There are a few different angles you'll want to take when digging into your testing group data. Initially when you open the testing group details page, you're presented with all the efforts neatly rolled up into their subgroups, with summary data shown. The data here is valuable, but so is the effort level data contributing to the summarized numbers.

Collapsed Subgroups

This initial view of your testing group consists of one row for each subgroup. You're free to change the stats shown by selecting columns using the cog menu to the right of the table. Whichever stats are shown while the subgroups are collapsed represent summarized data for all the efforts included within each subgroup. Comparing data at this level will likely heavily influence how you judge your test and which group is the winner.

In the example above, out of 186 total batch orders received between both subgroups, the control received 111 orders, while the test received 75. That's almost a 20% difference and pretty compelling. It might be of interest though if after processing issues and refunds there were only 55 net orders left of the 111 batch orders in the control subgroup, whereas the test subgroup had a much lower refund rate and ended up with 54 net orders. It's up to your team to decide what's valuable, but there's plenty of information to be gained by comparing subgroup-level data. 

Expanded Subgroups

When you click the arrow to expand a subgroup, you'll be able to see each individual effort included in the subgroup and the stats that pertain to each of those efforts. You'll still be able to see the summary data for all of those efforts in the sub-totals row at the bottom of the subgroup. 

Narrowing the Scope of Analysis

With the subgroups expanded, you have the opportunity to scour each effort for anomalies that might be skewing your subgroup data. Depending on the size of your test and how many efforts you have included, you may choose to exclude some outlier data points. Or, you may want to drill down to examine one multivariate group in particular. IRIS allows you to select just the efforts you want to take a closer look at and hide all other efforts in the testing group temporarily. 

Selecting Individual Efforts

In the example shown above, let's say you want to zoom in to review data from the multivariate group of efforts that ran on 3/20/2017. With both subgroups expanded, you'll just need to check off the 3/20/2017 effort from the 'Edgy (Test)' subgroup and the 3/20/2017 effort from the 'Traditional (Control)' subgroup. Then check the 'Show Selected Only' box. 

This will remove all other efforts from the screen while you focus on these particular efforts. In this mode, the sub-totals row at the bottom of each subgroup will reflect only the values in efforts you currently have selected for viewing. The sub-totals will continue to update as you select and deselect different efforts from the testing group. 

When you're done, just uncheck the 'Show Selected Only' box to bring back the rest of the efforts in the testing group. 

Filtering Efforts

In addition to hand-selecting efforts for analysis, it might make sense to review efforts based on some piece of criteria the efforts have in common. For example, in testing the traditional promo against the edgy promo, we knew that some of our lists would likely respond better to the edgy copy than others, so it would be good to filter by list and examine how each promo did to lists of interest. To do this, you can filter the efforts in your testing group by list the same way you'd achieve this on schedules. Click on any linked text in the subgroup table to filter by click. 

Further Data Manipulation

Sometimes you really need to spread your numbers out and move things around in your own special way. The Download tool is always available in Testing Groups for you to export your data in a spreadsheet and manipulate however you see fit. 

Make it a Team Effort

Whether you need another set of eyes on the data or want to spread the word about a breakthrough test you've just wrapped, don't forget to bring your team into the fold. Use the Share Results feature to blast out a note and direct your colleagues to your testing group, or use the Download feature to send a spreadsheet.