What is incremental measurement?
Incrementality refers to the additional impact or lift generated by a marketing effort or channel beyond what would have occurred naturally. Incremental measurement helps businesses distinguish between organic outcomes (e.g., purchases that would have happened without marketing) and those driven directly by campaigns.
For example, if a brand’s holiday sale ad leads to 200 extra purchases compared to a similar audience not exposed to the ad, those 200 purchases represent the incremental effect.
Why does incrementality measurement matter?
Incrementality measurement is essential for optimizing marketing strategies and budgets. By identifying which campaigns or channels truly drive additional revenue, you can:
- Reduce waste: Avoid spending on efforts that don’t generate incremental results.
- Boost ROI: Focus resources on high-performing campaigns.
- Improve decision-making: Gain actionable insights to refine marketing strategies.
Additionally, it’s especially valuable for evaluating the effectiveness of paid ads, email campaigns, and loyalty programs.
What’s different between incrementality and traditional attribution methods?
While traditional attribution models (e.g., last-click, first-click) allocate credit for conversions across touchpoints, they don’t account for actions that would have occurred without marketing.
| Attribution | Incrementality measurement |
| Focuses on distributing credit for conversions. | Quantifies the unique impact of a campaign by comparing exposed versus unexposed audiences. |
For instance, traditional attribution might assign credit to a Google Ad for a sale, but incrementality measurement evaluates if the sale would have occurred even without the ad.
How to do incrementality testing?
There are several techniques to measure incrementality and deliver accurate insights into what drives additional results as below.
- A/B testing: Divide audiences into two groups: one exposed to the campaign and another as a control. Compare outcomes (e.g., sales or sign-ups) between the groups to determine the campaign’s incremental effect.
- Holdout experiments: Exclude a portion of your target audience from seeing the campaign (holdout group). Measure the difference in performance metrics between the holdout and exposed groups.
- Audience segmentation: Analyze how different audience segments (e.g., new vs. returning customers) respond to marketing efforts. This helps pinpoint which groups experience the most incremental lift.
- Analyzing first-party transaction data: Use customer purchase histories to assess whether marketing campaigns influence buying behaviors, leveraging data from CRM systems or eCommerce platforms.
How can incrementality measurement help optimize ROI?
By focusing on campaigns that deliver the highest incremental lift, businesses can achieve better ROI through:
- Scaling up ad spend on campaigns with proven impact.
- Reallocating budget from low-performing channels to high-value ones.
- Catering messaging to audience segments that show the greatest responsiveness.
What are the challenges in measuring incrementality?
These challenges often arise from the complexity of isolating campaign impacts in dynamic, multi-channel marketing environments.
Addressing overlapping marketing channels
When multiple campaigns run simultaneously, it can be difficult to isolate the incremental impact of one campaign. Advanced statistical models or experimental designs can help mitigate this issue.
Aligning marketing spend with sales outcomes
Incrementality measurement requires tight alignment between marketing activities and measurable outcomes. Poor tracking or siloed data can make this challenging.
