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Survey Details

Methodology

The survey sample of 2,000 was selected in systematic, stratified fashion by Red 7 Media and Readex Research from Circulation Management subscribers qualified under any job title classification other than fulfillment director/manager, list rental director/manager, renewal or billing director/manager, circulation consultant, or customer service director/manager.  The sample represented 4,918 individuals meeting this criteria at the time of selection.

Data was collected via mail survey from August 29 to October 11, 2007.  The survey was closed for tabulation with 554 responses (a 27% response rate).  To ensure representation of the audience of interest, results have been filtered to include only the 451 respondents who indicated they work full time and their job functions are best described as:

• circulation director or top circulation executive
• circulation manager
• circulation associate/assistant

Results have been weighted in tabulation to restore true population proportions.  The margin of error for percentages based on all 451 respondents is ±4.4% at the 95% confidence level.  The margin of error for percentages based on smaller sample sizes will be larger.

The Compensation Calculator

The analysis of Folio:'s Circulation Salary Survey data used multiple regression analysis to model the determinants of salary by identifying those variables which, when taken together with appropriate weights, provide the best prediction of any individual's actual salary.

The final salary prediction model is somewhat restricted in its applicability—it represents only full-time professionals who indicated their job functions are best described as circulation director/top circulation executive, circulation manager, or circulation associate/assistant under 65 years old with under 40 years of experience and salaries in the range of $25,000 to $150,000 and accounting for at least 60% of their total compensation.

Statistically speaking, this model is moderately powerful: it explains 50% of the variation in salary (it has an equivalent adjusted R-square of .503), and is significant by the F-test at p<.0005.

While a model explaining roughly 50% of the dependent variable's variation may be described as "moderately powerful," it still leaves almost half of the variation unexplained.  It is virtually certain that other variables not captured through this survey also have an effect on salary levels: individual job performance, for example.  To the extent that this model does not include variables actually important in determining salary, its conclusions must be interpreted cautiously.