Marketing Compost (EAWAG) - The Water, Sanitation and Hygiene

Open questions invite people to express their considered opinions in their
own words. People tend to respond more honestly to open questions than to
closed or leading questions. It is also more difficult to answer an open-ended
question if it has not been properly understood, whereas answering a closed
question only requires a simple yes or no.
Designing questionnaires
Questionnaires will be designed differently depending on whether you
are collecting quantitative or qualitative data. However, all questionnaires
need to be pilot tested, and the following factors must be considered in
their design:
Does the flow of the questions work (i. e. are they in a logical order)
Are the words understood Are they too difficult, too simple or ambiguous
(e. g. confusion between compost and chemical fertiliser)
Do the response categories in quantitative surveys capture all options
Is there any cultural sensitivity in relation to specific questions Could
any questions be offensive
Are the questions interpreted in the same way by different respondents
(This is referred to as reliability).
Do they measure what they are supposed to measure (This is referred
to as validity).
Are the questions answered in the same way if repeated with the same
respondent (This is referred to as reproducibility).
Adapted from WHO, 2008
The time at which questions are asked can make a difference to the data you
collect. Just as the supply of raw materials to your composting plants is seasonal,
so are some markets. If you ask a householder how much compost he
uses in summer, he may give a different figure than if you ask him the same
question in winter.
Data analysis and reporting
There are many sophisticated pieces of software on the market to help with
analysis, but it is probably unnecessary for most composting businesses to
invest in these. By keeping your research simple and relevant, your analysis
should remain fairly simple. A calculator or common spreadsheet programme
(e. g. Excel) will often be sufficient for analysing quantitative data.
Marketing Compost—Background 29