Powerpop Analytics - Control Group
The Control Group section in Analytics allows you to compare customer behavior between those exposed to a campaign or experiment (Test Group) and those who were not (Control Group). By analyzing these results, you can measure the true impact of your marketing activities on key performance indicators such as purchases and revenue.
This data helps you:
- Identify whether changes in customer behavior are directly influenced by your campaign.
- Separate natural trends from campaign-driven results.
- Understand how much additional value (purchases or revenue) your strategy is generating compared to the baseline.
The charts provided in this section highlight purchases per visitor and average revenue per visitor, giving you clear visibility into both the frequency and value of customer transactions.
Dashboard Menu (Top Right Corner)
At the top right side of the dashboard, you can see a three-dot icon inside a square. This menu controls the overall dashboard settings and actions, not just a single chart.
Available Options:
- Refresh Dashboard: Updates all charts with the latest available data.
- Download:
- Export to PDF – Generates a PDF version of the entire dashboard.
- Download as Image – Saves the dashboard as an image for reporting or presentations
- Share:
- Copy Permalink to Clipboard – Creates a direct link to the current dashboard view.
- Share Permalink by Email – Sends the dashboard link by email for quick access.
- Set Auto-Refresh Interval: Allows you to schedule automatic data refresh at regular intervals, ensuring the charts always display the latest data without manual updates.
Purchases
The Purchases section provides insights into visitor buying behavior within the control and test groups. These charts allow you to compare purchase frequency and revenue contribution across groups to better understand the effectiveness of your campaigns.
Purchases per Visitor by Group
Description:
This chart shows the average number of purchases made per visitor, broken down by group:
- True (blue line): Represents the test group exposed to the variant or condition being analyzed.
- False (dark blue line): Represents the control group (not exposed).
How to interpret:
- A higher value indicates that, on average, visitors in that group are completing more purchases.
- Peaks in the graph reflect days when purchase activity increased, while dips suggest lower purchasing frequency.
- Comparing the lines shows whether the test group (True) outperforms or underperforms the control group (False).
Interactive detail:
When you hover your cursor over the chart line, detailed information for each point in time is displayed.
Example (Sat Aug 23):
- Blue Dot (True): 0.02445 → 52.29%
- Purple Dot (False): 0.02234 → 47.71%
- Total: 0.0466 → 100.00%
This breakdown allows you to see exact values and percentage contributions per group on a given date.
Average Revenue per Visitor by Group
Description:
This chart displays the average revenue generated per visitor for each group:
- True (blue line): Test group.
- False (dark blue line): Control group.
How to interpret:
- This metric captures not only how many purchases were made but also the value of those purchases.
- A higher value indicates that visitors in that group are spending more on average.
- Differences between the two lines show whether the test group drives higher revenue than the control group.
Interactive detail:
When you hover your cursor over the chart line, detailed information for each point in time is displayed.
Example (Fri Aug 22):
- Blue Dot (True): 421.36 → 64.17%
- Purple Dot (False): 235.30 → 35.83%
- Total: 656.67 → 100.00%
This breakdown helps you understand how much revenue each group contributes on a specific day, both in absolute values and as a percentage of the total.
Distribution (CG Health Check)
Description:
This chart shows the distribution of visitors between the control and test groups over time. It helps ensure that the control group is correctly balanced and that the experiment is being measured fairly.
- True (blue bars): Test group – visitors who are exposed to the campaign or experiment.
- False (purple bars): Control group – visitors who are not exposed.
How to interpret:
- A larger number of control group visitors (False) compared to test group visitors (True) is expected in many experiments, depending on how the groups were configured.
- Monitoring the balance between these groups is essential to validate the reliability of your experiment results.
- Any sudden drops or spikes could indicate tracking issues, sampling changes, or unusual visitor behavior on those dates.
Interactive detail:
When you hover your cursor over a bar, detailed group distribution values and percentages are displayed.
Example (Fri Aug 22):
- Blue Dot (True): 97 → 4.54%
- Purple Dot (False): 2.04k → 95.46%
- Total: 2.14k → 100.00%
This breakdown helps confirm that the control group remains dominant in size, while still allowing the test group to provide a measurable comparison.
Chart Tools & Options
Each chart in Control Group Analytics includes additional tools that help you interact with the data more efficiently.
1. All and Inv Buttons
- All: Displays the chart including both the test group (True) and the control group (False).
- Inv (Inverse): Allows you to quickly toggle or invert the group selection, making it easier to focus on one group at a time.
This feature is especially useful for comparing results side by side or isolating a single group’s performance.
2. Three-Dot Menu (⋮) Options
Located in the top-right corner of every chart, this menu gives you more control over how you view and share the data.
Force Refresh: Updates the chart with the latest available data.
Enter Fullscreen: Expands the chart to fullscreen mode for better visibility.
View Query: Displays the underlying data query powering the chart, useful for technical verification.
View as a Table: Converts the chart view into a table format for easier data inspection.
Share:
- Copy Permalink to Clipboard – Generates a direct link to the chart that can be shared internally.
- Share Chart by Email – Send the chart directly to chosen email addresses with an optional message. The recipient gets it as an image or link.
Continue Learning:
Discover how to evaluate customer interactions and cart behavior in the next article — Powerpop Analytics: Cart Analysis.