Using a powerful insurance segmentation model, these individuals have been identified as being highly likely to buy Term Life Insurance products based on policy value. The model uses in-depth, exhaustive research data of recent consumer insurance behavior and intentions. This very specific profile of Term Life Insurance Buyers drives the process for identifying those households with the greatest propensity to respond to a Term Life Insurance offer.

Using a powerful insurance segmentation model, these individuals have been identified as being highly likely to be Auto Insurance Switchers. The model uses in-depth, exhaustive research data of recent consumer insurance behavior and intentions. This very specific profile of Auto Insurance Switchers drives the process for identifying those households with the greatest propensity to respond to an offer toswitch their Auto Insurance coverage to another company.

These consumers have responded to offers for products and services relating to refinancing a mortgage. These people are excellent candidates or various offers including mortgages, home equity, refinancing, home decorating, renovation and landscaping, household items as well as catalog/online shopping credit cards, insurance and financial offers and more. Source: Online Responders.

These consumers have responded to offers for mortgage products and services. These people make an excellent audience for various offers including insurance, mortgages, home equity, refinancing, home decorating, renovation and landscaping, household items as well as catalog/online shopping credit cards and financial offers and more. Source: Online Responders.

This list identifies Americans who are prime prospects for bankcards. They tend to have bank cards but are perfect candidates for additional sources of credit. This group is an excellent audience for bank, gas, department store and secured cards, loans and sweepstakes offers as well as for rent-with-an-option to buy offers.

Using a powerful net worth segmentation model, these households have been identified as having net worths equal to or greater than one million dollars. The model uses in-depth, exhaustive research data of recent consumer financial behavior and intentions. This very specific profile of High Net Worth Households drives the process for identifying those households with the greatest propensity to have High Net Worth.

These consumers have responded to offers for life insurance products and services. These people make excellent prospects for financial and insurance offers, household items catalogs, travel, sweepstakes, subscriptions and more. Source: Online Responders.

Using a powerful insurance segmentation model, these individuals have been identified as being highly likely to buy Health Care Insurance products. The model uses in-depth, exhaustive research data of recent consumer insurance behavior and intentions. This very specific profile of Health Care Insurance Buyers drives the process for identifying those households with the greatest propensity to respond to a Health Care Insurance offer.

Using a powerful insurance segmentation model, these individuals have been identified as being highly likely to buy Individual Healthcare Insurance products. The model uses in-depth, exhaustive research data of recent consumer insurance behavior and intentions. This very specific profile of Individual Healthcare Insurance Buyers drives the process for identifying those households with the greatest propensity to respond to a Individual Healthcare Insurance offer.

These Financially Savvy Individuals are affluent, well educated heavy spenders. They have discretionary income and like to spend on themselves and their families. These spenders generally have multiple credit cards and spend on everything from Hi-Tech gadgets and fancy cars to jewelry, vacations and everything mail order. They welcome additional bank and credit cards.

Using a powerful insurance segmentation model, these individuals have been identified as being highly likely to buy Disability Insurance products. The model uses in-depth, exhaustive research data of recent consumer insurance behavior and intentions. This very specific profile of Disability Insurance Buyers drives the process for identifying those households with the greatest propensity to respond to a Disability Insurance offer.

Using a powerful insurance segmentation model, these individuals have been identified as being highly likely to buy either Individual or Group Supplemental Healthcare Insurance products. The model uses in-depth, exhaustive research data of recent consumer insurance behavior and intentions. This very specific profile of Senior Supplemental Group Healthcare drives the process for identifying those households with the greatest propensity to respond to a Senior Supplemental Group Healthcare offer.

Using a powerful insurance segmentation model, these individuals have been identified as being highly likely to buy either Individual or Group Supplemental Healthcare Insurance products. The model uses in-depth, exhaustive research data of recent consumer insurance behavior and intentions. This very specific profile of Senior Supplemental Individual Healthcare drives the process for identifying those households with the greatest propensity to respond to a Senior Supplemental Individual Healthcare offer.

Individuals on this list have been profiled as financial seminar attendees, making them likely to attend financial seminars. The formula for this list is based on a powerful financial segmentation model specifically designed to predict the intention of consumers to respond to attend seminars. The model uses in-depth, exhaustive research data of recent consumer insurance behavior and intentions. This very specific profile of Financial Seminar Attendees drives the process for identifying those households with the greatest propensity to respond to a Financial Seminar Attendees offer.

Using a powerful investor segmentation model, these individuals have been identified as having a very high likelihood to buy stock and bond mutual funds. The model uses in-depth, exhaustive research data covering a wide range of consumer financial behavior and intentions. The model uses in-depth, exhaustive research data of recent consumer insurance behavior and intentions. This very specific profile of Sophisticated Mutual Fund Investors drives the process for identifying those households with the greatest propensity to respond to a Mutual Fund offer.

Using a powerful financial behavior segmentation model, these individuals have been identified as being highly likely to buy Annuities by value and channel such as by direct mail, from a bank, from a broker or from an insurance agent. The model uses in-depth, exhaustive research data of recent consumer financial behavior and intentions. The model uses in-depth, exhaustive research data of recent consumer insurance behavior and intentions. This very specific profile of Annuity Buyers drives the process for identifying those households with the greatest propensity to respond to a Annuity offer.

Cash Rebate Credit Card Acceptors is derived from a powerful financial segmentation model designed to predict the intention of consumers to respond to a cash rebate credit card offer. The model uses in-depth, exhaustive research data of consumer financial behavior and intentions in order to profile these acceptors. The model uses in-depth, exhaustive research data of recent consumer insurance behavior and intentions. This very specific profile of Cash Rebate Credit Card Acceptors drives the process for identifying those households with the greatest propensity to respond to a Cash Rebate Credit Card offer.

Individuals on this list have been profiled as accepters of credit card offers offering frequent flyer mile benefits. The formula for this list is based on a powerful financial segmentation model specifically designed to predict the intention of consumers to respond to this specific credit card offer. The model uses in-depth, exhaustive research data of recent consumer insurance behavior and intentions. This very specific profile of Frequent Flyer Mile Credit Card Acceptors drives the process for identifying those households with the greatest propensity to respond to a Frequent Flyer Mile Credit Card offer.

Through a powerful financial segmentation model specifically designed to predict the intentions of consumers to respond to a credit card offer with a “no-annual-fee” benefit, the individuals on this list have been identified as having the greatest propensity to respond to such a credit card offer. Individuals on this list have been profiled as accepters of this very specific “no-annual-fee” credit card offers. The model uses in-depth, exhaustive research data of recent consumer insurance behavior and intentions. This very specific profile of No Annual Fee Credit Card Acceptors drives the process for identifying those households with the greatest propensity to respond to a No Annual Fee Credit Card offer.