Most UK businesses are making million-pound budget decisions on broken data. We build post-cookie measurement frameworks — marketing mix modelling, incrementality testing and first-party attribution — that show you what is genuinely working and what is merely claiming credit.
The measurement infrastructure that UK marketers relied on for a decade has fractured. Third-party cookies are gone, consent rates have dropped, GA4 migrated badly for most organisations, and last-click attribution was never accurate to begin with. The result is that most businesses are optimising toward noise, not signal.
Safari has blocked third-party cookies since 2017. Firefox followed. Whilst Chrome announced its deprecation was delayed, the cookieless era is already here for the majority of UK internet users. Any measurement approach that depends on cross-site cookies is already missing data from roughly 35–40% of your audience.
Last-click attribution assigns 100% of credit to the final touchpoint before conversion. It systematically undervalues brand campaigns, upper-funnel social, and display. It overvalues branded search and retargeting, because those channels intercept the intent that other channels created. Optimising to last-click moves budget away from the channels that actually generate demand.
Most UK businesses migrated to GA4 under time pressure and without a proper measurement plan. Session-based GA4 data does not match Universal Analytics benchmarks. Conversion events are misconfigured, cross-device journeys are broken, and Consent Mode v2 gaps mean data is modelled rather than observed for a growing proportion of UK users who decline cookies.
When your attribution is broken, your budget reallocation decisions are based on which channels are best at claiming credit — not which channels are best at driving revenue. Our clients routinely discover that 25–35% of their paid media budget is allocated to channels or campaigns whose reported ROAS is significantly higher than their true incremental contribution.
A full measurement stack built for the post-cookie era — from GA4 configuration to statistical mix modelling to incrementality experiments.
Most GA4 installations are broken. We audit your configuration and rebuild it around a data-driven attribution model with properly structured conversion events and cross-channel tracking.
Statistical models that quantify each channel’s contribution to revenue using aggregate spend and outcome data. No cookies required. Works across all media types including offline, TV, and out-of-home.
Holdout experiments that measure the true causal impact of your campaigns. The only way to know whether your paid media is genuinely driving conversions — or merely intercepting intent that would have converted anyway.
Build measurement infrastructure that does not depend on third-party cookies. Server-side tracking, Consent Mode v2 compliance, and Enhanced Conversions keep your data flowing regardless of browser restrictions.
Measurement is only useful if decision-makers can act on it. We build connected Looker Studio dashboards and GA4 Explorations that surface the right metrics for your commercial teams.
Where user-level data is available and consented, we build multi-touch attribution models that distribute credit more fairly across the customer journey than platform-native attribution.
Each measurement approach has different strengths. Understanding which method to use — and when to combine them — is the foundation of a mature measurement strategy.
| Criterion | Last-Click Attribution | Multi-Touch Attribution (MTA) | Marketing Mix Modelling (MMM) |
|---|---|---|---|
| Requires cookies / tracking? | Yes — user-level | Yes — user-level | No — aggregate data only |
| Measures offline & TV? | No | Rarely | Yes |
| Accounts for seasonality? | No | Partially | Yes — built into model |
| Privacy / UK GDPR compliant? | Partial | Requires consent | Fully compliant |
| Measures true incrementality? | No | No | Yes |
| Speed of insights | Real-time | Near real-time | Weeks (model build) |
| Budget optimisation guidance | Misleading | Partial | Full ROI curves + scenarios |
| Data volume required | Low | Medium | 18–24 months historical |
MMM uses regression-based statistical modelling — increasingly built on Bayesian frameworks — to decompose your revenue into its constituent drivers: each marketing channel, baseline business factors, and external variables. The result is a credible, cookieless view of what each pound of media investment is actually contributing.
We ingest weekly spend data across all channels alongside revenue, conversion volume, and external variables including seasonality indices, Google Trends data, competitor activity proxies, and macroeconomic factors.
Using Google Meridian or Recast, we build a Bayesian MMM that accounts for adstock (the lagged effect of advertising) and saturation (diminishing returns as spend increases). The model is calibrated against prior beliefs about channel effectiveness.
The model outputs a revenue decomposition showing the true contribution of each channel, plus marginal ROI curves that reveal where each channel hits saturation — the point at which additional spend starts delivering rapidly diminishing returns.
We run optimisation algorithms across the ROI curves to identify the budget allocation that maximises revenue at your current total spend level — and model scenarios for increased or decreased total investment.
We are tool-agnostic but opinionated. These are the platforms and frameworks we have found to deliver the most reliable measurement results for UK businesses.
Google’s open-source Bayesian MMM framework. Transparent, auditable, and calibratable with your own priors. Our preferred foundation for UK MMM projects.
Purpose-built incrementality testing platform. Enables geo-split holdout tests at scale, with rigorous statistical inference and clean causal estimates.
Fully Bayesian MMM platform with a strong UK and EU client base. Excellent for businesses with shorter data histories or complex multi-brand structures.
Meta’s in-platform incrementality testing tool. Measures the true sales lift driven by Facebook and Instagram campaigns through randomised holdout experiments.
Google’s holdout experiment tool for measuring the incremental impact of YouTube and Display campaigns beyond what last-click or data-driven attribution reports.
Google Analytics 4 properly configured with data-driven attribution, custom events, and BigQuery export for unsampled analysis and custom modelling.
Connected reporting dashboards that pull from GA4, BigQuery, Google Ads, Meta Ads, and your CRM to give leadership a single view of marketing performance.
Server-side Google Tag Manager to improve data quality, reduce client-side tag bloat, and keep conversion signals flowing in a consent-first environment.
Full implementation of Google’s Consent Mode v2 to comply with UK GDPR and ICO guidance whilst preserving maximum measurement signal through behavioural modelling.
Google Enhanced Conversions and Meta CAPI to share consented first-party signals directly with ad platforms, improving bidding accuracy in a cookieless environment.
Custom attribution models and propensity scoring built directly in BigQuery ML, using your own first-party data without reliance on platform-provided attribution.
Bespoke statistical modelling in Python and R for clients requiring fully custom MMM builds, time-series analysis, or causal inference methodologies.
From your first data audit to a live budget reallocation plan — a structured, four-step process that delivers tangible commercial insight within 10 weeks.
We audit your existing measurement setup — GA4 configuration, ad platform tracking, CRM data, and offline data sources — to identify gaps and establish data quality before model build. Delivered in weeks one and two.
We ingest and clean your data, build and iterate on the statistical model, and run validation checks to ensure the model’s outputs are credible and consistent with known business events. Weeks three through seven.
We deliver a structured findings workshop with your marketing leadership — covering channel decomposition, ROI curves, saturation points, and a clear interpretation of what the model is telling you about your media mix. Weeks eight and nine.
We work with your media teams to translate model outputs into a revised budget allocation plan, run scenario models for different spend levels, and establish an ongoing measurement cadence. Week ten and beyond.
No retainer lock-ins for project work. Clear deliverables at each stage. Most clients start with the data audit to understand what is possible before committing to a full model build.
Answers to the questions UK marketing teams ask most often when they start exploring advanced measurement.
Start with a measurement audit. We’ll tell you exactly what’s broken in your current setup and what it would take to fix it — no obligation.
Get a Free Measurement Audit →Audit delivered within 5 working days • No lock-in contracts • UK-based team