Gaps in survey data collection are common, but handling those gaps incorrectly can seriously affect the resulting metrics. In some cases, metrics like Count and Average should be calculated only with actual data collected. If there is a gap, the missing cell should be treated as if it did not exist. With Nextanalytics, this is the default behaviour; empty cells are ignored. For example, in a rating survey (PIC), although 100 surveys were completed, not everyone answered every question. Counts, Averages and other metrics are reported on only the data that does exist. There is no need for special handling or complex algorithms.

There are times when the lack of data does have a meaning, though, so Nextanalytics provides a simple function that assigns all empty cells with a specific value, like a ‘1’ or a ‘0’. For example, if there were no selections of a particular optional response (pic), the cell should be assigned a value of zero. This allows period-to-period comparisons or weighted calculations to be performed.

In yet other cases, where values are required for all steps in a sequence, but the data collection process failed somehow and the data was simply missing (pic). Dropping to zero is not the right thing to do because it would throw off all period calculations and metrics. In these cases, Nextanalytics can automatically assign empty cells with the previous value in the row or column; in the absence of data, remain unchanged.

Finally, when evaluating selected options and looking at segmentation, it is often important to review and contrast the scores for people that did not identify with a specific segment. For example, comparing scores for people that said they were in the area versus those that selected nothing (empty). Just because they didn’t select something does not mean they didn’t provide valuable information.

Nextanalytics makes all this possible through simple functions, freeing you to concentrate on your results.