Overview
Projective Mapping data can be analyzed in Compusense by using the Projective mapping workbook. This report, centered around MFA (Multiple Factor Analysis), includes multiple sheets to
allow you to explore your results in depth.
In this workflow we will focus on the analysis within Compusense.
Generate The Report
To generate the Projective mapping workbook:
In the Results area of your test, filter the results if necessary by clicking Filters.
Select Reports > Create report.
In 1. Select report type , select Projective mapping workbook.
In
2 Select options , select
the sheets you wish to include in the report. All sheets are included by default.
Select from the following options (details about these sheets are provided in the
Report Details section):

Minimum citations. The default value is 3 while the maximum value is 10. This threshold excludes from the analysis any tags with fewer occurrences than the selected value. To include all tags, set the value to 0 (zero).
If a tag is used an equal number of times in every sample, it will be automatically excluded from the analysis due to the lack of variability between samples.
In 3 Select questions , select the Projective mapping questions that you wish to include in the report. Only Projective mapping questions are compatible with this report.
The .xlsx is the only export type. Click Create my report.
Click the down arrow, save the report to a location on your computer or network drive and open it.
Projective Mapping Report Details
Review below the information found on each sheet in the report.
Summary Statistics

The Summary statistics sheet lets you review the Min, Max, Mean and Standard Deviation for each of your variables.
You can also review the complete list of tags and how many times each tag was used (cited) in the test. As seen in the example image above, spelling of the words matters and the letter case matters. We can see "crisp", "Crispy", and "crispy". Although we can assume that different people were trying to use the same term, they did not create the tags the same way, and so each of these terms is treated as a unique tag. The tags list can help you decide how to handle these instances. You might want to increase your citations threshold and thus exclude such tags, or clone your test by keeping results in the clone and edit raw results to update the spelling and/or letter case.
The citations threshold set prior to generating the report is displayed below the tags list. Tags that were cited less number of times than the threshold value will not be included in the analysis.
If a tag is used an equal number of times in every sample even if it meets the Minimum citations threshold, it will be automatically excluded from the analysis due to the lack of variability between samples.
MFA Summary

The MFA (Multiple Factor Analysis) summary allows you to review inertia extracted within the MFA. Inertia extracted represents the amount of variance explained by the dimensions.
RV Coefficient

The RV coefficient sheet represents the panel consensus configuration vs. each assessor configuration (after optimal scaling). The coefficient ranges from 0-1 with 0 meaning no correlation and 1 meaning strong correlation (i.e. what is the individual’s correlation to the panel).
Panelist coordinates
The panelist coordinates sheet provides one graph per sample set. These graphs use panelists' raw data to plot the placement of products on the mapping area. The panelists are displayed with green markers while panel is displayed with black markers.
Correlation Circle Graphs
The Correlation circle sheet provides 3 consensus graphs:
Correlation circle. Plots panelist and tag correlation.
Assessors. Plots panelist correlation.
- Tags. Plots tag correlation. Only tags that were used more times than the citation threshold value set before generating the report will be included in the plot.

Consensus Configuration
The consensus configuration sheet provides 2 graphs:
- Projection of panelists on consensus configuration. Plots the consensus sample configuration and individual panelist configuration.

- Consensus sample configuration. Plots the consensus sample configuration.

Partial Inertia
The Partial inertia sheet provides the plots of inertia extracted for each sample set and the tags, where tags are grouped together. The partial inertia measures how much each specific variable (i.e. sample sets and tags) contributes to the structure of the data. From this graph, you can determine which variables drive the dimension.
Only tags that met the citation threshold value set before generating the report will be included in the plot.