For decades, brands have invested heavily in advertising platforms built by major tech players. These technologies have reshaped market standards offering mass reach, precise audience targeting, and real-time performance optimization.
But today, more and more experts are challenging this technological dominance and calling for a fairer, more transparent way to measure advertising performance, one that includes incrementality. In this article, we’ll explore what incrementality really means, how to measure it, and why it’s becoming an essential pillar of programmatic strategy.
What Is Incrementality?
Borrowed from the world of science, incrementality has found its place in digital marketing as a key way to measure real advertising impact. Unlike attribution models, which simply divide credit across multiple touchpoints, incrementality answers the one question that really matters: “How much incremental revenue did this campaign actually generate?”
In other words, incrementality helps you understand whether a programmatic campaign truly delivered added value or if the results would have happened anyway. Despite its relevance, few advertisers are truly leveraging this approach today. Yet it should be the compass guiding every programmatic investment, because incrementality directly measures whether your advertising efforts created real, measurable business growth.
How Do You Measure Incrementality?
Now that we’ve defined the concept, let’s break down the two most common approaches for measuring it reliably and effectively.
1. A/B Testing
This method compares performance between two groups: one exposed to the campaign, and one unexposed. A/B testing is statistically sound and highly transparent but it requires a large enough sample and sufficient runtime. When implemented during the planning phase, it allows advertisers to fine-tune their strategy before launching full-scale campaigns.
2. Lift Modelling (Post-Campaign Analysis)
This method applies after a campaign has run. It measures the actual impact of your advertising beyond engagement metrics by isolating results directly caused by exposure. In a privacy-first context, lift modelling provides reliable insights on performance and return on investment (ROI), helping marketers make informed, data-driven budget decisions.
Whether you measure incrementality upfront with A/B testing or after the fact via lift modelling, the goal remains the same: prove and optimize the real business impact of every advertising dollar spent.
Key Metrics to Measure Incrementality :
Out of all the programmatic KPIs available, two stand out when it comes to quantifying net impact:
1.1 Incremental Lift:
This metric measures the increase in conversions (sales, leads, sign-ups) from a group exposed to ads versus a control group. It isolates the net effect of your campaign removing factors like organic sales, seasonality, or other concurrent marketing efforts.
Méthode de calcul : 
Example :
A brand typically sells 1,000 products per month with no advertising.
During a test, two groups of 1,000 users are observed:
- Exposed group: 60 purchases → 6% conversion
- Control group: 40 purchases → 4% conversion
Incremental lift = (6(6% – 4%) ÷ 4%(6 × 100 = 50%
Meaning: 20 of the 60 conversions are directly attributable to the ad campaign.
1.2 Return on Incremental Ad Spend (ROIncrementalAS):
Once you’ve calculated the incremental lift, this KPI expresses the financial impact.
Unlike traditional ROAS (Return on Ad Spend), which includes all revenue, ROIncrementalAS only counts the revenue that wouldn’t have happened without the campaign.
This metric answers the ultimate question for decision-makers : « Did every dollar invested in this campaign generate more than it cost? ». It shifts advertising from a spend mindset to an investment mindset—helping to allocate budgets toward high-impact campaigns while eliminating low-performing ones.
Calculation method:
Incrementality: A New Standard for Programmatic Success
After years of rapid growth, the global programmatic market is maturing. Economic pressures are forcing advertisers to demand more accountability and prove the effectiveness of every campaign.
Simultaneously, the programmatic ecosystem is evolving:
- Third-party cookies are disappearing
- Privacy regulations are tightening
- Media buying is consolidating around a few major platforms
In this complex environment, brands no longer settle for superficial metrics. They want hard proof of performance.
This is where incrementality becomes essential. It allows advertisers to back up their decisions with measurable results and transform programmatic from a volume game into a value strategy.
Moving from Volume to Value
Adopting an incremental approach means focusing on impact, not impressions. It’s about building a programmatic ecosystem that’s more transparent, more agile, and more responsible where performance is measured by outcomes, not just delivery.
Conclusion :
Incrementality is more than a performance metric it’s a philosophy. And it’s fully aligned with NÜ’s DNA.
In a programmatic space that’s increasingly opaque and fragmented, we believe in giving advertisers back full control with clear, independent insights into what’s truly working.
Through A/B testing, lift modelling, and metrics like incremental lift and ROIncrementalAS, NÜ empowers brands to go beyond surface-level reports and make better, evidence-based decisions.
At NÜ, we’re committed to shifting programmatic from a volume-driven model to one focused on measurable value. Our mission: bring clarity, independence, and precision to a space long dominated by complexity and opacity.
👉 Ready to see what your programmatic spend is really delivering?
Book a discovery call with NÜ today and find out how we can help you maximize your campaign efficiency across Canada.
