Credit Score Audience Targeting

Polls based on Credit Score specific focus groups: Unknown credit, Bad credit, Fair credit, Good credit, and Excellent credit

Polls with Credit Score-specific Targeting

Check out 2 surveys targeting credit score. Learn how they pose their questions and view the written responses.

  • Which design you like better?

    This is a 2 option poll with 50 respondents targeting Credit Score (720+, 690 719). A sample of responses:

    • In an online marketplace like Amazon I would certainly pic B because it has all the info I need "veggie pasta noodles" while also being easy to identify as noodles by the picture in the middle.
    • Looks much better with a pic of actual noodles on the box.
    • I really like the colors better.
    • Shows the product in an appealing way, letting me know what is inside at one glance.
    • I do not like veggie pasta,.

  • Pick brand name for a free mobile app and financial service designed for people with changing/un-steady/multiple/cash based/paycheck-paycheck/part-time income, that can be described as Venmo or Cash App+Creditcard-Evil

    This is a 3 option poll with 50 respondents targeting Employment Status (Student, Full Time, Part Time), Credit Score (630 689, 300 629, Don't Know Or Check, 690 719), Age Range (35 44, 18 24, 25 34), and App Store Spending (Under $10, $10 $100). A sample of responses:

    • Choice C still. I think that freepaid is a clever name.
    • sounds perfect and looks very user orientated
    • I like the name freepaid, it gives impressions of absence of fees.
    • The card B, looks like it is more customizable for the consumer to have a little fun with and truly design to represent them selves, like credit cards do now, you can choose a background image for the credit card. The writing on choice B look like you can customize it for you.
    • Hifi sounds like a more unique name than Freepaid!

Credit Score targeting is often combined with age range targeting, income targeting, employment status targeting, education targeting, community type targeting, home ownership targeting, gender targeting, amazon prime membership targeting, app store spending targeting, books read per month targeting, us geographic region targeting, alcohol: wine drinker targeting, and alcohol: liquor & spirits drinker targeting.

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