What is Incrementality in Marketing?
What would have happened to traffic, pipeline generation & velocity, conversion and valuation of your company, if your Marketing stopped working? Or another way of saying this is “What would be the aggregate loss to the company if entire Marketing team goes on vacation for one year? Think of Incrementality as the marketing’s definitive answer to this question?
Business results from marketing tactics that would not have occurred otherwise, is Marketing’s Incrementality. It is the measure of additional business outcomes (revenue, conversions, pipeline generation & velocity, brand) that occurred because of marketing activity. It refers to the true, causal lift that marketing activities generated above and beyond what would have naturally occurred without it. So, Incrementality at a functional level, is the marketing’s actual contribution to the company.
Distinguishing correlation from causation, it’s a way to isolate and quantify the genuine impact of marketing efforts & separating the credit-taking peacocks from the actual workhorses in your marketing mix.
Why Should You Measure Incrementality?
- Executive Credibility & Organizational Influence: CEO stops asking stupid budget questions and starts understanding “How can we scale what’s working?”, when you can prove that marketing drove an incremental $5M in pipeline (not just $5M that happened to have marketing touchpoints). And nothing shuts down dismissive sales leaders & skeptical product teams faster than incrementality evidence showing marketing-driven opportunities closed 23% faster with 15% higher deal values!
- Investment Decision Framework: CFOs love incrementality because it answers their core question: “What happens if we cut this budget?”. Instead of “We need more budget,” marketers can say, “Here’s the revenue impact of each spend level”, transforming budget negotiations into strategic growth planning sessions.
- Optimal Budget Allocation: It separates marketing theater from marketing effectiveness. Incrementality tells you which channels actually deserve your dollars versus which ones are just good at being in the right place at the right time. You can stop feeding the attribution monsters that claim credit for organic growth (completely different investment decisions).
- Valuation Tubelight Moments: Here’s the non-intuitive magic. Branding Incrementality data proves that marketing isn’t just generating short-term revenue, but it’s building durable brand equity. It unpacks the non-intuitive relationship between branding and valuation of a company.
How do we Measure Incrementality?
We have often get asked this question and solved for clients across countries & companies in the Enterprise SaaS context. There are numerous ways to measure incrementality ranging from A/B testing, holdout experiments (where a portion of the audience is withheld from marketing), geo-lift tests (comparing similar regions with & without campaigns), marketing mix modeling (MMM) to causal inference techniques like difference-in-differences(DiD) or uplift modeling. We believe all these approaches fall into two categories:
- DoE Experimentations
- Statistical / Machine Learned Modeling
In its essence, you are controlling for all the variables for a given KPI that you want to measure incrementality for. So, the Test and Control clusters have as similar scenarios as possible. If one has time-shifting, the other one will too, if one has seasonality, the other will to, etc. That is the entire goal: If we change one, or more, stimuli will we see different outcomes. Incrementality! At the leadership/Board level, you should measure & present these four incrementalities:
- Pipeline Incrementality: Additional pipeline value generated
- Velocity Incrementality: Faster deal progression due to branding & other activities
- Logo Incrementality: New customer acquisition beyond baseline
- Company Valuation Incrementality: Branding activities causal impact on the enterprise value
Having solved this problem, both as a consultant and as an advisory, we believe this is a pragmatic, enterprise ready incrementality pillar that helps Marketing disproportionately. We understand B2B sales cycles are long, deal values vary wildly, and attribution is messy. So, you should plan for 6+ month testing cycles and account for seasonality in planning cycles.
General Principles
- Pick one business KPI per decision. e.g., Pipeline Generation, Pipeline Velocity, Closed-Won or Unaided Awareness. Then measure if marketing changes that KPI versus comparable controls.
- Establish Baseline correctly is the most critical component is capturing the truth. A wrong baseline could mean the difference between scaling a channel or killing it entirely. Rolling Average Baseline uses 2-3 years of quarterly data, Trend-Adjusted Baseline accounts for business growth and Regression-Based Baseline uses statistical modeling to account for multiple variables, for example Baseline = f(seasonality, growth trend, market conditions, competitive factors). Choose that is the most relevant for you.
- Define meaningful windows. Brand/growth often need 8–12 weeks; give revenue reads longer if the cycle is >90 days. Use a one-month lag to link brand to pipeline.
- Freeze decisions parameters. Decide in advance the time window, the minimum lift you need, and what “scale vs. stop” means (ROI/payback thresholds).
- Run where you sell. Treat real markets or account clusters as your “labs.” Create Test and Control clusters matched on size, baseline, seasonality and sales capacity etc. Turn media/activity on in some (TEST), keep others as holdouts (CONTROL) and compare movement.
- Adjust for fairness. Compare change vs. baseline in Test and subtract change vs. baseline in Control (Difference-in-Differences) to remove background noise. Use last period’s baseline to stabilize the read (CUPED/“baseline adjust”).
- Triangulate once, not endlessly. Primary reads come from field tests (test vs. control). Use a lightweight model only to reconcile long-run or non-addressable effects.
- One truth table. Put exposures (spend, markets), outcomes (pipeline, revenue, brand), and the comparison math in a single table every time.
Example 1: Pipeline Incrementality (Sales Accepted Accounts) Measurement
We had created this set up for a Cloud Vendor that operated in UK. The CMO initially claimed credit for 17 SAAs by pointing to Ireland’s vs England’s strong Q1 performance. But CFO demanded proof that marketing actually drove those results, our incrementality analysis told a different story.
Test Setup
- Primary Metric: Sales Accepted Accounts (SAA)
- Test Period: Q1 2025
- Test Group: Ireland FinServ accounts (150 total) – Marketing lead gen activities ON
- Control Group: England FinServ accounts (150 total) – Marketing lead gen activities OFF
Baseline Calculations
- Trend Adjustment (+5% YoY Growth Rate)
- Ireland 2024 Baseline: 28 SAA → 2025 Expected: 28 × 1.05 = 29.4 SAA
- UK 2024 Baseline: 27 SAA → 2025 Expected: 27 × 1.05 = 28.4 SA
- Seasonal Adjustment (+10% Q1 Bump)
- Ireland Expected (Trend + Seasonal): 29.4 × 1.10 = 32.3 SAA
- UK Expected (Trend + Seasonal): 28.4 × 1.10 = 31.2 SAA.
True Incrementality Analysis Table
| Metric | Ireland (Test) | England (Control) | Methodology |
|---|---|---|---|
| Q1 2025 Raw Results | 45 SAA | 33 SAA | Actual test results |
| Historical Q1 2024 | 28 SAA | 27 SAA | Previous year baseline |
| Trend-Adjusted Baseline | 29.4 SAA | 28.4 SAA | 2024 × 1.05 growth |
| Full Adjusted Baseline (Expected) | 32.3 SAA | 31.2 SAA | Trend × 1.10 seasonal |
| Performance Delta | +12.7 SAA | +1.8 SAA | Raw – Expected |
| Marketing Incrementality | 10.9 SAAs | Baseline | 12.7 – 1.8 (Test – Control) |
| Marketing Effectiveness | +33.7% | (10.9 ÷ 32.3) × 100 |
The control group’s (England) performance actually validates the test design and reveals the true value of incrementality measurement:
- Without Control Group: “Marketing generated 17 extra SAAs” (misleading)
- With Control Group & Factoring-in Trends + Seasonality “Marketing generated 10.9 incremental SAAs beyond favorable market conditions” (accurate)
This 10.9 SAAs (~+34%) is true incrementality. This is less than what CMO had claimed but represents the pure marketing contribution that would disappear if lead generation activities were discontinued. This analysis provided the correct metric for budget allocation and scaling decisions.
Example 2: Proving Pipeline Velocity Incrementality at $25M ARR CyberSecurity
At StealthFlow Analytics, the CFO and Head of Sales were skeptical. They claimed “Marketing can’t move deals past SQL,” they claimed. “Podcasts and free pilots? Nice-to-haves. Not needle-movers.” The CMO commissioned us for an incrementality study to settle the debate.
Setup
We isolated two cohorts over a 6-month period:
- Control Group: Standard funnel, no new marketing interventions
- Test Group: Activated three pipeline-moving marketing programs such as Expert Network Podcasts (trust acceleration), Risk Reversal Offers (free pilots, fast-track evaluations) & Cybersecurity Thought Leadership (weekly expert sessions)
- Baseline: Adjusted for seasonality & moving average
True Velocity Incrementality Analysis Table
| Funnel Stage | Control Avg Time (Days) | Test Avg Time (Days) | Acceleration (Δ Days) | Acceleration (%) | Key Driver |
|---|---|---|---|---|---|
| MQL → SQL | 21 | 12 | –9 days | –43% | Podcast Trust |
| SQL → Demo | 18 | 10 | –8 days | –44% | Risk Reversal |
| Demo → Opp. | 30 | 16 | –14 days | –47% | Free POCs |
| Opp. → Close | 60 | 42 | –18 days | –30% | Pre-qualified urgency |
Pipeline velocity incrementality of 35% from MQL to Close clearly proves that Marketing intervention compressed by the sales cycle by 49 days. Because of these activities such as fast-track pilots and expert-led podcasts, friction was removed at critical stages. The CFO’s skepticism turned into budget reallocation tied to velocity KPIs.
Solving incrementality is, literally, adding value to a business that nothing else is. But, solving incrementality is a cultural problem, not just an awareness problem. Please signup for even more awesome Incrementality success stories that we have done for players like you.