A what-if simulator for next year's eB2B revenue.

Lightweight elasticity model fitted on a synthetic FMCG eB2B dataset. Drag the four levers; the chart redraws. Diminishing returns on promo intensity are built in.

// LEVERS

Price adjustment

avg shelf-price uplift across SKUs

+3%

Promo intensity

discount frequency · diminishing returns

Activation rate

new outlets onboarded per month

+5%

Churn rate

monthly churn Δ · negative = improvement

-2pp

PROJECTED ANNUAL REVENUE

$25.5M

baseline $24.2M · +5.4%

Δ vs baseline

+$1.3M

annualized

Revenue index

105

100 = baseline

12-MONTH FORECAST · MONTHLY REVENUE$M

ScenarioBaseline (no change)

Baseline reflects MY FMCG seasonality — CNY dip (Feb), Hari Raya spike (Mar), year-end ramp (Oct–Dec).

CONTRIBUTION TO DELTA · BY LEVER

Price adjustment

+2.10%

Promo intensity

+0.00%

Activation rate

+2.50%

Churn

+0.80%

// PRESETS · CLICK TO LOAD

Typical scenario shapes from FMCG planning decks

// METHODOLOGY

How the numbers are made.

Elasticities

Fitted on a synthetic FMCG order dataset using log-linear regression per SKU group. Coefficients informed by published industry benchmarks.

Diminishing returns

Quadratic dampening on promo intensity — effect peaks near 22% and turns negative past saturation. Promo fatigue is well-documented in FMCG trade marketing.

Not a causal model

Good for triangulation, not for board-approval commitments. Always pair with qualitative read.

Confidence

Directional within ±2.5% for perturbations inside the training envelope. Extrapolation is on you.