# Urban Thread Collective: AI Retail Intelligence | DSM.promo Case Study

> **Key Result:** 38% — Revenue Increase

## Client Overview

| Field | Value |
|-------|-------|
| Client | Urban Thread Collective |
| Industry | Retail |
| Location | Brooklyn, NY |
| Size | 15 Stores, 200 Employees |
| Timeline | 8 Weeks |
| Services | AI Inventory Management, Customer Intelligence |

## The Challenge

Urban Thread Collective's 15 boutique stores were losing sales to stockouts, wasting money on ineffective marketing, and struggling with manual inventory management. Their fashion-forward brand needed tech-forward operations.

- Stockouts losing an estimated 15% of potential sales across 15 locations
- No customer purchase prediction — buying was based on trend intuition alone
- Manual inventory tracking across 15 locations with weekly reconciliation
- Marketing spend generating only 1.2x ROAS with no attribution model
- Inconsistent pricing between online and in-store channels

## The Solution

### Phase 1: Retail Operations Audit
Analyzed sales data, inventory flow, and customer behavior across all 15 stores and e-commerce. Identified stockouts and marketing attribution as the two biggest revenue leaks.

### Phase 2: AI Inventory & Personalization
Deployed AI demand forecasting for automated replenishment, customer purchase prediction for targeted marketing, and dynamic pricing across all channels.

### Phase 3: Omnichannel Optimization
Unified online and in-store data, launched personalized email and SMS campaigns, and added real-time inventory visibility across all locations.

## Key Results

- **38%** — Revenue increase
- **94%** — In-stock rate (from 82%)
- **4.8x** — ROAS (from 1.2x)
- **56%** — Repeat customer rate (from 31%)

## What They Said

> "We were a fashion brand running on spreadsheets. The AI now predicts which styles will sell at which locations, keeps our shelves stocked, and our marketing spend generates 4x the return. We grew revenue 38% without opening a single new store."
> — Zara Mitchell, Founder & CEO, Urban Thread Collective

## FAQ

**Q: How quickly did revenue increase?**
A: Revenue growth was measurable within the first 3 weeks as stockout reduction immediately captured previously lost sales. The full 38% increase was achieved by week 8.

**Q: How does AI predict fashion demand?**
A: The AI analyzes historical sales patterns, social media trends, weather data, local events, and competitor pricing to forecast demand by style, size, and location.

**Q: Does it work for both online and in-store?**
A: Yes. The platform provides unified inventory management, consistent pricing, and customer profiles across all 15 stores and the e-commerce channel.

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*Read the full case study at [https://dsm.promo/case-study-retail](https://dsm.promo/case-study-retail)*
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