The Incomplete Data Problem

No matter how well a market research project is planned and executed, the reality is that there are usually some responses which are partially incomplete. Dealing with these holes in your data is a delicate matter. Leaving them in could distort the distributions. In addition, some systems cannot handle the empty values. Throwing away the responses is wasteful and going back to the field would not be economically feasible and cannot maintain the statistical integrity of the project.

The Ascription Solution

The best solution is to ascribe the data using statistical methods whereby the ascribed data will have the same distribution as the original distribution of the non-empty data cells.

Two Ascription methods

SM Research offers two technologies that can be applied during the ascription process. The first involves accumulated distribution filling, which fills empty cells with no special conditions. The second technology is called key demographic matching which fills the holes with the answers from matched demographic respondents.

Both methods will create a non-distorted, no black-hole dataset that can be used in further studies.