Buzz on the street: How we worked the survey
The targeted age group was 25-49 years, with equal representation across age groups.
By TNN |
The ET-Hansa Mood of the Nation survey was undertaken so that we at ET could understand what the people of the nation were feeling before the Budget, and subsequently to judge how much the people���s moods have swayed post-Budget.
The targeted age group was 25-49 years, with equal representation across age groups. This group constitutes the biggest working class in the country and has the maximum number of decision makers. Decreasing the age limit wouldn���t have helped as the Budget, perhaps, wouldn���t affect teenagers as much. Sure, they would have an opinion, but they remain least affected, in a sense.
The questionnaire was trying to establish the mood of the nation before the Budget and the buying propensity of consumers. Do they think, therefore, that buying a house or a car is a good idea now?
The targeted age group was 25-49 years, with equal representation across age groups. This group constitutes the biggest working class in the country and has the maximum number of decision makers. Decreasing the age limit wouldn���t have helped as the Budget, perhaps, wouldn���t affect teenagers as much. Sure, they would have an opinion, but they remain least affected, in a sense.
The questionnaire was trying to establish the mood of the nation before the Budget and the buying propensity of consumers. Do they think, therefore, that buying a house or a car is a good idea now?
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All the parameters used largely related to consumer confidence. A total of 1,212 people across socio-economic classes and age groups were sampled in the 11 cities where ET has an edition. There were three age groups, across which there was equal distribution. SEC A and B1 together accounted for 40% of the sample, and SECs B2&C and D&E1 accounted
for 30% each.
All the respondents were interviewed face-to-face at street corners in the cities between February 1 and February 3. To get a better representation of the cities, multiple starting points were used in different parts of the cities. The data was finally weighted to the IRS universe to avoid the bias introduced in the sample, because of the quotas imposed on age groups and SEC.
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