PID | HHID | FNAME | MNAME | LNAME | SUFFIX | GENDER | AGE | DOB | ADDRID | ADDRESS | HOUSE | PREDIR | STREET | STRTYPE | POSTDIR | APTTYPE | APTNBR | CITY | STATE | ZIP | Z4 | DPC | Z4TYPE | CRTE | DPV | VACANT | INTERNAL | INTERNAL2 | INTERNAL3 | MSA | CBSA | STATECD | CNTYCD | CENSUSTRACT | CENSUSBLCK | CNTYSIZECD | LATITUDE | LONGITUDE | GEOLEVEL | PHONE | DNC | PHONE2 | DNC2 | PHONE3 | DNC3 | LOR | HOMEOWNERCD | DWELLTYPE | EHI | MARRIEDCD | SGLPARENT | HHNBRSR | HHNBR | SPANISHSPCD | SOHOCD | VETERANCD | CREDITCARD | WEALTHSCR | CHARITYDNR | MRKTHOMEVAL | EDUCATIONCD | OCCUPATIONCD | ETHNICITYCD | RELIGIONCD | LANGUAGECD | CHILD | CHILDAGECD_6 | CHILDAGECD_6_10 | CHILDAGECD_11_15 | CHILDAGECD_16_17 | CHILDNBRCD | YRBLD | MOBHOMECD | POOL | FIREPLCD | MS_ACCESSORY | MS_APPAREL | MS_AUDIO | MS_AUTO | MS_AVIATION | MS_BARGAINS | MS_BIBLE | MS_BOATSAIL | MS_BOOKS | MS_BUSINESS | MS_CAMP | MS_CATALOG | MS_COLLECTIBLES | MS_COMPUTERS | MS_COOKING | MS_BEAUTY | MS_CRAFTS | MS_CULTUREARTS | MS_CURREVENT | MS_DIY | MS_ELECTRONICS | MS_EQUESTRIAN | MS_FAMILY | MS_FICTION | MS_FISHING | MS_FITNESS | MS_FOOD | MS_FUNDRAISING | MS_GAMES | MS_GARDEN | MS_MERCHANDISE | MS_GIFTGIVR | MS_GIFTEE | MS_GIFTS | MS_GOURMET | MS_HEALTH | MS_HISTORY | MS_HOLIDAY | MS_HOMEDECR | MS_HOMELIV | MS_HOUSEWARES | MS_HUMOR | MS_HUNTING | MS_INSPIRATION | MS_KIDAPP | MS_MAGS | MS_MENAPP | MS_MOTORCYCLES | MS_MUSIC | MS_MONEYMAKING | MS_OUTDOORS | MS_PFIN | MS_PETS | MS_PHOTOPROC | MS_PHOTO | MS_PUBLISH | MS_PUB_COOKING | MS_PUB_FAMILY | MS_PUB_GARDEN | MS_PUB_GIFTGIVR | MS_PUB_GIFTEE | MS_PUB_HOMEDECR | MS_PUB_HOMELIV | MS_PUB_OUTDOORS | MS_SCIENCE | MS_SPORTS | MS_TRAVEL | MS_TVMOVIES | MS_WILDLIFE | MS_WOMAN | MS_WOMAPP | MS_WOMFASH | CPI_HISTORY_AMERICAN_INDEX | CPI_APPAREL_INDEX | CPI_APPAREL_ACCESSORY_INDEX | CPI_APPAREL_KIDS_INDEX | CPI_APPAREL_MEN_INDEX | CPI_APPAREL_MENFASH_INDEX | CPI_APPAREL_WOMEN_INDEX | CPI_APPAREL_WOMFASH_INDEX | CPI_INSURANCE_AUTO_INDEX | CPI_AUTO_TRUCKS_INDEX | CPI_AUTO_INDEX | CPI_AVIATION_INDEX | CPI_BARGAINS_INDEX | CPI_BEAUTY_INDEX | CPI_BIBLE_INDEX | CPI_PUBLISH_BOOKS_INDEX | CPI_BUSINESS_INDEX | CPI_BUSINESS_HOMEOFFICE_INDEX | CPI_CATALOG_INDEX | CPI_DONOR_INDEX | CPI_FAMILY_INDEX | CPI_FAMILY_TEEN_INDEX | CPI_FAMILY_YOUNG_INDEX | CPI_COLLECTIBLES_INDEX | CPI_COLLEGE_INDEX | CPI_COMPUTERS_INDEX | CPI_CONTINUITY_INDEX | CPI_COOKING_INDEX | CPI_CRAFTS_INDEX | CPI_CRAFTS_CROCHET_INDEX | CPI_CRAFTS_KNIT_INDEX | CPI_CRAFTS_NEEDLEPOINT_INDEX | CPI_CRAFTS_QUILT_INDEX | CPI_CRAFTS_SEW_INDEX | CPI_CC_INDEX | CPI_CREDIT_REPAIR_INDEX | CPI_CREDIT_REPORT_INDEX | CPI_CULTUREARTS_INDEX | CPI_CURREVENT_INDEX | CPI_DIY_INDEX | CPI_EDUCATION_SEEKERS_INDEX | CPI_ELECTRONICS_INDEX | CPI_FICTION_INDEX | CPI_GAMBLING_INDEX | CPI_GAMES_INDEX | CPI_GARDENING_INDEX | CPI_GIFTGIVR_INDEX | CPI_GOURMET_INDEX | CPI_HEALTH_INDEX | CPI_INSURANCE_HEALTH_INDEX | CPI_HEALTH_DIET_INDEX | CPI_HEALTH_FITNESS_INDEX | CPI_HIGHTECH_INDEX | CPI_HISPANIC_INDEX | CPI_HISTORY_INDEX | CPI_HOBBIES_INDEX | CPI_HOMEDECR_INDEX | CPI_HOMELIV_INDEX | CPI_EQUESTRIAN_INDEX | CPI_INSPIRATION_INDEX | CPI_INSURANCE_INDEX | CPI_INTERNET_ACCESS_INDEX | CPI_INTERNET_BUY_INDEX | CPI_INTERNET_INDEX | CPI_JOB_SEEKERS_INDEX | CPI_PUBLISH_MAGS_INDEX | CPI_PUBLISH_INDEX | CPI_MOBILE_APPS_INDEX | CPI_MOTORCYCLES_INDEX | CPI_MUSIC_INDEX | CPI_NONFICTION_INDEX | CPI_MONEYMAKING_INDEX | CPI_OUTDOORS_INDEX | CPI_OUTDOORS_BOATSAIL_INDEX | CPI_OUTDOORS_CAMP_INDEX | CPI_OUTDOORS_FISHING_INDEX | CPI_OUTDOORS_HUNTING_INDEX | CPI_OUTDOORS_HUNTFISH_INDEX | CPI_PFIN_INDEX | CPI_EGO_INDEX | CPI_PETS_INDEX | CPI_PETS_CATS_INDEX | CPI_PETS_DOGS_INDEX | CPI_PHOTOPROC_INDEX | CPI_PHOTOG_INDEX | CPI_CONSERVATIVE_INDEX | CPI_LIBERAL_INDEX | CPI_SOCIAL_NETWORKING_INDEX | CPI_SPORTS_INDEX | CPI_SPORTS_BASEBALL_INDEX | CPI_SPORTS_BASKETBALL_INDEX | CPI_SPORTS_BIKING_INDEX | CPI_SPORTS_FOOTBALL_INDEX | CPI_SPORTS_GOLF_INDEX | CPI_SPORTS_HOCKEY_INDEX | CPI_SPORTS_RUNNING_INDEX | CPI_SPORTS_SKI_INDEX | CPI_SPORTS_SOCCER_INDEX | CPI_SPORTS_SWIMMING_INDEX | CPI_SPORTS_TENNIS_INDEX | CPI_SWEEPS_INDEX | CPI_TRAVEL_INDEX | CPI_TRAVEL_CRUISE_INDEX | CPI_TRAVEL_RV_INDEX | CPI_TRAVEL_US_INDEX | CPI_TVMOVIES_INDEX | CPI_WILDLIFE_INDEX | HHCLSTRDCD | NEIGHBORHOOD_CLSTRDCD | FMCLSTRDCD | MESSAGING_CLSTRDCD | DIGITALCLSTRDCD | GENERATION_CLSTRDCD | GENERATION_GRPCD | LIFESTG_CLSTRD | LIFESTG_GRPCD | CT_MEDIA_HEAVYUSAGE_MAGAZINE | CT_MEDIA_HEAVYUSAGE_NEWSPAPER | CT_MEDIA_HEAVYUSAGE_RADIO | CT_MEDIA_HEAVYUSAGE_PTRADIO | CT_MEDIA_HEAVYUSAGE_TV | CT_MEDIA_HEAVYUSAGE_INTERNET | CT_MEDIA_HEAVYUSAGE_ODRMDA | CT_SOCIALUSAGE30_FB | CT_SOCIALUSAGE30_INSTA | CT_SOCIALUSAGE30_LNKIN | CT_SOCIALUSAGE30_PINT | CT_SOCIALUSAGE30_TWITTER | CT_SOCIALUSAGE30_YOUTUBE | CT_STRMSUB_PRIME | CT_STRMSUB_HULU | CT_STRMSUB_NETFLIX | CT_SMRTPHN_TYPEOWNS_ANDROID | CT_SMRTPHN_TYPEOWNS_IPHONE | CT_HOMEIMPROVE12_ANY | CT_HOMEREMODEL12_ANY | CT_POLITICAL_PARTYAFF_DEMOCRAT | CT_POLITICAL_PARTYAFF_GOP | CT_POLITICAL_PARTYAFF_IND | CT_POLITICAL_OUTLK_VCONSERV | CT_POLITICAL_OUTLK_SWCONSERV | CT_POLITICAL_OUTLK_MID | CT_POLITICAL_OUTLK_SWLIBERAL | CT_POLITICAL_OUTLK_VLIBERAL | CT_ONLINESHOPSEG_OFFLINE | CT_ONLINESHOPSEG_TRAD | CT_ONLINESHOPSEG_STRAITFWD | CT_ONLINESHOPSEG_DEALSEEK | CT_ONLINESHOPSEG_QUALSEEK | CT_TECHTUDESEG_PHOBES | CT_TECHTUDESEG_LAGGRDS | CT_TECHTUDESEG_XPLOIT | CT_TECHTUDESEG_GAMER | CT_TECHTUDESEG_THUSIAST | CT_TECHTUDESEG_XPLOR | CT_DNR_CONTRIB_PBS | CT_DNR_CONTRIB_NPR | CT_DNR_CONTRIB_RELIGIOUS | CT_DNR_CONTRIB_ARTS | CT_DNR_CONTRIB_EDU | CT_DNR_CONTRIB_ENVIRO | CT_DNR_CONTRIB_HEALTH | CT_DNR_CONTRIB_POL | CT_DNR_CONTRIB_SOCSERV | CT_DNR_CONTRIB_NONREL | CT_DNR_CONTRIBAMT_HIGH | CT_VOLUNTEER_CHTYORG | CENSPCT_WATER | CENS_POP_DENSITY | CENS_HU_DENSITY | CENSPCT_POP_WHITE | CENSPCT_POP_BLACK | CENSPCT_POP_AMERIND | CENSPCT_POP_ASIAN | CENSPCT_POP_PACISL | CENSPCT_POP_OTHRACE | CENSPCT_POP_MULTIRACE | CENSPCT_POP_HISPANIC | CENSPCT_POP_AGELT18 | CENSPCT_POP_MALES | CENSPCT_ADULT_AGE1824 | CENSPCT_ADULT_AGE2534 | CENSPCT_ADULT_AGE3544 | CENSPCT_ADULT_AGE4554 | CENSPCT_ADULT_AGE5564 | CENSPCT_ADULT_AGEGE65 | CENS_POP_MEDAGE | CENS_HH_AVGSIZE | CENSPCT_HH_FAMILY | CENSPCT_HH_FAMILY_HUSBWIFE | CENSPCT_HU_OCCUPIED | CENSPCT_HU_OWNED | CENSPCT_HU_RENTED | CENSPCT_HU_VACANTSEASONAL | EHI_V2 | OCCUPATIONCD_V2 |
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Attribute | Type | Example |
---|---|---|
PID | String | C7E98C2E88B45E44D4192E5D0CEC68F1 |
HHID | String | 3BDC62AA2AFC2024C49AFAE0E5E89C8E850E41EBBD21F339992F894E65381BA5E16A69B379D83460486DBF100A7C409E |
FNAME | String | SINDY |
MNAME | Boolean | f |
LNAME | String | REED |
SUFFIX | ||
GENDER | Boolean | f |
AGE | Integer | 66 |
DOB | Integer | 195705 |
ADDRID | Integer | 224262685 |
ADDRESS | String | 1145 4TH WAY |
HOUSE | Integer | 1145 |
PREDIR | ||
STREET | String | 4TH |
STRTYPE | String | WAY |
POSTDIR | ||
APTTYPE | ||
APTNBR | ||
CITY | String | NORTH FORT MYERS |
STATE | String | FL |
ZIP | Integer | 33903 |
Z4 | Integer | 4441 |
DPC | Integer | 450 |
Z4TYPE | String | S |
CRTE | String | C031 |
DPV | Boolean | t |
VACANT | Boolean | f |
INTERNAL | ||
INTERNAL2 | ||
INTERNAL3 | ||
MSA | Integer | 2700 |
CBSA | Integer | 15980 |
STATECD | Integer | 12 |
CNTYCD | Integer | 71 |
CENSUSTRACT | Integer | 20600 |
CENSUSBLCK | Integer | 5004 |
CNTYSIZECD | String | B |
LATITUDE | Float | 26.665745 |
LONGITUDE | Float | -81.880837 |
GEOLEVEL | Integer | 1 |
PHONE | ||
DNC | ||
PHONE2 | ||
DNC2 | ||
PHONE3 | ||
DNC3 | ||
LOR | Integer | 7 |
HOMEOWNERCD | String | U |
DWELLTYPE | String | S |
EHI | String | B |
MARRIEDCD | String | S |
SGLPARENT | ||
HHNBRSR | ||
HHNBR | Integer | 1 |
SPANISHSPCD | ||
SOHOCD | ||
VETERANCD | ||
CREDITCARD | ||
WEALTHSCR | String | E |
CHARITYDNR | ||
MRKTHOMEVAL | String | A |
EDUCATIONCD | String | A |
OCCUPATIONCD | ||
ETHNICITYCD | ||
RELIGIONCD | ||
LANGUAGECD | ||
CHILD | ||
CHILDAGECD_6 | ||
CHILDAGECD_6_10 | ||
CHILDAGECD_11_15 | ||
CHILDAGECD_16_17 | ||
CHILDNBRCD | ||
YRBLD | ||
MOBHOMECD | ||
POOL | ||
FIREPLCD | ||
MS_ACCESSORY | Integer | 0 |
MS_APPAREL | Integer | 0 |
MS_AUDIO | Integer | 0 |
MS_AUTO | Integer | 0 |
MS_AVIATION | Integer | 0 |
MS_BARGAINS | Integer | 0 |
MS_BIBLE | Integer | 0 |
MS_BOATSAIL | Integer | 0 |
MS_BOOKS | Integer | 0 |
MS_BUSINESS | Integer | 0 |
MS_CAMP | Integer | 0 |
MS_CATALOG | Integer | 0 |
MS_COLLECTIBLES | Integer | 0 |
MS_COMPUTERS | Integer | 0 |
MS_COOKING | Integer | 0 |
MS_BEAUTY | Integer | 0 |
MS_CRAFTS | Integer | 0 |
MS_CULTUREARTS | Integer | 0 |
MS_CURREVENT | Integer | 0 |
MS_DIY | Integer | 0 |
MS_ELECTRONICS | Integer | 0 |
MS_EQUESTRIAN | Integer | 0 |
MS_FAMILY | Integer | 0 |
MS_FICTION | Integer | 0 |
MS_FISHING | Integer | 0 |
MS_FITNESS | Integer | 0 |
MS_FOOD | Integer | 0 |
MS_FUNDRAISING | Integer | 0 |
MS_GAMES | Integer | 0 |
MS_GARDEN | Integer | 0 |
MS_MERCHANDISE | Integer | 0 |
MS_GIFTGIVR | Integer | 0 |
MS_GIFTEE | Integer | 0 |
MS_GIFTS | Integer | 0 |
MS_GOURMET | Integer | 0 |
MS_HEALTH | Integer | 0 |
MS_HISTORY | Integer | 0 |
MS_HOLIDAY | Integer | 0 |
MS_HOMEDECR | Integer | 0 |
MS_HOMELIV | Integer | 0 |
MS_HOUSEWARES | Integer | 0 |
MS_HUMOR | Integer | 0 |
MS_HUNTING | Integer | 0 |
MS_INSPIRATION | Integer | 0 |
MS_KIDAPP | Integer | 0 |
MS_MAGS | Integer | 1 |
MS_MENAPP | Integer | 0 |
MS_MOTORCYCLES | Integer | 0 |
MS_MUSIC | Integer | 0 |
MS_MONEYMAKING | Integer | 1 |
MS_OUTDOORS | Integer | 0 |
MS_PFIN | Integer | 0 |
MS_PETS | Integer | 0 |
MS_PHOTOPROC | Integer | 0 |
MS_PHOTO | Integer | 0 |
MS_PUBLISH | Integer | 1 |
MS_PUB_COOKING | Integer | 0 |
MS_PUB_FAMILY | Integer | 0 |
MS_PUB_GARDEN | Integer | 0 |
MS_PUB_GIFTGIVR | Integer | 0 |
MS_PUB_GIFTEE | Integer | 0 |
MS_PUB_HOMEDECR | Integer | 0 |
MS_PUB_HOMELIV | Integer | 0 |
MS_PUB_OUTDOORS | Integer | 0 |
MS_SCIENCE | Integer | 0 |
MS_SPORTS | Integer | 0 |
MS_TRAVEL | Integer | 0 |
MS_TVMOVIES | Integer | 0 |
MS_WILDLIFE | Integer | 0 |
MS_WOMAN | Integer | 0 |
MS_WOMAPP | Integer | 0 |
MS_WOMFASH | Integer | 0 |
CPI_HISTORY_AMERICAN_INDEX | Integer | 0 |
CPI_APPAREL_INDEX | Integer | 0 |
CPI_APPAREL_ACCESSORY_INDEX | Integer | 0 |
CPI_APPAREL_KIDS_INDEX | Integer | 0 |
CPI_APPAREL_MEN_INDEX | Integer | 0 |
CPI_APPAREL_MENFASH_INDEX | Integer | 0 |
CPI_APPAREL_WOMEN_INDEX | Integer | 0 |
CPI_APPAREL_WOMFASH_INDEX | Integer | 0 |
CPI_INSURANCE_AUTO_INDEX | Integer | 0 |
CPI_AUTO_TRUCKS_INDEX | Integer | 0 |
CPI_AUTO_INDEX | Integer | 4 |
CPI_AVIATION_INDEX | Integer | 0 |
CPI_BARGAINS_INDEX | Integer | 0 |
CPI_BEAUTY_INDEX | Integer | 0 |
CPI_BIBLE_INDEX | Integer | 4 |
CPI_PUBLISH_BOOKS_INDEX | Integer | 2 |
CPI_BUSINESS_INDEX | Integer | 2 |
CPI_BUSINESS_HOMEOFFICE_INDEX | Integer | 3 |
CPI_CATALOG_INDEX | Integer | 1 |
CPI_DONOR_INDEX | Integer | 3 |
CPI_FAMILY_INDEX | Integer | 2 |
CPI_FAMILY_TEEN_INDEX | Integer | 0 |
CPI_FAMILY_YOUNG_INDEX | Integer | 0 |
CPI_COLLECTIBLES_INDEX | Integer | 4 |
CPI_COLLEGE_INDEX | Integer | 0 |
CPI_COMPUTERS_INDEX | Integer | 0 |
CPI_CONTINUITY_INDEX | Integer | 0 |
CPI_COOKING_INDEX | Integer | 1 |
CPI_CRAFTS_INDEX | Integer | 6 |
CPI_CRAFTS_CROCHET_INDEX | Integer | 0 |
CPI_CRAFTS_KNIT_INDEX | Integer | 9 |
CPI_CRAFTS_NEEDLEPOINT_INDEX | Integer | 0 |
CPI_CRAFTS_QUILT_INDEX | Integer | 0 |
CPI_CRAFTS_SEW_INDEX | Integer | 0 |
CPI_CC_INDEX | Integer | 0 |
CPI_CREDIT_REPAIR_INDEX | Integer | 0 |
CPI_CREDIT_REPORT_INDEX | Integer | 0 |
CPI_CULTUREARTS_INDEX | Integer | 5 |
CPI_CURREVENT_INDEX | Integer | 0 |
CPI_DIY_INDEX | Integer | 6 |
CPI_EDUCATION_SEEKERS_INDEX | Integer | 0 |
CPI_ELECTRONICS_INDEX | Integer | 0 |
CPI_FICTION_INDEX | Integer | 0 |
CPI_GAMBLING_INDEX | Integer | 0 |
CPI_GAMES_INDEX | Integer | 0 |
CPI_GARDENING_INDEX | Integer | 2 |
CPI_GIFTGIVR_INDEX | Integer | 0 |
CPI_GOURMET_INDEX | Integer | 0 |
CPI_HEALTH_INDEX | Integer | 1 |
CPI_INSURANCE_HEALTH_INDEX | Integer | 0 |
CPI_HEALTH_DIET_INDEX | Integer | 6 |
CPI_HEALTH_FITNESS_INDEX | Integer | 4 |
CPI_HIGHTECH_INDEX | Integer | 0 |
CPI_HISPANIC_INDEX | Integer | 0 |
CPI_HISTORY_INDEX | Integer | 0 |
CPI_HOBBIES_INDEX | Integer | 6 |
CPI_HOMEDECR_INDEX | Integer | 1 |
CPI_HOMELIV_INDEX | Integer | 1 |
CPI_EQUESTRIAN_INDEX | Integer | 0 |
CPI_INSPIRATION_INDEX | Integer | 0 |
CPI_INSURANCE_INDEX | Integer | 0 |
CPI_INTERNET_ACCESS_INDEX | Integer | 7 |
CPI_INTERNET_BUY_INDEX | Integer | 6 |
CPI_INTERNET_INDEX | Integer | 7 |
CPI_JOB_SEEKERS_INDEX | Integer | 0 |
CPI_PUBLISH_MAGS_INDEX | Integer | 5 |
CPI_PUBLISH_INDEX | Integer | 5 |
CPI_MOBILE_APPS_INDEX | Integer | 0 |
CPI_MOTORCYCLES_INDEX | Integer | 0 |
CPI_MUSIC_INDEX | Integer | 4 |
CPI_NONFICTION_INDEX | Integer | 0 |
CPI_MONEYMAKING_INDEX | Integer | 5 |
CPI_OUTDOORS_INDEX | Integer | 4 |
CPI_OUTDOORS_BOATSAIL_INDEX | Integer | 0 |
CPI_OUTDOORS_CAMP_INDEX | Integer | 9 |
CPI_OUTDOORS_FISHING_INDEX | Integer | 6 |
CPI_OUTDOORS_HUNTING_INDEX | Integer | 0 |
CPI_OUTDOORS_HUNTFISH_INDEX | Integer | 0 |
CPI_PFIN_INDEX | Integer | 4 |
CPI_EGO_INDEX | Integer | 0 |
CPI_PETS_INDEX | Integer | 3 |
CPI_PETS_CATS_INDEX | Integer | 4 |
CPI_PETS_DOGS_INDEX | Integer | 5 |
CPI_PHOTOPROC_INDEX | Integer | 0 |
CPI_PHOTOG_INDEX | Integer | 6 |
CPI_CONSERVATIVE_INDEX | Integer | 0 |
CPI_LIBERAL_INDEX | Integer | 0 |
CPI_SOCIAL_NETWORKING_INDEX | Integer | 0 |
CPI_SPORTS_INDEX | Integer | 2 |
CPI_SPORTS_BASEBALL_INDEX | Integer | 0 |
CPI_SPORTS_BASKETBALL_INDEX | Integer | 9 |
CPI_SPORTS_BIKING_INDEX | Integer | 0 |
CPI_SPORTS_FOOTBALL_INDEX | Integer | 8 |
CPI_SPORTS_GOLF_INDEX | Integer | 0 |
CPI_SPORTS_HOCKEY_INDEX | Integer | 0 |
CPI_SPORTS_RUNNING_INDEX | Integer | 0 |
CPI_SPORTS_SKI_INDEX | Integer | 0 |
CPI_SPORTS_SOCCER_INDEX | Integer | 0 |
CPI_SPORTS_SWIMMING_INDEX | Integer | 0 |
CPI_SPORTS_TENNIS_INDEX | Integer | 0 |
CPI_SWEEPS_INDEX | Integer | 8 |
CPI_TRAVEL_INDEX | Integer | 7 |
CPI_TRAVEL_CRUISE_INDEX | Integer | 5 |
CPI_TRAVEL_RV_INDEX | Integer | 9 |
CPI_TRAVEL_US_INDEX | Integer | 6 |
CPI_TVMOVIES_INDEX | Integer | 0 |
CPI_WILDLIFE_INDEX | Integer | 0 |
HHCLSTRDCD | ||
NEIGHBORHOOD_CLSTRDCD | Integer | 52 |
FMCLSTRDCD | Boolean | f |
MESSAGING_CLSTRDCD | ||
DIGITALCLSTRDCD | ||
GENERATION_CLSTRDCD | ||
GENERATION_GRPCD | ||
LIFESTG_CLSTRD | ||
LIFESTG_GRPCD | ||
CT_MEDIA_HEAVYUSAGE_MAGAZINE | ||
CT_MEDIA_HEAVYUSAGE_NEWSPAPER | ||
CT_MEDIA_HEAVYUSAGE_RADIO | ||
CT_MEDIA_HEAVYUSAGE_PTRADIO | ||
CT_MEDIA_HEAVYUSAGE_TV | ||
CT_MEDIA_HEAVYUSAGE_INTERNET | ||
CT_MEDIA_HEAVYUSAGE_ODRMDA | ||
CT_SOCIALUSAGE30_FB | ||
CT_SOCIALUSAGE30_INSTA | ||
CT_SOCIALUSAGE30_LNKIN | ||
CT_SOCIALUSAGE30_PINT | ||
CT_SOCIALUSAGE30_TWITTER | ||
CT_SOCIALUSAGE30_YOUTUBE | ||
CT_STRMSUB_PRIME | ||
CT_STRMSUB_HULU | ||
CT_STRMSUB_NETFLIX | ||
CT_SMRTPHN_TYPEOWNS_ANDROID | ||
CT_SMRTPHN_TYPEOWNS_IPHONE | ||
CT_HOMEIMPROVE12_ANY | ||
CT_HOMEREMODEL12_ANY | ||
CT_POLITICAL_PARTYAFF_DEMOCRAT | ||
CT_POLITICAL_PARTYAFF_GOP | ||
CT_POLITICAL_PARTYAFF_IND | ||
CT_POLITICAL_OUTLK_VCONSERV | ||
CT_POLITICAL_OUTLK_SWCONSERV | ||
CT_POLITICAL_OUTLK_MID | ||
CT_POLITICAL_OUTLK_SWLIBERAL | ||
CT_POLITICAL_OUTLK_VLIBERAL | ||
CT_ONLINESHOPSEG_OFFLINE | ||
CT_ONLINESHOPSEG_TRAD | ||
CT_ONLINESHOPSEG_STRAITFWD | ||
CT_ONLINESHOPSEG_DEALSEEK | ||
CT_ONLINESHOPSEG_QUALSEEK | ||
CT_TECHTUDESEG_PHOBES | ||
CT_TECHTUDESEG_LAGGRDS | ||
CT_TECHTUDESEG_XPLOIT | ||
CT_TECHTUDESEG_GAMER | ||
CT_TECHTUDESEG_THUSIAST | ||
CT_TECHTUDESEG_XPLOR | ||
CT_DNR_CONTRIB_PBS | ||
CT_DNR_CONTRIB_NPR | ||
CT_DNR_CONTRIB_RELIGIOUS | ||
CT_DNR_CONTRIB_ARTS | ||
CT_DNR_CONTRIB_EDU | ||
CT_DNR_CONTRIB_ENVIRO | ||
CT_DNR_CONTRIB_HEALTH | ||
CT_DNR_CONTRIB_POL | ||
CT_DNR_CONTRIB_SOCSERV | ||
CT_DNR_CONTRIB_NONREL | ||
CT_DNR_CONTRIBAMT_HIGH | ||
CT_VOLUNTEER_CHTYORG | ||
CENSPCT_WATER | Integer | 18 |
CENS_POP_DENSITY | Integer | 1362 |
CENS_HU_DENSITY | Integer | 961 |
CENSPCT_POP_WHITE | Integer | 93 |
CENSPCT_POP_BLACK | Integer | 2 |
CENSPCT_POP_AMERIND | Integer | 0 |
CENSPCT_POP_ASIAN | Integer | 1 |
CENSPCT_POP_PACISL | Integer | 0 |
CENSPCT_POP_OTHRACE | Integer | 2 |
CENSPCT_POP_MULTIRACE | Integer | 1 |
CENSPCT_POP_HISPANIC | Integer | 9 |
CENSPCT_POP_AGELT18 | Integer | 12 |
CENSPCT_POP_MALES | Integer | 49 |
CENSPCT_ADULT_AGE1824 | Integer | 5 |
CENSPCT_ADULT_AGE2534 | Integer | 7 |
CENSPCT_ADULT_AGE3544 | Integer | 9 |
CENSPCT_ADULT_AGE4554 | Integer | 14 |
CENSPCT_ADULT_AGE5564 | Integer | 19 |
CENSPCT_ADULT_AGEGE65 | Integer | 46 |
CENS_POP_MEDAGE | Integer | 60 |
CENS_HH_AVGSIZE | Integer | 2 |
CENSPCT_HH_FAMILY | Integer | 57 |
CENSPCT_HH_FAMILY_HUSBWIFE | Integer | 46 |
CENSPCT_HU_OCCUPIED | Integer | 72 |
CENSPCT_HU_OWNED | Integer | 56 |
CENSPCT_HU_RENTED | Integer | 15 |
CENSPCT_HU_VACANTSEASONAL | Integer | 16 |
EHI_V2 | String | A |
OCCUPATIONCD_V2 |
Description
Knowing who your consumers are is essential for businesses, marketers, and researchers. This detailed demographic file offers an in-depth look at American consumers, packed with insights about personal details, household information, financial status, and lifestyle choices. Let's take a closer look at the data: Personal Identifiers and Basic Demographics At the heart of this dataset are the key details that make up a consumer profile: Unique IDs (PID, HHID) for individuals and households Full names (First, Middle, Last) and suffixes Gender and age Date of birth Complete location details (address, city, state, ZIP) These identifiers are critical for accurate marketing and form the base for deeper analysis. Geospatial Intelligence This file goes beyond just listing addresses by including rich geospatial data like: Latitude and longitude Census tract and block details Codes for Metropolitan Statistical Areas (MSA) and Core-Based Statistical Areas (CBSA) County size codes Geocoding accuracy This allows for precise geographic segmentation and localized marketing. Housing and Property Data The dataset covers a lot of ground when it comes to housing, providing valuable insights for real estate professionals, lenders, and home service providers: Homeownership status Dwelling type (single-family, multi-family, etc.) Property values (market, assessed, and appraised) Year built and square footage Room count, amenities like fireplaces or pools, and building quality This data is crucial for targeting homeowners with products and services like refinancing or home improvement offers. Wealth and Financial Data For a deeper dive into consumer wealth, the file includes: Estimated household income Wealth scores Credit card usage Mortgage info (loan amounts, rates, terms) Home equity estimates and investment property ownership These indicators are invaluable for financial services, luxury brands, and fundraising organizations looking to reach affluent individuals. Lifestyle and Interests One of the most useful features of the dataset is its extensive lifestyle segmentation: Hobbies and interests (e.g., gardening, travel, sports) Book preferences, magazine subscriptions Outdoor activities (camping, fishing, hunting) Pet ownership, tech usage, political views, and religious affiliations This data is perfect for crafting personalized marketing campaigns and developing products that align with specific consumer preferences. Consumer Behavior and Purchase Habits The file also sheds light on how consumers behave and shop: Online and catalog shopping preferences Gift-giving tendencies, presence of children, vehicle ownership Media consumption (TV, radio, internet) Retailers and e-commerce businesses will find this behavioral data especially useful for tailoring their outreach. Demographic Clusters and Segmentation Pre-built segments like: Household, neighborhood, family, and digital clusters Generational and lifestage groups make it easier to quickly target specific demographics, streamlining the process for market analysis and campaign planning. Ethnicity and Language Preferences In today's multicultural market, knowing your audience's cultural background is key. The file includes: Ethnicity codes and language preferences Flags for Hispanic/Spanish-speaking households This helps ensure culturally relevant and sensitive communication. Education and Occupation Data The dataset also tracks education and career info: Education level and occupation codes Home-based business indicators This data is essential for B2B marketers, recruitment agencies, and education-focused campaigns. Digital and Social Media Habits With everyone online, digital behavior insights are a must: Internet, TV, radio, and magazine usage Social media platform engagement (Facebook, Instagram, LinkedIn) Streaming subscriptions (Netflix, Hulu) This data helps marketers, app developers, and social media managers connect with their audience in the digital space. Political and Charitable Tendencies For political campaigns or non-profits, this dataset offers: Political affiliations and outlook Charitable donation history Volunteer activities These insights are perfect for cause-related marketing and targeted political outreach. Neighborhood Characteristics By incorporating census data, the file provides a bigger picture of the consumer's environment: Population density, racial composition, and age distribution Housing occupancy and ownership rates This offers important context for understanding the demographic landscape. Predictive Consumer Indexes The dataset includes forward-looking indicators in categories like: Fashion, automotive, and beauty products Health, home decor, pet products, sports, and travel These predictive insights help businesses anticipate consumer trends and needs. Contact Information Finally, the file includes key communication details: Multiple phone numbers (landline, mobile) and email addresses Do Not Call (DNC) flags This ensures effective and compliant outreach across channels. Data Quality and Confidence To help users understand the reliability of each data point, the file includes quality indicators like: Geocoding accuracy Confidence scores for phone and email data Data source indicators (modeled vs. self-reported) These indicators are essential for making informed decisions. Time-Sensitive Information The file also tracks time-based data, including: Length of residence Recent moves Mortgage and property sale dates This information is useful for identifying life changes that often trigger new purchasing decisions. Use Cases and Applications This rich dataset has applications across a variety of industries: Marketing and Advertising: Create highly targeted campaigns, personalize messages, and expand customer bases through lookalike modeling. Real Estate and Mortgage: Identify buyers and sellers, tailor home loan offers, and target homeowners for renovations. Financial Services: Reach high-net-worth individuals, craft personalized credit offers, and prevent fraud. Retail and E-commerce: Personalize product recommendations and optimize store locations based on local demographics. Non-profits and Political Organizations: Find donors, target volunteers, and tailor political messaging. Healthcare and Insurance: Target markets for health services, assess risk factors, and tailor wellness programs. Education and Training: Target students based on age and occupation, and tailor outreach to alumni for fundraising. Travel and Hospitality: Target travel enthusiasts, tailor vacation packages, and find luxury travel customers. Technology and Telecommunications: Reach early adopters, tailor service plans, and identify areas for network investment. Media and Entertainment: Tailor content recommendations, find potential streaming service subscribers, and optimize ad placements. This dataset is a valuable resource for understanding and connecting with consumers on a deeper level.
Country Coverage
(1 country)Data Categories
- Consumer Marketing Data
- Email Address Data
- Phone Number Data
- Home Ownership Data
- Consumer Demographic Data
Pricing
Volumes
- People
- 255M
- Phones
- 143M
- Emails
- 154M
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