Retail & E-Commerce

Every customer.
Personally.

Personalization that converts, pricing that competes, and inventory intelligence that never leaves money on the table.

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+28%

Revenue per customer

$240M+

Incremental revenue driven

Major retailers served

What We Build

Retail AI capabilities

Purpose-built AI systems for retailers who compete on experience — where personalization is expected and loyalty is earned transaction by transaction.

Hyper-Personalization

1:1 product recommendations, dynamic content, and personalized experiences at scale.

Dynamic Pricing

AI-optimized pricing that maximizes margin while staying competitive in real-time.

Inventory Intelligence

Demand forecasting and allocation that prevents stockouts and overstock.

Customer Segmentation

Behavioral clustering that goes beyond demographics to actual purchase intent.

Cart Recovery

Predictive abandonment detection with personalized re-engagement triggers.

Attribution Modeling

True cross-channel attribution that shows what's actually driving conversions.

Case Study

Omnichannel Personalization at Scale

How AI-powered personalization increased revenue per customer by 28% and generated $86M in incremental revenue within the first year.

The Challenge

A leading omnichannel retailer with 450+ stores and $3.2B in annual revenue was losing the personalization war. Their recommendation engine was a black box from 2018. Cart abandonment hit 74%. Customer lifetime value was declining 8% year-over-year. Meanwhile, competitors were eating their market share with hyper-personalized experiences. The CEO set a clear mandate: fix this or fall behind.

Our Approach

Phase 1Customer Data Unification3 weeks

Consolidated 14 data sources — POS, e-commerce, loyalty, CRM, browsing behavior — into a single customer identity graph.

Phase 2Behavioral Modeling4 weeks

Built customer journey models capturing intent signals, category affinity, price sensitivity, and churn risk scores.

Phase 3Recommendation Engine5 weeks

Developed real-time personalization engine: product recommendations, dynamic pricing, and personalized promotions.

Phase 4Omnichannel Integration3 weeks

Deployed across web, mobile app, in-store kiosks, and email — unified experience regardless of touchpoint.

Phase 5Optimization Loop2 weeks

A/B testing framework with automatic winner selection. Continuous model retraining on fresh transaction data.

17 weeks from kickoff to full deployment