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Sample Weighting
No matter how hard we try, we are not in control of who decides to fill out our surveys and who decides not to.  There are things we can do to promote higher response rates, like using engaging messages or various incentives, but the ultimate decision to complete or to ignore an invitation to participate in a survey belongs to the potential respondents.  As a result, the samples we obtain are not always perfect fits to the samples we seek.

Breakdowns on key demographics in our returned surveys may not proportionally match the group that we sampled from.  For example:
  • 10% of the people you invite to participate in your survey may be senior executives
  • 20% may be managers
  • 70% may represent employees at other levels within  your company or your customers' companies. 
But, the proportions of completed surveys you get back in each of these categories may be different - you may only get 5% senior executives and 8% managers, but  wind up with 83% employees at other levels.  Or, other imbalances may occur.  We typically find, for example, that customers in Latin America or in certain countries within Europe are more likely to respond to surveys than are customers in other world regions or in other countries in Europe.  While it is nice to know that the quality of relationships can be so warm as to promote higher response rates in some countries, it is important to us as researchers to know that we can often adjust our data to compensate for imbalances.  Otherwise, we could not give you accurate estimates of what how people are feeling in various world regions or in Europe as a whole. 

By weighting data to compensate for imbalances between the proportions we invite to participate among subgroups in your population and the proportions in those subgroups who choose to respond, we can help to ensure that the estimates of the population as a whole or of large groupings within the population that we compute (e.g., the percentage of your employees overall who love their jobs) are adjusted to provide a better fit to what we believe to be the true characteristics of your target group.  Using the example above, the responses of senior executives and managers would be weighted up and those of other employees would be weighted down to approximate the known proportions in the original mailing list for invitees.  This provides us with more accurate estimates of the group as a whole. 
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