Top 10 Incrementality Testing Tools & Companies in 2026

Incrementality testing tools help marketers estimate the true incremental impact of advertising when attribution models and platform-reported metrics cannot be used to measure paid media performance.

This guide compares the best incrementality testing vendors in 2026, explains how incrementality testing platforms work in real marketing environment, and helps you choose the right solution based on your company size, spend, and measurement maturity.

Incrementality Testing in Marketing: What Is It and When to Use It

Incrementality testing in marketing is a way to measure whether advertising actually drives additional outcomes — such as conversions or revenue — that would not have happened without the ads.

Instead of distributing credit across touchpoints (as attribution models do), incrementality testing compares a test group exposed to marketing with a control group that is not, and measures the difference in results.

👉 The most common approaches include geo holdout and geo lift experiments.

Incrementality testing is best used when:

• Media spend is large enough to produce a detectable effect
• Attribution cannot reliably measure a channel
• Results will influence major budget or strategy decisions

Typical real-world scenarios include:

• Testing brand search cannibalization
• Validating upper-funnel media (CTV, YouTube, paid social)
• Measuring offline or retail-driven campaigns

Incrementality measurement platforms tools are not a replacement for attribution or MMM software. In modern marketing analytics stacks, geo-lift experimentation is a causality measurement approach used alongside other methods to solve for different use cases.

Best Incrementality Testing Vendors in 2026 (Quick Comparison)

Rank	Company
#1 ⭐ ⭐ ⭐	SegmentStream
#2 ⭐ ⭐	Measured
#3 ⭐ ⭐	Haus
#4 ⭐	LifeSight
#5 ⭐	WorkMagic
#6	Rockerbox
#7	Recast
#8	LiftLab
#9	INCRMNTAL
#10	Funnel.io

1. SegmentStream Incrementality Testing Platform — Best Overall Choice ⭐ ⭐ ⭐

Highest-ranked solution for running Geo Lift Experiments and Lift Studies

SegmentStream Incrementality Testing Solution

Best for: Marketing teams that want to run precise, expert-led incrementality tests to make confident budget decisions. Suitable for advertisers investing over $100K USD per month in cross-channel ad spend.

Clients: Leading B2C Enterprises and fast-growing DTC brands

G2 Review Rating: 4.7/5

G2 Customer Quotes: “A highly effective tool which helps make informed budget allocations to optimise performance and ROI”

Key Capabilities

• Geo holdout and geo lift experiments
• Synthetic control modeling
• Minimum Detectable Effect (MDE) and power analysis
• Confidence intervals evaluation
• Clear translation from lift to revenue and profit impact

Unlike many software platforms, SegmentStream also provides an full-service with senior expert support to help CMOs and marketing leaders design, run, and evaluate geo-holdout experiments end-to-end.

Strengths

• Strong guardrails around experiment validity
• High transparency into methodology
• Suitable for ongoing experimentation programs

SegmentStream Incrementality Testing Product Demo

Limitations

• Requires experimentation discipline
• Not suitable for low-spend advertisers

2. Measured ⭐ ⭐

Best for: Large advertisers with MMM as a core planning tool

Measured combines incrementality testing with large-scale MMM, making it popular among global brands.

Strengths

• Handles complex, multi-market environments
• Mature synthetic control capabilities
• Deep experience with CPG advertisers

Limitations

• Heavy implementation effort
• Slower iteration cycles
• Incrementality results often require expert interpretation
• Users report high costs

3. Haus ⭐ ⭐

Best for: Paid media teams running frequent geo lift tests

Haus focuses on simplifying geo experiments for faster execution.

Strengths

• Simple setup and execution
• Clear regional reporting
• Fast time to directional insights

Limitations

• Narrow scope beyond geo lift
• Limited experimental flexibility
• Less suitable for noisy markets

4. LifeSight ⭐

Best for: Brands seeking MMM, attribution, and incrementality in one system

LifeSight positions incrementality testing as part of a broader measurement stack.

Strengths

• Covers MMM, attribution, and experimentation
• Enterprise infrastructure
• Geo experimentation support

Limitations

• Incrementality is not the primary focus
• Less flexibility for experimentation-heavy teams

5. WorkMagic ⭐

Best for: Smaller brands prioritizing speed and automation.

WorkMagic emphasizes reducing operational friction through automated workflows.

Strengths

• Faster setup compared to traditional tools
• Cross-channel experimentation support

Limitations

• Limited transparency into methods
• Fewer controls for advanced users

6. Rockerbox

Best for: Teams with strong attribution foundations exploring incrementality

Strengths

• Multiple measurement methodologies in one platform
• Deep ad platform integrations

Limitations

• Incrementality is not a core capability
• Limited native experiment design

7. Recast

Best for: Organizations focused on long-term planning and forecasting

Strengths

• Good choice for technical data teams
• Strong modeling

Limitations

• Heavy MMM focus, incrementality is a side product
• Incrementality insights are indirect
• Too technical for CMOs and media buying teams

8. LiftLab

Best for: Teams running traditional holdout experiments across channels

LiftLab specializes in holdout-based experimentation, including geo and audience-level tests.

Strengths

• Experience with randomized and quasi-randomized holdouts
• Cross-channel testing support

Limitations

• Requires strong internal experimentation expertise
• Niche vendor

9. INCRMNTAL

Best for: Brands focused on geo-based brand lift and incrementality

Pros

• Strong presence in mobile gaming
• European presence

Cons

• Promised always-on approach is more similar to MMM than true incrementality testing
• Limited e-commerce expertise
• AI capabilities are not transparent

10. Funnel.io

Best for: Teams that need clean, centralized data before testing incrementality

Funnel.io claims to have incrementality testing tool, but users’ reports are limited.

Pros

• Good for data ingestion and normalization
• Enables experimentation by fixing data foundations

Cons

• Little information available
• Less popular compared to other specialized vendors

How to Choose the Right Incrementality Testing Tool

Before selecting a platform, ask:

• Can we realistically run this experiment and detect lift at our spend level?
• What decision will this test change?
• Is the opportunity cost justified?

We advise scheduling a meeting with top vendors to discuss your business case, and validate team’s expertise before committing to a full contract.

Incrementality Measurement vs Attribution vs MMM

These approaches solve different problems:

• Attribution: Continuous, directional performance monitoring
• Incrementality testing: Episodic, decision-driven validation
• MMM: Strategic, system-wide planning

Mature organizations use all three — selectively.

Common Incrementality Testing Pitfalls

• Running tests below detectable scale
• Ignoring confidence intervals
• Allowing ad platforms to rebalance budgets
• Confusing lift with profit
• Over-testing low-impact channels

Most failures are caused by poor test design, not tooling.

Incrementality Testing FAQs

• Is incrementality testing better than attribution?

  No — it answers a different question and should complement attribution.

• How long does an incrementality test take?

  Typically 4–8 weeks, depending on scale and variance.

• Is MMM the same as incrementality testing?

  No — MMM focuses on observing correlations in statistical data, while incrementality testing is experimental.

• Can small companies run incrementality tests?

  In most cases, no — effects are often below detectable thresholds.

Final Thoughts

When using correctly, incrementality testing tools can deliver valuable insights about the true impact of your ad activities ad efficency. In 2026, the most successful teams are not running more tests, but running fewer tests that materially change decisions.

Choosing the right tool starts with understanding whether incrementality testing is appropriate for your business at all.