In business and research settings, Pivot Table is widely used for many different purposes. For analyzing opinions data, the primary use case is to identify multi-variate relationships. In other words, to study how one question’s answers related to those from another question.
Exporting Pivot Tables
After you have created a cross-tab, such as the following, the “Export” button on the top right corner lets you export what you see on the screen into a spreadsheet.
The pivot table looks like the following.
It is easy to set up additional graphics to include in your presentation. The following is just a straightforward example.
Additional Analysis Using Pivot Tables
Very often, you may need to create some benchmarking analysis. You can do so via an Action Priorities Grid (APG) when you need to compare hierarchies of needs across customer/employee profiles. When you need to create some very specific KPIs, you can use Pivot Table quite easily.
For example, the following is a cross-tab comparing the distribution of promoters, passive promoters, and detractors across different shows at the Tennessee Theatre.
The exported pivot table allows an easy computation such as the one shown below, where you can tally up the total counts of responses in column F, and then use the equation specified in column G to reveal the exact NPS scores for each show. This use of Pivot Table is very popular because of Net Promoter Score is becoming popular for both internal and external use cases in many major corporations.
Note: if these NPS scores look unrealistically high to you, it’s because you don’t know how fantastic Tennessee Theatre is. It is a culture treasure and an icon in East Tennessee!