Sold by: AnalyticsIQ
Deployed on AWS
Consumer Finance Audiences – Digital contains individual or household level audiences with a variety of unique financial characteristics ranging from core information such as household income to predicted financial motivations and more.
Overview
Consumer Finance Audiences – Digital (Individual or Household Level) Data Product Overview
Consumer Finance Audiences – Digital contains individual or household level audiences with a variety of unique financial characteristics ranging from core information such as household income to predicted financial motivations and more.
Use Cases
Consumer Finance Audiences – Digital 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 & up-sell, and engagement rates.
Consumer Finance Audiences – Digital can be used for analytics, insights, and measurement of programmatic and advanced TV campaigns.
Metadata
| Description | Value |
|---|---|
| Geographic coverage | United States of America |
| Data Population Level | Individual or Household |
| Number of individuals/households covered | 242.5+ million individuals & 117+ million households |
| Raw or scraped data | Raw Data |
| Key Fields | Household Income, Net Worth, Discretionary Spending, Liquid Investable Assets |
| 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 | Financial Services, FinTech, Insurance, Banking, Credit Cards, Consumer Finances, Personal Finances, Wealth, Income, Investing |
Key Data Points
Examples of key data points include:
- WealthIQ_Plus_v3_1000_1999: Estimated net worth $1M to $1.9M
- Financial_Motivation: Likely to be motivated to find opportunities for financial growth
- Spontaneous_Spenders: Likely to be spontaneous spenders
- IncomeIQ_Plus_v2_60_74: Predicted annual household income $60k to $74k
- Millennial_Investor_Ind: Millennials likely to have active investments
- InvestorIQ_Plus_v3_80_899: Likely have $80k to $899k in liquid investable assets
- SD_Motivated_to_Rebound: Likely to be interested in financial growth while social distancing
- IoT_FinTech_Digital_MostLikely: Likely to use digital payment apps
Additional Information
Automotive Audiences – Digital Data Dictionary and AnalyticsIQ Full Data Dictionary are available for download. Please contact aws-support@analytics-iq.com for access.
Pricing Information
For pricing information on our 12-month licenses please reach out to Margo Hock at margoh@analytics-iq.com .
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.
For information, please reach out to aws-support@analytics-iq.com .
Need Help?
If you have any questions about AnalyticsIQ or our data, please reach out to aws-support@analytics-iq.com .
About Your Company
Founded in 2007 and based in Atlanta, AnalyticsIQ is vastly made up of data scientists, analysts, researchers, and cognitive psychologists with over 100 years of collective analytical experience. AnalyticsIQ is the first data company to consistently blend cognitive psychology with data science to understand the heart of individuals and their motivations – both as a consumer and as a professional. By linking an individual’s consumer profile at home to their professional profile at work, AnalyticsIQ strives to help companies know their customers and prospects like they know their friends, and its mission is for data to fuel every brand experience. AnalyticsIQ’s data consistently outperforms other data providers, and the company’s flexible approach means that they will do whatever it takes to work with clients to solve the challenges they may be facing. To learn more about AnalyticsIQ, please visit https://analytics-iq.com/ .
Details
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Deployed on AWS
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Delivery details
AWS Data Exchange (ADX)
AWS Data Exchange is a service that helps AWS easily share and manage data entitlements from other organizations at scale.
Additional details
You will receive access to the following data sets.
Data set name | Type | Historical revisions | Future revisions | Sensitive information | Data dictionaries | Data samples |
|---|---|---|---|---|---|---|
AnalyticsIQ Audiences – Digital (Individual or Household Level) | All historical revisions | All future revisions | Not included | Not included |
Resources
Vendor resources
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