AARC’s Different and Better Survey Methodology

Most survey research is conducted online among panels of people who are compensated for participating in regular and frequent surveys. This methodology has become popular, because it is usually less expensive and less time consuming than personal, telephone, and mail surveys. AARC believes this methodology is particularly inappropriate for surveys of the affluent and that such research can lead to inaccurate and misleading results, just like anecdotal research.

AARC’s methodology avoids the several potential weaknesses of online panel research – see Sample Quality of Online Panels: Putting Lipstick on the Piggy Bank, the new report More Dirty Little Secrets of Panel Research, and the original Dirty Little Secrets of Online Panels by Grey Matter Research. AARC conducts its research by direct mail surveys sent to samples drawn at random to be representative of the precisely defined population of affluent households, consistent with the research of The Federal Reserve Board. Confident of their anonymity, the respondents to AARC’s surveys are typically more affluent and more open in providing confidential information.

Similar to the Consumer Confidence Index of The Conference Board, AARC’s twice-yearly tracking studies are based on self-administered questionnaires mailed to a national sample of at least 4,000 households that, based on their income and ownership of certain assets, are expected to meet the minimum net worth requirement of $800,000. The overall survey response rate (net of undeliverables) is about 18% for recent surveys. The survey results are based upon the responses of over 500 men and women who promptly respond to the survey and meet the minimum net worth requirement. The maximum margin of error of the surveys, at 95% confidence, is five percentage points

AARC’s tracking studies are also unique in that they, unlike most other surveys of luxury and affluent consumers, focus on the future outlook and spending plans of the affluent, rather than attempting to extrapolate historic data by asking the respondents to remember and reconstruct past spending.