[cosmie]

> In my experience, the hardest thing about quota sampling as opposed to the old RDD phone samples 20 years ago is that it's very difficult to get high education / high SES / high income respondents. High income respondents should be 10% of the population and they simply are nowhere near 10% of the pools that you get from standard recruitment methods. Can you speak a bit about a) how you recruit high income people into your pool; and b) what percentage of your pool would be high income (say HHI > $125k a year or so).

A friend of mine runs into this periodically, with her response pools over-sampling on lower income and older individuals, with a lot of geographic skewing (she does local/regional research, so appropriate sampling at a census block and/or zip code level is needed).

I've worked with her several times to fill that gap, by leveraging Facebook ads for recruitment to balance out the deficiencies in her response pool. Ad cost + incentive tends to work out to the ~$10 range per qualified response. Which is too expensive as a recruitment method for her entire pool, but she's found fantastic to reach the otherwise unreachable demographic gaps she'd have. Different demographics respond better to certain incentive structures and ad copy than others, but in general it's been effective for capturing those hard-to-get groups.

Leveraging the same avenue for re-contact is also handy if your response pool is large enough to create a custom audience to target for follow-up ads. Even out of date contact info can be useful for this. Although your IRB (if relevant) may shut that down if you didn't account for it if the language in your initial contact didn't account for it, since doing this involves disclosing the subject's PII to a third party (Facebook) for creating the custom audience.