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E-Commerce / Retail 90 days

22% Revenue Lift Through Predictive AI Marketing

22%

Revenue Increase

The Challenge

The brand was spending $180K/month on paid ads with diminishing returns. Their email marketing was batch-and-blast with a 2.1% open rate. Inventory predictions were manual spreadsheets updated weekly, leading to frequent stockouts on bestsellers.

Our Approach

1

Built a predictive inventory model using 18 months of sales data, seasonality patterns, and trend signals

2

Deployed programmatic email personalization engine — each customer receives dynamically generated product recommendations

3

Created an automated content pipeline that generates SEO-optimized product descriptions and blog content

4

Integrated a real-time pricing optimization layer that adjusts based on inventory levels and demand signals

Results

22%

Revenue Lift

5.8% (from 2.1%)

Email Open Rate

Down 91%

Stockout Rate

+340%

Organic Traffic

Tech Stack

PythonTensorFlowNext.jsShopify APISendGridBigQuery

The programmatic SEO system they built generates more qualified leads than our entire marketing team. It's a machine.

Priya Patel

Head of Growth, NovaBrand