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AI / ML
Scenario Testing
Running thousands of hypothetical budget allocations, channel mixes, or creative strategies through ML models to predict outcomes before committing real spend. 'What happens if I shift $20K from Google Search to Meta prospecting?' generates a probability distribution of outcomes in seconds. Reduces risk by testing decisions mathematically against historical patterns, diminishing returns curves, and competitive dynamics.
Why it matters
It puts a number on a decision before the money is spent, which turns a reallocation argument into a comparison.
In practice
Model the downside with the same care as the upside, and treat the range as the output rather than the midpoint.
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