Incrementality Testing

What Is Incrementality Testing?

Incrementality testing is a measurement method used to determine whether advertising generates additional outcomes that would not have occurred without the campaign. It typically involves comparing the results of a group exposed to advertising with those of a comparable control group that does not receive the advertising.

In native advertising, incrementality testing can help brands evaluate whether sponsored content contributes to additional conversions, sales or brand awareness. Unlike traditional attribution models, which assign credit to advertising interactions, incrementality testing aims to establish the causal impact of advertising activity.

Examples of Incrementality Testing

• Conversion Lift Testing: Comparing conversion rates between randomly assigned treatment and control groups to estimate how many additional conversions a native advertising campaign generates.
• Geographic Lift Testing: Running advertising campaigns in selected geographic markets while using comparable markets as a control group to estimate incremental sales or other outcomes.
• Brand Lift Experiments: Comparing brand awareness, recall or purchase intent between exposed and control groups to evaluate the additional impact of sponsored content.

Key Points about Incrementality Testing

• Causal Measurement: Incrementality testing helps advertisers distinguish outcomes caused by advertising from those that might have occurred naturally.
• Beyond Attribution: Unlike multi-touch attribution, incrementality testing focuses on measuring additional outcomes rather than distributing credit across advertising touchpoints.
• Budget Effectiveness: Incremental results can help advertisers understand which campaigns contribute genuine business value and make more informed budget decisions.

Incrementality Testing Best Practices

• Establish Comparable Groups: Use randomised treatment and control groups where possible to minimise differences that could influence campaign results.
• Define Clear Objectives: Identify the primary outcome, such as incremental conversions, sales or brand awareness, before launching the experiment.
• Ensure Sufficient Data: Plan an appropriate test duration and sample size to improve the reliability of results, particularly when measuring relatively infrequent conversions.

Considerations

• Testing Complexity: Designing reliable experiments requires careful planning, suitable control groups and appropriate statistical analysis.
• Audience and Campaign Limitations: Some native advertising campaigns may lack sufficient audience reach, conversion volume or control over ad exposure to support robust testing.
• Measurement Uncertainty: Incrementality results are estimates subject to statistical uncertainty and may not apply equally to different audiences, publishers or campaign conditions.