Three Pillars of
Marketing Measurement

Each methodology answers different questions at different levels of granularity. Together, they form a complete measurement framework that gives you confidence in every marketing decision.

Lift Tests Did this work? Causal proof of incrementality
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MTA How does the journey work? Granular touchpoint attribution
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MMM Where should we invest? Strategic budget optimisation
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Unified Framework Complete measurement confidence

Prove Causation, Not Correlation

The gold standard of marketing measurement. Lift tests use controlled experiments to establish the true causal impact of your marketing activity, separating signal from noise.

How It Works

We design and execute rigorous holdout experiments where matched geographic regions or audience segments are randomly assigned to test and control groups. By comparing outcomes between groups, we isolate the true incremental effect of marketing activity.

Capabilities

Geo Experiments Region-level holdout tests using matched markets with Bayesian causal impact analysis
Audience Tests User-level randomised controlled trials across digital channels
Cross-Channel Test incrementality across search, social, display, TV, and offline channels
Calibration Use lift results to calibrate and validate your MMM and MTA models

Example Result

Control
Baseline
Test
+23% Lift

Statistically significant incremental lift identified with 95% confidence interval

Map Every Touchpoint in the Journey

Granular, user-level attribution that goes beyond last-click. Understand how every channel and touchpoint contributes to conversion, across devices and over time.

How It Works

Using algorithmic attribution models, we analyse individual customer journeys to assign fractional credit to each marketing touchpoint. This reveals which channels assist, which convert, and how the customer journey unfolds across devices and sessions.

Capabilities

Algorithmic Models Data-driven attribution models that learn credit allocation from your conversion data
Cross-Device Stitch customer journeys across mobile, desktop, and tablet touchpoints
Real-Time Signals Near real-time performance insights for rapid campaign optimisation
Privacy-First Built for a cookieless future with privacy-compliant data frameworks

Journey Attribution

Paid Social 18%
Organic Search 12%
Display 22%
Email 15%
Paid Search 33%

Fractional credit assigned across the full customer journey

Optimise the Full Marketing Portfolio

Bayesian econometric models that quantify the impact of every marketing channel on business outcomes, while accounting for seasonality, competitor activity, and macroeconomic factors.

How It Works

We build custom Bayesian regression models that decompose your KPIs into the contributions of each marketing channel, along with external factors. The models produce ROI estimates, saturation curves, and adstock effects that power budget optimisation and scenario planning.

Capabilities

Bayesian Models Full posterior distributions for every parameter, giving you uncertainty estimates, not just point predictions
Scenario Planning Simulate budget reallocation scenarios and forecast outcomes before committing spend
Brand & Performance Separate short-term performance effects from long-term brand building impact
Saturation & Adstock Model diminishing returns and carryover effects for each channel

Channel Contribution

TV
3.2x
Paid Search
4.1x
Social
2.8x
Display
1.9x
OOH
1.4x

Revenue contribution and ROAS by channel from Bayesian MMM

Ready to Build Your Measurement Framework?

Let's discuss which combination of Lift Tests, MTA, and MMM is right for your organisation.