention, customer acquisition, cross-sell or up-sell, and engagement rates.

Health & Wellness Attributes – Offline can be used to enrich CRM data by appending attributes to existing individuals in order to learn more about your customers.

Health & Wellness Attributes – Offline can be used for your own modeling processes.

Health & Wellness Attributes – Offline can be used to analyze health trends and social determinants of health across different geographies and time periods.

Geographic coverage | United States of America

Data Population Level | Individual or Household

Number of individuals/households covered | 257+ million
individuals & 120+ million households

Raw or scraped data | Raw Data
Key Fields | BMI, Exercise Level & Types, Alternative Medicine Interests
Data Source(s) | 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.
Update Frequency | AnalyticsIQ data is updated on a quarterly basis
Key Words | Health & Wellness, Healthcare, Patient Data, Social Determinants of Health
households

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## Key Data Points
Key data points include:

* Covid19_Vaccine: Likely to take COVID-19 vaccine once available
* LT_Exercise: Most likely frequency of exercise
* HW_BMI: Predicted BMI
* HW_Junk_Diet: Tendency to have an unhealthy diet
* HW_Primary_Care_Visits: Likely to have visited primary care doctor in last 12-months
* HW_Sleep_v3: Likely sleep quality
* HW_WebMD: Likely to use WebMD

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## Regulatory and Compliance Information
All AnalyticsIQ audiences are HIPAA compliant, and many audiences are Regulation B / FLA friendly or have alternative Regulation B / FLA friendly versions. To learn more about AnalyticsIQ’s Regulation B / FLA Friendly data.

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.

健康与福祉属性-离线版（Health & Wellness Attributes – Offline）包含个体或家庭层面的数据变量，可提供并预测一系列与健康相关的独特特征，涵盖饮食、健康相关兴趣、运动水平以及健康社会决定因素等多个领域。

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应用场景
健康与福祉属性-离线版可用于个性化定向营销传播：营销人员可基于特定消费者的特征、行为与偏好，优化营销信息、创意内容及优惠方案，进而提升客户留存、客户获取、交叉销售或追加销售效率以及用户参与度。
健康与福祉属性-离线版可用于丰富客户关系管理（CRM）数据，通过为现有个体添加属性标签，加深对客户的了解。
健康与福祉属性-离线版可应用于自有建模流程。
健康与福祉属性-离线版可用于分析不同地理区域与时间段内的健康趋势及健康社会决定因素。

地理覆盖范围 | 美利坚合众国
数据人口层级 | 个体或家庭
覆盖个体/家庭数量 | 2.57亿+个体及1.2亿+家庭
原始或爬取数据 | 原始数据
关键字段 | 身体质量指数（BMI）、运动水平与类型、替代医学兴趣
数据来源 | 本数据通过离线流程生成，但同时整合离线与在线数据及用户行为。本数据库绝大多数为专有数据，仅在开发过程中借助部分公开数据源。AnalyticsIQ从100余个数据源获取数据，其中绝大多数为公开数据源，包括：*多渠道核心人口统计数据；普查区块与区块组层面数据；美国政府发布的计量经济学数据；多家征信机构汇总的信贷数据；县法院公开的房产与抵押贷款信息；州执业执照委员会发布的职业信息；目录零售商与零售商按类别提供的过往购买行为数据。* AnalyticsIQ并非原始数据汇编方，上述数据均可在市场上公开购买。但AnalyticsIQ通过顶尖的数据分析技术，打造出行业领先的优质数据。AnalyticsIQ产品开发流程中独有的一项工具为专有调研数据：我们的认知科学部门精心设计调研问卷，面向消费者调研面板投放。调研结果不会直接发布至数据集，而是将问卷答案通过建模方式覆盖至全体消费者数据集，从而生成全球独有的数据点。
更新频率 | AnalyticsIQ数据每季度更新一次
关键词 | 健康与福祉、医疗保健、患者数据、健康社会决定因素

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关键数据点
关键数据点包括：
* Covid19_Vaccine：新冠疫苗可用时的接种意向
* LT_Exercise：高频运动情况
* HW_BMI：预测身体质量指数
* HW_Junk_Diet：不健康饮食倾向
* HW_Primary_Care_Visits：过去12个月内就诊全科医生的可能性
* HW_Sleep_v3：睡眠质量预估
* HW_WebMD：使用WebMD医疗平台的可能性

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监管与合规信息
AnalyticsIQ的所有受众数据集均符合《健康保险流通与责任法案》（HIPAA）要求，多数数据集符合法规B / 公平信贷法案（FLA）相关要求，或提供符合法规B / FLA要求的替代版本。欲了解更多关于AnalyticsIQ符合法规B / FLA要求的数据相关信息。
对于希望避免接触个人可识别信息（PII）的用户，依托与数据去标识化服务领先提供商Datavant的深度合作，AnalyticsIQ所有数据均可通过标记化（tokenization）实现匿名化。