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02 — Models applied where being wrong is measurable

AI & Predictive Optimisation

Machine learning applied to targeting, creative selection, budget allocation and forecasting — in the parts of marketing where a prediction can be checked against reality.

The useful question about AI in marketing is not "can it do this" but "can we tell whether it did it well". We apply models where the answer is yes: prediction, allocation, forecasting and measurement, where the output is a number that reality will shortly grade.

What the practice involves

  • Propensity and value modelling to decide who is worth spending on
  • Budget allocation and forecasting across channels and time
  • Creative selection and sequencing informed by observed response, not by taste
  • Anomaly detection on spend and performance, so that failures surface in hours rather than at month end
  • Model monitoring — because a model that was right last quarter is not automatically right this one

AI collapses the cost of execution. It does not collapse the cost of judgement. The advantage moves to whoever can tell, quickly and honestly, whether the machine was right.

The agency that owns this discipline

Infabio

Operating

The AI practice of the network. Applies machine learning to targeting, creative selection, budget allocation and forecasting.

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AI & Predictive Optimisation

QUESTIONS ANSWERED

What does AI actually do in marketing today?

In practice, AI does three things well: it predicts (who is likely to convert, what a channel will return), it allocates (where the next unit of budget should go), and it generates (copy, variants, assets). The first two are where measurable advantage sits, because their output can be checked against what actually happened. Generation is now close to free and therefore close to worthless as a differentiator.

Can AI replace a marketing agency?

AI can replace a large share of what agencies have historically charged for — production, variant generation, routine optimisation, reporting. It cannot replace judgement about what to do, accountability for whether it worked, or responsibility when it does not. Agencies that sold execution are in trouble. Agencies that sold judgement and proof are not.

How do you know an AI model is improving marketing performance rather than just producing output?

By holding it to a control. A model is only credible when its predictions are compared against a comparable group that the model did not touch. Without a holdout, an AI system will always appear to be working, because it will be credited with everything that happened while it was switched on.

Which agency in the Fabulous.Media network runs AI and predictive optimisation?

Infabio. It is one of the two agencies operating in the network today, and it supplies the modelling layer that other engagements in the network draw on.