Introduction
to DQE technology:
Questionnaire surveys based on Dynamic Questionnaire Engine™ (patent pending) technology use a technique which enables a respondent's emotional and rational responses to a number of questions to be measured and then compared.
Based on the theory that satisfaction is a measure of how well a respondent's rational and emotional responses match, a value can then be assigned to the respondent's level of satisfaction with the subject matter being monitored.
Disagreeing
with the summary:
The Dynamic Questionnaire Engine™ (DQE) requires that a summary of the respondent's inputs be presented to the respondent immediately after they have completed their inputs. This can sometimes lead to disagreements between how a respondent believes they feel and the summary displayed.
However, an analysis of respondents' opinions to surveys based upon DQE technology have shown that on average, 60% agree with the summary of their individual inputs on completion of the survey. From the remaining 40%, 80% have agreed with the summary "on reflection" - i.e. having been able to "sleep on it".
This is an unprecedented accuracy of over 90% in the summary report and is the reason why questionnaire surveys based on DQE technology require a fewer number of responses in order to gather a representative input.
Beating the
system:
Two of the benefits of DQE technology are that firstly, it filters out a respondent's daily emotional state (which always influences the responses to a typical satisfaction survey) and secondly, it records the respondent's "level of conviction" in their answers (i.e. how convinced the respondent is in the responses they have given).
The technique used to filter out the respondent's emotional state also means that if a respondent attempts to complete a survey "as someone else" i.e. as someone with a different opinion than the respondent's true opinion, then the results will still tend to reflect the opinion of the respondent more than the "bogus" person.
Also, if a respondent tries to deliberately give false answers, the resulting "level of conviction" factor recorded will be low, meaning that the impact of these 'false' inputs on the overall inputs from all other respondents will be minimal. |
