# PPC & Inventory Intelligence Platform

E-Commerce — Amazon Advertising & Inventory

> A platform that watches every dollar of Amazon ad spend and every unit of inventory, and tells you exactly what to do about both.

PPC waste cut 50–60%, SKU availability up from 47% to 70%+, repeat purchase rate doubled — five gut-feel decisions replaced with five data-driven systems including survival-analysis inventory and competitive bidding simulation.

**Recoverable value identified:** $1.4M–$2.1M/year

**13 / E-COMMERCE / AMAZON ADVERTISING & INVENTORY**


A platform that watches every dollar of Amazon ad spend and every unit of inventory, and tells you exactly what to do about both.

**Client:** Amazon-based exporter

**Tags:** E-Commerce · Amazon PPC · Demand Forecasting · Optimization · MLOps

## Problem

- $1M/month GMV, scaling toward $2M+ — inefficiencies were set to scale right along with it
- 52.5% of SKU-days sat at zero available inventory
- 29% of PPC spend wasted — zero-sale campaigns plus runaway ACOS, up to 267% on some
- 6% repeat customer rate against a 20–25% category benchmark
- Launches and budget calls made on gut feel — no demand signal behind either

## The Contribution

A predictive analytics platform replacing five gut-feel decisions with five data-driven systems.

- PPC engine auto-pauses zero-sale campaigns and flags runaway ACOS before it burns budget
- Demand forecasting predicts stockouts 90 days out and triggers reorders against real lead times
- Inventory depletion is modeled with survival analysis, not a flat reorder point
- Return-risk scoring flags high-risk orders at the moment of purchase
- Every model is watched for drift and retrained automatically once its inputs move

## Results

- PPC waste cut 50–60% within 90 days
- SKU availability up from 47% to 70%+
- Repeat purchase rate roughly doubled
- $1.4M–$2.1M/year in recoverable value identified and sequenced against an ICE-scored roadmap
- Net contribution margin improved from ~26% to ~33.5%

## Technical Details

**Anomaly Detection & Explainability**
Isolation Forest over search-term-level spend, clicks, and impressions — every flag paired with a SHAP explanation, not just a score.

**Demand Forecasting & Inventory Survival**
Holt-Winters per SKU, weekly seasonality, confidence-bound forecasts with backtested accuracy. Kaplan-Meier and Weibull hazard models estimate time-to-stockout per SKU.

**Optimization**
LP solvers reallocate PPC budget across campaigns by expected ROAS. Markowitz-style portfolio optimization across SKUs. Inventory carrying-cost minimization under lead-time and capacity constraints.

**Competitive Bidding Simulation**
GSP auction simulator, Nash-equilibrium bidding solver, multi-round bid-war simulator — tests a bidding strategy against modeled competitors before any real budget is committed.

**Drift Monitoring & Retraining**
PSI and Kolmogorov-Smirnov tests catch feature drift against each model's training baseline. A drifted model is flagged and routed through a dedicated retraining pipeline automatically.

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