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# Interpreting a Group Comparison Analysis

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When investigating a metric, understanding what’s driving the performance and which subgroups might be driving this KPI is key. For a Group Comparison Analysis, Sisu compares two groups of data that you define, then returns key statistics for the metric selected, as well as min, max, median, average, sum, the number of rows to help validate the quality of the data used. The Analysis results also include detailed information about facts that impact the group comparison and performance of the chosen metric.

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## General Layout of the Analysis Results

The following image provides an overview of the information and actions you can take from a Group Comparison Analysis results screen.

## The Key Statistics Cards

These cards provide a quick overview of key statistics for all records that meet the criteria set in the configuration of the Analysis that Sisu uncovered as a result of the Analysis.

In the example, this Group Comparison Analysis based on the metric “Average Order Value - Digital” analyzed the average order value for all orders generated from the Order Channel “digital_mobile” in the data (this was set as a filter in the configuration), and compared the results between two groups of data:  sales in LA and Sales in NY.

The two cards on the left display the following stats for each time period defined:

• The average of the metric’s column within the data
(in this example, average digital order value, since that is the metric selected for the Analysis)
• The minimum, maximum, median values of the metric’s column within the data
• The total sum of the metric’s column within the data
• The number of rows included (records in the data - in this case, it’s the number of digital orders)

The card on the right displays a bar graph of the data for each group.

## The Top Drivers Subtab

This subtab is displayed by default, and helps you identify what is meaningfully impacting metric performance in each defined group so that you can take action with confidence. Each line of the table represents a “Subgroup”, or a subset of rows in your data determined by the factor, that had a statistically significant impact on the metric.

The following table describes each of the columns in this view.

 Some Analyses include many, many rows. You can use the filter icons in each column to filter the rows using properties applicable to that column, if desired.

 Subgroup A subgroup is defined by a set of factors. A factor is a column-value pair (such as order_store_city = new york). Some subgroups are determined by multiple factors, referred to as "2nd order facts" or “3rd order facts”. The name of each subgroup describes which column and value pair it refers to. For example, “LIST_SKU_FLAVOR contains “Chocolate Brownie”” refers to order records that contained chocolate brownies. Use the expand/collapse icon to view/hide details about certain subgroups: In this example, Sisu identified additional information about sales of chocolate brownies that impacted the metric’s performance, such as buyers’ gender trends and orders that only contained only chocolate brownies. Refer to Understanding Facts & How They Are Grouped. Use the column’s filter icon to include only orders in a certain city or SKU, for example. Refer to Sorting & Filtering the Fact Table. Click on a Subgroup name to display more details. Refer to Exploring & Drilling Down Into a Fact. Subgroup size Describes how big each subgroup of the data for each group is as a percentage of the total. For example, if there are 100 rows in the data and the subgroup size is 40%, it means that 40 rows out of the 100 match that criteria. In Group Comparison Analyses, the sizes are displayed as follows: vs   The percentage shown highlighted in grey is the difference between the two. In the example above, the subgroup’s size for the second group was 5.4% less than the first group. (Positive percentages indicate an increase in size.). Use the column’s filter icon to include only subgroups that are over or under a specified size. Refer to Sorting & Filtering the Fact Table. Subgroup metric Note: this column reflects the calculation type that was used for the metric. Describes the average (or sum or count) for each subgroup or subset of rows in the data for each time period defined. This column will reflect the calculation type that was selected, so it could be a Subgroup sum, average, or count in General Performance Analyses. In Group Comparison Analyses, the values are displayed as follows: vs   The percentage shown highlighted in grey is the difference between the two. In the example above, the subgroup’s metric for the second group increased over the first group by 43.9%. (Negative percentages indicate a decrease.) Use the column’s filter icon to include only subgroups that are over or under a certain average value. Refer to Sorting & Filtering the Fact Table. Impact column Describes each subgroup’s impact on the overall metric performance for each defined time period. Subgroups may overlap. Refer to Understanding Impact for details about impact and how it is determined. Use the column’s filter icon to include only subgroups that have an impact value over or under a certain number. Refer to Sorting & Filtering the Fact Table.

There are several actions you can perform for each fact in the table.

 For more details on exploring facts, refer to Exploring & Drilling Down Into a Fact.

Finally, the default view of the Top Drivers tab is the table view. You can choose to view the same information in “natural language view”.

This option is a toggle, so you can easily switch between the two views.

 For more details on the natural language view, refer to Fact Table: Natural Language & Table Views.

## The Waterfall Subtab

This subtab displays data for the analysis in the form of a waterfall plot.

 Refer to Using Smart Waterfall Plots to Visualize Key Data for a description of how to interpret this screen.

## The Query Preview Subtab

 This subtab is only visible if the underlying data is based on a query. If the underlying data is a table with no query applied, the Table Preview subtab will be used instead.

This subtab in the Analysis results allows you to explore a preview of the underlying query used to generate the analysis.

 For more details, refer to Previewing the Underlying Data Table.

## The Query Subtab

 This subtab is only visible if the underlying data is based on a query. If the underlying data is a table with no query applied, the Table Preview Subtab will be used instead.

This subtab in the Analysis results allows you to view the actual underlying query that defines the metric used within this analysis.

 For more details, refer to Creating & Managing Queries.

## The Table Preview Subtab

 This subtab is only visible if the underlying data is not based on a query. If a query is used for the analysis, the Query Subtab and Query Preview Subtab are displayed instead.

This subtab in the Analysis results allows you to view the data table used to generate the analysis.

 For more details, refer to Previewing the Underlying Data Table.