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COMMON WAYS OF LOOKING AT DATA
Depending on your specific needs, Canmark can provide you with exhaustive analysis and reporting, or simply a clean data set – or anything in between.

Top Box / Bottom Box: Looking at survey results in terms of the percentage of respondents whose answer given was one of the extreme top or bottom response options can clearly indicate the magnitude of success, or lack thereof. Depending on the number of response options, the top or bottom one, two or three choices are used in this type of review.

Assume that a particular survey question was answered by 100 respondents as follows:

Rating Count Percent
Excellent 19 19%
Good 28 28%
Neutral 14 14%
Fair 21 21%
Poor 18 18%

The top-two box score is 19% + 28%, or 47%. Almost half of respondents rate the characteristic being measured in a positive way.

Net Promoter: While several variants exist, the “net promoter” concept basically consists of determining defined positive responses to a survey question (usually a “recommendation” type question) as a percentage of the total responses, and subtracting out defined negative responses also as a percentage of total responses.

Assume that a particular survey question was answered by 1,000 respondents as follows:

Rating Count Percent
Excellent 124 12.4%
Very Good 268 26.8%
Good 230 23.0%
Neutral 117 11.7%
Fair 63 6.3%
Bad 110 11.0%
Poor 88 8.8%

It should be clear that the definition of “positive” and “negative” is absolutely crucial. The determination of the net percentage of total respondents who would actively promote your program, business or opportunity can be easily misstated if stakeholders do not agree on key concepts. Tracking this score over time should give a clear indication of the direction the company is going and the magnitude positive or negative sentiment outstanding.

If the organization agrees that the top two rating groups can be assumed to promote the business, and that the bottom two groups can be counted on to campaign against the business, while the middle three groups are indifferent, the score would be computed as:

39.2 – 19.8 = 19.4


Thus, on the “balance sheet” of goodwill among customers, about twice as many customers have a positive outlook, however, the significant number of “neutrals” and non-promoters should be cause for concern. While the score is somewhat industry dependent, evaluating this against stated company goals, and/or comparing this with scores from direct competitors is necessary to capture all the value possible.

There are many more ways of looking at quantitative survey results than are listed here, from banners and cross-tabs to advanced PI Charting. Once we have a better idea of your survey content and project goals we’ll be pleased to discuss reporting requirements. Of course, Canmark will always provide your cleansed raw data set for your internal analysis as well.

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