Unlocking incrementality: Go beyond surface metrics
We are surrounded by metrics in digital marketing: Clicks, views, ROAS and CPA. But do these metrics tell you the real story about campaigns? Incrementality cuts through the noise, revealing the true impact of the marketing efforts. It’s about understanding which actions genuinely add value and drive results that wouldn’t have happened otherwise.
Whether you’re optimizing ad spend or fine-tuning email campaigns, incrementality ensures every euro delivers measurable growth.
What is Incrementality?
Incrementality measures the additional value created by your marketing actions beyond what would occur naturally. It answers questions like:
- How many additional conversions did this campaign generate?
- Did it attract new customers or encourage repeat purchases?
By focusing on incremental value, you can prioritize campaigns that contribute meaningfully to growth while avoiding wasteful spend.
How to measure incrementality
Now the question remains: how can you measure incrementality? Measuring incrementality requires a data-driven approach that uses various methods to determine the actual impact of marketing campaigns, such as:
- A/B Testing
A/B testing involves splitting your audience into two groups: one group (the test group) is exposed to the campaign, while the other group (the control group) is not. By comparing the results of the two groups, you can determine the incremental impact of your campaign. - Holdout Groups
In this method, a specific portion of your audience is deliberately excluded from a campaign or promotion. The performance of this holdout group is compared to those who received the campaign, helping you understand the additional value the promotion brings. - Geographical Splits
Geographical split testing launches a campaign in one region while withholding it from a similar, comparable region. This allows you to observe differences in results and assess the incremental lift in areas where the campaign was active. - AI and Machine Learning
Artificial intelligence can analyze vast datasets quickly and identify patterns in customer behavior. Predictive models and real-time insights provided by machine learning tools make it easier to measure incrementality on a large scale, offering precision that manual methods can’t match.
Why incrementality matters more than traditional KPIs
Metrics like ROAS and CTR are valuable, but they can be misleading when viewed in isolation.
For instance, a high ROAS might seem like a success, but if most of those conversions came from customers who were already planning to buy, the incremental value of the campaign is low. Similarly, a high CTR tells you how many people clicked on an ad but doesn’t reveal whether those clicks led to valuable conversions.
With incrementality, you can focus on campaigns that truly drive growth, enabling smarter budget allocation and a more effective overall strategy.
📌 Pinpoints of action
- Test & Learn
- Begin with small-scale A/B tests to understand your campaigns’ incremental impact.
- AI for the Win
- Use machine learning tools to streamline your analysis and scale your insights.
- Focus on Growth
- Align campaigns with broader business goals, prioritizing those with measurable incremental value.
