Incrementality in marketing is the measurement of the additional value a specific campaign or channel brings to your business—such as increased leads, enhanced conversion rates, or higher engagement—by assessing the positive effect, or incremental lift, that would not have occurred organically.
Incrementality isolates a campaign’s contribution from other initiatives so you can accurately measure its impact. By identifying which marketing strategies deliver the highest additional value, you can optimize budget allocation and better justify your spend.
No wonder there’s a growing shift from traditional return on ad spend (ROAS) to incremental return on ad spend (iROAS), as marketers seek a more nuanced and holistic approach to measuring campaign performance—in other words, an approach that goes beyond deterministic attribution.
This guide explains what marketing incrementality is, why it’s essential for accurate measurement, and how to implement it to optimize your budget and prove ROI.
Key highlights:
- Unlike attribution models that assign credit based on touchpoints, incrementality in marketing isolates the additional value your marketing actually creates by comparing exposed groups to control groups who didn’t see your campaigns.
- Companies like Dramamine increased marketing ROI by 9.5% by testing incrementality in off-season periods, while a household CPG portfolio unlocked $79M in incremental marketing revenue through systematic optimization across brands.
- Keen’s AI-powered platform simplifies incrementality measurement by integrating results from diverse methodologies and providing predictive analytics. We help marketers isolate incremental lift, quantify ROI by tactic, and optimize budgets.
Incrementality vs attribution: Key differences
Incrementality and attribution are complementary approaches to understanding marketing performance. Imagine you run a campaign with paid search ads and email marketing. Then:
- Attribution helps you to understand which channel was the last touchpoint before a conversion. You can use this information to allocate budget to converting channels, but keep in mind that attribution may overstate the value of specific channels by giving credit only based on the interaction sequence.
- Incrementality reveals how much of the observed conversions are genuinely driven by a specific campaign versus what would have occurred naturally. You can run an incrementality test showing an ad to a set of customers while withholding it from a similar group. If those who didn’t see the ad still converted, then the true additional impact of the ads is lower than initially thought.
| Approach | Marketing incrementality | Marketing attribution |
| Description | Measures the additional value or impact of a marketing activity by isolating its effect from other factors | Assigns credit to various customer touchpoints with a brand, such as ad clicks, social media engagement, email opens, and website visits |
| Methodology | Relies on experimental design, such as A/B testing. It compares results between the exposed and control groups to isolate the effect of marketing activities. | Typically uses rule-based or data-driven algorithms to distribute credit across touchpoints. Standard models include last-click, first-click, linear, and multi-touch attribution. |
Why marketing incrementality matters
Incrementality in marketing matters because it helps you make data-driven media planning decisions and avoid overestimating success due to external influences such as market trends and economic conditions. Benefits include:
- Better understanding of the actual impact of your marketing efforts: By distinguishing between actual performance improvements and organic results, you can assess return on investment more precisely. This assessment leads to a more accurate evaluation of campaign effectiveness.
- Budget optimization: With Gartner reporting that 59% of CMOs have insufficient budget to execute their strategy, maximizing resources becomes more important than ever. Assessing the true incremental lift generated allows you to focus on the most effective efforts and scale back on those with lower impact.
- Reduced wasted spend: Identifying campaigns generating genuine incremental value allows you to allocate your budget more strategically—for example, avoiding investing in media channels that are not delivering a positive return on investment (ROI).
You can answer questions like:
- What is the true effectiveness of each of my marketing channels? Incrementality measurement can help you determine which channels are driving the most incremental sales and which ones may be cannibalizing each other.
- Am I reaching my target audience efficiently? By measuring marketing incrementality, you can identify which demographics or segments are most responsive to your advertising and allocate your budget accordingly.
- How can I optimize my marketing spend? Incrementality testing can help you identify areas where you can reduce your advertising spend without sacrificing results, such as by cutting back on underperforming channels or refining your targeting.
Keep learning: How to identify the right channel for product launches
How to calculate incrementality
Calculating incrementality in marketing involves isolating the specific impact of a campaign or initiative from other factors.
A common method is through controlled experiments (A/B testing).
- Randomly split your target audience into two groups (control and test), then expose the test group to the marketing campaign being evaluated.
- Compare the performance of the test group to the control group to determine the incremental impact of the campaign.
This way, you understand how much of the observed change in outcomes (e.g., sales, website traffic, conversions) can be directly attributed to the campaign, rather than other factors such as seasonal trends or broader economic conditions.
With AI tools, measuring marketing incrementality has become more accurate and efficient. Three-fourths of marketers surveyed by Salesforce are already experimenting with or fully implementing AI.
One use case is to identify intricate patterns and correlations within data that traditional methods might miss. AI also helps to create sophisticated models that accurately predict the impact of marketing campaigns.
Types of incrementality measurement experiments
Let’s break down the most common types of incrementality measurement experiments:
Holdout experiments
Holdout experiments reserve a part of your target audience or market segment from exposure to a campaign. When comparing the behavior of the holdout group with that of those who were exposed, you can assess the incremental effect of your marketing efforts. You can use this method in digital advertising to determine the lift of paid media amidst organic activity and baseline trends.
Scale
Scale experiments measure marketing incrementality by gradually adjusting the level of media investment across groups or regions. For instance, increasing spend by a set percentage in one area while holding steady in another can reveal the relationship between ad spend and incremental marketing returns. These insights enable better marketing budget allocation and risk management.
Multi-treatment
Multi-treatment experiments test multiple marketing channels or tactics simultaneously to evaluate their individual and combined effects. This approach is effective for optimizing complex marketing mixes, as it reveals potential interactions or overlaps between channels, guiding more integrated and effective strategies.
Geo-based experiments
Geo-based experiments use geographic regions as test and control groups. By activating media in one region and withholding it in another, marketers can measure incremental lift at scale without relying on user-level tracking. This approach is particularly valuable for large campaigns or when privacy restrictions limit the use of individual-level data.
Time-based experiments
Time-based experiments analyze performance over alternating periods of media activity—for example, running campaigns for a week and pausing for another. By comparing these time windows, marketers can assess the incremental impact of advertising over time and detect seasonality or baseline shifts in demand.
Incremental marketing case studies
Real-world case studies show how incrementality measurement transforms marketing decisions from assumption-based to evidence-based. By testing, learning, and optimizing media investment, you uncover which channels and strategies truly drive incremental growth.
Case in point: after partnering with Keen, major brands were able isolate the incremental impact of marketing spend, revealing opportunities to reallocate budgets and maximize ROI. Let’s review two Keen case studies:
- A top household CPG portfolio used Keen’s modeling to systematically optimize spend across their diverse brand categories. The shift to causal measurement resulted in a 42% increase in overall media ROI and unlocked $79 million in incremental media-driven revenue in one year.
- Dramamine leveraged Keen to evaluate the marginal return on investments and predict the financial impact of an incremental marketing investment in the off-season. This data-driven approach, executed in a “test and learn environment,” proved profitable, resulting in a 9.5% increase in marketing ROI and driving the brand to record high sales.
Keen: All the analysis you need to unlock incremental lift
Keen’s marketing mix modeling (MMM) platform leverages AI to empower marketers with dynamic budget optimization based on real-time performance and predictive analytics, ensuring funds are allocated to the most effective channels for optimal incremental lift.
You can integrate results from diverse methodologies, including incrementality, into the Keen Platform, for a comprehensive and triangulated understanding of marketing impact. You can isolate incremental vs base volume, quantifying the incremental for each tactic. By comparing the incremental revenue driven by each tactic to the spend on that tactic, you can determine the ROI.
Start planning with confidence and precision. Get a Keen demo—and make the most out of incrementality in marketing to optimize your spend.
