Tango.ad Analytics - Control Group

The Control Group in Tango.ad Analytics is used to measure the true impact of your campaigns by comparing users who were exposed to Tango.ad experiences (popups, recommendations, banners, etc.) with users who were not.

By analyzing the Control Group, you can:

• Understand real performance impact
• Measure revenue uplift accurately
• Avoid false positives caused by natural user behavior
• Validate A/B-style results without manual experiments

This documentation explains each section visible in the Control Group Analytics Dashboard, including metrics, charts, and how to interpret them.

Revenue Uplift Section

1. Tango.ad Revenue Uplift (in %)

This metric shows how much additional revenue was generated due to Tango.ad compared to the control group.

What it means:

• It compares the exposed group (users who saw Tango.ad experiences) vs the control group (users who did not).
• The result is displayed as a percentage increase or decrease.

Example:

If the uplift is +15%, it means users exposed to Tango.ad generated 15% more revenue than users in the control group.

Empty State:

If you see the message:

No results were returned for this query

It means:

• There is not enough data for the selected time range
• The campaign is too new
• Or the control group has not been properly assigned

2. Avg Revenue per Visitor by Group (in %)

This chart visualizes how the average revenue per visitor (ARPV) changes over time between:

• Control Group
• Exposed Group

It also highlights incremental revenue, which is the additional value created by tango.ad.

Key elements:

• Timeline slider (bottom) allows zooming into a specific date range
• Data points show daily or periodic changes
• "Incremental revenue" highlights the difference between groups

Why this matters:

This chart helps you understand:

• Whether tango.ad has a consistent positive effect
• If performance spikes are temporary or stable
• How revenue behavior differs over time

3. Average Revenue per Group

This chart compares the actual revenue values of:

• Control Group (blue)
• Exposed Group (orange)

Metrics displayed:

• ARPV = Average Revenue Per Visitor
• Shown as a time series

How to interpret:

• If the exposed group line is consistently higher → Tango.ad is working
• If both lines overlap → little or no measurable effect
• If control group is higher → campaign may need optimization

Control Group Health Check

The Control Group Health Check ensures that your test setup is statistically valid.

A healthy control group should:

• Have enough users
• Be evenly distributed
• Not fluctuate heavily
• Be randomly selected

4. Control Group Distribution

This bar chart shows how users are distributed between:

• True → Users in the control group
• False → Users exposed to Tango.ad

Displayed over time (daily or periodically).

Why this is important:

A poor distribution can lead to misleading results.

For example:

• If the control group is too small → results are unreliable
• If distribution suddenly changes → tracking issues may exist
• If one group dominates → uplift calculations become inaccurate

Common Issues & Troubleshooting

1. Seeing all zeros

Possible reasons:

• Campaign just started
• No conversions yet
• Tracking not properly implemented
• Control group not assigned

2. No uplift data available

This can happen when:

• Control group is missing
• Data is insufficient
• Time range is too short

Try extending the date range or verifying campaign setup.

Best Practices

• Always allow campaigns to run for several days before analyzing
• Ensure control group is at least 5–10% of total traffic
• Avoid changing campaign rules too frequently
• Monitor distribution regularly
• Use longer time windows for more reliable insights

Summary

The Control Group Analytics in Tango.ad provides a reliable way to measure real business impact. By comparing exposed users with a randomized control group, you can confidently assess:

• Revenue uplift
• Behavioral changes
• Campaign effectiveness
• Long-term performance

This ensures that your optimization decisions are based on real, unbiased data—not assumptions.

Continue Learning

Discover how to evaluate customer interactions and cart behavior in the next article — Tango.ad Analytics: Cart Analysis.