y suggest alternatives not listed in a closed-ended data acquisition questionnaire. For example, a previously unrecognised problem relating to the trash pick-up service might be uncovered from an open-ended data acquisition questionnaire. Open-ended questions are not without their problems. One factor is the time and money consuming process of editing and coding.

Editing open-ended responses requires collapsing the many response alternatives into some reasonable number. If too many categories are utilized, data patterns and response frequencies may be difficult for the researcher to interpret. If the categories are too broad, the data is too general and impor

Often open-ended questions require 'probes' from the interviewer. A probe is encouragement from the interviewer for the respondent to elaborate or continue the discussion. The interviewer may say, "Is there anything else?" or "Would you elaborate on that?" Probes aid in clarifying the respondent's interests, attitudes and feelings. Today computers are playing an increasingly important role in data acquisition - analysing and recording probes to open-ended questions.

Open-ended questions offer several advantages to the researcher. They enable respondents to give their general reactions to questions like: (1) What advantages, if any, do you think ordering from a mail-order catalogue company offers compared to local retail outlets? (probe: what else?). (2) Why do you have one or more of your rugs or carpets professionally cleaned rather than cleaning them yourself or having someone else in the household clean them? (3) What is there about the colour of product that makes you like it the best? (probe with: what colour is that?) (4) Why do you say that brand is better?

Note that in questions 2 and 4, the open-ended question is part of a skip pattern. In question 2, for example, the respondents have already indicated that they use a professional carpet cleaning service and do not depend on members of the household.

Another advantage of open-ended responses is that they can provide the researcher with a rich array of data. Respondents are answering from their own frame of reference. Advantages are described in 'real world' terminology rather than laboratory or marketing jargon. Often it is helpful in designing promotion themes and campaigns. It enables copywriters to use the consumers' language. This rich array of data can now be captured even in computer-assisted interviews, streamlining the data acquisition process.

The inspection of open-ended data acquisition can also serve as a means of interpreting closed-ended questions. This analysis often sheds additional light on the motivations or attitudes behind the closed-ended response patterns. It is one thing to know that colour ranks second in importance out of five product attributes. But it might be much more valuable to know why colour is important. For example, a study on mobile home park residents might uncover a great deal of dissatisfaction with the trash pick-up service. However, further inspection of answers to an open-ended questionnaire may uncover that the reason for the dissatisfaction may have been caused by freely roaming dogs overturning the trash receptacles and not shoddy work on the part of the trash pick-up service.

Similarly, open-ended questions may suggest alternatives not listed in a closed-ended data acquisition questionnaire. For example, a previously unrecognised problem relating to the trash pick-up service might be uncovered from an open-ended data acquisition questionnaire. Open-ended questions are not without their problems. One factor is the time and money consuming process of editing and coding.

Editing open-ended responses requires collapsing the many response alternatives into some reasonable number. If too many categories are utilized, data patterns and response frequencies may be difficult for the researcher to interpret. If the categories are too broad, the data is too general and import

a mail-order catalogue company offers compared to local retail outlets? (probe: what else?). (2) Why do you have one or more of your rugs or carpets professionally cleaned rather than cleaning them yourself or having someone else in the household clean them? (3) What is there about the colour of product that makes you like it the best? (probe with: what colour is that?) (4) Why do you say that brand is better?

Note that in questions 2 and 4, the open-ended question is part of a skip pattern. In question 2, for example, the respondents have already indicated that they use a professional carpet cleaning service and do not depend on members of the household.

Another advantage of open-ended responses is that they can provide the researcher with a rich array of data. Respondents are answering from their own frame of reference. Advantages are described in 'real world' terminology rather than laboratory or marketing jargon. Often it is helpful in designing promotion themes and campaigns. It enables copywriters to use the consumers' language. This rich array of data can now be captured even in computer-assisted interviews, streamlining the data acquisition process.

The inspection of open-ended data acquisition can also serve as a means of interpreting closed-ended questions. This analysis often sheds additional light on the motivations or attitudes behind the closed-ended response patterns. It is one thing to know that colour ranks second in importance out of five product attributes. But it might be much more valuable to know why colour is important. For example, a study on mobile home park residents might uncover a great deal of dissatisfaction with the trash pick-up service. However, further inspection of answers to an open-ended questionnaire may uncover that the reason for the dissatisfaction may have been caused by freely roaming dogs overturning the trash receptacles and not shoddy work on the part of the trash pick-up service.

Similarly, open-ended questions may suggest alternatives not listed in a closed-ended data acquisition questionnaire. For example, a previously unrecognised problem relating to the trash pick-up service might be uncovered from an open-ended data acquisition questionnaire. Open-ended questions are not without their problems. One factor is the time and money consuming process of editing and coding.

Editing open-ended responses requires collapsing the many response alternatives into some reasonable number. If too many categories are utilized, data patterns and response frequencies may be difficult for the researcher to interpret. If the categories are too broad, the data is too general and impor

>

Another advantage of open-ended responses is that they can provide the researcher with a rich array of data. Respondents are answering from their own frame of reference. Advantages are described in 'real world' terminology rather than laboratory or marketing jargon. Often it is helpful in designing promotion themes and campaigns. It enables copywriters to use the consumers' language. This rich array of data can now be captured even in computer-assisted interviews, streamlining the data acquisition process.

The inspection of open-ended data acquisition can also serve as a means of interpreting closed-ended questions. This analysis often sheds additional light on the motivations or attitudes behind the closed-ended response patterns. It is one thing to know that colour ranks second in importance out of five product attributes. But it might be much more valuable to know why colour is important. For example, a study on mobile home park residents might uncover a great deal of dissatisfaction with the trash pick-up service. However, further inspection of answers to an open-ended questionnaire may uncover that the reason for the dissatisfaction may have been caused by freely roaming dogs overturning the trash receptacles and not shoddy work on the part of the trash pick-up service.

Similarly, open-ended questions may suggest alternatives not listed in a closed-ended data acquisition questionnaire. For example, a previously unrecognised problem relating to the trash pick-up service might be uncovered from an open-ended data acquisition questionnaire. Open-ended questions are not without their problems. One factor is the time and money consuming process of editing and coding.

Editing open-ended responses requires collapsing the many response alternatives into some reasonable number. If too many categories are utilized, data patterns and response frequencies may be difficult for the researcher to interpret. If the categories are too broad, the data is too general and impor

ight on the motivations or attitudes behind the closed-ended response patterns. It is one thing to know that colour ranks second in importance out of five product attributes. But it might be much more valuable to know why colour is important. For example, a study on mobile home park residents might uncover a great deal of dissatisfaction with the trash pick-up service. However, further inspection of answers to an open-ended questionnaire may uncover that the reason for the dissatisfaction may have been caused by freely roaming dogs overturning the trash receptacles and not shoddy work on the part of the trash pick-up service.

Similarly, open-ended questions may suggest alternatives not listed in a closed-ended data acquisition questionnaire. For example, a previously unrecognised problem relating to the trash pick-up service might be uncovered from an open-ended data acquisition questionnaire. Open-ended questions are not without their problems. One factor is the time and money consuming process of editing and coding.

Editing open-ended responses requires collapsing the many response alternatives into some reasonable number. If too many categories are utilized, data patterns and response frequencies may be difficult for the researcher to interpret. If the categories are too broad, the data is too general and impor

y suggest alternatives not listed in a closed-ended data acquisition questionnaire. For example, a previously unrecognised problem relating to the trash pick-up service might be uncovered from an open-ended data acquisition questionnaire. Open-ended questions are not without their problems. One factor is the time and money consuming process of editing and coding.

Editing open-ended responses requires collapsing the many response alternatives into some reasonable number. If too many categories are utilized, data patterns and response frequencies may be difficult for the researcher to interpret. If the categories are too broad, the data is too general and important meanings may be lost. The open-ended question data acquisition process may also be influenced by interviewer bias. Although training sessions continually stress the importance of verbatim recording of open-ended question, it is often not practised in the field. Open-ended questions may also be biased toward the articulate interviewee. A person with elaborate opinions and the ability to express them may have much greater input than a shy, inarticulate, or withdrawn respondent. Yet both could be equally likely prospects for a product.