Trust it · independent review

Marketing effectiveness audit

A structured review of how your organisation turns marketing investment into evidence-based decisions, people, data, technology, process, and whether results actually change spend.

Models don't fail in isolation, systems do

A strong MMM sitting on weak data, unclear ownership, or a culture that ignores inconvenient results won't improve decisions. Likewise, great people with fragmented tools and no operating rhythm burn out before they create impact.

This audit looks at the full effectiveness system, not just the maths, so you know where capability is solid, where it's fragile, and what to fix first.

Insights that don't change budgets Reports land, slides get shared, then spend decisions revert to last year's plan or platform ROAS.
Measurement owned by a single hero Capability lives with one person or vendor. When they leave, or the contract ends, the system stalls.
Tools without an operating model Dashboards, MMM, MTA, and experiments exist in parallel, with no clear hierarchy of evidence or decision rights.
Data that can't answer the next question Spend, sales, and media are patched together each cycle. New channels, markets, or SKUs break the pipeline.

Five pillars of marketing effectiveness

We assess each pillar independently, then look at how they connect. Strengths in one area rarely compensate for gaps in another.

01

People & culture

Skills, incentives, and the willingness to act on evidence, even when it's uncomfortable.

02

Data

Coverage, quality, governance, and whether inputs can support the questions leadership asks.

03

Technology

Tools, platforms, and model stack, fit for purpose, maintainable, and free of lock-in traps.

04

Process

How measurement is planned, run, quality-checked, and tied into planning and investment cycles.

05

Results utilisation

Whether outputs change decisions, budgets, and creative, with clear ownership of follow-through.

Pillar 01

People & culture

Effectiveness is a human system before it is a technical one. We look at who owns measurement, how teams collaborate, and whether the organisation rewards learning or theatre.

Capability & coverage

Do you have the right mix of analytical, commercial, and media skills, in-house or partnered, for the ambition you've set?

Ownership & succession

Is measurement dependent on a single individual or vendor relationship, or is knowledge shared and documented?

Incentives & mindsets

Are teams rewarded for defending channel budgets, or for improving the evidence base and reallocating honestly?

Stakeholder trust

Do finance, brand, and performance treat measurement as a shared language, or as a battleground for competing narratives?

Pillar 02

Data

Every model and dashboard is only as good as what feeds it. We assess whether your data estate can support the decisions you want to make, now and next year.

Coverage & completeness

Media, sales, pricing, promotions, distribution, brand, and external factors, what's measured, what's missing, what's guessed.

Quality & lineage

Definitions, transformations, and join logic. Can you trace a KPI from source to slide without tribal knowledge?

Governance & access

Who can change definitions? How are privacy, consent, and commercial sensitivity handled across partners?

Readiness for modelling

Granularity, history, and consistency needed for MMM, experiments, and forecasting, without heroic cleaning each cycle.

Pillar 03

Technology

Tools should serve the operating model, not the other way around. We review your stack for fitness, maintainability, and the risk of black-box dependency.

Measurement stack fit

MMM, attribution, experimentation, dashboards, and planning tools, do they cover the full evidence hierarchy?

Transparency & control

Can your team inspect, challenge, and reproduce outputs, or are you renting a black box with a slide deck?

Integration & workflow

How data moves from source systems into models and back into planning tools without spreadsheet glue.

Build vs buy clarity

Where in-housing makes sense, where partners add leverage, and where tool sprawl is creating cost without insight.

Pillar 04

Process

Good measurement needs a rhythm: planning, delivery, quality control, and a clear path into investment decisions. We map how work actually gets done.

Annual & quarterly cadence

How measurement informs annual planning, in-year reallocation, and post-campaign learning, not just end-of-year reviews.

Quality gates

What checks exist before results are shared? Who signs off methodology changes, new channels, or model refreshes?

Experimentation design

How lift tests and geo experiments are prioritised, designed, and used to calibrate broader models.

Vendor & agency governance

Briefs, acceptance criteria, and challenge processes so external work meets the same standard as internal work.

Pillar 05

Results utilisation

The value of measurement is realised only when it changes something. We examine whether insights reach the right people, in time, with decision rights attached.

Decision rights

Who can move budget based on evidence? Are recommendations owned, deferred, or quietly ignored?

Communication & storytelling

Are outputs framed for the audience, board, brand, performance, without losing the integrity of the finding?

Closed-loop learning

Do you track whether recommended changes were made, and whether outcomes matched the forecast?

Conflict with vanity metrics

Where platform ROAS, last-click, or brand KPIs override incrementality, and how the organisation resolves that tension.

A four-to-six week engagement

We combine stakeholder interviews, artefact review, and structured scoring, then leave you with a prioritised roadmap, not a 200-page shelfware report.

1

Scope & stakeholder map

Agree which markets, brands, and teams are in scope. Identify the people and artefacts we need access to.

Week 1
2

Discovery

Interviews across marketing, analytics, finance, and agencies. Review of data pipelines, models, tools, and recent decision cycles.

Weeks 2-3
3

Pillar scoring & diagnosis

Each pillar is scored with evidence. We map dependencies, for example, where a technology gap is really a process or culture problem.

Week 4
4

Roadmap & debrief

Leadership presentation with traffic-light scorecard, quick wins, and a sequenced capability roadmap. Optional deep-dive for technical teams.

Weeks 5-6

What you walk away with

Five-pillar scorecard

At-a-glance strengths and gaps across people, data, technology, process, and results utilisation.

Evidence pack

Documented findings with examples from interviews, artefacts, and decision cycles, not generic maturity slogans.

Prioritised roadmap

Sequenced actions by impact and effort, spanning quick process fixes through to longer capability builds.

Leadership debrief

A clear session for marketing and finance leaders, what matters, why, and who needs to own the next step.

When to commission this audit

Building or resetting in-house capability

You're investing in people and tools and want a clear baseline before you hire, buy, or reorganise.

Measurement isn't changing decisions

You have models and reports, but budgets and creative still move on instinct or last-click metrics.

New leadership or strategy

A new CMO, CFO, or growth agenda needs an honest read on what the effectiveness system can and cannot support.

Vendor or agency transition

Before you renew, switch, or in-house, understand what capability actually exists beyond the current partner.

Post-MMM reality check

You've invested in modelling and now need the surrounding people, process, and utilisation to catch up.

Board or finance scrutiny

You need a structured answer to "can we trust how marketing effectiveness is run here?"

Effectiveness specialists, not generic consultants

Led by practitioners who have built and judged marketing effectiveness programmes, including IPA Effectiveness Awards technical judges, in partnership with Inference Works and Nous Analytics.

Joe Wilkinson Tyedal, analytics, in-housing, IPA technical judge (2026)
Nadya Ochirova Nous Analytics, marketing effectiveness leadership, IPA technical judge (2024)
Dr Ben Vincent Inference Works, Bayesian methods, causal inference, modelling stack review

Get a clear read on your effectiveness system

Book a scoping call to discuss markets, stakeholders, and timeline, or send a message and we'll respond within one working day.