Managing Partner & Co-Founder at Exactius | Former CRO at Fiverr & ideeli | Scaled Dozens of Companies 10x through Growth Marketing | Several Have Achieved Unicorn Status
Finding Efficiency to Expand Digital Investment for Omni-Channel Retailer: Increase Variable Contribution Margin by $14 Million in first 9 Months
B2C Fashion Transactional Growth
Company Profile
- Industry & Footprint: Leading fashion brand operating across multiple locations in the U.S.
- Business Type: B2C (Business-to-Consumer)
- Engagement Channels: Retail locations, Email, SMS, Phone, and Online
- Transaction Size: $50 to $500 per transaction
- Geographical Scope: Specific locations in the U.S. and key international cities
Business Problem:
- Need for Real-Time Performance Visibility
- Struggled to track performance across all platforms, channels, and campaigns in real-time (LC + MTA).
- Required optimization down to the fully loaded margin (FLM) at the campaign level.
- Segmentation of New vs. Existing Buyers
- Needed separate planning and reporting to accurately map activity drivers for each group.
- Saw an opportunity to increase activity among existing buyers and better target new customers.
- Inefficient Budget Allocation
- Prior-year investment mix was unclear; team needed to determine optimal daily spend per channel.
- Sought to balance spending efficiency with key brand objectives (e.g., Women’s Lifestyle).
- How to decide investment mix between D2C channels and other channels (like Amazon)
- Complexity of Measurement & Reporting
- Required Multi-Touch Attribution (MTA) and Marketing Mix Modeling (MMM) to accurately tie outcomes to investments.
- Operational issues (e.g., QA concerns, brand mishaps) lowered confidence in data and performance.
Deployed Solutions
- Comprehensive Data Platform
- Real-Time Tracking: Implemented real-time monitoring for all platforms, channels, and campaigns (LC + MTA).
- FLM Optimization: Enabled day-to-day adjustments in spending based on fully loaded margin data.
- Differentiated Strategy for New vs. Existing Buyers
- Activity Mapping: Identified unique conversion and engagement drivers for new vs. existing customers.
- Improved Engagement: Focused on boosting activity among existing customers while scaling new customer acquisition.
- Marketing Mix Modeling (MMM) & Multi-Touch Attribution (MTA)
- First-Ever MMM: Conducted 3,000 model iterations with 94% accuracy, incorporating category-level data.
- Live MTA Model: Provided more precise budget allocation insights, especially for top-of-funnel investments.
Key Results & Outcomes
Significant YoY Growth
$13.9M YoY increase in Fully Loaded Variable Contribution Margin over 9 months.
David Manela
