Marketing Effectiveness · Decision ArchitectureMMM Advisory

    When the data is right, but the decision still feels wrong.

    Sometimes the numbers look right, but something still doesn't add up. That's usually where the interesting work begins.

    Most of our conversations start with something like this.

    Sound familiar?

    If any of these have come up in a recent meeting, the next conversation is probably worth having.

    We've got 10% less budget but we're still expected to deliver 3% year-on-year growth.

    Everyone keeps telling us TV is dead. Is it?

    We've cut TV. Why didn't digital make up the difference?

    Sales are flat, but every channel is reporting success.

    Our models are all telling us different things. Which one do we trust?

    We've optimised every channel. Why haven't we improved overall performance?

    TV or search?Do we still need outdoor?Programmatic or direct?CTV or social?Brand or performance?National or geo-targeted?More frequency or more reach?In-house or agency?TV or search?Do we still need outdoor?Programmatic or direct?CTV or social?Brand or performance?National or geo-targeted?More frequency or more reach?In-house or agency?

    Where we begin

    So where do we start?

    We start with where you are, what you're unsure of, and what you already have. We look at where the evidence agrees, where it conflicts, and work from there.

    Only then do we decide what comes next.

    Start with the question

    Common questions

    Not every marketing question needs a model or a major measurement project. Sometimes you just need a clear, evidence-based answer.

    • How long should our campaign run?
    • What's the right media mix?
    • How do we know who we're actually reaching?
    • Are we spending enough to make a difference?
    • Should we be on TV?
    • Are we spreading our budget too thinly?
    • How much should we spend on brand versus performance?

    Measurement

    Marketing Effectiveness

    Aligning measurement with commercial reality, so budget decisions reflect contribution — not just visibility.

    • Demand creation vs demand capture
    • Where efficiency is masking stagnation
    • Reconciling MMM, platforms and analytics
    • Fragmented reporting → clear direction
    The Methodology

    Modelling

    MMM Advisory

    Making MMM outputs usable in planning, budgeting and real investment decisions.

    • Where models reflect past allocation, not future potential
    • Weak channel or under-scaled channel
    • Interpreting disagreement across models
    • Model outputs → planning decisions
    The Advisory

    Work with me

    Bring me the question.

    You don't need to know what kind of analysis you need. Start with what you're seeing, what you're unsure about, or what you need to work out.