How experiment groups organize tests

Where experiments fit in the operation

Experiment groups organize variations that an agency wants to compare for a client. Each group contains related experiments, while each experiment combines resources and produces its own view of status, budget, and performance.

Experiments is not just another campaign list. It provides a comparative lens: the group appears first, and the team can expand it to analyze the variations that belong to that test.

Why this matters

Without a shared structure, comparing audiences, ads, conversion zones, or keywords can mix different objectives, periods, and budgets. The group keeps those variations together and helps the team evaluate performance within a shared context.

This organization does not turn every difference into a reliable conclusion. Data volume, delivery time, platform configuration, and changes made during the test still affect interpretation. Agencify organizes the comparison, but the team still needs to understand its context.

Mental model

Think of the group as the test container and the experiments as the variations compared inside it. The group row summarizes the set. When expanded, it shows the experiments and resources connected to each variation.

Group and experiment

The group holds the name, state, aggregate budget, and summary metrics. Experiments show specific resource combinations. After creation, an experiment structure does not behave like a freely editable manual campaign. Actions focus on state, budget, and management of the group.

Comparative lens

The Resources library helps explain how an item performs individually. Experiments compare variations within the same group. Campaigns shows the published operation as a whole. The three areas use related data but answer different questions.

Budget and state

Pausing or activating experiments changes how many variations remain in delivery. Depending on the chosen action, budget may need to be redistributed among active experiments. The summary state of the group follows the state of its variations.

A realistic scenario

An agency wants to compare three audiences using the same ad and conversion zone. The team places the variations in one group, follows results over the same period, and expands the row to compare each experiment. If one variation is paused, the team reviews the effect on the remaining budgets before confirming the decision.

Main capabilities

• Creation of a group from resources available to the client.
• Group table with search, filters, date range, sorting, and configurable columns.
• Summary metrics on the group and experiment details in an expanded panel.
• Identification of the resources used by each experiment.
• Actions to pause, activate, and adjust budget when the current state allows them.
• Budget redistribution when it applies to pausing experiments.
• Related access to History, Reports, and AI recommendations.

Limits and recovery

A recent comparison or one with little volume should not be treated as a final decision. Metrics can arrive partially, and results depend on the objective, platform, and period. Missing resources, expired integrations, minimum budget requirements, or a blocked subscription can prevent creation or change.

If an operation continues in the background, wait for the refresh and review notifications and History. Before repeating a pause, activation, or adjustment, confirm the state of the group and experiments in Agencify and in the provider. If a variation does not appear, review the resources and whether group creation completed.

Up next

After this overview, go deeper into experiment metrics and learn how History records changes and AI decisions without confusing internal confidence with a performance metric.