In this article
- Choosing your descriptors
- Discover analysis
- Add descriptors or discover selections to your analysis
- Remove descriptors from your analysis
- Switching between standard and discover analysis
- Graph your discover results
1. First things first - choosing your descriptors
Descriptors are the variables you want to use for profiling. Descriptors can include demographic, psychographic, behavioral variables, or a combination.
Selecting your descriptors is an iterative process. The key is to choose variables that are relevant to your analysis and avoid those that could dominate the analysis.
To achieve this:
- Choose axes that do not have too many elements. For example, instead of the Age axis, use the Age (Grouped) axis.
- For rating scales, it is best to use summary axes. For example, instead of using the Satisfaction Detail axes, use Overall Satisfaction – NZ (Grouped).
- Don’t double up. You can use the Age or Age (Grouped) axis but not both.
- Measures are currently not supported.
- The data may be spread too thin with axes with too many elements. You should use variables with elements that have a robust sample.
- Avoid having too many elements. For example, if you choose thousands of variable elements, you may get hundreds or even thousands of statistically significant elements. This can make it difficult to determine what is important strategically.
Descriptor Groups
You can create different sets of descriptors and manage them through the descriptor manager.
2. Discover analysis
There are a couple of ways to create a Discover analysis table:
a) From an existing analysis
On a table view, select the group you are interested in profiling. Selecting will enable the Discover option located in the modify menu.
Discover will profile a target group against the set of descriptors you have defined. The Discover table ranks the rows so that the descriptors that most differentiate your target from others rise to the top, and those that are less likely differentiators go to the bottom of the table.
b) Drag and drop from the project tree into the analysis pane
From the project tree, select the group you are interested in profiling (i.e., Discover selection) and drag it into the Discover analysis zone.
As a default, discover will use the first element of the axis selected as the target (i.e., from the Top 10 Markets, the element Australia). You can change the target by selecting the item you want to use and then choosing the option TARGET under tests in the modify menu.
Discover also sorts the groups across the table so those most similar to the TARGET are closest and those most different are furthest away. Rows are ranked so that the descriptors that most differentiate your target come to the top.
Arrow Coloring
When ranking, Harmoni uses green arrows to indicate the descriptors that most differentiate the target and red arrows to indicate those that are less likely to differentiate the target.
For the coloring of the arrows, three shades of green and three shades of red add an additional level of differentiation within the level of likelihood. The brighter the shade of green or red, the higher the probability.
3. Add descriptors or discover selections to your analysis
After creating a Discover analysis, you can still interact with your descriptors and discover selections.
You can add or replace descriptors in your analysis with any axis from the project tree, even when not flagged as a descriptor. You can achieve this by dragging and dropping the relevant variables into the Discover Descriptor drop zone.
The same is true for your discover selections; you can add groups you are interested in profiling by dragging and dropping into the Discover Selection drop zone.
4. Remove descriptors from your analysis
You can remove descriptors from your discover analysis by using the interactive title and de-selecting the descriptors you don’t wish to use.
5. Switching between standard and discover analysis
After creating a Discover analysis followed by a Standard analysis, you can switch between them using the toggle under the visualize menu.
6. Graph your discover results
Special bubble chart
Under the visualize menu, you can find the special bubble chart. This chart visually represents what differentiates the profile target from the group.
This chart shows the size, proximity, and level of differentiation of each subgroup.
Space Graph
When graphing discover results, to ensure clear and interpretable space graphs, it's recommended to use a targeted set of descriptors. Harmoni uses all available data from the table and this can result in cluttered visualizations, making analysis challenging. It's not possible to manually select rows or columns from the discover table to limit the data used in the space graph.
For more information on Harmoni's space graph methodology and interpretation, please refer to the space graph article.