Retail & E-Commerce
Demand forecasting, inventory optimization, and customer lifetime value at scale
Forecast demand with Monte Carlo uncertainty, optimize inventory across channels, analyze price waterfalls, score customer lifetime value, and detect fraud, replacing fragmented retail analytics with structured decision science.
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Retail Models
Monte Carlo
Demand Forecast
CLV
Scoring
Challenges We Solve
Industry-specific pain points that structured decision models eliminate.
Demand Forecasting Gaps
Seasonal patterns, promotions, and external factors make demand unpredictable. Model demand with Monte Carlo uncertainty bands across SKUs, channels, and geographies.
Inventory Imbalance
Overstocked in one warehouse, out of stock in another. Optimize inventory levels with EOQ, safety stock, and channel-specific demand factored in across the entire network.
Margin Erosion
Promotions, markdowns, and channel fees silently erode margins. Price waterfall analysis decomposes list-to-pocket margin by channel, product, and customer segment.
Customer Value Blindness
All customers get the same treatment regardless of lifetime value. Score CLV by cohort, detect health decay signals, and allocate retention spend where it generates the highest ROI.
Use Cases
Industry-specific scenarios powered by DecisionLedger.
Uses demand forecasting to model holiday season scenarios with Monte Carlo uncertainty, setting inventory levels that balance stockout risk against overstock markdown costs across 2,000 SKUs.
Reduced holiday stockouts 45% while cutting post-season markdowns by $1.2M
Runs price waterfall analysis across channels to identify that marketplace fees and promotional discounts erode direct-to-consumer margins by 18 points vs 6 points for owned channels.
Shifted 15% of marketing spend to owned channels, improving blended margin by 4 points
Deploys cohort LTV/CAC analysis to segment customers by acquisition source and purchase behavior. Identifies that referral customers have 3.2x higher LTV than paid social customers.
Launched referral program that grew to 22% of new customers, reducing blended CAC by 28%
Measurable Impact
Based on platform benchmarks across early adopters.
Demand Accuracy
+/-20% forecast error
+/-7% with Monte Carlo
Stockouts
12% out-of-stock rate
Demand-driven replenishment
Markdown Waste
Reactive end-of-season
Optimized inventory levels
Customer Retention
Same treatment for all
CLV-based segmented retention
Built for Retail & E-Commerce
Demand intelligence, inventory optimization, and customer economics for omnichannel retail.
Demand Intelligence
Monte Carlo demand forecasting incorporating seasonality, promotions, weather, and economic indicators with SKU-level uncertainty bands.
Inventory Optimization
Network-wide inventory allocation with EOQ, safety stock, and demand-driven replenishment across warehouses, stores, and fulfillment centers.
Customer Economics
Cohort-level CLV analysis, health decay detection, and retention ROI modeling that allocates marketing spend to highest-value segments.
Connects With
Part of 150+ native integrations across CRM, marketing, finance, HR, ecommerce, and analytics
Shopify
WooCommerce
BigCommerce
Square
Amazon Seller Central
Etsy
Klaviyo
Mailchimp
Stripe
Google Analytics 4ShopifyWooCommerceBigCommerceSquareAmazon Seller CentralEtsyKlaviyoMailchimpStripeGoogle Analytics 4Featured Models
Pre-built decision models ready to run with your data.
Cohort Ltv Cac Payback
Builds cohorts by acquisition channel and segment, models gross margin LTV, CAC, payback period, and retention curves so growth decisions do not silently destroy cash.
Demand Capacity Planner
Demand and capacity planning model. Balances production capacity against forecast demand, factoring in labor, equipment, and overtime to identify capacity gaps and recommend staffing or CapEx actions.
Fraud Spend Anomaly Detection
Detects duplicate payments, abnormal expense patterns, off-policy spend, unusual vendor behavior, and approval bypasses using anomaly detection plus rules-based controls.
Inventory Optimization
Inventory optimization model. Determines optimal stock levels by balancing carrying costs against stockout risk, computing reorder points and economic order quantities.
Logistics Routing
Logistics and routing optimizer. Evaluates delivery routes and transportation modes to minimize cost, transit time, and carbon emissions while meeting service level requirements.
Price Waterfall
Traces list price to street price through each discount layer (volume, negotiated, promotional, payment terms, bundling). Identifies leakage points and margin erosion drivers across the deal portfolio.
Customer Health Decay
Time-series early warning for accounts trending toward churn.
Revenue Demand Forecast Engine
Forecasts revenue and demand using scenario modeling with statistical trend analysis, seasonality adjustment, and probability-weighted projections across growth, base, and downside scenarios.
How It Works
Three steps to structured, auditable decisions.
Connect Retail Data
Pull sales data from Shopify/Magento, inventory from WMS, and customer data from CRM. Map SKUs, locations, channels, and customer segments.
Forecast & Optimize
Run demand forecasting with Monte Carlo, optimize inventory allocation, analyze price waterfalls, and score customer lifetime value across segments.
Execute & Monitor
Push replenishment recommendations to inventory systems, monitor margin realization, and track forecast accuracy against actual sell-through.
Your best-selling product was out of stock for 3 days last month while 4,000 units sat in the wrong warehouse. Meanwhile, your worst-performing SKUs are taking markdowns.
Excel demand plans
Single-point forecasts with no uncertainty quantification or scenario modeling
ERP inventory modules
Replenishment based on fixed reorder points, not demand-driven optimization
Standalone CLV tools
Customer scoring without connection to inventory, pricing, or demand decisions
Manual markdown optimization
End-of-season markdowns instead of demand-aligned inventory from the start