Marketing Science

Response Curve Explorer

Visualize how marketing efficiency changes across spending levels — from threshold to saturation. Understand where each dollar stops working.

Response Function

R(x) = L / (1 + e−k(x−m))

Sigmoid model — L = max response, k = steepness, m = midpoint

Marketing spend$45K
$0K$100K
Current zoneOptimal

Peak efficiency. Returns are still strong but beginning to flatten. This is the target range for most channels.

Response40.1%
Total ROI89.2%
Marginal efficiency1.924

Efficiency Zones

Threshold
0–15K
Growth
15–35K
Optimal
35–60K
Diminishing
60–85K
Saturation
85–100K

Response Curve

Response (%)
ThresholdGrowthOptimalDiminishingSaturation
$0K$25K$50K$75K$100K
100%75%50%25%0%

$45K

Spend

40.1%

Response

1.924

Marginal ROI

Optimal

Zone

Interpretation

The response curve maps marketing execution to incremental impact. The shape is driven by two dynamics: frequency thresholds at the low end (minimum exposure before a consumer responds) and audience exhaustion at the high end (the addressable market is finite).

The optimal zone is not where total response is highest — it is where marginal efficiency is still strong enough to justify the spend. Beyond that point, the same budget produces more impact when reallocated to a channel still in its growth phase.

Scope

This explorer uses a fixed sigmoid function to illustrate zone dynamics. In a production MMM, the response curve shape is estimated per channel using Hill functions or similar transformations, with parameters inferred through Bayesian estimation. The zone boundaries shown here are illustrative — actual thresholds depend on channel, market, and creative quality.