Tell us about your current situation: What is the 5-digit Zip code for the home location. * In most cases this will be your current home address Zip code, or if you are in the process of moving, the new Zip code. Are you currently insured or have been insured during the past 30 days (on any policy, for any vehicle) ? * --Select-- Yes No If so, what is the name of your insurance company? * "
data = data + ""
data = data + "--Select-- "
data = data + " "
data = data + " AAA "
data = data + "AIG "
data = data + "Allied "
data = data + "Allstate "
data = data + "American Family "
data = data + "Amica "
data = data + "Farm Bureau "
data = data + "Farmers "
data = data + "GEICO "
data = data + "Hartford "
data = data + "Liberty Mutual "
data = data + "Metropolitan Co. "
data = data + "Nationwide "
data = data + "Progressive "
data = data + "Prudential "
data = data + "SAFECO "
data = data + "State Farm "
data = data + "Travelers "
data = data + "United Services Automobile Association "
data = data + "Unitrin Direct "
data = data + "Other Company (Not Listed) "
data = data + ""
data = data + ""
data = data + ""
data = data + "Other Company (Not Listed) "
data = data + "AAA "
data = data + "AABCO "
data = data + "Acceptance "
data = data + "Access Insurance "
data = data + "Acordia "
data = data + "Aegis Security "
data = data + "AETNA "
data = data + "Affirmative "
data = data + "AIG "
data = data + "AIU "
data = data + "Alliance for Affordable Services "
data = data + "Allied "
data = data + "All Nation "
data = data + "All Risk "
data = data + "Allianz "
data = data + "Allstate "
data = data + "Amalgamated Life Insurance "
data = data + "AMCO "
data = data + "America's Ins. Consultants "
data = data + "American Alliance "
data = data + "American Banks "
data = data + "American Economy "
data = data + "American Empire Group "
data = data + "American Family "
data = data + "American General "
data = data + "American International Group "
data = data + "American Investors "
data = data + "American National "
data = data + "American Premier "
data = data + "American Reliable "
data = data + "American Republic "
data = data + "American Standard "
data = data + "American States "
data = data + "American Sterling Insurance "
data = data + "American Underwriters "
data = data + "American United Life Insurance "
data = data + "Amerisure "
data = data + "AmerUs Life "
data = data + "AmwestInsurance Group "
data = data + "Amica "
data = data + "API "
data = data + "Arbella "
data = data + "Arizona General "
data = data + "Assigned Risk "
data = data + "Association Field Services "
data = data + "Associated Indemnity "
data = data + "Assurity LIfe "
data = data + "Atlanta Casualty "
data = data + "Atlantic Indemnity "
data = data + "Austin Mutual "
data = data + "Auto Owners "
data = data + "Avomark "
data = data + "Badger Mutual "
data = data + "Bankers & Shippers "
data = data + "Bankers Life and Casualty "
data = data + "Beneficial Life Insurance "
data = data + "Berkshire Life Insurance "
data = data + "Blue Cross/Blue Shield "
data = data + "Bonneville "
data = data + "Boston Old Colony "
data = data + "Builders "
data = data + "Cal Farm "
data = data + "California Casualty "
data = data + "California State Automobile Association "
data = data + "Camden "
data = data + "Capital Choice "
data = data + "Care Entrie "
data = data + "Cascade National Ins "
data = data + "Casualty Assurance "
data = data + "Centennial "
data = data + "Charter Oak "
data = data + "Chicago Insurance "
data = data + "Chubb "
data = data + "church Mutual "
data = data + "Cigna "
data = data + "Citizens "
data = data + "Clarendon American "
data = data + "Cloverleaf "
data = data + "CMA "
data = data + "CMA Alliance "
data = data + "CNA "
data = data + "Colonial "
data = data + "Combined "
data = data + "Commercial Union "
data = data + "Commonwealth "
data = data + "Continental "
data = data + "Cotton States "
data = data + "Cottonwood "
data = data + "Country Financial Services "
data = data + "Country Insurance "
data = data + "Credit Union "
data = data + "Criterion "
data = data + "CUNA Mutual "
data = data + "Dairyland "
data = data + "Dakota Fire "
data = data + "Deerbrook "
data = data + "Depositors Emcasc "
data = data + "Dixie "
data = data + "Ebco General "
data = data + "Economy "
data = data + "Electric "
data = data + "EMC "
data = data + "Empire "
data = data + "Employers Fire "
data = data + "Ensure "
data = data + "Equitable "
data = data + "Erie Insurance "
data = data + "Facility "
data = data + "Farm Bureau "
data = data + "Farmers "
data = data + "Farmland "
data = data + "Federal "
data = data + "Federated "
data = data + "Fidelity "
data = data + "Financial Indemnity "
data = data + "Fire and Casualty Co of CT "
data = data + "Fireman's Fund "
data = data + "First American "
data = data + "First Colony "
data = data + "First Financial "
data = data + "First General "
data = data + "First National "
data = data + "Ford Motor Credit "
data = data + "Foremost "
data = data + "Fortis Group "
data = data + "Franklin "
data = data + "Golden Rule "
data = data + "GEICO "
data = data + "GE Financial Network "
data = data + "General Accident "
data = data + "Gerber Life Insurance "
data = data + "Globe "
data = data + "GMAC "
data = data + "Golden Rule "
data = data + "Government Employees "
data = data + "Grange "
data = data + "GRE "
data = data + "Great American "
data = data + "Great Way "
data = data + "Great West "
data = data + "Grinnell Mutual "
data = data + "Guaranty National "
data = data + "Guardian "
data = data + "Guide One "
data = data + "GEICO "
data = data + "Halcyon "
data = data + "Hanover Lloyd's Company "
data = data + "Happy Days "
data = data + "Hartford "
data = data + "Hawkeye Security "
data = data + "Health Net "
data = data + "Health Plus of America "
data = data + "Heritage "
data = data + "Horace Mann "
data = data + "Humana "
data = data + "IDS "
data = data + "IFA Auto "
data = data + "IGF "
data = data + "Infinity "
data = data + "Insurance of Evanston "
data = data + "Integon "
data = data + "Interstatey "
data = data + "John Deere "
data = data + "John Hancock "
data = data + "Kaiser Foundation Health Plan "
data = data + "Kemper Lloyds "
data = data + "Kemper Insurance "
data = data + "Kentucky Central "
data = data + "Landmark American "
data = data + "Landmark Life Insurance "
data = data + "Leader General "
data = data + "Leader National "
data = data + "League General "
data = data + "Liberty Mutual "
data = data + "Lincoln Financial Group "
data = data + "London Life Insurance "
data = data + "Lumbermens Mutual "
data = data + "Managed Comp "
data = data + "Marathon "
data = data + "Markel American "
data = data + "Maryland Casualty "
data = data + "Mass Mutual "
data = data + "MBA Insurance "
data = data + "Mendota "
data = data + "Mega Life and Health Ins. "
data = data + "Merastar "
data = data + "Mercury "
data = data + "Met Life "
data = data + "Metropolitan Co. "
data = data + "Mid Century "
data = data + "Mid-Continent Casualty "
data = data + "MidWest Mutual "
data = data + "Mid-West Ntl. Life "
data = data + "MidCentury (Farmers) "
data = data + "Midwest Mutual "
data = data + "Middlesex "
data = data + "Millbank "
data = data + "Millers Mutual "
data = data + "Milwaukee "
data = data + "Milwaukee Guardian "
data = data + "Milwaukee Mutual "
data = data + "Minnehoma "
data = data + "Missouri General "
data = data + "Modern Woodmen of America "
data = data + "MONY Group "
data = data + "Motors "
data = data + "Mountain Laurel "
data = data + "MSI "
data = data + "Mutual of Enumclaw "
data = data + "Mutual of New York "
data = data + "Mutual Of Omaha "
data = data + "N.A.S.E. "
data = data + "National Alliance "
data = data + "National Assoc - Self Employed "
data = data + "National Colonial "
data = data + "National Continental "
data = data + "National Farmers Union "
data = data + "National Health "
data = data + "National Indemnity "
data = data + "National Merit "
data = data + "National Surety Corp "
data = data + "Nationwide "
data = data + "New England Financial "
data = data + "New York Life "
data = data + "North American "
data = data + "North Pacific "
data = data + "Northe Pointe "
data = data + "North Shore "
data = data + "Northern Capital "
data = data + "Northern States "
data = data + "Northland "
data = data + "Northwestern "
data = data + "Northwestern Mutual Life "
data = data + "Ohio Casualty "
data = data + "First Security "
data = data + "Olympia "
data = data + "Omaha "
data = data + "Omni "
data = data + "Oregon Mutual "
data = data + "Orion "
data = data + "Oxford Insurance "
data = data + "Pacific "
data = data + "Pacific Life Insurance "
data = data + "Pafco General "
data = data + "Paloverde "
data = data + "Pan-American Life Insurance "
data = data + "Patriot General "
data = data + "Peak Property and Casualty "
data = data + "PEMCO "
data = data + "Penn America "
data = data + "Penn Mutual "
data = data + "Pennsylvania Natl "
data = data + "Phoenix "
data = data + "Pinnacle "
data = data + "Pioneer Life "
data = data + "Preferred Abstainers "
data = data + "Preferred Risk "
data = data + "Premier "
data = data + "Prestige "
data = data + "Primerica "
data = data + "Principal Financial "
data = data + "Progressive Insurance "
data = data + "Protective Casualty "
data = data + "Protective Life "
data = data + "Provident Corporation "
data = data + "Prudential "
data = data + "Quality "
data = data + "RBC Liberty Insurance "
data = data + "Ramsey "
data = data + "Ranger "
data = data + "Regal "
data = data + "Reliance "
data = data + "Reliant "
data = data + "ReliaStar Life "
data = data + "Republic Indemnity "
data = data + "Response "
data = data + "Rockford Mutual "
data = data + "SAFECO "
data = data + "Safeway "
data = data + "Savings Bank Life Insurance "
data = data + "Sea West Insurance "
data = data + "Secura "
data = data + "Security Co of Hartford "
data = data + "Security National Co of FL "
data = data + "Sedgwick James "
data = data + "Sentinel "
data = data + "Sentry Group "
data = data + "Shelter Co. "
data = data + "Skandia "
data = data + "Spectrum "
data = data + "St. Paul "
data = data + "Standard Fire Company "
data = data + "Standard Guaranty "
data = data + "State Auto "
data = data + "State Farm "
data = data + "State Mutual "
data = data + "State National Ins "
data = data + "Sun Coast "
data = data + "Sun Life "
data = data + "Superior "
data = data + "Sutter "
data = data + "TICO "
data = data + "TIG Countrywide "
data = data + "Titan "
data = data + "Total "
data = data + "Tower "
data = data + "Travelers "
data = data + "Tri-State Consumer "
data = data + "Trinity Universal "
data = data + "Trust Hall "
data = data + "Twentieth Century "
data = data + "Twin City Fire "
data = data + "UGA "
data = data + "Unicare "
data = data + "Uniguard "
data = data + "Union "
data = data + "United American "
data = data + "United Financial "
data = data + "United Fire & Casual "
data = data + "United Security "
data = data + "United States Fideli "
data = data + "Unitrin "
data = data + "Unsure "
data = data + "US Health Advisors "
data = data + "USF&G "
data = data + "USAA "
data = data + "Utah Home and Fire "
data = data + "Utica "
data = data + "Vasa North Atlantic "
data = data + "Vigilant "
data = data + "Viking County Mutual "
data = data + "Viking Co of WI "
data = data + "Wausau Insurance "
data = data + "Wawaunesa "
data = data + "Wellington "
data = data + "West American "
data = data + "West Bend Mutual "
data = data + "West Field "
data = data + "West Plains "
data = data + "Western Mutal "
data = data + "Western National "
data = data + "Western Southern Life "
data = data + "Westfield "
data = data + "William Penn Life "
data = data + "Windsor "
data = data + "Windstar "
data = data + "Wisconsin Mutual "
data = data + "Workmans Auto "
data = data + "WorldWide "
data = data + "Yellow Key "
data = data + "Yosemite "
data = data + "Zurich North America "
data = data + "Other Company (Not Listed) "
data = data + " "
data = data + "Is this home a new purchase? * Yes Insurance Information How long have you been at your current residence? "
data = data + "less than 1 year 1-2 years 3-5 years 6-10 years more than 10 years --Select-- When does your policy expire? * "
data = data + ""
data = data + "Month "
data = data + "Jan "
data = data + "Feb "
data = data + "Mar "
data = data + "Apr "
data = data + "May "
data = data + "Jun "
data = data + "Jul "
data = data + "Aug "
data = data + "Sep "
data = data + "Oct "
data = data + "Nov "
data = data + "Dec "
data = data + " "
data = data + ""
data = data + "Date "
data = data + "01 "
data = data + "02 "
data = data + "03 "
data = data + "04 "
data = data + "05 "
data = data + "06 "
data = data + "07 "
data = data + "08 "
data = data + "09 "
data = data + "10 "
data = data + "11 "
data = data + "12 "
data = data + "13 "
data = data + "14 "
data = data + "15 "
data = data + "16 "
data = data + "17 "
data = data + "18 "
data = data + "19 "
data = data + "20 "
data = data + "21 "
data = data + "22 "
data = data + "23 "
data = data + "24 "
data = data + "25 "
data = data + "26 "
data = data + "27 "
data = data + "28 "
data = data + "29 "
data = data + "30 "
data = data + "31 "
data = data + " "
data = data + "20 How long has this home been continuously insured (with any company)? * --Select-- Less than 1 1 year 2 years 3 years 4 years 5 years 6 years 7 years 8 years 9 years 10+ years How long have you been with this company? * --Select-- Less than 1 1 year 2 years 3 years 4 years 5 years 6 years 7 years 8 years 9 years 10+ years How much is your current premium? * How often do you pay this premium? * --Select-- Monthly Quarterly Every 6 Months Yearly Home Information What Type of Dwelling are you Insuring? * Single Family Home Condo Duplex Mobile Home Manufactured Home Apartment Other --Select-- What is the Occupancy Status of this Dwelling? * --Select-- Primary Residence Seasonal Residence Vacation Property Rental Property Address to be insured * City * State * --Select-- Alabama Alaska Arizona Arkansas California Colorado Connecticut Delaware District Of Columbia Florida Georgia Hawaii Idaho Illinois Indiana Iowa Kansas Kentucky Louisiana Maine Maryland Massachusetts Michigan Minnesota Mississippi Missouri Montana Nebraska Nevada New Hampshire New Jersey New Mexico New York North Carolina North Dakota Ohio Oklahoma Oregon Pennsylvania Rhode Island South Carolina South Dakota Tennessee Texas Utah Vermont Virginia Washington West Virginia Wisconsin Wyoming Zip * County * What year was the dwelling built? * What type of dogs do you have, if any? * --Select-- None Doberman German Shepherd Pit Bull Rottweiler Other What is the total square footage of the dwelling? * How many stories (excluding basement) are there? * 1 1 1/2 2 3 4+ Bi-Level Tri-Level --Select-- How many bedrooms do you have? * 1 2 3 4 5 6 7 8 9 10+ --Select-- How many bathrooms do you have? * 1 1 1/2 2 2 1/2 3 3 1/2 4 4 1/2 5 5 1/2 6 6 1/2 7 7 1/2 8+ --Select-- What type of heat source do you use? * --Select-- Gas Electric Boiler Oil Propane Stove Other Unknown How many fireplaces do you have? * --Select-- 0 1 2 3 4+ What type of garage do you have? * No Garage Carport Attached - 1 car Attached - 2 cars Attached - 3 cars Not Attached - 1 car Not Attached - 2 cars Not Attached - 3 cars Other --Select-- How is your dwelling sided? * --Select-- Brick Stucco Vinyl Wood Stone Metal Veneer Cinder Block Log Home Other/Not Sure What type of foundation do you have? * --Select-- Basement less than 50% finished Basement more than 50% finished Crawl Space Open (Cement Non-Solid) Piers Pilings Stilts Slab (Cement Solid) Other Don't Know How far away from a fire station is your dwelling? * --Select-- less than 5 miles 5-10 miles more than 10 miles How far away from a fire hydrant is your dwelling? * --Select-- less than 500 feet 500-1,000 feet more than 1,000 feet Have you made any upgrades to your Home in the last 10 years? (i.e. electrical, siding, etc.) * No Yes Please check any of the following features that you have at your dwelling * "
data = data + " "
data = data + "Coverage Requested How much coverage is needed on the dwelling? (Value of your home minus the value of the land) * How much coverage is needed on the contents? * Requested amount of liability * $50,000 $100,000 $200,000 $300,000 (Most Common) $400,000 $500,000 $1,000,000 more than $1 million Not Sure --Select-- Requested Deductible * $100 $250 $500 $1,000 $2,000 $2,500 $5,000 How would you describe your credit history? * Poor Fair Good Excellent How many homeowners claims have you filed in the last 5 years? None 1 2 3 4 5+ Claim Approximate Date And Type of Claim: For Claim 1* "
data = data + ""
data = data + "Month "
data = data + "Jan "
data = data + "Feb "
data = data + "Mar "
data = data + "Apr "
data = data + "May "
data = data + "Jun "
data = data + "Jul "
data = data + "Aug "
data = data + "Sep "
data = data + "Oct "
data = data + "Nov "
data = data + "Dec "
data = data + " "
data = data + ""
data = data + "Year "
data = data + "2002 "
data = data + "2003 "
data = data + "2004 "
data = data + "2005 "
data = data + "2006 "
data = data + "2007 "
data = data + " "
data = data + "Fire Hail Liability Lightning Medical Theft Water Wind Other --Select Claim Type-- "
/*data = data + "How long have you been at your current residence? * less than 1 year 1-2 years 3-5 years 6-10 years more than 10 years --Select-- How long were you at your previous address? * less than 1 year 1-2 years 3-5 years 6-10 years more than 10 years --Select-- How many wooded porches, patios, or decks do you have? 0 1 2 3 4+ What type of roofing do you have?* Asphalt (Most Common) Colored Granules Metal Clay Wooden Shingle Flat Roof Composite Shingle Other If yes, please describe the upgrades. Include information such as approximate date, what upgrades were made, and any details that may help the agents provide a more accurate quote. For Claim 2* "
data = data + ""
data = data + "Month "
data = data + "Jan "
data = data + "Feb "
data = data + "Mar "
data = data + "Apr "
data = data + "May "
data = data + "Jun "
data = data + "Jul "
data = data + "Aug "
data = data + "Sep "
data = data + "Oct "
data = data + "Nov "
data = data + "Dec "
data = data + " "
data = data + ""
data = data + "Year "
data = data + "1999 "
data = data + "2000 "
data = data + "2001 "
data = data + "2002 "
data = data + "2003 "
data = data + "2004 "
data = data + "2005 "
data = data + "2006 "
data = data + "2007 "
data = data + " "
data = data + "Fire Hail Liability Lightning Medical Theft Water Wind Other --Select Claim Type-- "
//3
data = data + "For Claim 3* "
data = data + ""
data = data + "Month "
data = data + "Jan "
data = data + "Feb "
data = data + "Mar "
data = data + "Apr "
data = data + "May "
data = data + "Jun "
data = data + "Jul "
data = data + "Aug "
data = data + "Sep "
data = data + "Oct "
data = data + "Nov "
data = data + "Dec "
data = data + " "
data = data + ""
data = data + "Year "
data = data + "1999 "
data = data + "2000 "
data = data + "2001 "
data = data + "2002 "
data = data + "2003 "
data = data + "2004 "
data = data + "2005 "
data = data + "2006 "
data = data + "2007 "
data = data + " "
data = data + "Fire Hail Liability Lightning Medical Theft Water Wind Other --Select Claim Type-- "
//4
data = data + "For Claim 4* "
data = data + ""
data = data + "Month "
data = data + "Jan "
data = data + "Feb "
data = data + "Mar "
data = data + "Apr "
data = data + "May "
data = data + "Jun "
data = data + "Jul "
data = data + "Aug "
data = data + "Sep "
data = data + "Oct "
data = data + "Nov "
data = data + "Dec "
data = data + " "
data = data + ""
data = data + "Year "
data = data + "1999 "
data = data + "2000 "
data = data + "2001 "
data = data + "2002 "
data = data + "2003 "
data = data + "2004 "
data = data + "2005 "
data = data + "2006 "
data = data + "2007 "
data = data + " "
data = data + "Fire Hail Liability Lightning Medical Theft Water Wind Other --Select Claim Type-- "
//5
data = data + "For Claim 5* "
data = data + ""
data = data + "Month "
data = data + "Jan "
data = data + "Feb "
data = data + "Mar "
data = data + "Apr "
data = data + "May "
data = data + "Jun "
data = data + "Jul "
data = data + "Aug "
data = data + "Sep "
data = data + "Oct "
data = data + "Nov "
data = data + "Dec "
data = data + " "
data = data + ""
data = data + "Year "
data = data + "1999 "
data = data + "2000 "
data = data + "2001 "
data = data + "2002 "
data = data + "2003 "
data = data + "2004 "
data = data + "2005 "
data = data + "2006 "
data = data + "2007 "
data = data + " "
data = data + "Fire Hail Liability Lightning Medical Theft Water Wind Other --Select Claim Type-- "
*/
data = data + "Best Time to Contact You * --Select-- Morning Afternoon evening
"
}
if (x == "Home Renters Insurance")
{
//hahha
data="Tell us about your current situation: Are you currently insured? * --Select-- Yes No If so, what is the name of your insurance company? * "
data = data + ""
data = data + "--Select-- "
data = data + " "
data = data + " AAA "
data = data + "AIG "
data = data + "Allied "
data = data + "Allstate "
data = data + "American Family "
data = data + "Amica "
data = data + "Farm Bureau "
data = data + "Farmers "
data = data + "GEICO "
data = data + "Hartford "
data = data + "Liberty Mutual "
data = data + "Metropolitan Co. "
data = data + "Nationwide "
data = data + "Progressive "
data = data + "Prudential "
data = data + "SAFECO "
data = data + "State Farm "
data = data + "Travelers "
data = data + "United Services Automobile Association "
data = data + "Unitrin Direct "
data = data + "Other Company (Not Listed) "
data = data + ""
data = data + ""
data = data + ""
data = data + "Other Company (Not Listed) "
data = data + "AAA "
data = data + "AABCO "
data = data + "Acceptance "
data = data + "Access Insurance "
data = data + "Acordia "
data = data + "Aegis Security "
data = data + "AETNA "
data = data + "Affirmative "
data = data + "AIG "
data = data + "AIU "
data = data + "Alliance for Affordable Services "
data = data + "Allied "
data = data + "All Nation "
data = data + "All Risk "
data = data + "Allianz "
data = data + "Allstate "
data = data + "Amalgamated Life Insurance "
data = data + "AMCO "
data = data + "America's Ins. Consultants "
data = data + "American Alliance "
data = data + "American Banks "
data = data + "American Economy "
data = data + "American Empire Group "
data = data + "American Family "
data = data + "American General "
data = data + "American International Group "
data = data + "American Investors "
data = data + "American National "
data = data + "American Premier "
data = data + "American Reliable "
data = data + "American Republic "
data = data + "American Standard "
data = data + "American States "
data = data + "American Sterling Insurance "
data = data + "American Underwriters "
data = data + "American United Life Insurance "
data = data + "Amerisure "
data = data + "AmerUs Life "
data = data + "AmwestInsurance Group "
data = data + "Amica "
data = data + "API "
data = data + "Arbella "
data = data + "Arizona General "
data = data + "Assigned Risk "
data = data + "Association Field Services "
data = data + "Associated Indemnity "
data = data + "Assurity LIfe "
data = data + "Atlanta Casualty "
data = data + "Atlantic Indemnity "
data = data + "Austin Mutual "
data = data + "Auto Owners "
data = data + "Avomark "
data = data + "Badger Mutual "
data = data + "Bankers & Shippers "
data = data + "Bankers Life and Casualty "
data = data + "Beneficial Life Insurance "
data = data + "Berkshire Life Insurance "
data = data + "Blue Cross/Blue Shield "
data = data + "Bonneville "
data = data + "Boston Old Colony "
data = data + "Builders "
data = data + "Cal Farm "
data = data + "California Casualty "
data = data + "California State Automobile Association "
data = data + "Camden "
data = data + "Capital Choice "
data = data + "Care Entrie "
data = data + "Cascade National Ins "
data = data + "Casualty Assurance "
data = data + "Centennial "
data = data + "Charter Oak "
data = data + "Chicago Insurance "
data = data + "Chubb "
data = data + "church Mutual "
data = data + "Cigna "
data = data + "Citizens "
data = data + "Clarendon American "
data = data + "Cloverleaf "
data = data + "CMA "
data = data + "CMA Alliance "
data = data + "CNA "
data = data + "Colonial "
data = data + "Combined "
data = data + "Commercial Union "
data = data + "Commonwealth "
data = data + "Continental "
data = data + "Cotton States "
data = data + "Cottonwood "
data = data + "Country Financial Services "
data = data + "Country Insurance "
data = data + "Credit Union "
data = data + "Criterion "
data = data + "CUNA Mutual "
data = data + "Dairyland "
data = data + "Dakota Fire "
data = data + "Deerbrook "
data = data + "Depositors Emcasc "
data = data + "Dixie "
data = data + "Ebco General "
data = data + "Economy "
data = data + "Electric "
data = data + "EMC "
data = data + "Empire "
data = data + "Employers Fire "
data = data + "Ensure "
data = data + "Equitable "
data = data + "Erie Insurance "
data = data + "Facility "
data = data + "Farm Bureau "
data = data + "Farmers "
data = data + "Farmland "
data = data + "Federal "
data = data + "Federated "
data = data + "Fidelity "
data = data + "Financial Indemnity "
data = data + "Fire and Casualty Co of CT "
data = data + "Fireman's Fund "
data = data + "First American "
data = data + "First Colony "
data = data + "First Financial "
data = data + "First General "
data = data + "First National "
data = data + "Ford Motor Credit "
data = data + "Foremost "
data = data + "Fortis Group "
data = data + "Franklin "
data = data + "Golden Rule "
data = data + "GEICO "
data = data + "GE Financial Network "
data = data + "General Accident "
data = data + "Gerber Life Insurance "
data = data + "Globe "
data = data + "GMAC "
data = data + "Golden Rule "
data = data + "Government Employees "
data = data + "Grange "
data = data + "GRE "
data = data + "Great American "
data = data + "Great Way "
data = data + "Great West "
data = data + "Grinnell Mutual "
data = data + "Guaranty National "
data = data + "Guardian "
data = data + "Guide One "
data = data + "GEICO "
data = data + "Halcyon "
data = data + "Hanover Lloyd's Company "
data = data + "Happy Days "
data = data + "Hartford "
data = data + "Hawkeye Security "
data = data + "Health Net "
data = data + "Health Plus of America "
data = data + "Heritage "
data = data + "Horace Mann "
data = data + "Humana "
data = data + "IDS "
data = data + "IFA Auto "
data = data + "IGF "
data = data + "Infinity "
data = data + "Insurance of Evanston "
data = data + "Integon "
data = data + "Interstatey "
data = data + "John Deere "
data = data + "John Hancock "
data = data + "Kaiser Foundation Health Plan "
data = data + "Kemper Lloyds "
data = data + "Kemper Insurance "
data = data + "Kentucky Central "
data = data + "Landmark American "
data = data + "Landmark Life Insurance "
data = data + "Leader General "
data = data + "Leader National "
data = data + "League General "
data = data + "Liberty Mutual "
data = data + "Lincoln Financial Group "
data = data + "London Life Insurance "
data = data + "Lumbermens Mutual "
data = data + "Managed Comp "
data = data + "Marathon "
data = data + "Markel American "
data = data + "Maryland Casualty "
data = data + "Mass Mutual "
data = data + "MBA Insurance "
data = data + "Mendota "
data = data + "Mega Life and Health Ins. "
data = data + "Merastar "
data = data + "Mercury "
data = data + "Met Life "
data = data + "Metropolitan Co. "
data = data + "Mid Century "
data = data + "Mid-Continent Casualty "
data = data + "MidWest Mutual "
data = data + "Mid-West Ntl. Life "
data = data + "MidCentury (Farmers) "
data = data + "Midwest Mutual "
data = data + "Middlesex "
data = data + "Millbank "
data = data + "Millers Mutual "
data = data + "Milwaukee "
data = data + "Milwaukee Guardian "
data = data + "Milwaukee Mutual "
data = data + "Minnehoma "
data = data + "Missouri General "
data = data + "Modern Woodmen of America "
data = data + "MONY Group "
data = data + "Motors "
data = data + "Mountain Laurel "
data = data + "MSI "
data = data + "Mutual of Enumclaw "
data = data + "Mutual of New York "
data = data + "Mutual Of Omaha "
data = data + "N.A.S.E. "
data = data + "National Alliance "
data = data + "National Assoc - Self Employed "
data = data + "National Colonial "
data = data + "National Continental "
data = data + "National Farmers Union "
data = data + "National Health "
data = data + "National Indemnity "
data = data + "National Merit "
data = data + "National Surety Corp "
data = data + "Nationwide "
data = data + "New England Financial "
data = data + "New York Life "
data = data + "North American "
data = data + "North Pacific "
data = data + "Northe Pointe "
data = data + "North Shore "
data = data + "Northern Capital "
data = data + "Northern States "
data = data + "Northland "
data = data + "Northwestern "
data = data + "Northwestern Mutual Life "
data = data + "Ohio Casualty "
data = data + "First Security "
data = data + "Olympia "
data = data + "Omaha "
data = data + "Omni "
data = data + "Oregon Mutual "
data = data + "Orion "
data = data + "Oxford Insurance "
data = data + "Pacific "
data = data + "Pacific Life Insurance "
data = data + "Pafco General "
data = data + "Paloverde "
data = data + "Pan-American Life Insurance "
data = data + "Patriot General "
data = data + "Peak Property and Casualty "
data = data + "PEMCO "
data = data + "Penn America "
data = data + "Penn Mutual "
data = data + "Pennsylvania Natl "
data = data + "Phoenix "
data = data + "Pinnacle "
data = data + "Pioneer Life "
data = data + "Preferred Abstainers "
data = data + "Preferred Risk "
data = data + "Premier "
data = data + "Prestige "
data = data + "Primerica "
data = data + "Principal Financial "
data = data + "Progressive Insurance "
data = data + "Protective Casualty "
data = data + "Protective Life "
data = data + "Provident Corporation "
data = data + "Prudential "
data = data + "Quality "
data = data + "RBC Liberty Insurance "
data = data + "Ramsey "
data = data + "Ranger "
data = data + "Regal "
data = data + "Reliance "
data = data + "Reliant "
data = data + "ReliaStar Life "
data = data + "Republic Indemnity "
data = data + "Response "
data = data + "Rockford Mutual "
data = data + "SAFECO "
data = data + "Safeway "
data = data + "Savings Bank Life Insurance "
data = data + "Sea West Insurance "
data = data + "Secura "
data = data + "Security Co of Hartford "
data = data + "Security National Co of FL "
data = data + "Sedgwick James "
data = data + "Sentinel "
data = data + "Sentry Group "
data = data + "Shelter Co. "
data = data + "Skandia "
data = data + "Spectrum "
data = data + "St. Paul "
data = data + "Standard Fire Company "
data = data + "Standard Guaranty "
data = data + "State Auto "
data = data + "State Farm "
data = data + "State Mutual "
data = data + "State National Ins "
data = data + "Sun Coast "
data = data + "Sun Life "
data = data + "Superior "
data = data + "Sutter "
data = data + "TICO "
data = data + "TIG Countrywide "
data = data + "Titan "
data = data + "Total "
data = data + "Tower "
data = data + "Travelers "
data = data + "Tri-State Consumer "
data = data + "Trinity Universal "
data = data + "Trust Hall "
data = data + "Twentieth Century "
data = data + "Twin City Fire "
data = data + "UGA "
data = data + "Unicare "
data = data + "Uniguard "
data = data + "Union "
data = data + "United American "
data = data + "United Financial "
data = data + "United Fire & Casual "
data = data + "United Security "
data = data + "United States Fideli "
data = data + "Unitrin "
data = data + "Unsure "
data = data + "US Health Advisors "
data = data + "USF&G "
data = data + "USAA "
data = data + "Utah Home and Fire "
data = data + "Utica "
data = data + "Vasa North Atlantic "
data = data + "Vigilant "
data = data + "Viking County Mutual "
data = data + "Viking Co of WI "
data = data + "Wausau Insurance "
data = data + "Wawaunesa "
data = data + "Wellington "
data = data + "West American "
data = data + "West Bend Mutual "
data = data + "West Field "
data = data + "West Plains "
data = data + "Western Mutal "
data = data + "Western National "
data = data + "Western Southern Life "
data = data + "Westfield "
data = data + "William Penn Life "
data = data + "Windsor "
data = data + "Windstar "
data = data + "Wisconsin Mutual "
data = data + "Workmans Auto "
data = data + "WorldWide "
data = data + "Yellow Key "
data = data + "Yosemite "
data = data + "Zurich North America "
data = data + "Other Company (Not Listed) "
data = data + " "
data = data + "What is the zip code of the property to be insured? * Residence Information Address to be insured * City * State * --Select-- Alabama Alaska Arizona Arkansas California Colorado Connecticut Delaware District Of Columbia Florida Georgia Hawaii Idaho Illinois Indiana Iowa Kansas Kentucky Louisiana Maine Maryland Massachusetts Michigan Minnesota Mississippi Missouri Montana Nebraska Nevada New Hampshire New Jersey New Mexico New York North Carolina North Dakota Ohio Oklahoma Oregon Pennsylvania Rhode Island South Carolina South Dakota Tennessee Texas Utah Vermont Virginia Washington West Virginia Wisconsin Wyoming Zip * What Type of Dwelling are you Insuring? * Apartment Single-Family Home Multiple Family Home Condo Duplex Mobile Home Dormitory Other --Select-- What is the total square footage of the dwelling? * How many stories are in your building? * --Select-- 1 2 3 4+ How many bedrooms do you have? * --Select-- 1 2 3 4+ How many bathrooms do you have? * --Select-- 1 1 1/2 2 2 1/2 3 3 1/2 4 4 1/2 Residence Features What type of heat source do you use? * --Select-- Gas Electric Boiler Oil Propane Stove Other Unknown How is your dwelling sided? * --Select-- Brick Stucco Vinyl Wood Stone Metal Veneer Cinder Block Other/Not Sure How far away from a fire station is your dwelling? * --Select-- less than 5 miles 5-10 miles more than 10 miles How far away from a fire hydrant is your dwelling? * --Select-- less than 500 feet 500-1,000 feet more than 1,000 feet Please check any of the following features that you have at your dwelling * "
data = data + " "
data = data + "Coverage Requested How much insurance is needed on the contents (personal property) of your dwelling? * Requested amount of liability * $50,000 $100,000 $200,000 $300,000 (Most Common) $400,000 $500,000 more than $500,000 Not Sure --Select-- Requested Deductible * --Select-- $100 $250 $500 $1,000 $2,000 $2,500 $5,000 Not Sure Many companies use credit scores for rates and discounts. How would you honestly rate your credit history? * Poor Fair Good Excellent Claims History How many homeowners or renters claims have you had in the last 5 years? * --Select-- 0 1 2 3 4+ Best Time to Contact You * --Select-- Morning Afternoon evening
"
//chacha
}
if (document.frm.InsuranceType.value == "Auto Insurance")
{
data="Tell us about your current situation: Are you currently insured or have been insured during the past 30 days (on any policy, for any vehicle) ? * --Select-- Yes No what is the name of your insurance company? * "
data = data + ""
data = data + "--Select-- "
data = data + " "
data = data + " AAA "
data = data + "AIG "
data = data + "Allied "
data = data + "Allstate "
data = data + "American Family "
data = data + "Amica "
data = data + "Farm Bureau "
data = data + "Farmers "
data = data + "GEICO "
data = data + "Hartford "
data = data + "Liberty Mutual "
data = data + "Metropolitan Co. "
data = data + "Nationwide "
data = data + "Progressive "
data = data + "Prudential "
data = data + "SAFECO "
data = data + "State Farm "
data = data + "Travelers "
data = data + "United Services Automobile Association "
data = data + "Unitrin Direct "
data = data + "Other Company (Not Listed) "
data = data + ""
data = data + ""
data = data + ""
data = data + "Other Company (Not Listed) "
data = data + "AAA "
data = data + "AABCO "
data = data + "Acceptance "
data = data + "Access Insurance "
data = data + "Acordia "
data = data + "Aegis Security "
data = data + "AETNA "
data = data + "Affirmative "
data = data + "AIG "
data = data + "AIU "
data = data + "Alliance for Affordable Services "
data = data + "Allied "
data = data + "All Nation "
data = data + "All Risk "
data = data + "Allianz "
data = data + "Allstate "
data = data + "Amalgamated Life Insurance "
data = data + "AMCO "
data = data + "America's Ins. Consultants "
data = data + "American Alliance "
data = data + "American Banks "
data = data + "American Economy "
data = data + "American Empire Group "
data = data + "American Family "
data = data + "American General "
data = data + "American International Group "
data = data + "American Investors "
data = data + "American National "
data = data + "American Premier "
data = data + "American Reliable "
data = data + "American Republic "
data = data + "American Standard "
data = data + "American States "
data = data + "American Sterling Insurance "
data = data + "American Underwriters "
data = data + "American United Life Insurance "
data = data + "Amerisure "
data = data + "AmerUs Life "
data = data + "AmwestInsurance Group "
data = data + "Amica "
data = data + "API "
data = data + "Arbella "
data = data + "Arizona General "
data = data + "Assigned Risk "
data = data + "Association Field Services "
data = data + "Associated Indemnity "
data = data + "Assurity LIfe "
data = data + "Atlanta Casualty "
data = data + "Atlantic Indemnity "
data = data + "Austin Mutual "
data = data + "Auto Owners "
data = data + "Avomark "
data = data + "Badger Mutual "
data = data + "Bankers & Shippers "
data = data + "Bankers Life and Casualty "
data = data + "Beneficial Life Insurance "
data = data + "Berkshire Life Insurance "
data = data + "Blue Cross/Blue Shield "
data = data + "Bonneville "
data = data + "Boston Old Colony "
data = data + "Builders "
data = data + "Cal Farm "
data = data + "California Casualty "
data = data + "California State Automobile Association "
data = data + "Camden "
data = data + "Capital Choice "
data = data + "Care Entrie "
data = data + "Cascade National Ins "
data = data + "Casualty Assurance "
data = data + "Centennial "
data = data + "Charter Oak "
data = data + "Chicago Insurance "
data = data + "Chubb "
data = data + "church Mutual "
data = data + "Cigna "
data = data + "Citizens "
data = data + "Clarendon American "
data = data + "Cloverleaf "
data = data + "CMA "
data = data + "CMA Alliance "
data = data + "CNA "
data = data + "Colonial "
data = data + "Combined "
data = data + "Commercial Union "
data = data + "Commonwealth "
data = data + "Continental "
data = data + "Cotton States "
data = data + "Cottonwood "
data = data + "Country Financial Services "
data = data + "Country Insurance "
data = data + "Credit Union "
data = data + "Criterion "
data = data + "CUNA Mutual "
data = data + "Dairyland "
data = data + "Dakota Fire "
data = data + "Deerbrook "
data = data + "Depositors Emcasc "
data = data + "Dixie "
data = data + "Ebco General "
data = data + "Economy "
data = data + "Electric "
data = data + "EMC "
data = data + "Empire "
data = data + "Employers Fire "
data = data + "Ensure "
data = data + "Equitable "
data = data + "Erie Insurance "
data = data + "Facility "
data = data + "Farm Bureau "
data = data + "Farmers "
data = data + "Farmland "
data = data + "Federal "
data = data + "Federated "
data = data + "Fidelity "
data = data + "Financial Indemnity "
data = data + "Fire and Casualty Co of CT "
data = data + "Fireman's Fund "
data = data + "First American "
data = data + "First Colony "
data = data + "First Financial "
data = data + "First General "
data = data + "First National "
data = data + "Ford Motor Credit "
data = data + "Foremost "
data = data + "Fortis Group "
data = data + "Franklin "
data = data + "Golden Rule "
data = data + "GEICO "
data = data + "GE Financial Network "
data = data + "General Accident "
data = data + "Gerber Life Insurance "
data = data + "Globe "
data = data + "GMAC "
data = data + "Golden Rule "
data = data + "Government Employees "
data = data + "Grange "
data = data + "GRE "
data = data + "Great American "
data = data + "Great Way "
data = data + "Great West "
data = data + "Grinnell Mutual "
data = data + "Guaranty National "
data = data + "Guardian "
data = data + "Guide One "
data = data + "GEICO "
data = data + "Halcyon "
data = data + "Hanover Lloyd's Company "
data = data + "Happy Days "
data = data + "Hartford "
data = data + "Hawkeye Security "
data = data + "Health Net "
data = data + "Health Plus of America "
data = data + "Heritage "
data = data + "Horace Mann "
data = data + "Humana "
data = data + "IDS "
data = data + "IFA Auto "
data = data + "IGF "
data = data + "Infinity "
data = data + "Insurance of Evanston "
data = data + "Integon "
data = data + "Interstatey "
data = data + "John Deere "
data = data + "John Hancock "
data = data + "Kaiser Foundation Health Plan "
data = data + "Kemper Lloyds "
data = data + "Kemper Insurance "
data = data + "Kentucky Central "
data = data + "Landmark American "
data = data + "Landmark Life Insurance "
data = data + "Leader General "
data = data + "Leader National "
data = data + "League General "
data = data + "Liberty Mutual "
data = data + "Lincoln Financial Group "
data = data + "London Life Insurance "
data = data + "Lumbermens Mutual "
data = data + "Managed Comp "
data = data + "Marathon "
data = data + "Markel American "
data = data + "Maryland Casualty "
data = data + "Mass Mutual "
data = data + "MBA Insurance "
data = data + "Mendota "
data = data + "Mega Life and Health Ins. "
data = data + "Merastar "
data = data + "Mercury "
data = data + "Met Life "
data = data + "Metropolitan Co. "
data = data + "Mid Century "
data = data + "Mid-Continent Casualty "
data = data + "MidWest Mutual "
data = data + "Mid-West Ntl. Life "
data = data + "MidCentury (Farmers) "
data = data + "Midwest Mutual "
data = data + "Middlesex "
data = data + "Millbank "
data = data + "Millers Mutual "
data = data + "Milwaukee "
data = data + "Milwaukee Guardian "
data = data + "Milwaukee Mutual "
data = data + "Minnehoma "
data = data + "Missouri General "
data = data + "Modern Woodmen of America "
data = data + "MONY Group "
data = data + "Motors "
data = data + "Mountain Laurel "
data = data + "MSI "
data = data + "Mutual of Enumclaw "
data = data + "Mutual of New York "
data = data + "Mutual Of Omaha "
data = data + "N.A.S.E. "
data = data + "National Alliance "
data = data + "National Assoc - Self Employed "
data = data + "National Colonial "
data = data + "National Continental "
data = data + "National Farmers Union "
data = data + "National Health "
data = data + "National Indemnity "
data = data + "National Merit "
data = data + "National Surety Corp "
data = data + "Nationwide "
data = data + "New England Financial "
data = data + "New York Life "
data = data + "North American "
data = data + "North Pacific "
data = data + "Northe Pointe "
data = data + "North Shore "
data = data + "Northern Capital "
data = data + "Northern States "
data = data + "Northland "
data = data + "Northwestern "
data = data + "Northwestern Mutual Life "
data = data + "Ohio Casualty "
data = data + "First Security "
data = data + "Olympia "
data = data + "Omaha "
data = data + "Omni "
data = data + "Oregon Mutual "
data = data + "Orion "
data = data + "Oxford Insurance "
data = data + "Pacific "
data = data + "Pacific Life Insurance "
data = data + "Pafco General "
data = data + "Paloverde "
data = data + "Pan-American Life Insurance "
data = data + "Patriot General "
data = data + "Peak Property and Casualty "
data = data + "PEMCO "
data = data + "Penn America "
data = data + "Penn Mutual "
data = data + "Pennsylvania Natl "
data = data + "Phoenix "
data = data + "Pinnacle "
data = data + "Pioneer Life "
data = data + "Preferred Abstainers "
data = data + "Preferred Risk "
data = data + "Premier "
data = data + "Prestige "
data = data + "Primerica "
data = data + "Principal Financial "
data = data + "Progressive Insurance "
data = data + "Protective Casualty "
data = data + "Protective Life "
data = data + "Provident Corporation "
data = data + "Prudential "
data = data + "Quality "
data = data + "RBC Liberty Insurance "
data = data + "Ramsey "
data = data + "Ranger "
data = data + "Regal "
data = data + "Reliance "
data = data + "Reliant "
data = data + "ReliaStar Life "
data = data + "Republic Indemnity "
data = data + "Response "
data = data + "Rockford Mutual "
data = data + "SAFECO "
data = data + "Safeway "
data = data + "Savings Bank Life Insurance "
data = data + "Sea West Insurance "
data = data + "Secura "
data = data + "Security Co of Hartford "
data = data + "Security National Co of FL "
data = data + "Sedgwick James "
data = data + "Sentinel "
data = data + "Sentry Group "
data = data + "Shelter Co. "
data = data + "Skandia "
data = data + "Spectrum "
data = data + "St. Paul "
data = data + "Standard Fire Company "
data = data + "Standard Guaranty "
data = data + "State Auto "
data = data + "State Farm "
data = data + "State Mutual "
data = data + "State National Ins "
data = data + "Sun Coast "
data = data + "Sun Life "
data = data + "Superior "
data = data + "Sutter "
data = data + "TICO "
data = data + "TIG Countrywide "
data = data + "Titan "
data = data + "Total "
data = data + "Tower "
data = data + "Travelers "
data = data + "Tri-State Consumer "
data = data + "Trinity Universal "
data = data + "Trust Hall "
data = data + "Twentieth Century "
data = data + "Twin City Fire "
data = data + "UGA "
data = data + "Unicare "
data = data + "Uniguard "
data = data + "Union "
data = data + "United American "
data = data + "United Financial "
data = data + "United Fire & Casual "
data = data + "United Security "
data = data + "United States Fideli "
data = data + "Unitrin "
data = data + "Unsure "
data = data + "US Health Advisors "
data = data + "USF&G "
data = data + "USAA "
data = data + "Utah Home and Fire "
data = data + "Utica "
data = data + "Vasa North Atlantic "
data = data + "Vigilant "
data = data + "Viking County Mutual "
data = data + "Viking Co of WI "
data = data + "Wausau Insurance "
data = data + "Wawaunesa "
data = data + "Wellington "
data = data + "West American "
data = data + "West Bend Mutual "
data = data + "West Field "
data = data + "West Plains "
data = data + "Western Mutal "
data = data + "Western National "
data = data + "Western Southern Life "
data = data + "Westfield "
data = data + "William Penn Life "
data = data + "Windsor "
data = data + "Windstar "
data = data + "Wisconsin Mutual "
data = data + "Workmans Auto "
data = data + "WorldWide "
data = data + "Yellow Key "
data = data + "Yosemite "
data = data + "Zurich North America "
data = data + "Other Company (Not Listed) "
data = data + " "
data = data + "How long have you had auto insurance with this company? * --Select-- Less than 6 months 6 months - 1 year 1-3 Years 3-5 Years 5+ Years Zero Months When does your policy renew? * "
data = data + ""
data = data + "Month "
data = data + "Jan "
data = data + "Feb "
data = data + "Mar "
data = data + "Apr "
data = data + "May "
data = data + "Jun "
data = data + "Jul "
data = data + "Aug "
data = data + "Sep "
data = data + "Oct "
data = data + "Nov "
data = data + "Dec "
data = data + " "
data = data + ""
data = data + "Date "
data = data + "01 "
data = data + "02 "
data = data + "03 "
data = data + "04 "
data = data + "05 "
data = data + "06 "
data = data + "07 "
data = data + "08 "
data = data + "09 "
data = data + "10 "
data = data + "11 "
data = data + "12 "
data = data + "13 "
data = data + "14 "
data = data + "15 "
data = data + "16 "
data = data + "17 "
data = data + "18 "
data = data + "19 "
data = data + "20 "
data = data + "21 "
data = data + "22 "
data = data + "23 "
data = data + "24 "
data = data + "25 "
data = data + "26 "
data = data + "27 "
data = data + "28 "
data = data + "29 "
data = data + "30 "
data = data + "31 "
data = data + " "
data = data + ""
data = data + "Year "
data = data + "2007 "
data = data + "2008 "
data = data + "2009 "
data = data + "2010 "
data = data + "2011 "
data = data + "2012 "
data = data + "2013 "
data = data + "2014 "
data = data + "2015 "
data = data + "2016 "
data = data + "2017 "
data = data + "2018 "
data = data + "2019 "
data = data + "2020 "
data = data + " "
data = data + " How much do you currently pay for your insurance? * How often do you pay that premium? * --Select-- Monthly Quarterly Every 6 Months Yearly what is your current liability limit? * --Select-- Not Currently Insured State Minimum $25,000/$50,000/$10,000 $50,000/$100,000/$25,000 $100,000/$300,000/$50,000 (Most Common) $250,000/$500,000/$100,000 $500,000/$1,000,000/100,000+ $1,000,000/$1,000,000/100,000+ Not Sure "
data = data + "How long have you continuously had auto insurance (with any company ) without a lapse in coverage? * --Select-- Less than 6 months 6 months - 1 year 1 Year 2 Years 3 Years 4 Years 5 Years 6+ Years Liability Information What is your approximate household income? --Select-- None 1-$10,000 $10,001-$25,000 $25,001-$50,000 $50,001-$100,000 $100,001-$150,000 $150,001-$250,000 $250,001-$400,000 $400,001+ Do your own your own home? * --Select-- Yes No Will Be Purchasing Home Within 90 Days "
data = data + "How long have you been at your current address? * --Select-- Less than 1 year 1-2 years 3-4 years 5 years more than 5 years How would you describe your credit history? * --Select-- Poor Fair Good Excellent How much liability coverage would you like to have? * State Minimum $50,000/$100,000/$25,000 $100,000/$300,000/$50,000 (Most Common) $250,000/$500,000/$100,000 "
data = data + "Would you like rental car coverage? * Would you like emergency roadside service (towing reimbursement)? * Driver Information Driver's First Name? * Driver's Last Name? * What State is this license for? * "
data = data + ""
data = data + "--Select-- "
data = data + "Alabama "
data = data + "Alaska "
data = data + "Arizona "
data = data + "Arkansas "
data = data + "California "
data = data + "Colorado "
data = data + "Connecticut "
data = data + "Delaware "
data = data + "District Of Columbia "
data = data + "Florida "
data = data + "Georgia "
data = data + "Hawaii "
data = data + "Idaho "
data = data + "Illinois "
data = data + "Indiana "
data = data + "Iowa "
data = data + "Kansas "
data = data + "Kentucky "
data = data + "Louisiana "
data = data + "Maine "
data = data + "Maryland "
data = data + "Massachusetts "
data = data + "Michigan "
data = data + "Minnesota "
data = data + "Mississippi "
data = data + "Missouri "
data = data + "Montana "
data = data + "Nebraska "
data = data + "Nevada "
data = data + "New Hampshire "
data = data + "New Jersey "
data = data + "New Mexico "
data = data + "New York "
data = data + "North Carolina "
data = data + "North Dakota "
data = data + "Ohio "
data = data + "Oklahoma "
data = data + "Oregon "
data = data + "Pennsylvania "
data = data + "Rhode Island "
data = data + "South Carolina "
data = data + "South Dakota "
data = data + "Tennessee "
data = data + "Texas "
data = data + "Utah "
data = data + "Vermont "
data = data + "Virginia "
data = data + "Washington "
data = data + "West Virginia "
data = data + "Wisconsin "
data = data + "Wyoming "
data = data + " "
data = data + " License Status * --Select-- Active Expired Foreign Permit Restricted Suspended Temporary Unlicensed Date of Birth * "
data = data + ""
data = data + "Month "
data = data + "Jan "
data = data + "Feb "
data = data + "Mar "
data = data + "Apr "
data = data + "May "
data = data + "Jun "
data = data + "Jul "
data = data + "Aug "
data = data + "Sep "
data = data + "Oct "
data = data + "Nov "
data = data + "Dec "
data = data + " "
data = data + ""
data = data + "Date "
data = data + "01 "
data = data + "02 "
data = data + "03 "
data = data + "04 "
data = data + "05 "
data = data + "06 "
data = data + "07 "
data = data + "08 "
data = data + "09 "
data = data + "10 "
data = data + "11 "
data = data + "12 "
data = data + "13 "
data = data + "14 "
data = data + "15 "
data = data + "16 "
data = data + "17 "
data = data + "18 "
data = data + "19 "
data = data + "20 "
data = data + "21 "
data = data + "22 "
data = data + "23 "
data = data + "24 "
data = data + "25 "
data = data + "26 "
data = data + "27 "
data = data + "28 "
data = data + "29 "
data = data + "30 "
data = data + "31 "
data = data + " "
data = data + ""
data = data + "1992 "
data = data + "1991 "
data = data + "1990 "
data = data + "1989 "
data = data + "1988 "
data = data + "1987 "
data = data + "1986 "
data = data + "1985 "
data = data + "1984 "
data = data + "1983 "
data = data + "1982 "
data = data + "1981 "
data = data + "1980 "
data = data + "1979 "
data = data + "1978 "
data = data + "1977 "
data = data + "1976 "
data = data + "1975 "
data = data + "1974 "
data = data + "1973 "
data = data + "1972 "
data = data + "1971 "
data = data + "1970 "
data = data + "1969 "
data = data + "1968 "
data = data + "1967 "
data = data + "1966 "
data = data + "1965 "
data = data + "1964 "
data = data + "1963 "
data = data + "1962 "
data = data + "1961 "
data = data + "1960 "
data = data + "1959 "
data = data + "1958 "
data = data + "1957 "
data = data + "1956 "
data = data + "1955 "
data = data + "1954 "
data = data + "1953 "
data = data + "1952 "
data = data + "1951 "
data = data + "1950 "
data = data + "1949 "
data = data + "1948 "
data = data + "1947 "
data = data + "1946 "
data = data + "1945 "
data = data + "1944 "
data = data + "1943 "
data = data + "1942 "
data = data + "1941 "
data = data + "1940 "
data = data + "1939 "
data = data + "1938 "
data = data + "1937 "
data = data + "1936 "
data = data + "1935 "
data = data + "1934 "
data = data + "1933 "
data = data + "1932 "
data = data + "1931 "
data = data + "1930 "
data = data + "1929 "
data = data + "1928 "
data = data + "1927 "
data = data + "1926 "
data = data + "1925 "
data = data + "1924 "
data = data + "1923 "
data = data + "1922 "
data = data + "1921 "
data = data + "1920 "
data = data + "1919 "
data = data + "1918 "
data = data + "1917 "
data = data + "1916 "
data = data + "1915 "
data = data + "1914 "
data = data + "1913 "
data = data + "1912 "
data = data + "1911 "
data = data + "1910 "
data = data + " "
data = data + " Gender * How long has this driver been licensed in the U.S. or Canada? * --Select-- less than 1 year between 1 and 2 years between 2 and 3 years between 3 and 4 years between 4 and 5 more than 5 years Marital Status * Single Single-parent Married Seperated Divorced Widowed --Select ( not given )-- Occupation * "
data= data + ""
data= data + "--Select-- "
data= data + "Account Executive "
data= data + "Accountant/Auditor "
data= data + "Actuarial Clerk "
data= data + "Actuary "
data= data + "Administrative Assistant "
data= data + "Agent/Broker "
data= data + "Agriculture Inspector/Grader "
data= data + "Air Traffic Control "
data= data + "Analyst "
data= data + "Analyst Broker "
data= data + "Animal Control Officer "
data= data + "Announcer/Broadcaster "
data= data + "Arborist "
data= data + "Architect "
data= data + "Assistant - Medic/Dent/Vet "
data= data + "Attorney "
data= data + "Audio-Visual Tech "
data= data + "Bailiff "
data= data + "Baker "
data= data + "Building Maintenance Engineer "
data= data + "Bookkeeper "
data= data + "Buyer "
data= data + "Camp Counselor/Lead "
data= data + "Caterer "
data= data + "chief Executive "
data= data + "Claims Adjuster "
data= data + "Clergy "
data= data + "Clerk "
data= data + "Clinical Data Coordinator "
data= data + "Coach "
data= data + "Collections "
data= data + "Commissioner "
data= data + " Composer/Director "
data= data + "Concessionaire "
data= data + "Construction - Project Manager "
data= data + "Consultant "
data= data + "Controller "
data= data + "Corrections Officer "
data= data + "Council Member "
data= data + "Counselor "
data= data + "Court Clerk/Reporter "
data= data + "CSR/Teller "
data= data + "Curator "
data= data + "Dental Hygenist "
data= data + "Deputy Sheriff "
data= data + "Designer "
data= data + "Director, Program "
data= data + "Director/Administrator "
data= data + "Disable "
data= data + "Dispatcher "
data= data + "Doctor/Dentist "
data= data + "Drafter "
data= data + "Editor "
data= data + "Electrician/Linesman "
data= data + "Engineer "
data= data + "Event Manager/Promoter "
data= data + "Examiner "
data= data + "Executive "
data= data + "Farm/Ranch Owner "
data= data + "Federal Agent/Marshall "
data= data + "Field Service Technician "
data= data + "Financial Advisor "
data= data + "Fire Chief "
data= data + "Fire Fighter/Supervisor "
data= data + "Flight Attendant "
data= data + "Florist "
data= data + "Foreman/Supervisor "
data= data + "Gaming Officer/Investigator "
data= data + "Graduate Teaching Assistant "
data= data + "H.R. Representative "
data= data + "Heat/Air Conditioner Repair "
data= data + "Heat/Air Technician "
data= data + "Highway Patrol Officer "
data= data + "Homemaker/House person "
data= data + "Hospice Volunteer "
data= data + "Inspector "
data= data + "Instructor-Vocation "
data= data + "Investment Banker "
data= data + "Journalist/Reporter "
data= data + "Judge/Hearing Officer "
data= data + "Legal Assistant/Secretary "
data= data + "Legislator "
data= data + "Librarian/Curator "
data= data + "Loan/Escrow Processor "
data= data + "Manager - Other "
data= data + "Marketing Researcher "
data= data + "Mathematician "
data= data + "Mayor/City Manager "
data= data + "Meter Reader "
data= data + "Military "
data= data + "Military E5-E9 "
data= data + "Military Officer "
data= data + "Mortician "
data= data + "Network Administrator "
data= data + "Nurse - C.N.A. "
data= data + "Nurse - RN/LPN/Practitioner "
data= data + "Officer-Warrant "
data= data + "Optometrist "
data= data + "Other "
data= data + "Paralegal/Law Clerk "
data= data + "Paramedic/E.M.Technician "
data= data + "Park Ranger "
data= data + "Pharmacist "
data= data + "Pilot/Captain/Engineer "
data= data + "Planner "
data= data + "Plumber "
data= data + "Police Officer/Sheriff/Detective "
data= data + "Postmaster "
data= data + "Printer/Bookbinder "
data= data + "Producer "
data= data + "Product Manager "
data= data + "Professor, College "
data= data + "Programmer "
data= data + "Project Coordinator "
data= data + "Quality Control "
data= data + "Ranger "
data= data + "Realtor "
data= data + "Receptionist/Secretary "
data= data + "Regulator "
data= data + "Research Program Director "
data= data + "Researcher "
data= data + "Retired "
data= data + "Sales Agent/Representative "
data= data + "Scientist "
data= data + "Secretary "
data= data + "Shoemaker "
data= data + "Social Worker "
data= data + "Sociologist "
data= data + "Sports Broadcaster/Journalist "
data= data + "Student "
data= data + "Superintendent "
data= data + "Support Technician "
data= data + "Surveyor/Mapmaker "
data= data + "Systems Security "
data= data + "Tailor/Custom Sewer "
data= data + "Teacher, K-12/College "
data= data + "Teaching Assistant/Aide "
data= data + "Technical Writer "
data= data + "Technician "
data= data + "Therapist "
data= data + "Ticket Agent "
data= data + "Ticket Sales/Usher "
data= data + "Trader, Financial Instruments "
data= data + "Trainer/Instructor "
data= data + "Tutor "
data= data + "Umpire/Referee "
data= data + "Underwriter "
data= data + "Unemployed "
data= data + "Upholsterer "
data= data + "US Postal Worker "
data= data + "Valet "
data= data + "Veterinarian "
data= data + "Web Developer "
data= data + "Wine Steward "
data= data + " "
data= data + " If this driver is a student, what is his/her GPA? Education Level * Some High School High School Grad Some College Associates Degree Bachelors Degree Masters Degree Doctorate --Select (not Given) -- Driving Record violations/claims in * "
data = data + ""
data = data + "Month "
data = data + "Jan "
data = data + "Feb "
data = data + "Mar "
data = data + "Apr "
data = data + "May "
data = data + "Jun "
data = data + "Jul "
data = data + "Aug "
data = data + "Sep "
data = data + "Oct "
data = data + "Nov "
data = data + "Dec "
data = data + " "
data = data + ""
data = data + "Year "
data = data + "1999 "
data = data + "2000 "
data = data + "2001 "
data = data + "2002 "
data = data + "2003 "
data = data + "2004 "
data = data + "2005 "
data = data + "2006 "
data = data + "2007 "
data = data + " "
data = data + ""
data = data + "Type "
data = data + "Minor Violation (Speeding, Running a stop sign, etc.) "
data = data + "Major Violation (Reckless Driving, Hit and Run, etc.) "
data = data + "Not At Fault Accident "
data = data + "At-fault Accident (Property damage only) "
data = data + "At-fault Accident (Person injured) "
data = data + "Loss or theft claim (theft, vandalism, etc.) "
data = data + " "
data = data + " "
data = data + "Auto Information Vehicle Year * "
data = data + ""
data = data + "--Year-- "
data = data + "2008 "
data = data + "2007 "
data = data + "2006 "
data = data + "2005 "
data = data + "2004 "
data = data + "2003 "
data = data + "2002 "
data = data + "2001 "
data = data + "2000 "
data = data + "1999 "
data = data + "1998 "
data = data + "1997 "
data = data + "1996 "
data = data + "1995 "
data = data + "1994 "
data = data + "1993 "
data = data + "1992 "
data = data + "1991 "
data = data + "1990 "
data = data + "1989 "
data = data + "1988 "
data = data + "1987 "
data = data + "1986 "
data = data + "1985 "
data = data + "1984 "
data = data + "1983 "
data = data + "1982 "
data = data + "1981 "
data = data + "1980 "
data = data + "1979 "
data = data + "1978 "
data = data + "1977 "
data = data + "1976 "
data = data + "1975 "
data = data + "1974 "
data = data + "1973 "
data = data + "1972 "
data = data + "1971 "
data = data + "1970 "
data = data + "1969 "
data = data + "1968 "
data = data + "1967 "
data = data + "1966 "
data = data + "1965 "
data = data + "1964 "
data = data + "1963 "
data = data + "1962 "
data = data + "1961 "
data = data + "1960 "
data = data + "1959 "
data = data + "1958 "
data = data + "1957 "
data = data + "1956 "
data = data + "1955 "
data = data + "1954 "
data = data + "1953 "
data = data + "1952 "
data = data + "1951 "
data = data + "1950 "
data = data + "1949 "
data = data + "1948 "
data = data + "1947 "
data = data + "1946 "
data = data + "1945 "
data = data + "1944 "
data = data + "1943 "
data = data + "1942 "
data = data + "1941 "
data = data + "1940 "
data = data + "1939 "
data = data + "1938 "
data = data + "1937 "
data = data + "1936 "
data = data + "1935 "
data = data + "1934 "
data = data + "1933 "
data = data + "1932 "
data = data + "1931 "
data = data + "1930 "
data = data + "1929 "
data = data + "1928 "
data = data + "1927 "
data = data + "1926 "
data = data + "1925 "
data = data + "1924 "
data = data + "1923 "
data = data + "1922 "
data = data + "1921 "
data = data + "1920 "
data = data + "1919 "
data = data + "1918 "
data = data + "1917 "
data = data + "1916 "
data = data + "1915 "
data = data + "1914 "
data = data + "1913 "
data = data + "1912 "
data = data + "1911 "
data = data + "1910 "
data = data + "
"
data = data + " "
data = data + " Vehicle Make: "
data = data + " "
data = data + " "
data = data + " "
data = data + " --Select-- "
data = data + " (Not Listed) "
data = data + " AMERICAN MOTORS "
data = data + " ASTON MARTIN "
data = data + " AUSTIN "
data = data + " AVANTI "
data = data + " BENTLEY "
data = data + " BMW "
data = data + " BUICK "
data = data + " CADILLAC "
data = data + " CHEVROLET "
data = data + " CHRYSLER "
data = data + " DAIMLER "
data = data + " DODGE "
data = data + " FERRARI "
data = data + " FIAT "
data = data + " FORD "
data = data + " GMC "
data = data + " HONDA "
data = data + " IMPERIAL "
data = data + " INTERNATIONAL "
data = data + " JAGUAR "
data = data + " JEEP "
data = data + " JENSEN "
data = data + " LINCOLN "
data = data + " MASERATI "
data = data + " MAZDA "
data = data + " MERCEDES-BENZ "
data = data + " MERCURY "
data = data + " MG "
data = data + " MORGAN "
data = data + " NISSAN "
data = data + " OLDSMOBILE "
data = data + " OPEL "
data = data + " PLYMOUTH "
data = data + " PONTIAC "
data = data + " PORSCHE "
data = data + " RENAULT "
data = data + " RILEY "
data = data + " ROLLS ROYCE "
data = data + " SHELBY "
data = data + " STUDEBAKER "
data = data + " SUNBEAM "
data = data + " TOYOTA "
data = data + " TRIUMPH "
data = data + " VOLKSWAGEN "
data = data + " VOLVO "
data = data + " WILLYS wrinivar "
data = data + " "
data = data + "
"
data = data + " "
data = data + ""
data = data + " Vehicle Model: "
data = data + " "
data = data + " "
data = data + "
"
data = data + " "
data = data + " "
data = data + ""
data = data + " Vehicle Trim: "
data = data + " "
data = data + " "
data = data + "
"
data = data + " "
data = data + " "
data = data + "Type of fuel * --selecte-- Gas Diesel Electric Number of Doors * 2 3 4 5+ What is the Main Use of your Car? * "
data = data + ""
data = data + "Commute to Work less than 5 miles "
data = data + "Commute to Work 5-10 miles "
data = data + "Commute to Work 11-20 miles "
data = data + "Commute to Work more than 20 miles "
data = data + "Commute to School less than 5 miles "
data = data + "Commute to School 5-10 miles "
data = data + "Commute to School 11-20 miles "
data = data + "Commute to School more than 20 miles "
data = data + "Business (Individual) "
data = data + "Business (Corporate) "
data = data + "Pleasure "
data = data + "Farm "
data = data + " "
data = data + " Estimated Annual Usage (in miles) * Desired Comprehensive Deductible * $50 $100 $250 $500 $1,000 $2,500 $5,000 None Desired Collision Deductible * $50 $100 $250 $500 $1,000 None Is this car Leased or Owned? * --Select-- Owned Financed Leased Best Time to Contact You * --Select-- Morning Afternoon evening
"
}
if (document.frm.InsuranceType.value == "Life Insurance")
{
/*
data=data + "Tell us about what your coverage should be: How much insurance do you want? $100,000 - $199,999 $200,000 - $299,999 $300,000 - $399,999 $400,000 - $499,999 $500,000 - $599,999 $600,000 - $699,999 $700,000 - $799,999 $800,000 - $899,999 $900,000 - $999,999 $1,000,000 - $2,000,000 $2,000,000 - $3,000,000 $3,000,000 - $4,000,000 $4,000,000 - $5,000,000 $5,000,000 + What type of insurance do you want? Term Insurance Universal Life Whole Life Variable Universal Life I Don't Know How long do you want coverage for? 99 Years (Whole Life) 30 or More Years 25 or More Years 20 or More Years 15 or More Years 10 or More Years 5 or More Years 1 or More Years "
data=data+" Purpose of insurance: Income to family in case of death Mortgage protection Child's Education Estate protection Replace existing insurance "
data=data+" Tell us about your current coverage: "
data=data+" Amount of insurance in force now: $100,000 - $199,999 $200,000 - $299,999 $300,000 - $399,999 $400,000 - $499,999 $500,000 - $599,999 $600,000 - $699,999 $700,000 - $799,999 $800,000 - $899,999 $900,000 - $999,999 $1,000,000 - $2,000,000 $2,000,000 - $3,000,000 $3,000,000 - $4,000,000 $4,000,000 - $5,000,000 $5,000,000 + None "
data=data+" When did you last apply for insurance? Within past month Within past 3 months Within past 6 months Within past 9 months Within past year Within past 3 years Within past 5 years Longer than 5 years ago "
data=data+"To which companies? (separate with commas) What was the outcome? Accepted Denied "
data=data+" Tell us about any health concerns:
"
data=data+" Medical Information :Have,have had: (blank if N/A) "
data=data+" Please list medications and dosage: (blank if N/A) "
data=data+" Describe your family's history of cancer and/or heart disease: (blank if N/A) "
data=data+" Some one in the family has,has had: (blank if N/A) "
data=data+" Do you Smoke,If yes Select Type: None Cigarettes Cigars Chewing tobacco Pipe
"
*/
//New Fields For HTQ
data="Tell us about your current situation: Is any applicant a smoker? * --Select-- Yes No Have you been rated or declined for health or life insurance in the last 5 years? * Have you been hospitalized in the last 5 years? * Have you had a DUI/DWI in the last 5 years? * Have you been a resident of the U.S. or Canada for the last 12 months? * Do you currently take prescription medications? * If yes, please list medication names and dosages: * Do you currently have a life insurance? * --Select-- Yes No If so, with what company? * "
data = data + ""
data = data + "--Select-- "
data = data + ""
data = data + "AAA "
data = data + "AIG "
data = data + "Allied "
data = data + "Allstate "
data = data + "American Family "
data = data + "Amica "
data = data + "Farm Bureau "
data = data + "Farmers "
data = data + "GEICO "
data = data + "Hartford "
data = data + "Liberty Mutual "
data = data + "Metropolitan Co. "
data = data + "Nationwide "
data = data + "Progressive "
data = data + "Prudential "
data = data + "SAFECO "
data = data + "State Farm "
data = data + "Travelers "
data = data + "United Services Automobile Association "
data = data + "Unitrin Direct "
data = data + "Other Company (Not Listed) "
data = data + ""
data = data + ""
data = data + ""
data = data + "Other Company (Not Listed) "
data = data + "AAA "
data = data + "AABCO "
data = data + "Acceptance "
data = data + "Access Insurance "
data = data + "Acordia "
data = data + "Aegis Security "
data = data + "AETNA "
data = data + "Affirmative "
data = data + "AIG "
data = data + "AIU "
data = data + "Alliance for Affordable Services "
data = data + "Allied "
data = data + "All Nation "
data = data + "All Risk "
data = data + "Allianz "
data = data + "Allstate "
data = data + "Amalgamated Life Insurance "
data = data + "AMCO "
data = data + "America's Ins. Consultants "
data = data + "American Alliance "
data = data + "American Banks "
data = data + "American Economy "
data = data + "American Empire Group "
data = data + "American Family "
data = data + "American General "
data = data + "American International Group "
data = data + "American Investors "
data = data + "American National "
data = data + "American Premier "
data = data + "American Reliable "
data = data + "American Republic "
data = data + "American Standard "
data = data + "American States "
data = data + "American Sterling Insurance "
data = data + "American Underwriters "
data = data + "American United Life Insurance "
data = data + "Amerisure "
data = data + "AmerUs Life "
data = data + "AmwestInsurance Group "
data = data + "Amica "
data = data + "API "
data = data + "Arbella "
data = data + "Arizona General "
data = data + "Assigned Risk "
data = data + "Association Field Services "
data = data + "Associated Indemnity "
data = data + "Assurity LIfe "
data = data + "Atlanta Casualty "
data = data + "Atlantic Indemnity "
data = data + "Austin Mutual "
data = data + "Auto Owners "
data = data + "Avomark "
data = data + "Badger Mutual "
data = data + "Bankers & Shippers "
data = data + "Bankers Life and Casualty "
data = data + "Beneficial Life Insurance "
data = data + "Berkshire Life Insurance "
data = data + "Blue Cross/Blue Shield "
data = data + "Bonneville "
data = data + "Boston Old Colony "
data = data + "Builders "
data = data + "Cal Farm "
data = data + "California Casualty "
data = data + "California State Automobile Association "
data = data + "Camden "
data = data + "Capital Choice "
data = data + "Care Entrie "
data = data + "Cascade National Ins "
data = data + "Casualty Assurance "
data = data + "Centennial "
data = data + "Charter Oak "
data = data + "Chicago Insurance "
data = data + "Chubb "
data = data + "church Mutual "
data = data + "Cigna "
data = data + "Citizens "
data = data + "Clarendon American "
data = data + "Cloverleaf "
data = data + "CMA "
data = data + "CMA Alliance "
data = data + "CNA "
data = data + "Colonial "
data = data + "Combined "
data = data + "Commercial Union "
data = data + "Commonwealth "
data = data + "Continental "
data = data + "Cotton States "
data = data + "Cottonwood "
data = data + "Country Financial Services "
data = data + "Country Insurance "
data = data + "Credit Union "
data = data + "Criterion "
data = data + "CUNA Mutual "
data = data + "Dairyland "
data = data + "Dakota Fire "
data = data + "Deerbrook "
data = data + "Depositors Emcasc "
data = data + "Dixie "
data = data + "Ebco General "
data = data + "Economy "
data = data + "Electric "
data = data + "EMC "
data = data + "Empire "
data = data + "Employers Fire "
data = data + "Ensure "
data = data + "Equitable "
data = data + "Erie Insurance "
data = data + "Facility "
data = data + "Farm Bureau "
data = data + "Farmers "
data = data + "Farmland "
data = data + "Federal "
data = data + "Federated "
data = data + "Fidelity "
data = data + "Financial Indemnity "
data = data + "Fire and Casualty Co of CT "
data = data + "Fireman's Fund "
data = data + "First American "
data = data + "First Colony "
data = data + "First Financial "
data = data + "First General "
data = data + "First National "
data = data + "Ford Motor Credit "
data = data + "Foremost "
data = data + "Fortis Group "
data = data + "Franklin "
data = data + "Golden Rule "
data = data + "GEICO "
data = data + "GE Financial Network "
data = data + "General Accident "
data = data + "Gerber Life Insurance "
data = data + "Globe "
data = data + "GMAC "
data = data + "Golden Rule "
data = data + "Government Employees "
data = data + "Grange "
data = data + "GRE "
data = data + "Great American "
data = data + "Great Way "
data = data + "Great West "
data = data + "Grinnell Mutual "
data = data + "Guaranty National "
data = data + "Guardian "
data = data + "Guide One "
data = data + "GEICO "
data = data + "Halcyon "
data = data + "Hanover Lloyd's Company "
data = data + "Happy Days "
data = data + "Hartford "
data = data + "Hawkeye Security "
data = data + "Health Net "
data = data + "Health Plus of America "
data = data + "Heritage "
data = data + "Horace Mann "
data = data + "Humana "
data = data + "IDS "
data = data + "IFA Auto "
data = data + "IGF "
data = data + "Infinity "
data = data + "Insurance of Evanston "
data = data + "Integon "
data = data + "Interstatey "
data = data + "John Deere "
data = data + "John Hancock "
data = data + "Kaiser Foundation Health Plan "
data = data + "Kemper Lloyds "
data = data + "Kemper Insurance "
data = data + "Kentucky Central "
data = data + "Landmark American "
data = data + "Landmark Life Insurance "
data = data + "Leader General "
data = data + "Leader National "
data = data + "League General "
data = data + "Liberty Mutual "
data = data + "Lincoln Financial Group "
data = data + "London Life Insurance "
data = data + "Lumbermens Mutual "
data = data + "Managed Comp "
data = data + "Marathon "
data = data + "Markel American "
data = data + "Maryland Casualty "
data = data + "Mass Mutual "
data = data + "MBA Insurance "
data = data + "Mendota "
data = data + "Mega Life and Health Ins. "
data = data + "Merastar "
data = data + "Mercury "
data = data + "Met Life "
data = data + "Metropolitan Co. "
data = data + "Mid Century "
data = data + "Mid-Continent Casualty "
data = data + "MidWest Mutual "
data = data + "Mid-West Ntl. Life "
data = data + "MidCentury (Farmers) "
data = data + "Midwest Mutual "
data = data + "Middlesex "
data = data + "Millbank "
data = data + "Millers Mutual "
data = data + "Milwaukee "
data = data + "Milwaukee Guardian "
data = data + "Milwaukee Mutual "
data = data + "Minnehoma "
data = data + "Missouri General "
data = data + "Modern Woodmen of America "
data = data + "MONY Group "
data = data + "Motors "
data = data + "Mountain Laurel "
data = data + "MSI "
data = data + "Mutual of Enumclaw "
data = data + "Mutual of New York "
data = data + "Mutual Of Omaha "
data = data + "N.A.S.E. "
data = data + "National Alliance "
data = data + "National Assoc - Self Employed "
data = data + "National Colonial "
data = data + "National Continental "
data = data + "National Farmers Union "
data = data + "National Health "
data = data + "National Indemnity "
data = data + "National Merit "
data = data + "National Surety Corp "
data = data + "Nationwide "
data = data + "New England Financial "
data = data + "New York Life "
data = data + "North American "
data = data + "North Pacific "
data = data + "Northe Pointe "
data = data + "North Shore "
data = data + "Northern Capital "
data = data + "Northern States "
data = data + "Northland "
data = data + "Northwestern "
data = data + "Northwestern Mutual Life "
data = data + "Ohio Casualty "
data = data + "First Security "
data = data + "Olympia "
data = data + "Omaha "
data = data + "Omni "
data = data + "Oregon Mutual "
data = data + "Orion "
data = data + "Oxford Insurance "
data = data + "Pacific "
data = data + "Pacific Life Insurance "
data = data + "Pafco General "
data = data + "Paloverde "
data = data + "Pan-American Life Insurance "
data = data + "Patriot General "
data = data + "Peak Property and Casualty "
data = data + "PEMCO "
data = data + "Penn America "
data = data + "Penn Mutual "
data = data + "Pennsylvania Natl "
data = data + "Phoenix "
data = data + "Pinnacle "
data = data + "Pioneer Life "
data = data + "Preferred Abstainers "
data = data + "Preferred Risk "
data = data + "Premier "
data = data + "Prestige "
data = data + "Primerica "
data = data + "Principal Financial "
data = data + "Progressive Insurance "
data = data + "Protective Casualty "
data = data + "Protective Life "
data = data + "Provident Corporation "
data = data + "Prudential "
data = data + "Quality "
data = data + "RBC Liberty Insurance "
data = data + "Ramsey "
data = data + "Ranger "
data = data + "Regal "
data = data + "Reliance "
data = data + "Reliant "
data = data + "ReliaStar Life "
data = data + "Republic Indemnity "
data = data + "Response "
data = data + "Rockford Mutual "
data = data + "SAFECO "
data = data + "Safeway "
data = data + "Savings Bank Life Insurance "
data = data + "Sea West Insurance "
data = data + "Secura "
data = data + "Security Co of Hartford "
data = data + "Security National Co of FL "
data = data + "Sedgwick James "
data = data + "Sentinel "
data = data + "Sentry Group "
data = data + "Shelter Co. "
data = data + "Skandia "
data = data + "Spectrum "
data = data + "St. Paul "
data = data + "Standard Fire Company "
data = data + "Standard Guaranty "
data = data + "State Auto "
data = data + "State Farm "
data = data + "State Mutual "
data = data + "State National Ins "
data = data + "Sun Coast "
data = data + "Sun Life "
data = data + "Superior "
data = data + "Sutter "
data = data + "TICO "
data = data + "TIG Countrywide "
data = data + "Titan "
data = data + "Total "
data = data + "Tower "
data = data + "Travelers "
data = data + "Tri-State Consumer "
data = data + "Trinity Universal "
data = data + "Trust Hall "
data = data + "Twentieth Century "
data = data + "Twin City Fire "
data = data + "UGA "
data = data + "Unicare "
data = data + "Uniguard "
data = data + "Union "
data = data + "United American "
data = data + "United Financial "
data = data + "United Fire & Casual "
data = data + "United Security "
data = data + "United States Fideli "
data = data + "Unitrin "
data = data + "Unsure "
data = data + "US Health Advisors "
data = data + "USF&G "
data = data + "USAA "
data = data + "Utah Home and Fire "
data = data + "Utica "
data = data + "Vasa North Atlantic "
data = data + "Vigilant "
data = data + "Viking County Mutual "
data = data + "Viking Co of WI "
data = data + "Wausau Insurance "
data = data + "Wawaunesa "
data = data + "Wellington "
data = data + "West American "
data = data + "West Bend Mutual "
data = data + "West Field "
data = data + "West Plains "
data = data + "Western Mutal "
data = data + "Western National "
data = data + "Western Southern Life "
data = data + "Westfield "
data = data + "William Penn Life "
data = data + "Windsor "
data = data + "Windstar "
data = data + "Wisconsin Mutual "
data = data + "Workmans Auto "
data = data + "WorldWide "
data = data + "Yellow Key "
data = data + "Yosemite "
data = data + "Zurich North America "
data = data + "Other Company (Not Listed) "
data = data + " Do you want coverage for your spouse? * --Select-- Yes No Not Applicable Do you want coverage for your children? * --Select-- Yes No Not Applicable What type of life insurance coverage are you interested in? * "
data = data + ""
data = data + ""
data = data + ""
data = data + ""
data = data + "--Select-- "
data = data + "$10,000 "
data = data + "$25,000 "
data = data + "$50,000 "
data = data + "$75,000 "
data = data + "$100,000 "
data = data + "$150,000 "
data = data + "$200,000 "
data = data + "$250,000 "
data = data + "$300,000 "
data = data + "$350,000 "
data = data + "$400,000 "
data = data + "$450,000 "
data = data + "$500,000 "
data = data + "$600,000 "
data = data + "$700,000 "
data = data + "$800,000 "
data = data + "$900,000 "
data = data + "$1 MILLION "
data = data + "$1.5 MILLION "
data = data + "$2 MILLION "
data = data + "$2.5 MILLION "
data = data + "$3 MILLION "
data = data + "$3.5 MILLION "
data = data + "$4 MILLION "
data = data + "$4.5 MILLION "
data = data + "$5 MILLION "
data = data + "$6 MILLION "
data = data + "$7 MILLION "
data = data + "$8 MILLION "
data = data + "$9 MILLION "
data = data + "$10+ MILLION "
data = data + "NOT SURE "
data = data + " "
data = data + "--Select-- "
data = data + "Term 1 Year Annually Renewable "
data = data + "Term 5 Year Guaranteed Level Premium "
data = data + "Term 10 Year Guaranteed Level Premium "
data = data + "Term 15 Year Guaranteed Level Premium "
data = data + "Term 20 Year Guaranteed Level Premium "
data = data + "Term 25 Year Guaranteed Level Premium "
data = data + "Term 30 Year Guaranteed Level Premium "
data = data + " "
data = data + "
"
data = data + " "
data = data + " "
data = data + ""
data = data + ""
data = data + ""
data = data + ""
data = data + ""
data = data + "--Select-- "
data = data + "$10,000 "
data = data + "$25,000 "
data = data + "$50,000 "
data = data + "$75,000 "
data = data + "$100,000 "
data = data + "$150,000 "
data = data + "$200,000 "
data = data + "$250,000 "
data = data + "$300,000 "
data = data + "$350,000 "
data = data + "$400,000 "
data = data + "$450,000 "
data = data + "$500,000 "
data = data + "$600,000 "
data = data + "$700,000 "
data = data + "$800,000 "
data = data + "$900,000 "
data = data + "$1 MILLION "
data = data + "$1.5 MILLION "
data = data + "$2 MILLION "
data = data + "$2.5 MILLION "
data = data + "$3 MILLION "
data = data + "$3.5 MILLION "
data = data + "$4 MILLION "
data = data + "$4.5 MILLION "
data = data + "$5 MILLION "
data = data + "$6 MILLION "
data = data + "$7 MILLION "
data = data + "$8 MILLION "
data = data + "$9 MILLION "
data = data + "$10+ MILLION "
data = data + "NOT SURE "
data = data + " "
data = data + "--Select-- "
data = data + "Permanent Whole "
data = data + "Permanent Universal "
data = data + "Permanent Variable "
data = data + " "
data = data + "
"
data = data + " "
data = data + " "
data = data + ""
data = data + ""
data = data + ""
data = data + ""
data = data + ""
data = data + "--Select-- "
data = data + "$10,000 "
data = data + "$25,000 "
data = data + "$50,000 "
data = data + "$75,000 "
data = data + "$100,000 "
data = data + "$150,000 "
data = data + "$200,000 "
data = data + "$250,000 "
data = data + "$300,000 "
data = data + "$350,000 "
data = data + "$400,000 "
data = data + "$450,000 "
data = data + "$500,000 "
data = data + "$600,000 "
data = data + "$700,000 "
data = data + "$800,000 "
data = data + "$900,000 "
data = data + "$1 MILLION "
data = data + "$1.5 MILLION "
data = data + "$2 MILLION "
data = data + "$2.5 MILLION "
data = data + "$3 MILLION "
data = data + "$3.5 MILLION "
data = data + "$4 MILLION "
data = data + "$4.5 MILLION "
data = data + "$5 MILLION "
data = data + "$6 MILLION "
data = data + "$7 MILLION "
data = data + "$8 MILLION "
data = data + "$9 MILLION "
data = data + "$10+ MILLION "
data = data + "NOT SURE "
data = data + " "
data = data + " "
data = data + " "
data = data + "
"
data = data + " "
data = data + " "
data = data + "Best Time to Contact You * Select Morning Afternoon evening How soon do you need this policy? * Select Immediately 48 Hours This Week
"
//end of life ins new fields
}
pop.innerHTML=data;
}