100+ datasets found
  1. d

    US Consumer Marketing Data - 269M+ Consumer Records - 95% Email and Direct...

    • datarade.ai
    Updated Jun 1, 2022
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    Giant Partners (2022). US Consumer Marketing Data - 269M+ Consumer Records - 95% Email and Direct Dials Accuracy [Dataset]. https://datarade.ai/data-products/consumer-business-data-postal-phone-email-demographics-giant-partners
    Explore at:
    Dataset updated
    Jun 1, 2022
    Dataset authored and provided by
    Giant Partners
    Area covered
    United States
    Description

    Premium B2C Consumer Database - 269+ Million US Records

    Supercharge your B2C marketing campaigns with comprehensive consumer database, featuring over 269 million verified US consumer records. Our 20+ year data expertise delivers higher quality and more extensive coverage than competitors.

    Core Database Statistics

    Consumer Records: Over 269 million

    Email Addresses: Over 160 million (verified and deliverable)

    Phone Numbers: Over 76 million (mobile and landline)

    Mailing Addresses: Over 116,000,000 (NCOA processed)

    Geographic Coverage: Complete US (all 50 states)

    Compliance Status: CCPA compliant with consent management

    Targeting Categories Available

    Demographics: Age ranges, education levels, occupation types, household composition, marital status, presence of children, income brackets, and gender (where legally permitted)

    Geographic: Nationwide, state-level, MSA (Metropolitan Service Area), zip code radius, city, county, and SCF range targeting options

    Property & Dwelling: Home ownership status, estimated home value, years in residence, property type (single-family, condo, apartment), and dwelling characteristics

    Financial Indicators: Income levels, investment activity, mortgage information, credit indicators, and wealth markers for premium audience targeting

    Lifestyle & Interests: Purchase history, donation patterns, political preferences, health interests, recreational activities, and hobby-based targeting

    Behavioral Data: Shopping preferences, brand affinities, online activity patterns, and purchase timing behaviors

    Multi-Channel Campaign Applications

    Deploy across all major marketing channels:

    Email marketing and automation

    Social media advertising

    Search and display advertising (Google, YouTube)

    Direct mail and print campaigns

    Telemarketing and SMS campaigns

    Programmatic advertising platforms

    Data Quality & Sources

    Our consumer data aggregates from multiple verified sources:

    Public records and government databases

    Opt-in subscription services and registrations

    Purchase transaction data from retail partners

    Survey participation and research studies

    Online behavioral data (privacy compliant)

    Technical Delivery Options

    File Formats: CSV, Excel, JSON, XML formats available

    Delivery Methods: Secure FTP, API integration, direct download

    Processing: Real-time NCOA, email validation, phone verification

    Custom Selections: 1,000+ selectable demographic and behavioral attributes

    Minimum Orders: Flexible based on targeting complexity

    Unique Value Propositions

    Dual Spouse Targeting: Reach both household decision-makers for maximum impact

    Cross-Platform Integration: Seamless deployment to major ad platforms

    Real-Time Updates: Monthly data refreshes ensure maximum accuracy

    Advanced Segmentation: Combine multiple targeting criteria for precision campaigns

    Compliance Management: Built-in opt-out and suppression list management

    Ideal Customer Profiles

    E-commerce retailers seeking customer acquisition

    Financial services companies targeting specific demographics

    Healthcare organizations with compliant marketing needs

    Automotive dealers and service providers

    Home improvement and real estate professionals

    Insurance companies and agents

    Subscription services and SaaS providers

    Performance Optimization Features

    Lookalike Modeling: Create audiences similar to your best customers

    Predictive Scoring: Identify high-value prospects using AI algorithms

    Campaign Attribution: Track performance across multiple touchpoints

    A/B Testing Support: Split audiences for campaign optimization

    Suppression Management: Automatic opt-out and DNC compliance

    Pricing & Volume Options

    Flexible pricing structures accommodate businesses of all sizes:

    Pay-per-record for small campaigns

    Volume discounts for large deployments

    Subscription models for ongoing campaigns

    Custom enterprise pricing for high-volume users

    Data Compliance & Privacy

    VIA.tools maintains industry-leading compliance standards:

    CCPA (California Consumer Privacy Act) compliant

    CAN-SPAM Act adherence for email marketing

    TCPA compliance for phone and SMS campaigns

    Regular privacy audits and data governance reviews

    Transparent opt-out and data deletion processes

    Getting Started

    Our data specialists work with you to:

    1. Define your target audience criteria

    2. Recommend optimal data selections

    3. Provide sample data for testing

    4. Configure delivery methods and formats

    5. Implement ongoing campaign optimization

    Why We Lead the Industry

    With over two decades of data industry experience, we combine extensive database coverage with advanced targeting capabilities. Our commitment to data quality, compliance, and customer success has made us the preferred choice for businesses seeking superior B2C marketing performance.

    Contact our team to discuss your specific targeting requirements and receive custom pricing for your marketing objectives.

  2. Personalization data companies use for customer profiling 2023

    • statista.com
    Updated Jun 23, 2025
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    Statista (2025). Personalization data companies use for customer profiling 2023 [Dataset]. https://www.statista.com/statistics/1426127/customer-profiling-data-demands/
    Explore at:
    Dataset updated
    Jun 23, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    2023
    Area covered
    Worldwide
    Description

    During a 2023 survey among senior marketing executives worldwide, ** percent of respondents listed demographics as the most important type of data used for customer profiling. Behavioral data came next, with ** percent, while data about business details rounded up the top three with ** percent.

  3. Synthetic Customer Analytics Dataset

    • kaggle.com
    Updated May 5, 2025
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    Siddharth Vora (2025). Synthetic Customer Analytics Dataset [Dataset]. https://www.kaggle.com/datasets/siddharth0935/synthetic-customer-analytics-dataset/code
    Explore at:
    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    May 5, 2025
    Dataset provided by
    Kagglehttp://kaggle.com/
    Authors
    Siddharth Vora
    License

    https://creativecommons.org/publicdomain/zero/1.0/https://creativecommons.org/publicdomain/zero/1.0/

    Description

    Dataset Overview

    A high-quality synthetic dataset simulating 100,000+ customers with:
    - Demographics (age, gender, location, income)
    - Transaction history (purchase dates, spending, product categories)
    - Behavioral metrics (churn risk, device usage, support tickets)
    - Perfect for segmentation, CLV prediction, and churn modeling

    No real PII – Safe for sharing
    Realistic distributions – Mimics e-commerce patterns
    Ready-to-use – Clean, structured, and documented

    Files

    1. synthetic_customers.csv (100K rows × 20 columns)
      • Primary dataset with customer profiles and behavior
    2. synthetic_customers_metadata.json
      • Field descriptions, data types, and missing value counts
  4. d

    Factori | US Consumer Graph Data - Acquisition Marketing & Consumer Data...

    • datarade.ai
    .json, .csv
    Updated Jul 23, 2022
    + more versions
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    Factori (2022). Factori | US Consumer Graph Data - Acquisition Marketing & Consumer Data Insights | Append 100+ Attributes from 220M+ Consumer Profiles [Dataset]. https://datarade.ai/data-products/factori-usa-consumer-graph-data-acquisition-marketing-a-factori
    Explore at:
    .json, .csvAvailable download formats
    Dataset updated
    Jul 23, 2022
    Dataset authored and provided by
    Factori
    Area covered
    United States of America
    Description

    Our consumer data is gathered and aggregated via surveys, digital services, and public data sources. We use powerful profiling algorithms to collect and ingest only fresh and reliable data points.

    Our comprehensive data enrichment solution includes a variety of data sets that can help you address gaps in your customer data, gain a deeper understanding of your customers, and power superior client experiences. 1. Geography - City, State, ZIP, County, CBSA, Census Tract, etc. 2. Demographics - Gender, Age Group, Marital Status, Language etc. 3. Financial - Income Range, Credit Rating Range, Credit Type, Net worth Range, etc 4. Persona - Consumer type, Communication preferences, Family type, etc 5. Interests - Content, Brands, Shopping, Hobbies, Lifestyle etc. 6. Household - Number of Children, Number of Adults, IP Address, etc. 7. Behaviours - Brand Affinity, App Usage, Web Browsing etc. 8. Firmographics - Industry, Company, Occupation, Revenue, etc 9. Retail Purchase - Store, Category, Brand, SKU, Quantity, Price etc. 10. Auto - Car Make, Model, Type, Year, etc. 11. Housing - Home type, Home value, Renter/Owner, Year Built etc.

    Consumer Graph Schema & Reach: Our data reach represents the total number of counts available within various categories and comprises attributes such as country location, MAU, DAU & Monthly Location Pings:

    Data Export Methodology: Since we collect data dynamically, we provide the most updated data and insights via a best-suited method on a suitable interval (daily/weekly/monthly).

    Consumer Graph Use Cases: 360-Degree Customer View: Get a comprehensive image of customers by the means of internal and external data aggregation. Data Enrichment: Leverage Online to offline consumer profiles to build holistic audience segments to improve campaign targeting using user data enrichment Fraud Detection: Use multiple digital (web and mobile) identities to verify real users and detect anomalies or fraudulent activity. Advertising & Marketing: Understand audience demographics, interests, lifestyle, hobbies, and behaviors to build targeted marketing campaigns.

    Here's the schema of Consumer Data: person_id first_name last_name age gender linkedin_url twitter_url facebook_url city state address zip zip4 country delivery_point_bar_code carrier_route walk_seuqence_code fips_state_code fips_country_code country_name latitude longtiude address_type metropolitan_statistical_area core_based+statistical_area census_tract census_block_group census_block primary_address pre_address streer post_address address_suffix address_secondline address_abrev census_median_home_value home_market_value property_build+year property_with_ac property_with_pool property_with_water property_with_sewer general_home_value property_fuel_type year month household_id Census_median_household_income household_size marital_status length+of_residence number_of_kids pre_school_kids single_parents working_women_in_house_hold homeowner children adults generations net_worth education_level occupation education_history credit_lines credit_card_user newly_issued_credit_card_user credit_range_new
    credit_cards loan_to_value mortgage_loan2_amount mortgage_loan_type
    mortgage_loan2_type mortgage_lender_code
    mortgage_loan2_render_code
    mortgage_lender mortgage_loan2_lender
    mortgage_loan2_ratetype mortgage_rate
    mortgage_loan2_rate donor investor interest buyer hobby personal_email work_email devices phone employee_title employee_department employee_job_function skills recent_job_change company_id company_name company_description technologies_used office_address office_city office_country office_state office_zip5 office_zip4 office_carrier_route office_latitude office_longitude office_cbsa_code
    office_census_block_group
    office_census_tract office_county_code
    company_phone
    company_credit_score
    company_csa_code
    company_dpbc
    company_franchiseflag
    company_facebookurl company_linkedinurl company_twitterurl
    company_website company_fortune_rank
    company_government_type company_headquarters_branch company_home_business
    company_industry
    company_num_pcs_used
    company_num_employees
    company_firm_individual company_msa company_msa_name
    company_naics_code
    company_naics_description
    company_naics_code2 company_naics_description2
    company_sic_code2
    company_sic_code2_description
    company_sic_code4 company_sic_code4_description
    company_sic_code6
    company_sic_code6_description
    company_sic_code8
    company_sic_code8_description company_parent_company
    company_parent_company_location company_public_private company_subsidiary_company company_residential_business_code company_revenue_at_side_code company_revenue_range
    company_revenue company_sales_volume
    company_small_business company_stock_ticker company_year_founded company_minorityowned
    company_female_owned_or_operated company_franchise_code company_dma company_dma_name
    company_hq_address
    company_hq_city company_hq_duns company_hq_state
    company_hq_zip5 company_hq_zip4 co...

  5. d

    Demographic and Housing Profiles by Borough

    • catalog.data.gov
    • data.cityofnewyork.us
    • +3more
    Updated Nov 1, 2024
    + more versions
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    data.cityofnewyork.us (2024). Demographic and Housing Profiles by Borough [Dataset]. https://catalog.data.gov/dataset/demographic-and-housing-profiles-by-borough
    Explore at:
    Dataset updated
    Nov 1, 2024
    Dataset provided by
    data.cityofnewyork.us
    Description

    Selected demographic and housing estimates data citywide and by borough. Five year estimates of population data from the Census Bureau's American Community Survey.

  6. d

    Geodemographic Data | Asia/ MENA | Latest Estimates on Population, Consuming...

    • datarade.ai
    .json, .csv
    Updated Nov 23, 2024
    + more versions
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    GapMaps (2024). Geodemographic Data | Asia/ MENA | Latest Estimates on Population, Consuming Class, Demographics, Retail Spend | GIS Data | Map Data [Dataset]. https://datarade.ai/data-products/gapmaps-premium-geodemographic-data-asia-mena-150m-x-150-gapmaps
    Explore at:
    .json, .csvAvailable download formats
    Dataset updated
    Nov 23, 2024
    Dataset authored and provided by
    GapMaps
    Area covered
    Malaysia, Saudi Arabia, Indonesia, Philippines, Singapore, India, Asia
    Description

    Sourcing accurate and up-to-date geodemographic data across Asia and MENA has historically been difficult for retail brands looking to expand their store networks in these regions. Either the data does not exist or it isn't readily accessible or updated regularly.

    GapMaps uses known population data combined with billions of mobile device location points to provide highly accurate and globally consistent geodemographic datasets across Asia and MENA at 150m x 150m grid levels in major cities and 1km grids outside of major cities.

    With this information, brands can get a detailed understanding of who lives in a catchment, where they work and their spending potential which allows you to:

    • Better understand your customers
    • Identify optimal locations to expand your retail footprint
    • Define sales territories for franchisees
    • Run targeted marketing campaigns.

    Premium geodemographics data for Asia and MENA includes the latest estimates (updated annually) on:

    1. Population (how many people live in your local catchment)
    2. Demographics (who lives within your local catchment)
    3. Worker population (how many people work within your local catchment)
    4. Consuming Class and Premium Consuming Class (who can can afford to buy goods & services beyond their basic needs and /or shop at premium retailers)
    5. Retail Spending (Food & Beverage, Grocery, Apparel, Other). How much are consumers spending on retail goods and services by category.

    Primary Use Cases for GapMaps Geodemographic Data:

    1. Retail (eg. Fast Food/ QSR, Cafe, Fitness, Supermarket/Grocery)
    2. Customer Profiling: get a detailed understanding of the demographic profile of your customers, where they work and their spending potential
    3. Analyse your trade areas at a granular 150m x 150m grid levels using all the key metrics
    4. Site Selection: Identify optimal locations for future expansion and benchmark performance across existing locations.
    5. Target Marketing: Develop effective marketing strategies to acquire more customers.
    6. Integrate GapMaps demographic data with your existing GIS or BI platform to generate powerful visualizations.

    7. Commercial Real-Estate (Brokers, Developers, Investors, Single & Multi-tenant O/O)

    8. Tenant Recruitment

    9. Target Marketing

    10. Market Potential / Gap Analysis

    11. Marketing / Advertising (Billboards/OOH, Marketing Agencies, Indoor Screens)

    12. Customer Profiling

    13. Target Marketing

    14. Market Share Analysis

  7. d

    Deterministic Consumer Demographics | 1st Party | 3B+ events verified, US...

    • datarade.ai
    .csv, .parquet
    Updated Jan 1, 2000
    + more versions
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    MFour (2000). Deterministic Consumer Demographics | 1st Party | 3B+ events verified, US consumers | Age, gender, location, education, income, ethnicity, more [Dataset]. https://datarade.ai/data-products/deterministic-consumer-demographics-1st-party-3b-events-mfour
    Explore at:
    .csv, .parquetAvailable download formats
    Dataset updated
    Jan 1, 2000
    Dataset authored and provided by
    MFour
    Area covered
    United States
    Description

    This dataset encompasses deterministic consumer demographics, collected from over 150,000 triple-opt-in first-party US Daily Active Users (DAU). Included are age, gender, ethnicity, location, employment, education, income, pet ownership, having kids/children, relationship status, military status, number of people in household, car ownership vs lease, small business owner, spanish TV viewership as a proxy for acculturation, and having kids under 18 in the home.

  8. d

    Wave 17, January 2011

    • search.dataone.org
    • borealisdata.ca
    Updated Dec 28, 2023
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    Ipsos (2023). Wave 17, January 2011 [Dataset]. http://doi.org/10.5683/SP2/ZHIPUK
    Explore at:
    Dataset updated
    Dec 28, 2023
    Dataset provided by
    Borealis
    Authors
    Ipsos
    Time period covered
    Jan 1, 2011
    Description

    Ipsos Global @dvisor wave 17 was conducted on January 14 and January 24, 2011. It included the following question sections: A: Demographic Profile, B: Consumer Confidence, R: Reuters Battery, BY: Consumer Goods Questions.

  9. d

    Demographic Data | Asia & MENA | Make Informed Business Decisions with High...

    • datarade.ai
    .json, .csv
    Updated Jun 25, 2024
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    GapMaps (2024). Demographic Data | Asia & MENA | Make Informed Business Decisions with High Quality and Granular Insights [Dataset]. https://datarade.ai/data-products/gapmaps-premium-demographics-data-asia-mena-accurate-and-gapmaps
    Explore at:
    .json, .csvAvailable download formats
    Dataset updated
    Jun 25, 2024
    Dataset authored and provided by
    GapMaps
    Area covered
    Indonesia, India, Malaysia, Saudi Arabia, Singapore, Philippines, Asia
    Description

    Sourcing accurate and up-to-date demographic data across Asia and MENA has historically been difficult for retail brands looking to expand their store networks in these regions. Either the data does not exist or it isn't readily accessible or updated regularly.

    GapMaps uses known population data combined with billions of mobile device location points to provide highly accurate and globally consistent demographic datasets across Asia and MENA at 150m x 150m grid levels in major cities and 1km grids outside of major cities.

    With this information, brands can get a detailed understanding of who lives in a catchment, where they work and their spending potential which allows you to:

    • Better understand your customers
    • Identify optimal locations to expand your retail footprint
    • Define sales territories for franchisees
    • Run targeted marketing campaigns.

    Premium demographics data for Asia and MENA includes the latest estimates (updated annually) on:

    1. Population (how many people live in your local catchment)
    2. Demographics (who lives within your local catchment)
    3. Worker population (how many people work within your local catchment)
    4. Consuming Class and Premium Consuming Class (who can can afford to buy goods & services beyond their basic needs and /or shop at premium retailers)
    5. Retail Spending (Food & Beverage, Grocery, Apparel, Other). How much are consumers spending on retail goods and services by category.

    Primary Use Cases for GapMaps Demographic Data:

    1. Retail (eg. Fast Food/ QSR, Cafe, Fitness, Supermarket/Grocery)
    2. Customer Profiling: get a detailed understanding of the demographic profile of your customers, where they work and their spending potential
    3. Analyse your trade areas at a granular 150m x 150m grid levels using all the key metrics
    4. Site Selection: Identify optimal locations for future expansion and benchmark performance across existing locations.
    5. Target Marketing: Develop effective marketing strategies to acquire more customers.
    6. Integrate GapMaps demographic data with your existing GIS or BI platform to generate powerful visualizations.

    7. Commercial Real-Estate (Brokers, Developers, Investors, Single & Multi-tenant O/O)

    8. Tenant Recruitment

    9. Target Marketing

    10. Market Potential / Gap Analysis

    11. Marketing / Advertising (Billboards/OOH, Marketing Agencies, Indoor Screens)

    12. Customer Profiling

    13. Target Marketing

    14. Market Share Analysis

  10. d

    Wave 72, August 2015

    • search.dataone.org
    • borealisdata.ca
    Updated Dec 28, 2023
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    Ipsos (2023). Wave 72, August 2015 [Dataset]. http://doi.org/10.5683/SP2/V5MLOQ
    Explore at:
    Dataset updated
    Dec 28, 2023
    Dataset provided by
    Borealis
    Authors
    Ipsos
    Time period covered
    Aug 1, 2018
    Description

    Ipsos Global @dvisor wave 72 was conducted from July 24 - August 7, 2015. It included the following question sections: A: Demographic Profile, B: Consumer Confidence, R: Small Business/Executive Decision Makers Demo; KN: Euro Questions; BM: Social Issues.

  11. d

    Wave 52, December 2013

    • search.dataone.org
    • borealisdata.ca
    • +1more
    Updated Dec 28, 2023
    + more versions
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    Ipsos (2023). Wave 52, December 2013 [Dataset]. http://doi.org/10.5683/SP2/XWTM8Q
    Explore at:
    Dataset updated
    Dec 28, 2023
    Dataset provided by
    Borealis
    Authors
    Ipsos
    Time period covered
    Dec 1, 2013
    Description

    Ipsos Global @dvisor wave 52 was conducted on December 3 and December 17, 2013. It included the following question sections: A: Demographic Profile, B: Consumer Confidence, R: Small Business/Executive Decision Makers Demo, FV: Christmas Questions.

  12. d

    Demographic, Social, Economic, and Housing Profiles by Community...

    • catalog.data.gov
    • data.cityofnewyork.us
    • +3more
    Updated Nov 1, 2024
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    data.cityofnewyork.us (2024). Demographic, Social, Economic, and Housing Profiles by Community District/PUMA [Dataset]. https://catalog.data.gov/dataset/demographic-social-economic-and-housing-profiles-by-community-district-puma
    Explore at:
    Dataset updated
    Nov 1, 2024
    Dataset provided by
    data.cityofnewyork.us
    Description

    Selected demographic, social, economic, and housing estimates data by community district/PUMA (Public Use Micro Data Sample Area). Three year estimates of population data from the Census Bureau's American Community Survey

  13. d

    Wave 69, May 2015

    • search.dataone.org
    • borealisdata.ca
    Updated Dec 28, 2023
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    Ipsos (2023). Wave 69, May 2015 [Dataset]. http://doi.org/10.5683/SP2/QUHO2R
    Explore at:
    Dataset updated
    Dec 28, 2023
    Dataset provided by
    Borealis
    Authors
    Ipsos
    Time period covered
    May 1, 2015
    Description

    Ipsos Global @dvisor wave 69 was conducted from April 24 - May 8, 2015. It included the following question sections: A: Demographic Profile, B: Consumer Confidence, R: Small Business/Executive Decision Makers Demo; KI: Military Perils; HF2: Same Sex Marriage.

  14. d

    Wave 33, May 2012

    • search.dataone.org
    • borealisdata.ca
    Updated Dec 28, 2023
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    Ipsos (2023). Wave 33, May 2012 [Dataset]. http://doi.org/10.5683/SP2/N8HJT7
    Explore at:
    Dataset updated
    Dec 28, 2023
    Dataset provided by
    Borealis
    Authors
    Ipsos
    Time period covered
    May 1, 2012
    Description

    Ipsos Global @dvisor wave 33 was conducted on May 1 and May 15, 2012. It included the following question sections: A: Demographic Profile, B: Consumer Confidence, R: Reuters Battery, EV: Energy Barometer, EW: Healthcare, EX: Debt.

  15. M

    Profile of General Demographic Characteristics for Census Tracts: 2000

    • gisdata.mn.gov
    • data.wu.ac.at
    fgdb, html, shp
    Updated Jul 9, 2020
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    Metropolitan Council (2020). Profile of General Demographic Characteristics for Census Tracts: 2000 [Dataset]. https://gisdata.mn.gov/dataset/us-mn-state-metc-society-census-genchar-trct2000
    Explore at:
    html, shp, fgdbAvailable download formats
    Dataset updated
    Jul 9, 2020
    Dataset provided by
    Metropolitan Council
    Description

    Summary File 1 Data Profile 1 (SF1 Table DP-1) for Census Tracts in the Minneapolis-St. Paul 7 County metropolitan area is a subset of the profile of general demographic characteristics for 2000 prepared by the U.S. Census Bureau.

    This table (DP-1) includes: Sex and Age, Race, Race alone or in combination with one or more otehr races, Hispanic or Latino and Race, Relationship, Household by Type, Housing Occupancy, Housing Tenure

    US Census 2000 Demographic Profiles: 100-percent and Sample Data

    The profile includes four tables (DP-1 thru DP-4) that provide various demographic, social, economic, and housing characteristics for the United States, states, counties, minor civil divisions in selected states, places, metropolitan areas, American Indian and Alaska Native areas, Hawaiian home lands and congressional districts (106th Congress). It includes 100-percent and sample data from Census 2000. The DP-1 table is available as part of the Summary File 1 (SF 1) dataset, and the other three tables are available as part of the Summary File 3 (SF 3) dataset.

    The US Census provides DP-1 thru DP-4 data at the Census tract level through their DataFinder search engine. However, since the Metropolitan Council and MetroGIS participants are interested in all Census tracts within the seven county metropolitan area, it was quicker to take the raw Census SF-1 and SF-3 data at tract levels and recreate the DP1-4 variables using the appropriate formula for each DP variable. This file lists the formulas used to create the DP variables.

  16. d

    Demographic Profiles of ACS 5 Year Estimates at the Public Use Microdata...

    • datasets.ai
    • data.cityofnewyork.us
    • +2more
    57
    Updated Aug 7, 2024
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    City of New York (2024). Demographic Profiles of ACS 5 Year Estimates at the Public Use Microdata Areas (PUMA) Level [Dataset]. https://datasets.ai/datasets/demographic-profiles-of-acs-5-year-estimates-at-the-public-use-microdata-areas-puma-level
    Explore at:
    57Available download formats
    Dataset updated
    Aug 7, 2024
    Dataset authored and provided by
    City of New York
    Description

    Four tables of ACS demographic profiles for 2012 to 2016 at the PUMA level. Four profiles include demographics, economic, housing and sociological. Column headers in this database are abbreviated. Please see the data dictionary (shown in worksheet entitled “Dictionary”) for an explanation of these abbreviated headers.

  17. SIXT brand profile in the United States 2022

    • statista.com
    Updated Jul 10, 2025
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    Statista (2025). SIXT brand profile in the United States 2022 [Dataset]. https://www.statista.com/forecasts/1335139/sixt-car-rental-brand-profile-in-the-united-states
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    Dataset updated
    Jul 10, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    Aug 9, 2022 - Aug 15, 2022
    Area covered
    United States
    Description

    How high is the brand awareness of SIXT in the United States?When it comes to car rental customers, brand awareness of SIXT is at **% in the United States. The survey was conducted using the concept of aided brand recognition, showing respondents both the brand's logo and the written brand name.How popular is SIXT in the United States?In total, *% of U.S. car rental customers say they like SIXT. However, in actuality, among the **% of U.S. respondents who know SIXT, **% of people like the brand.What is the usage share of SIXT in the United States?All in all, *% of car rental customers in the United States use SIXT. That means, of the **% who know the brand, **% use them.How loyal are the customers of SIXT?Around *% of car rental customers in the United States say they are likely to use SIXT again. Set in relation to the *% usage share of the brand, this means that **% of their customers show loyalty to the brand.What's the buzz around SIXT in the United States?In August 2022, about *% of U.S. car rental customers had heard about SIXT in the media, on social media, or in advertising over the past three months. Of the **% who know the brand, that's **%, meaning at the time of the survey there's little buzz around SIXT in the United States.If you want to compare brands, do deep-dives by survey items of your choice, filter by total online population or users of a certain brand, or drill down on your very own hand-tailored target groups, our Consumer Insights Brand KPI survey has you covered.

  18. d

    pass_by Consumer Demographic Data | USA | 93% retail coverage

    • datarade.ai
    .json, .csv
    Updated Jul 1, 2024
    + more versions
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    pass_by (2024). pass_by Consumer Demographic Data | USA | 93% retail coverage [Dataset]. https://datarade.ai/data-products/consumer-demographic-data-usa-coverage-95-inside-mall-co-passby-technologies-limited
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    .json, .csvAvailable download formats
    Dataset updated
    Jul 1, 2024
    Dataset authored and provided by
    pass_by
    Area covered
    United States
    Description

    This product provides a monthly breakdown of the shopper profile for individual Points of Interest (POI), offering invaluable insight into the characteristics of who is visiting that location each month. It includes aggregated psychographic and demographic attributes such as age, gender, income level, lifestyle segments, and other key behavioral indicators. Furthermore, it surfaces the distribution of home ZIP codes, illustrating the geographic origins of visitors, and highlights other brands and POIs those same visitors also frequent during the month, revealing broader consumer behavior.

    All metrics are consistently expressed as a percentage share of total visits to the POI in that month. This standardized approach allows for robust month-over-month comparison and precise audience trend analysis. Users can therefore comprehensively understand how the composition of shoppers is changing over time, where they live, what defines their consumer preferences, and how they behave across the wider retail landscape.

    The data is fully anonymized and aggregated, with no access to individual-level or device-level records. It is delivered monthly and is commonly utilized for in-depth audience profiling, strategic market segmentation, powerful brand affinity analysis, and informed strategic decision-making

  19. Facebook: distribution of global audiences 2025, by age and gender

    • statista.com
    Updated Jun 19, 2025
    + more versions
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    Statista (2025). Facebook: distribution of global audiences 2025, by age and gender [Dataset]. https://www.statista.com/statistics/376128/facebook-global-user-age-distribution/
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    Dataset updated
    Jun 19, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    Feb 2025
    Area covered
    Worldwide
    Description

    As of February 2025, it was found that men between the ages of 25 and 34 years made up Facebook's largest audience, accounting for 18.5 percent of global users. Additionally, Facebook's second-largest audience base could be found with men aged 18 to 24 years. Facebook connects the world Founded in 2004 and going public in 2012, Facebook is one of the biggest internet companies in the world with influence that goes beyond social media. It is widely considered as one of the Big Four tech companies, along with Google, Apple, and Amazon (all together known under the acronym GAFA). Facebook is the most popular social network worldwide and the company also owns three other billion-user properties: mobile messaging apps WhatsApp and Facebook Messenger, as well as photo-sharing app Instagram. Facebook usersThe vast majority of Facebook users connect to the social network via mobile devices. This is unsurprising, as Facebook has many users in mobile-first online markets. Currently, India ranks first in terms of Facebook audience size with 378 million users. The United States, Brazil, and Indonesia also all have more than 100 million Facebook users each.

  20. Decennial Census: Summary File 3 Demographic Profile

    • catalog.data.gov
    • res1catalogd-o-tdatad-o-tgov.vcapture.xyz
    Updated Jul 19, 2023
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    U.S. Census Bureau (2023). Decennial Census: Summary File 3 Demographic Profile [Dataset]. https://catalog.data.gov/dataset/decennial-census-summary-file-3-demographic-profile
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    Dataset updated
    Jul 19, 2023
    Dataset provided by
    United States Census Bureauhttp://census.gov/
    Description

    The census of population and housing, taken by the Census Bureau in years ending in 0 (zero). Article I of the Constitution requires that a census be taken every ten years for the purpose of reapportioning the U.S. House of Representatives. Title 13 of the U. S. Code provides the authorization for conducting the census in Puerto Rico and the Island Areas. After each decennial census, the results are released to the public in a variety of ways, including publishing multiple series of reports titled Census of Population and Housing. The abbreviation for these reports was CPH for some decades (including 1990 and 2010) and PHC for some decades (including 1970 and 2000).

Share
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Giant Partners (2022). US Consumer Marketing Data - 269M+ Consumer Records - 95% Email and Direct Dials Accuracy [Dataset]. https://datarade.ai/data-products/consumer-business-data-postal-phone-email-demographics-giant-partners

US Consumer Marketing Data - 269M+ Consumer Records - 95% Email and Direct Dials Accuracy

Explore at:
Dataset updated
Jun 1, 2022
Dataset authored and provided by
Giant Partners
Area covered
United States
Description

Premium B2C Consumer Database - 269+ Million US Records

Supercharge your B2C marketing campaigns with comprehensive consumer database, featuring over 269 million verified US consumer records. Our 20+ year data expertise delivers higher quality and more extensive coverage than competitors.

Core Database Statistics

Consumer Records: Over 269 million

Email Addresses: Over 160 million (verified and deliverable)

Phone Numbers: Over 76 million (mobile and landline)

Mailing Addresses: Over 116,000,000 (NCOA processed)

Geographic Coverage: Complete US (all 50 states)

Compliance Status: CCPA compliant with consent management

Targeting Categories Available

Demographics: Age ranges, education levels, occupation types, household composition, marital status, presence of children, income brackets, and gender (where legally permitted)

Geographic: Nationwide, state-level, MSA (Metropolitan Service Area), zip code radius, city, county, and SCF range targeting options

Property & Dwelling: Home ownership status, estimated home value, years in residence, property type (single-family, condo, apartment), and dwelling characteristics

Financial Indicators: Income levels, investment activity, mortgage information, credit indicators, and wealth markers for premium audience targeting

Lifestyle & Interests: Purchase history, donation patterns, political preferences, health interests, recreational activities, and hobby-based targeting

Behavioral Data: Shopping preferences, brand affinities, online activity patterns, and purchase timing behaviors

Multi-Channel Campaign Applications

Deploy across all major marketing channels:

Email marketing and automation

Social media advertising

Search and display advertising (Google, YouTube)

Direct mail and print campaigns

Telemarketing and SMS campaigns

Programmatic advertising platforms

Data Quality & Sources

Our consumer data aggregates from multiple verified sources:

Public records and government databases

Opt-in subscription services and registrations

Purchase transaction data from retail partners

Survey participation and research studies

Online behavioral data (privacy compliant)

Technical Delivery Options

File Formats: CSV, Excel, JSON, XML formats available

Delivery Methods: Secure FTP, API integration, direct download

Processing: Real-time NCOA, email validation, phone verification

Custom Selections: 1,000+ selectable demographic and behavioral attributes

Minimum Orders: Flexible based on targeting complexity

Unique Value Propositions

Dual Spouse Targeting: Reach both household decision-makers for maximum impact

Cross-Platform Integration: Seamless deployment to major ad platforms

Real-Time Updates: Monthly data refreshes ensure maximum accuracy

Advanced Segmentation: Combine multiple targeting criteria for precision campaigns

Compliance Management: Built-in opt-out and suppression list management

Ideal Customer Profiles

E-commerce retailers seeking customer acquisition

Financial services companies targeting specific demographics

Healthcare organizations with compliant marketing needs

Automotive dealers and service providers

Home improvement and real estate professionals

Insurance companies and agents

Subscription services and SaaS providers

Performance Optimization Features

Lookalike Modeling: Create audiences similar to your best customers

Predictive Scoring: Identify high-value prospects using AI algorithms

Campaign Attribution: Track performance across multiple touchpoints

A/B Testing Support: Split audiences for campaign optimization

Suppression Management: Automatic opt-out and DNC compliance

Pricing & Volume Options

Flexible pricing structures accommodate businesses of all sizes:

Pay-per-record for small campaigns

Volume discounts for large deployments

Subscription models for ongoing campaigns

Custom enterprise pricing for high-volume users

Data Compliance & Privacy

VIA.tools maintains industry-leading compliance standards:

CCPA (California Consumer Privacy Act) compliant

CAN-SPAM Act adherence for email marketing

TCPA compliance for phone and SMS campaigns

Regular privacy audits and data governance reviews

Transparent opt-out and data deletion processes

Getting Started

Our data specialists work with you to:

  1. Define your target audience criteria

  2. Recommend optimal data selections

  3. Provide sample data for testing

  4. Configure delivery methods and formats

  5. Implement ongoing campaign optimization

Why We Lead the Industry

With over two decades of data industry experience, we combine extensive database coverage with advanced targeting capabilities. Our commitment to data quality, compliance, and customer success has made us the preferred choice for businesses seeking superior B2C marketing performance.

Contact our team to discuss your specific targeting requirements and receive custom pricing for your marketing objectives.

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