This quiz challenges you on spend allocation algorithms, constraints, and scenario planning techniques.
Budget optimisation simulations use response curves to allocate spend until marginal ROI equals ______.
maximum CPM
share of voice
target threshold
cookie cap
Gradient‑free optimisers like Nelder‑Mead are preferred when response curves are ______.
linear
perfect
quadratic
non‑differentiable
2025 Google LightweightMMM added a simplex‑based optimiser constrained by ______ floors.
creative IDs
tracker length
pixel ratio
channel minimum spends
Scenario planning runs multiple optimisations varying total budget to produce an ______ curve.
efficient frontier
keyword
bounce rate
cookie usage
Optimisers often enforce a diversification rule, limiting any one channel to ______ % of total spend.
1
50
100
5
A what‑if on price reduction can be paired with budget optimisation because MMM includes price as a ______ variable.
baseline control
tag
target
cookie
Monte Carlo budget simulations incorporate channel ROI uncertainty by sampling from ______ distributions.
posterior
cookie
uniform cost
fixed
Spend granularity (e.g., $10k steps) controls the optimiser’s ______ space.
pixel
creative
search
cookie
2025 MMM tools export optimisation results via ______ API endpoint.
/device
/media
/crm
/v1/optimisations
Log‑transformed spend is back‑converted to linear dollars after optimisation to ensure ______ feasibility.
cookie
pixel
real‑world
color
Starter
Review the basics.
Solid
Nice work—refine the details.
Expert!
Exceptional command of the topic.
Going through Budget Optimization Simulations Interview Questions can help you predict which spend shifts will drive the most impact. Kick things off with our Attribution & Marketing-Mix Modelling interview questions to see how simulation scenarios plug into your mix analysis. Then sharpen your segmentation skills with the channel grouping logic practice MCQs and explore key demand levers through the baseline sales drivers interview guide. Finally, round out your prep by tackling the granular versus aggregate data interview resources to master modeling at every level.
