Client

StyleBrand Fashion

Industry

Retail

Duration

3 months

ROI

420%

The problem

StyleBrand was sending the same promotional emails to their entire 2M subscriber list. Open rates were declining, unsubscribe rates were climbing, and email revenue had plateaued. They knew personalization was the answer but didn't know where to start with millions of customers and thousands of products.

What we built

We built a personalization engine that determines the optimal content, products, send time, and subject line for each subscriber. The system analyzes browsing behavior, purchase history, email engagement, and seasonal patterns. It generates dynamic email content that's different for each recipient.

Tech stack

Python TensorFlow Klaviyo API Redis PostgreSQL AWS

Results

Email revenue increased 34% within 6 months. Open rates improved from 18% to 32%. Unsubscribes dropped by 40%. The system now generates personalized versions of each campaign in real-time, something their old manual process could never achieve.

Think you might have a similar problem?

We can share more details on a call.

Let's talk