The Analysis Wizard allows users to choose amongst different types of analysis based on the selected Question type on which they want to perform their analysis.
Mentioned below are the analysis types offered by Analysis Wizard:-
- Distribution: Distribution analysis should be used when your are trying to compare the choices your respondents have selected in a question.
- Descriptive Statistics: Descriptive Statistics is best when you have a question where you have asked the respondent to rate a product or service, or any question where you have used a scale. It is also perfect for those questions where you are asking the respondent to enter in a number.
- Rank-wise Distribution: This analysis is mostly used when you are trying to see if there is a pattern in how people have ranked your attributes.
- Average Rank: A ranking question is usually analyzed using the average score. The score represents the proxy rank score than an attribute has received across all the respondents. A lower number represents a higher rank.
- Rank-wise Distribution Across Groups: To see patterns in ranking and differences across groups you should use this analysis.
- Average Rank Across Groups: You should use this analysis if you wish to compare the average ranks across the groups and as a whole.
- Grid Analysis Distribution: Grids attributes are usually best viewed all together. If you are using a category scale (like brands, city etc.) then in your grid question, looking at the distribution of responses across the attributes is recommended.
- Grid Analysis Descriptive Statistics: When you use a likart scale (like/dislike, satisfy/dissatisfy etc.) or numbers in a grid question, it usually better to compare the mean scores across attributes.
- Cross Grid Descriptive Statistics: Use this analysis type if your grid is a ratings grid. In this case the mean rating for each attribute is crossed with the second variable you have chosen.
- Cross Grid Distribution Attribute Wise: This is a special analysis that will automatically create one analysis for each attribute in the grid and compare the percentage scores of the grid items with the second variable you have selected.
- Cross Grid Distribution Item Wise: This is a special analysis that will automatically create one analysis for each item in the grid. The analysis will show you for that item, percentage of respondents compared across the other variable you have selected.
- NPS: NPS provides a clear measure of an organization's performance through its customer's eyes and one of the key predictor of growth.
- Net Promoter Distribution: See the proportion of 'Promoters', 'Passives' and 'Detractors' amongst your respondents.
- Recommendation Distribution: This allows you to see how your recommendation question was answered by your respondents.
- Recommendation Descriptive: This allows you to see how your recommendation question was answered by your respondents.
- Loop Distribution: When you want to analyze the data across loop iterations you would want to use this analysis. For example, if you want to know the proportion of people who have chosen a category across your iterations then you should use this analysis.
- Loop Descriptive: When you want to measure means score, sum etc. across loop iterations you should use this measure. For example, if your are capturing 'Units on shelves' across SKU's running in loops, this analysis can be used to quickly calculate total units on shelves.
- Numeric Grid Analysis: When you use a likart scale (like/dislike, satisfy/dissatisfy etc.) or numbers in a grid question, it usually better to compare the mean scores across attributes.