Media mix: assigning a role and a horizon to every spend.

SUPPORTED DECISIONAllocate media according to their incremental contribution to the expected role and to the decision horizon, then explicitly set aside a share of the result for the measured interactions.

Key distinctions

Three conditions before calculating.

01

Role before channel

The same channel can create demand in one campaign and capture it in another. The role depends on targeting, message, format, sequence and audience, not on the platform's name.

02

Differentiated windows

Direct measurement, persistence and brand effect must be observed over windows consistent with their mechanism. A short window does not refute a long effect; it simply does not allow it to be measured.

03

Interaction without double credit

When two media together produce an effect greater than the sum of their separate effects, the interaction must be isolated. Re-crediting it in full to both channels inflates the portfolio and distorts the allocation.

Method

Moving from a channel ranking to a portfolio of roles

  1. 01Formulate the mechanisms

    For each activity, state the audience, the intermediate behaviour, the expected time lag and the outcome metric; an activity without an explicit mechanism remains a spend to diagnose.

  2. 02Choose the evidence

    Match individual experiments, geo tests, MMM, surveys or journey data to the role and to the available granularity, and keep incompatible estimands separate.

  3. 03Build the scenarios

    Project direct, assisted and persistent effects without adding them twice, and apply margin, media cost and an uncertainty range to each allocation scenario.

  4. 04Revise by marginal increment

    Compare the next budget increment, not the historical average return, and reserve a learning budget for the roles whose uncertainty prevents a robust decision.

ORIGINAL ASSET

The role × horizon × evidence matrix

The media mix is shown as a time chain: creation, capture, conversion and retention, with the evidence suited to each role.

RoleActivityHorizonEvidenceSales
CreationVideo
Geo test / MMM600
CaptureSearch
Experiment / MMM900
ConversionCRM
Journey test250
InteractionVideo × search
Factorial design350
CAPTURE PLAN€4,150
→
ROLE PLAN€35,500
CSVDownload the media-role model↓
ILLUSTRATIVE EXAMPLE · SIMULATED DATA

A balanced portfolio creates €31,350 of additional contribution

01 · SITUATION

Two plans spend €80,000. The capture plan allocates €60,000 to search, €10,000 to video and €10,000 to CRM. The role plan allocates €30,000, €40,000 and €10,000 respectively. The margin per incremental sale is €55.

02 · CALCULATION

Capture plan: 1,100 search sales + 150 video + 50 assisted + 230 CRM = 1,530 sales; net contribution 1,530 × 55 − 80,000 = €4,150. Role plan: 900 + 600 + 350 + 250 = 2,100 sales; net contribution €35,500.

03 · DECISION

The role plan is adopted if the 350 assisted sales are confirmed by a causal design. Without that evidence, they become a sensitivity assumption and not a certain credit.

Acceptance conditions

What must be true to act.

  1. 01

    Each activity has a role, an audience, a time lag and expected evidence.

  2. 02

    Direct, persistent and interactive effects are not counted twice.

  3. 03

    The scenarios apply the same margin and the same economic horizon.

  4. 04

    The allocation is revised on marginal returns and on uncertainty.

Limits

What this analysis does not prove.

  • Roles change with targeting, creative and spend level.
  • Brand effects are hard to convert immediately into contribution.
  • An interaction observed in one sequence is not automatically transportable to another.

References

Works cited.

  1. Naik, P. A. & Raman, K. (2003), “Understanding the Impact of Synergy in Multimedia Communications”, Journal of Marketing Research, 40(4), 375–388.
  2. Stephen, A. T. & Galak, J. (2012), “The Effects of Traditional and Social Earned Media on Sales”, Journal of Marketing Research, 49(5), 624–639.
  3. Lewis, R. A. & Rao, J. M. (2015), “The Unfavorable Economics of Measuring the Returns to Advertising”, Quarterly Journal of Economics, 130(4), 1941–1973.