Case Studies

How FMCG leaders win with TheProfit.AI

Five high-stakes growth plays simulated, optimized, and executed with measurable ROI—from seasonal promotions to multi-city expansion.

Case Study 01

Ramadan Promotional Optimization – Edible Oil Category

A national FMCG distributor needed to scale Ramadan demand without destroying margins.

Baseline Budget

$500K

Promo Window

30 days

Client Challenge

Historical discounting drove volume but eroded Ramadan margins. The team needed a simulator that balanced promo intensity, cross-category lifts, and customer acquisition targets with guardrails on profitability.

Simulation Parameters

• 15% discount on premium SKUs
• Cross-elasticity for rice, flour, spices
• Budget cap $580K (projected)
• KPI: volume uplift + net margin + acquisition

Direct Impact

• Budget requirement +16% ($580K)
• 47% volume uplift, +8.2pp market share
• 12,400 new households acquired
• Basket size +$18.50, net margin 11.3%

Causal Intelligence via Simulator

• 23% lift in complementary cooking essentials
• Repeat-rate probability +34% post-Ramadan
• Cross-category lift drove $18.5 average basket gain
• Team concluded via the simulator to dial promo down to 12% while keeping cross-category bundles live

Optimization Insight

A 12% discount delivered 89% of the volume impact at $545K total budget, improving net margin to 12.8% while sustaining strategic acquisition goals.

Business Outcome

• 42% volume growth with controlled spend
• +4.7% overall category profitability
• 67% retention of newly acquired shoppers
• Ramadan playbook templated for 2025-26

Case Study 02

Multi-Category Portfolio Balancing – Frozen Products Counter-Strategy

After Ramadan, the distributor needed to rebuild margins without shaking market share.

Post-Promo Budget

$580K

Elastic Focus

Frozen category

Client Challenge

Margin pressure from aggressive oil promotions required a counter-play. The team needed guidance on where price increases would stick versus where loyalty risked eroding.

Simulation Parameters

• 8-12% price tests across frozen SKUs
• Elasticity: veg -0.68, seafood -1.12, RTE -0.89
• KPI: margin recovery + market share protection

Optimized Pricing

• Frozen vegetables: +11% (inelastic)
• Frozen seafood: +5% (managed for elasticity)
• Ready-to-eat: +8% (balanced)

Financial Impact

• Budget tightened to $480K (-17.2%)
• Margin recovery +6.8 percentage points
• Net profit +$67K vs. status quo

Causal Intelligence via Simulator

Scenario runs showed only 18% overlap with Ramadan buyers and 72% loyalty, so the team used those simulator insights to green-light their selective price increase plan without fearing churn.

Business Outcome

• Portfolio profitability rebalanced
• Market share held at 23.7%
• Budget tracked to $485K actuals (±1%)
• Quarterly EBITDA +12.4%

Case Study 03

Seasonal Beverage Portfolio Optimization – Summer Peak Planning

Overstock waste and premium stockouts plagued a 4-month summer window.

Budget Range

$695K–$820K

Portfolio

127 SKUs

Client Challenge

Hot summers created unpredictable demand swings. Overstocking drove 18% expiry waste, while premium shortages left revenue on the table.

Simulation Parameters

• AI demand forecasts w/ weather overlays
• Dynamic pricing + stocking by week
• Categories: CSD, juices, energy, water

Demand Signals

• +34% demand per +5°C heatwave
• +56% weekend uplift (Fri–Sat)
• Energy drinks sustained growth later in summer

Financial Impact

• Waste reduced from 18% to 4.2%
• Revenue +$340K vs. static plan
• Net margin +3.8 percentage points

Causal Intelligence via Simulator

By quantifying that carbonated promos cannibalized juice by 23% while energy drink pushes remained isolated, the team used simulator evidence to stagger campaigns instead of running blanket discounts.

Business Outcome

• 91% forecast accuracy across 127 SKUs
• Working capital reduced by $180K
• Customer satisfaction +28% (fewer stockouts)
• +$127K profit vs. previous summer

Case Study 04

Private Label Launch Simulation – Dairy Category Disruption

The retailer needed a launch strategy that avoided cannibalizing profitable branded partners.

Category Budget

$420K

Marketing

$85K planned

Client Challenge

Leadership worried that aggressive private-label pricing would gut branded sales and compress margins. They needed confidence in the pricing, phasing, and marketing plan.

Scenario Modeling

• A: -25% pricing (high cannibalization)
• B: -20% pricing (balanced)
• C: -18% pricing (premium private label)

Key Findings

• 63% of private-label buyers were net-new to the category
• Quality perception dropped sharply beyond -18% pricing
• Marketing spend could be trimmed to $62K

Optimized Strategy

• Launch milk first at -19%, stagger yogurt +6 weeks
• Maintain branded placement & co-op support
• Forecast net profit +$41K, revenue +$94K

Business Outcome

• 21% private label share in 10 months
• 89% accuracy vs. simulation forecast
• Branded partners retained 94% volume
• Category profitability +2.1 points

Case Study 05

Distribution Network Expansion – Tier-2 City Penetration

Before investing $1.8M, the distributor piloted three city clusters in the simulator.

Pilot Budget

$320K

Target Cities

12 (phased)

Cluster A (Value)

65% value mix, pricing 8-12% below metros, break-even 11 months, Year-1 budget $510K.

Cluster B (Aspirational)

45% mid-tier focus, pricing 3-5% below metros, break-even 8 months, Year-1 budget $680K.

Cluster C (Premium)

30% premium mix at metro pricing, break-even 6 months, Year-1 budget $390K.

Causal Intelligence via Simulator

• Tier-2 loyalty +34% after trial, validating phased rollout
• Sampling investment needed to be 2.3x metros to trigger stickiness
• Festival spikes +67% demand, steering the team toward dynamic inventory buffers

3-Year Projection

• Total investment $1.58M (12% below plan)
• Revenue $8.7M, net profit $1.24M
• Payback 19 months, market share 11-14%

Business Outcome

• Phase 1 break-even at 7 months (±1 month)
• 94% accuracy to simulation KPIs
• $340K in suboptimal inventory avoided
• $180K additional profit via dynamic pricing

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