Surveys

OPEN-ENDED

Questions that offer most freedom to respond have the benefit of obtaining higher level of detail but also take the most time to decipher and analyze.

Sample questions are:

1) Great price
2) Referral from a friend/family
3) Already own one, good reputation and trust
4) Good warranty
5) Higher quality and fair price compared to competition
6) Nothing else on the market

These responses would be reviewed by the team and broken down into categories such as Quality, Price, Brand, Service.

Then organize the responses into the categories and it is possible that one response may get multiple categories (such as question #5) which is the benefit of open-ended questions.

The following is a methodical way to break down the responses to open-ended questions.

1) Have the team review the responses and try group consensus to categorize the response.

2) Create possible categories for answers and there will likely be some responses that don't seem to fit, or can be labeled as miscellaneous. If there are too many of these, it is possible the question needed to be more specific.

3) Determine the number (count) of responses in each category.

4) Display counts in each category and now the BB/GB can provide the team results in terms of percentages, mode, rankings, or just the count of each category.

BINARY QUESTIONS

Questions that offer two choices to respond are binary questions. You may offer the responses and have the survey taker select one, or it may be obvious to the two choices and they can write in.

Sample questions are:

These are simply categorized and then analyzed.

CATEGORICAL PREFERENCE "WORDED" QUESTIONS

Many surveys use numbers to represent categories or classifications and the difference between each number has meaning. This is ORDINAL data and is one level higher than the lowest level of data, known as NOMINAL data.

1 = POOR
2 = FAIR
3 = AVERAGE
4 = GOOD
5 = EXCELLENT

Other questions are:

When you provide the possible answers it is easier to categorize and count but sometimes may not be exactly the respondents best choice or ideal answer. They may feel obligated to pick one and this can lead to wrong decisions from the statistical analysis.

This is non-metric or qualititative data and requires the use of non-parametric tests to evaluate statistically.

Quantitative Surveys

Summary

This often is more time consuming and difficult to perform than quantitative analysis but usually provides more information and detailed responses than just a number.

Quantitative analysis is usually less expensive to conduct and are easier to conduct with automation and electonic mediums. It is also easier to mine the data to investigate trends and statistics but lacks some of the details a worded response or open-ended response will provide.

An excellent source for survey guidance and creation is at www.surveymonkey.com